fix(image): Cap Uploaded File Image Count (#10298)

Co-authored-by: Raunak Bhagat <r@rabh.io>

backend/ee/onyx/server/scim/api.py

@@ -11,6 +11,8 @@ require a valid SCIM bearer token.
 
 from __future__ import annotations
 
+import hashlib
+import struct
 from uuid import UUID
 
 from fastapi import APIRouter
@@ -22,6 +24,7 @@ from fastapi import Response
 from fastapi.responses import JSONResponse
 from fastapi_users.password import PasswordHelper
 from sqlalchemy import func
+from sqlalchemy import text
 from sqlalchemy.exc import IntegrityError
 from sqlalchemy.orm import Session
 
@@ -59,9 +62,25 @@ from onyx.db.models import UserGroup
 from onyx.db.models import UserRole
 from onyx.utils.logger import setup_logger
 from onyx.utils.variable_functionality import fetch_ee_implementation_or_noop
+from shared_configs.contextvars import get_current_tenant_id
 
 logger = setup_logger()
 
+# Group names reserved for system default groups (seeded by migration).
+_RESERVED_GROUP_NAMES = frozenset({"Admin", "Basic"})
+
+# Namespace prefix for the seat-allocation advisory lock. Hashed together
+# with the tenant ID so the lock is scoped per-tenant (unrelated tenants
+# never block each other) and cannot collide with unrelated advisory locks.
+_SEAT_LOCK_NAMESPACE = "onyx_scim_seat_lock"
+
+
+def _seat_lock_id_for_tenant(tenant_id: str) -> int:
+    """Derive a stable 64-bit signed int lock id for this tenant's seat lock."""
+    digest = hashlib.sha256(f"{_SEAT_LOCK_NAMESPACE}:{tenant_id}".encode()).digest()
+    # pg_advisory_xact_lock takes a signed 8-byte int; unpack as such.
+    return struct.unpack("q", digest[:8])[0]
+
 
 class ScimJSONResponse(JSONResponse):
     """JSONResponse with Content-Type: application/scim+json (RFC 7644 §3.1)."""
@@ -200,12 +219,37 @@ def _apply_exclusions(
 
 
 def _check_seat_availability(dal: ScimDAL) -> str | None:
-    """Return an error message if seat limit is reached, else None."""
+    """Return an error message if seat limit is reached, else None.
+
+    Acquires a transaction-scoped advisory lock so that concurrent
+    SCIM requests are serialized.  IdPs like Okta send provisioning
+    requests in parallel batches — without serialization the check is
+    vulnerable to a TOCTOU race where N concurrent requests each see
+    "seats available", all insert, and the tenant ends up over its
+    seat limit.
+
+    The lock is held until the caller's next COMMIT or ROLLBACK, which
+    means the seat count cannot change between the check here and the
+    subsequent INSERT/UPDATE.  Each call site in this module follows
+    the pattern: _check_seat_availability → write → dal.commit()
+    (which releases the lock for the next waiting request).
+    """
     check_fn = fetch_ee_implementation_or_noop(
         "onyx.db.license", "check_seat_availability", None
     )
     if check_fn is None:
         return None
+
+    # Transaction-scoped advisory lock — released on dal.commit() / dal.rollback().
+    # The lock id is derived from the tenant so unrelated tenants never block
+    # each other, and from a namespace string so it cannot collide with
+    # unrelated advisory locks elsewhere in the codebase.
+    lock_id = _seat_lock_id_for_tenant(get_current_tenant_id())
+    dal.session.execute(
+        text("SELECT pg_advisory_xact_lock(:lock_id)"),
+        {"lock_id": lock_id},
+    )
+
     result = check_fn(dal.session, seats_needed=1)
     if not result.available:
         return result.error_message or "Seat limit reached"

backend/onyx/configs/app_configs.py

@@ -816,6 +816,29 @@ MAX_FILE_SIZE_BYTES = int(
     os.environ.get("MAX_FILE_SIZE_BYTES") or 2 * 1024 * 1024 * 1024
 )  # 2GB in bytes
 
+# Maximum embedded images allowed in a single file. PDFs (and other formats)
+# with thousands of embedded images can OOM the user-file-processing worker
+# because every image is decoded with PIL and then sent to the vision LLM.
+# Enforced both at upload time (rejects the file) and during extraction
+# (defense-in-depth: caps the number of images materialized).
+#
+# Clamped to >= 0; a negative env value would turn upload validation into
+# always-fail and extraction into always-stop, which is never desired. 0
+# disables image extraction entirely, which is a valid (if aggressive) setting.
+MAX_EMBEDDED_IMAGES_PER_FILE = max(
+    0, int(os.environ.get("MAX_EMBEDDED_IMAGES_PER_FILE") or 500)
+)
+
+# Maximum embedded images allowed across all files in a single upload batch.
+# Protects against the scenario where a user uploads many files that each
+# fall under MAX_EMBEDDED_IMAGES_PER_FILE but aggregate to enough work
+# (serial-ish celery fan-out plus per-image vision-LLM calls) to OOM the
+# worker under concurrency or run up surprise latency/cost. Also clamped
+# to >= 0.
+MAX_EMBEDDED_IMAGES_PER_UPLOAD = max(
+    0, int(os.environ.get("MAX_EMBEDDED_IMAGES_PER_UPLOAD") or 1000)
+)
+
 # Use document summary for contextual rag
 USE_DOCUMENT_SUMMARY = os.environ.get("USE_DOCUMENT_SUMMARY", "true").lower() == "true"
 # Use chunk summary for contextual rag

backend/onyx/context/search/federated/models.py

@@ -1,3 +1,4 @@
+from dataclasses import dataclass
 from datetime import datetime
 from typing import TypedDict
 
@@ -6,6 +7,14 @@ from pydantic import BaseModel
 from onyx.onyxbot.slack.models import ChannelType
 
 
+@dataclass(frozen=True)
+class DirectThreadFetch:
+    """Request to fetch a Slack thread directly by channel and timestamp."""
+
+    channel_id: str
+    thread_ts: str
+
+
 class ChannelMetadata(TypedDict):
     """Type definition for cached channel metadata."""
 

backend/onyx/context/search/federated/slack_search.py

@@ -19,6 +19,7 @@ from onyx.configs.chat_configs import DOC_TIME_DECAY
 from onyx.connectors.models import IndexingDocument
 from onyx.connectors.models import TextSection
 from onyx.context.search.federated.models import ChannelMetadata
+from onyx.context.search.federated.models import DirectThreadFetch
 from onyx.context.search.federated.models import SlackMessage
 from onyx.context.search.federated.slack_search_utils import ALL_CHANNEL_TYPES
 from onyx.context.search.federated.slack_search_utils import build_channel_query_filter
@@ -49,7 +50,6 @@ from onyx.server.federated.models import FederatedConnectorDetail
 from onyx.utils.logger import setup_logger
 from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
 from onyx.utils.timing import log_function_time
-from shared_configs.configs import DOC_EMBEDDING_CONTEXT_SIZE
 
 logger = setup_logger()
 
@@ -58,7 +58,6 @@ HIGHLIGHT_END_CHAR = "\ue001"
 
 CHANNEL_METADATA_CACHE_TTL = 60 * 60 * 24  # 24 hours
 USER_PROFILE_CACHE_TTL = 60 * 60 * 24  # 24 hours
-SLACK_THREAD_CONTEXT_WINDOW = 3  # Number of messages before matched message to include
 CHANNEL_METADATA_MAX_RETRIES = 3  # Maximum retry attempts for channel metadata fetching
 CHANNEL_METADATA_RETRY_DELAY = 1  # Initial retry delay in seconds (exponential backoff)
 
@@ -421,6 +420,94 @@ class SlackQueryResult(BaseModel):
     filtered_channels: list[str]  # Channels filtered out during this query
 
 
+def _fetch_thread_from_url(
+    thread_fetch: DirectThreadFetch,
+    access_token: str,
+    channel_metadata_dict: dict[str, ChannelMetadata] | None = None,
+) -> SlackQueryResult:
+    """Fetch a thread directly from a Slack URL via conversations.replies."""
+    channel_id = thread_fetch.channel_id
+    thread_ts = thread_fetch.thread_ts
+
+    slack_client = WebClient(token=access_token)
+    try:
+        response = slack_client.conversations_replies(
+            channel=channel_id,
+            ts=thread_ts,
+        )
+        response.validate()
+        messages: list[dict[str, Any]] = response.get("messages", [])
+    except SlackApiError as e:
+        logger.warning(
+            f"Failed to fetch thread from URL (channel={channel_id}, ts={thread_ts}): {e}"
+        )
+        return SlackQueryResult(messages=[], filtered_channels=[])
+
+    if not messages:
+        logger.warning(
+            f"No messages found for URL override (channel={channel_id}, ts={thread_ts})"
+        )
+        return SlackQueryResult(messages=[], filtered_channels=[])
+
+    # Build thread text from all messages
+    thread_text = _build_thread_text(messages, access_token, None, slack_client)
+
+    # Get channel name from metadata cache or API
+    channel_name = "unknown"
+    if channel_metadata_dict and channel_id in channel_metadata_dict:
+        channel_name = channel_metadata_dict[channel_id].get("name", "unknown")
+    else:
+        try:
+            ch_response = slack_client.conversations_info(channel=channel_id)
+            ch_response.validate()
+            channel_info: dict[str, Any] = ch_response.get("channel", {})
+            channel_name = channel_info.get("name", "unknown")
+        except SlackApiError:
+            pass
+
+    # Build the SlackMessage
+    parent_msg = messages[0]
+    message_ts = parent_msg.get("ts", thread_ts)
+    username = parent_msg.get("user", "unknown_user")
+    parent_text = parent_msg.get("text", "")
+    snippet = (
+        parent_text[:50].rstrip() + "..." if len(parent_text) > 50 else parent_text
+    ).replace("\n", " ")
+
+    doc_time = datetime.fromtimestamp(float(message_ts))
+    decay_factor = DOC_TIME_DECAY
+    doc_age_years = (datetime.now() - doc_time).total_seconds() / (365 * 24 * 60 * 60)
+    recency_bias = max(1 / (1 + decay_factor * doc_age_years), 0.75)
+
+    permalink = (
+        f"https://slack.com/archives/{channel_id}/p{message_ts.replace('.', '')}"
+    )
+
+    slack_message = SlackMessage(
+        document_id=f"{channel_id}_{message_ts}",
+        channel_id=channel_id,
+        message_id=message_ts,
+        thread_id=None,  # Prevent double-enrichment in thread context fetch
+        link=permalink,
+        metadata={
+            "channel": channel_name,
+            "time": doc_time.isoformat(),
+        },
+        timestamp=doc_time,
+        recency_bias=recency_bias,
+        semantic_identifier=f"{username} in #{channel_name}: {snippet}",
+        text=thread_text,
+        highlighted_texts=set(),
+        slack_score=100000.0,  # High priority — user explicitly asked for this thread
+    )
+
+    logger.info(
+        f"URL override: fetched thread from channel={channel_id}, ts={thread_ts}, {len(messages)} messages"
+    )
+
+    return SlackQueryResult(messages=[slack_message], filtered_channels=[])
+
+
 def query_slack(
     query_string: str,
     access_token: str,
@@ -432,7 +519,6 @@ def query_slack(
     available_channels: list[str] | None = None,
     channel_metadata_dict: dict[str, ChannelMetadata] | None = None,
 ) -> SlackQueryResult:
-
     # Check if query has channel override (user specified channels in query)
     has_channel_override = query_string.startswith("__CHANNEL_OVERRIDE__")
 
@@ -662,7 +748,6 @@ def _fetch_thread_context(
     """
     channel_id = message.channel_id
     thread_id = message.thread_id
-    message_id = message.message_id
 
     # If not a thread, return original text as success
     if thread_id is None:
@@ -695,62 +780,37 @@ def _fetch_thread_context(
     if len(messages) <= 1:
         return ThreadContextResult.success(message.text)
 
-    # Build thread text from thread starter + context window around matched message
-    thread_text = _build_thread_text(
-        messages, message_id, thread_id, access_token, team_id, slack_client
-    )
+    # Build thread text from thread starter + all replies
+    thread_text = _build_thread_text(messages, access_token, team_id, slack_client)
     return ThreadContextResult.success(thread_text)
 
 
 def _build_thread_text(
     messages: list[dict[str, Any]],
-    message_id: str,
-    thread_id: str,
     access_token: str,
     team_id: str | None,
     slack_client: WebClient,
 ) -> str:
-    """Build the thread text from messages."""
+    """Build thread text including all replies.
+
+    Includes the thread parent message followed by all replies in order.
+    """
     msg_text = messages[0].get("text", "")
     msg_sender = messages[0].get("user", "")
     thread_text = f"<@{msg_sender}>: {msg_text}"
 
+    # All messages after index 0 are replies
+    replies = messages[1:]
+    if not replies:
+        return thread_text
+
+    logger.debug(f"Thread {messages[0].get('ts')}: {len(replies)} replies included")
     thread_text += "\n\nReplies:"
-    if thread_id == message_id:
-        message_id_idx = 0
-    else:
-        message_id_idx = next(
-            (i for i, msg in enumerate(messages) if msg.get("ts") == message_id), 0
-        )
-        if not message_id_idx:
-            return thread_text
 
-        start_idx = max(1, message_id_idx - SLACK_THREAD_CONTEXT_WINDOW)
-
-        if start_idx > 1:
-            thread_text += "\n..."
-
-        for i in range(start_idx, message_id_idx):
-            msg_text = messages[i].get("text", "")
-            msg_sender = messages[i].get("user", "")
-            thread_text += f"\n\n<@{msg_sender}>: {msg_text}"
-
-        msg_text = messages[message_id_idx].get("text", "")
-        msg_sender = messages[message_id_idx].get("user", "")
-        thread_text += f"\n\n<@{msg_sender}>: {msg_text}"
-
-    # Add following replies
-    len_replies = 0
-    for msg in messages[message_id_idx + 1 :]:
+    for msg in replies:
         msg_text = msg.get("text", "")
         msg_sender = msg.get("user", "")
-        reply = f"\n\n<@{msg_sender}>: {msg_text}"
-        thread_text += reply
-
-        len_replies += len(reply)
-        if len_replies >= DOC_EMBEDDING_CONTEXT_SIZE * 4:
-            thread_text += "\n..."
-            break
+        thread_text += f"\n\n<@{msg_sender}>: {msg_text}"
 
     # Replace user IDs with names using cached lookups
     userids: set[str] = set(re.findall(r"<@([A-Z0-9]+)>", thread_text))
@@ -976,7 +1036,16 @@ def slack_retrieval(
 
     # Query slack with entity filtering
     llm = get_default_llm()
-    query_strings = build_slack_queries(query, llm, entities, available_channels)
+    query_items = build_slack_queries(query, llm, entities, available_channels)
+
+    # Partition into direct thread fetches and search query strings
+    direct_fetches: list[DirectThreadFetch] = []
+    query_strings: list[str] = []
+    for item in query_items:
+        if isinstance(item, DirectThreadFetch):
+            direct_fetches.append(item)
+        else:
+            query_strings.append(item)
 
     # Determine filtering based on entities OR context (bot)
     include_dm = False
@@ -993,8 +1062,16 @@ def slack_retrieval(
                 f"Private channel context: will only allow messages from {allowed_private_channel} + public channels"
             )
 
-    # Build search tasks
-    search_tasks = [
+    # Build search tasks — direct thread fetches + keyword searches
+    search_tasks: list[tuple] = [
+        (
+            _fetch_thread_from_url,
+            (fetch, access_token, channel_metadata_dict),
+        )
+        for fetch in direct_fetches
+    ]
+
+    search_tasks.extend(
         (
             query_slack,
             (
@@ -1010,7 +1087,7 @@ def slack_retrieval(
             ),
         )
         for query_string in query_strings
-    ]
+    )
 
     # If include_dm is True AND we're not already searching all channels,
     # add additional searches without channel filters.

backend/onyx/context/search/federated/slack_search_utils.py

@@ -10,6 +10,7 @@ from pydantic import ValidationError
 
 from onyx.configs.app_configs import MAX_SLACK_QUERY_EXPANSIONS
 from onyx.context.search.federated.models import ChannelMetadata
+from onyx.context.search.federated.models import DirectThreadFetch
 from onyx.context.search.models import ChunkIndexRequest
 from onyx.federated_connectors.slack.models import SlackEntities
 from onyx.llm.interfaces import LLM
@@ -638,12 +639,38 @@ def expand_query_with_llm(query_text: str, llm: LLM) -> list[str]:
         return [query_text]
 
 
+SLACK_URL_PATTERN = re.compile(
+    r"https?://[a-z0-9-]+\.slack\.com/archives/([A-Z0-9]+)/p(\d{16})"
+)
+
+
+def extract_slack_message_urls(
+    query_text: str,
+) -> list[tuple[str, str]]:
+    """Extract Slack message URLs from query text.
+
+    Parses URLs like:
+      https://onyx-company.slack.com/archives/C097NBWMY8Y/p1775491616524769
+
+    Returns list of (channel_id, thread_ts) tuples.
+    The 16-digit timestamp is converted to Slack ts format (with dot).
+    """
+    results = []
+    for match in SLACK_URL_PATTERN.finditer(query_text):
+        channel_id = match.group(1)
+        raw_ts = match.group(2)
+        # Convert p1775491616524769 -> 1775491616.524769
+        thread_ts = f"{raw_ts[:10]}.{raw_ts[10:]}"
+        results.append((channel_id, thread_ts))
+    return results
+
+
 def build_slack_queries(
     query: ChunkIndexRequest,
     llm: LLM,
     entities: dict[str, Any] | None = None,
     available_channels: list[str] | None = None,
-) -> list[str]:
+) -> list[str | DirectThreadFetch]:
     """Build Slack query strings with date filtering and query expansion."""
     default_search_days = 30
     if entities:
@@ -668,6 +695,15 @@ def build_slack_queries(
             cutoff_date = datetime.now(timezone.utc) - timedelta(days=days_back)
             time_filter = f" after:{cutoff_date.strftime('%Y-%m-%d')}"
 
+    # Check for Slack message URLs — if found, add direct fetch requests
+    url_fetches: list[DirectThreadFetch] = []
+    slack_urls = extract_slack_message_urls(query.query)
+    for channel_id, thread_ts in slack_urls:
+        url_fetches.append(
+            DirectThreadFetch(channel_id=channel_id, thread_ts=thread_ts)
+        )
+        logger.info(f"Detected Slack URL: channel={channel_id}, ts={thread_ts}")
+
     # ALWAYS extract channel references from the query (not just for recency queries)
     channel_references = extract_channel_references_from_query(query.query)
 
@@ -684,7 +720,9 @@ def build_slack_queries(
 
             # If valid channels detected, use ONLY those channels with NO keywords
             # Return query with ONLY time filter + channel filter (no keywords)
-            return [build_channel_override_query(channel_references, time_filter)]
+            return url_fetches + [
+                build_channel_override_query(channel_references, time_filter)
+            ]
         except ValueError as e:
             # If validation fails, log the error and continue with normal flow
             logger.warning(f"Channel reference validation failed: {e}")
@@ -702,7 +740,8 @@ def build_slack_queries(
         rephrased_queries = expand_query_with_llm(query.query, llm)
 
     # Build final query strings with time filters
-    return [
+    search_queries = [
         rephrased_query.strip() + time_filter
         for rephrased_query in rephrased_queries[:MAX_SLACK_QUERY_EXPANSIONS]
     ]
+    return url_fetches + search_queries

backend/onyx/file_processing/extract_file_text.py

@@ -21,6 +21,7 @@ import chardet
 import openpyxl
 from PIL import Image
 
+from onyx.configs.app_configs import MAX_EMBEDDED_IMAGES_PER_FILE
 from onyx.configs.constants import ONYX_METADATA_FILENAME
 from onyx.configs.llm_configs import get_image_extraction_and_analysis_enabled
 from onyx.file_processing.file_types import OnyxFileExtensions
@@ -188,6 +189,56 @@ def read_text_file(
     return file_content_raw, metadata
 
 
+def count_pdf_embedded_images(file: IO[Any], cap: int) -> int:
+    """Return the number of embedded images in a PDF, short-circuiting at cap+1.
+
+    Used to reject PDFs whose image count would OOM the user-file-processing
+    worker during indexing. Returns a value > cap as a sentinel once the count
+    exceeds the cap, so callers do not iterate thousands of image objects just
+    to report a number. Returns 0 if the PDF cannot be parsed.
+
+    Owner-password-only PDFs (permission restrictions but no open password) are
+    counted normally — they decrypt with an empty string. Truly password-locked
+    PDFs are skipped (return 0) since we can't inspect them; the caller should
+    ensure the password-protected check runs first.
+
+    Always restores the file pointer to its original position before returning.
+    """
+    from pypdf import PdfReader
+
+    try:
+        start_pos = file.tell()
+    except Exception:
+        start_pos = None
+    try:
+        if start_pos is not None:
+            file.seek(0)
+        reader = PdfReader(file)
+        if reader.is_encrypted:
+            # Try empty password first (owner-password-only PDFs); give up if that fails.
+            try:
+                if reader.decrypt("") == 0:
+                    return 0
+            except Exception:
+                return 0
+        count = 0
+        for page in reader.pages:
+            for _ in page.images:
+                count += 1
+                if count > cap:
+                    return count
+        return count
+    except Exception:
+        logger.warning("Failed to count embedded images in PDF", exc_info=True)
+        return 0
+    finally:
+        if start_pos is not None:
+            try:
+                file.seek(start_pos)
+            except Exception:
+                pass
+
+
 def pdf_to_text(file: IO[Any], pdf_pass: str | None = None) -> str:
     """
     Extract text from a PDF. For embedded images, a more complex approach is needed.
@@ -251,8 +302,27 @@ def read_pdf_file(
         )
 
         if extract_images:
+            image_cap = MAX_EMBEDDED_IMAGES_PER_FILE
+            images_processed = 0
+            cap_reached = False
             for page_num, page in enumerate(pdf_reader.pages):
+                if cap_reached:
+                    break
                 for image_file_object in page.images:
+                    if images_processed >= image_cap:
+                        # Defense-in-depth backstop. Upload-time validation
+                        # should have rejected files exceeding the cap, but
+                        # we also break here so a single oversized file can
+                        # never pin a worker.
+                        logger.warning(
+                            "PDF embedded image cap reached (%d). "
+                            "Skipping remaining images on page %d and beyond.",
+                            image_cap,
+                            page_num + 1,
+                        )
+                        cap_reached = True
+                        break
+
                     image = Image.open(io.BytesIO(image_file_object.data))
                     img_byte_arr = io.BytesIO()
                     image.save(img_byte_arr, format=image.format)
@@ -265,6 +335,7 @@ def read_pdf_file(
                         image_callback(img_bytes, image_name)
                     else:
                         extracted_images.append((img_bytes, image_name))
+                    images_processed += 1
 
         return text, metadata, extracted_images
 

backend/onyx/llm/constants.py

@@ -26,6 +26,7 @@ class LlmProviderNames(str, Enum):
     MISTRAL = "mistral"
     LITELLM_PROXY = "litellm_proxy"
     BIFROST = "bifrost"
+    OPENAI_COMPATIBLE = "openai_compatible"
 
     def __str__(self) -> str:
         """Needed so things like:
@@ -46,6 +47,7 @@ WELL_KNOWN_PROVIDER_NAMES = [
     LlmProviderNames.LM_STUDIO,
     LlmProviderNames.LITELLM_PROXY,
     LlmProviderNames.BIFROST,
+    LlmProviderNames.OPENAI_COMPATIBLE,
 ]
 
 
@@ -64,6 +66,7 @@ PROVIDER_DISPLAY_NAMES: dict[str, str] = {
     LlmProviderNames.LM_STUDIO: "LM Studio",
     LlmProviderNames.LITELLM_PROXY: "LiteLLM Proxy",
     LlmProviderNames.BIFROST: "Bifrost",
+    LlmProviderNames.OPENAI_COMPATIBLE: "OpenAI Compatible",
     "groq": "Groq",
     "anyscale": "Anyscale",
     "deepseek": "DeepSeek",
@@ -116,6 +119,7 @@ AGGREGATOR_PROVIDERS: set[str] = {
     LlmProviderNames.AZURE,
     LlmProviderNames.LITELLM_PROXY,
     LlmProviderNames.BIFROST,
+    LlmProviderNames.OPENAI_COMPATIBLE,
 }
 
 # Model family name mappings for display name generation

backend/onyx/llm/multi_llm.py

@@ -175,6 +175,28 @@ def _strip_tool_content_from_messages(
     return result
 
 
+def _fix_tool_user_message_ordering(
+    messages: list[dict[str, Any]],
+) -> list[dict[str, Any]]:
+    """Insert a synthetic assistant message between tool and user messages.
+
+    Some models (e.g. Mistral on Azure) require strict message ordering where
+    a user message cannot immediately follow a tool message. This function
+    inserts a minimal assistant message to bridge the gap.
+    """
+    if len(messages) < 2:
+        return messages
+
+    result: list[dict[str, Any]] = [messages[0]]
+    for msg in messages[1:]:
+        prev_role = result[-1].get("role")
+        curr_role = msg.get("role")
+        if prev_role == "tool" and curr_role == "user":
+            result.append({"role": "assistant", "content": "Noted. Continuing."})
+        result.append(msg)
+    return result
+
+
 def _messages_contain_tool_content(messages: list[dict[str, Any]]) -> bool:
     """Check if any messages contain tool-related content blocks."""
     for msg in messages:
@@ -305,12 +327,19 @@ class LitellmLLM(LLM):
         ):
             model_kwargs[VERTEX_LOCATION_KWARG] = "global"
 
-        # Bifrost: OpenAI-compatible proxy that expects model names in
-        # provider/model format (e.g. "anthropic/claude-sonnet-4-6").
-        # We route through LiteLLM's openai provider with the Bifrost base URL,
-        # and ensure /v1 is appended.
-        if model_provider == LlmProviderNames.BIFROST:
+        # Bifrost and OpenAI-compatible: OpenAI-compatible proxies that send
+        # model names directly to the endpoint. We route through LiteLLM's
+        # openai provider with the server's base URL, and ensure /v1 is appended.
+        if model_provider in (
+            LlmProviderNames.BIFROST,
+            LlmProviderNames.OPENAI_COMPATIBLE,
+        ):
             self._custom_llm_provider = "openai"
+            # LiteLLM's OpenAI client requires an api_key to be set.
+            # Many OpenAI-compatible servers don't need auth, so supply a
+            # placeholder to prevent LiteLLM from raising AuthenticationError.
+            if not self._api_key:
+                model_kwargs.setdefault("api_key", "not-needed")
             if self._api_base is not None:
                 base = self._api_base.rstrip("/")
                 self._api_base = base if base.endswith("/v1") else f"{base}/v1"
@@ -427,17 +456,20 @@ class LitellmLLM(LLM):
         optional_kwargs: dict[str, Any] = {}
 
         # Model name
-        is_bifrost = self._model_provider == LlmProviderNames.BIFROST
+        is_openai_compatible_proxy = self._model_provider in (
+            LlmProviderNames.BIFROST,
+            LlmProviderNames.OPENAI_COMPATIBLE,
+        )
         model_provider = (
             f"{self.config.model_provider}/responses"
             if is_openai_model  # Uses litellm's completions -> responses bridge
             else self.config.model_provider
         )
-        if is_bifrost:
-            # Bifrost expects model names in provider/model format
-            # (e.g. "anthropic/claude-sonnet-4-6") sent directly to its
-            # OpenAI-compatible endpoint. We use custom_llm_provider="openai"
-            # so LiteLLM doesn't try to route based on the provider prefix.
+        if is_openai_compatible_proxy:
+            # OpenAI-compatible proxies (Bifrost, generic OpenAI-compatible
+            # servers) expect model names sent directly to their endpoint.
+            # We use custom_llm_provider="openai" so LiteLLM doesn't try
+            # to route based on the provider prefix.
             model = self.config.deployment_name or self.config.model_name
         else:
             model = f"{model_provider}/{self.config.deployment_name or self.config.model_name}"
@@ -528,7 +560,10 @@ class LitellmLLM(LLM):
         if structured_response_format:
             optional_kwargs["response_format"] = structured_response_format
 
-        if not (is_claude_model or is_ollama or is_mistral) or is_bifrost:
+        if (
+            not (is_claude_model or is_ollama or is_mistral)
+            or is_openai_compatible_proxy
+        ):
             # Litellm bug: tool_choice is dropped silently if not specified here for OpenAI
             # However, this param breaks Anthropic and Mistral models,
             # so it must be conditionally included unless the request is
@@ -576,6 +611,18 @@ class LitellmLLM(LLM):
                 ):
                     messages = _strip_tool_content_from_messages(messages)
 
+                # Some models (e.g. Mistral) reject a user message
+                # immediately after a tool message. Insert a synthetic
+                # assistant bridge message to satisfy the ordering
+                # constraint. Check both the provider and the deployment/
+                # model name to catch Mistral hosted on Azure.
+                model_or_deployment = (
+                    self._deployment_name or self._model_version or ""
+                ).lower()
+                is_mistral_model = is_mistral or "mistral" in model_or_deployment
+                if is_mistral_model:
+                    messages = _fix_tool_user_message_ordering(messages)
+
                 # Only pass tool_choice when tools are present — some providers (e.g. Fireworks)
                 # reject requests where tool_choice is explicitly null.
                 if tools and tool_choice is not None:

backend/onyx/llm/well_known_providers/constants.py

@@ -15,6 +15,8 @@ LITELLM_PROXY_PROVIDER_NAME = "litellm_proxy"
 
 BIFROST_PROVIDER_NAME = "bifrost"
 
+OPENAI_COMPATIBLE_PROVIDER_NAME = "openai_compatible"
+
 # Providers that use optional Bearer auth from custom_config
 PROVIDERS_WITH_SPECIAL_API_KEY_HANDLING: dict[str, str] = {
     LlmProviderNames.OLLAMA_CHAT: OLLAMA_API_KEY_CONFIG_KEY,

backend/onyx/llm/well_known_providers/llm_provider_options.py

@@ -19,6 +19,7 @@ from onyx.llm.well_known_providers.constants import BIFROST_PROVIDER_NAME
 from onyx.llm.well_known_providers.constants import LITELLM_PROXY_PROVIDER_NAME
 from onyx.llm.well_known_providers.constants import LM_STUDIO_PROVIDER_NAME
 from onyx.llm.well_known_providers.constants import OLLAMA_PROVIDER_NAME
+from onyx.llm.well_known_providers.constants import OPENAI_COMPATIBLE_PROVIDER_NAME
 from onyx.llm.well_known_providers.constants import OPENAI_PROVIDER_NAME
 from onyx.llm.well_known_providers.constants import OPENROUTER_PROVIDER_NAME
 from onyx.llm.well_known_providers.constants import VERTEXAI_PROVIDER_NAME
@@ -51,6 +52,7 @@ def _get_provider_to_models_map() -> dict[str, list[str]]:
         OPENROUTER_PROVIDER_NAME: [],  # Dynamic - fetched from OpenRouter API
         LITELLM_PROXY_PROVIDER_NAME: [],  # Dynamic - fetched from LiteLLM proxy API
         BIFROST_PROVIDER_NAME: [],  # Dynamic - fetched from Bifrost API
+        OPENAI_COMPATIBLE_PROVIDER_NAME: [],  # Dynamic - fetched from OpenAI-compatible API
     }
 
 
@@ -336,6 +338,7 @@ def get_provider_display_name(provider_name: str) -> str:
         VERTEXAI_PROVIDER_NAME: "Google Vertex AI",
         OPENROUTER_PROVIDER_NAME: "OpenRouter",
         LITELLM_PROXY_PROVIDER_NAME: "LiteLLM Proxy",
+        OPENAI_COMPATIBLE_PROVIDER_NAME: "OpenAI Compatible",
     }
 
     if provider_name in _ONYX_PROVIDER_DISPLAY_NAMES:

backend/onyx/server/features/build/api/user_library.py

@@ -40,6 +40,8 @@ from sqlalchemy.orm import Session
 
 from onyx.auth.users import current_user
 from onyx.background.celery.versioned_apps.client import app as celery_app
+from onyx.configs.app_configs import MAX_EMBEDDED_IMAGES_PER_FILE
+from onyx.configs.app_configs import MAX_EMBEDDED_IMAGES_PER_UPLOAD
 from onyx.configs.constants import DocumentSource
 from onyx.configs.constants import OnyxCeleryQueues
 from onyx.configs.constants import OnyxCeleryTask
@@ -50,6 +52,9 @@ from onyx.db.engine.sql_engine import get_session
 from onyx.db.enums import ConnectorCredentialPairStatus
 from onyx.db.models import User
 from onyx.document_index.interfaces import DocumentMetadata
+from onyx.error_handling.error_codes import OnyxErrorCode
+from onyx.error_handling.exceptions import OnyxError
+from onyx.file_processing.extract_file_text import count_pdf_embedded_images
 from onyx.server.features.build.configs import USER_LIBRARY_MAX_FILE_SIZE_BYTES
 from onyx.server.features.build.configs import USER_LIBRARY_MAX_FILES_PER_UPLOAD
 from onyx.server.features.build.configs import USER_LIBRARY_MAX_TOTAL_SIZE_BYTES
@@ -127,6 +132,49 @@ class DeleteFileResponse(BaseModel):
 # =============================================================================
 
 
+def _looks_like_pdf(filename: str, content_type: str | None) -> bool:
+    """True if either the filename or the content-type indicates a PDF.
+
+    Client-supplied ``content_type`` can be spoofed (e.g. a PDF uploaded with
+    ``Content-Type: application/octet-stream``), so we also fall back to
+    extension-based detection via ``mimetypes.guess_type`` on the filename.
+    """
+    if content_type == "application/pdf":
+        return True
+    guessed, _ = mimetypes.guess_type(filename)
+    return guessed == "application/pdf"
+
+
+def _check_pdf_image_caps(
+    filename: str, content: bytes, content_type: str | None, batch_total: int
+) -> int:
+    """Enforce per-file and per-batch embedded-image caps for PDFs.
+
+    Returns the number of embedded images in this file (0 for non-PDFs) so
+    callers can update their running batch total. Raises OnyxError(INVALID_INPUT)
+    if either cap is exceeded.
+    """
+    if not _looks_like_pdf(filename, content_type):
+        return 0
+    file_cap = MAX_EMBEDDED_IMAGES_PER_FILE
+    batch_cap = MAX_EMBEDDED_IMAGES_PER_UPLOAD
+    # Short-circuit at the larger cap so we get a useful count for both checks.
+    count = count_pdf_embedded_images(BytesIO(content), max(file_cap, batch_cap))
+    if count > file_cap:
+        raise OnyxError(
+            OnyxErrorCode.INVALID_INPUT,
+            f"PDF '{filename}' contains too many embedded images "
+            f"(more than {file_cap}). Try splitting the document into smaller files.",
+        )
+    if batch_total + count > batch_cap:
+        raise OnyxError(
+            OnyxErrorCode.INVALID_INPUT,
+            f"Upload would exceed the {batch_cap}-image limit across all "
+            f"files in this batch. Try uploading fewer image-heavy files at once.",
+        )
+    return count
+
+
 def _sanitize_path(path: str) -> str:
     """Sanitize a file path, removing traversal attempts and normalizing.
 
@@ -355,6 +403,7 @@ async def upload_files(
 
     uploaded_entries: list[LibraryEntryResponse] = []
     total_size = 0
+    batch_image_total = 0
     now = datetime.now(timezone.utc)
 
     # Sanitize the base path
@@ -374,6 +423,14 @@ async def upload_files(
                 detail=f"File '{file.filename}' exceeds maximum size of {USER_LIBRARY_MAX_FILE_SIZE_BYTES // (1024 * 1024)}MB",
             )
 
+        # Reject PDFs with an unreasonable per-file or per-batch image count
+        batch_image_total += _check_pdf_image_caps(
+            filename=file.filename or "unnamed",
+            content=content,
+            content_type=file.content_type,
+            batch_total=batch_image_total,
+        )
+
         # Validate cumulative storage (existing + this upload batch)
         total_size += file_size
         if existing_usage + total_size > USER_LIBRARY_MAX_TOTAL_SIZE_BYTES:
@@ -472,6 +529,7 @@ async def upload_zip(
 
     uploaded_entries: list[LibraryEntryResponse] = []
     total_size = 0
+    batch_image_total = 0
 
     # Extract zip contents into a subfolder named after the zip file
     zip_name = api_sanitize_filename(file.filename or "upload")
@@ -510,6 +568,36 @@ async def upload_zip(
                     logger.warning(f"Skipping '{zip_info.filename}' - exceeds max size")
                     continue
 
+                # Skip PDFs that would trip the per-file or per-batch image
+                # cap (would OOM the user-file-processing worker). Matches
+                # /upload behavior but uses skip-and-warn to stay consistent
+                # with the zip path's handling of oversized files.
+                zip_file_name = zip_info.filename.split("/")[-1]
+                zip_content_type, _ = mimetypes.guess_type(zip_file_name)
+                if zip_content_type == "application/pdf":
+                    image_count = count_pdf_embedded_images(
+                        BytesIO(file_content),
+                        max(
+                            MAX_EMBEDDED_IMAGES_PER_FILE,
+                            MAX_EMBEDDED_IMAGES_PER_UPLOAD,
+                        ),
+                    )
+                    if image_count > MAX_EMBEDDED_IMAGES_PER_FILE:
+                        logger.warning(
+                            "Skipping '%s' - exceeds %d per-file embedded-image cap",
+                            zip_info.filename,
+                            MAX_EMBEDDED_IMAGES_PER_FILE,
+                        )
+                        continue
+                    if batch_image_total + image_count > MAX_EMBEDDED_IMAGES_PER_UPLOAD:
+                        logger.warning(
+                            "Skipping '%s' - would exceed %d per-batch embedded-image cap",
+                            zip_info.filename,
+                            MAX_EMBEDDED_IMAGES_PER_UPLOAD,
+                        )
+                        continue
+                    batch_image_total += image_count
+
                 total_size += file_size
 
                 # Validate cumulative storage

backend/onyx/server/features/projects/projects_file_utils.py

@@ -10,9 +10,12 @@ from pydantic import Field
 from sqlalchemy.orm import Session
 
 from onyx.configs.app_configs import FILE_TOKEN_COUNT_THRESHOLD
+from onyx.configs.app_configs import MAX_EMBEDDED_IMAGES_PER_FILE
+from onyx.configs.app_configs import MAX_EMBEDDED_IMAGES_PER_UPLOAD
 from onyx.configs.app_configs import USER_FILE_MAX_UPLOAD_SIZE_BYTES
 from onyx.configs.app_configs import USER_FILE_MAX_UPLOAD_SIZE_MB
 from onyx.db.llm import fetch_default_llm_model
+from onyx.file_processing.extract_file_text import count_pdf_embedded_images
 from onyx.file_processing.extract_file_text import extract_file_text
 from onyx.file_processing.extract_file_text import get_file_ext
 from onyx.file_processing.file_types import OnyxFileExtensions
@@ -192,6 +195,11 @@ def categorize_uploaded_files(
         except RuntimeError as e:
             logger.warning(f"Failed to get current tenant ID: {str(e)}")
 
+    # Running total of embedded images across PDFs in this batch. Once the
+    # aggregate cap is reached, subsequent PDFs in the same upload are
+    # rejected even if they'd individually fit under MAX_EMBEDDED_IMAGES_PER_FILE.
+    batch_image_total = 0
+
     for upload in files:
         try:
             filename = get_safe_filename(upload)
@@ -253,6 +261,47 @@ def categorize_uploaded_files(
                     )
                     continue
 
+                # Reject PDFs with an unreasonable number of embedded images
+                # (either per-file or accumulated across this upload batch).
+                # A PDF with thousands of embedded images can OOM the
+                # user-file-processing celery worker because every image is
+                # decoded with PIL and then sent to the vision LLM.
+                if extension == ".pdf":
+                    file_cap = MAX_EMBEDDED_IMAGES_PER_FILE
+                    batch_cap = MAX_EMBEDDED_IMAGES_PER_UPLOAD
+                    # Use the larger of the two caps as the short-circuit
+                    # threshold so we get a useful count for both checks.
+                    # count_pdf_embedded_images restores the stream position.
+                    count = count_pdf_embedded_images(
+                        upload.file, max(file_cap, batch_cap)
+                    )
+                    if count > file_cap:
+                        results.rejected.append(
+                            RejectedFile(
+                                filename=filename,
+                                reason=(
+                                    f"PDF contains too many embedded images "
+                                    f"(more than {file_cap}). Try splitting "
+                                    f"the document into smaller files."
+                                ),
+                            )
+                        )
+                        continue
+                    if batch_image_total + count > batch_cap:
+                        results.rejected.append(
+                            RejectedFile(
+                                filename=filename,
+                                reason=(
+                                    f"Upload would exceed the "
+                                    f"{batch_cap}-image limit across all "
+                                    f"files in this batch. Try uploading "
+                                    f"fewer image-heavy files at once."
+                                ),
+                            )
+                        )
+                        continue
+                    batch_image_total += count
+
                 text_content = extract_file_text(
                     file=upload.file,
                     file_name=filename,

backend/onyx/server/manage/llm/api.py

@@ -74,6 +74,8 @@ from onyx.server.manage.llm.models import ModelConfigurationUpsertRequest
 from onyx.server.manage.llm.models import OllamaFinalModelResponse
 from onyx.server.manage.llm.models import OllamaModelDetails
 from onyx.server.manage.llm.models import OllamaModelsRequest
+from onyx.server.manage.llm.models import OpenAICompatibleFinalModelResponse
+from onyx.server.manage.llm.models import OpenAICompatibleModelsRequest
 from onyx.server.manage.llm.models import OpenRouterFinalModelResponse
 from onyx.server.manage.llm.models import OpenRouterModelDetails
 from onyx.server.manage.llm.models import OpenRouterModelsRequest
@@ -1575,3 +1577,95 @@ def _get_bifrost_models_response(api_base: str, api_key: str | None = None) -> d
         source_name="Bifrost",
         api_key=api_key,
     )
+
+
+@admin_router.post("/openai-compatible/available-models")
+def get_openai_compatible_server_available_models(
+    request: OpenAICompatibleModelsRequest,
+    _: User = Depends(current_admin_user),
+    db_session: Session = Depends(get_session),
+) -> list[OpenAICompatibleFinalModelResponse]:
+    """Fetch available models from a generic OpenAI-compatible /v1/models endpoint."""
+    response_json = _get_openai_compatible_server_response(
+        api_base=request.api_base, api_key=request.api_key
+    )
+
+    models = response_json.get("data", [])
+    if not isinstance(models, list) or len(models) == 0:
+        raise OnyxError(
+            OnyxErrorCode.VALIDATION_ERROR,
+            "No models found from your OpenAI-compatible endpoint",
+        )
+
+    results: list[OpenAICompatibleFinalModelResponse] = []
+    for model in models:
+        try:
+            model_id = model.get("id", "")
+            model_name = model.get("name", model_id)
+
+            if not model_id:
+                continue
+
+            # Skip embedding models
+            if is_embedding_model(model_id):
+                continue
+
+            results.append(
+                OpenAICompatibleFinalModelResponse(
+                    name=model_id,
+                    display_name=model_name,
+                    max_input_tokens=model.get("context_length"),
+                    supports_image_input=infer_vision_support(model_id),
+                    supports_reasoning=is_reasoning_model(model_id, model_name),
+                )
+            )
+        except Exception as e:
+            logger.warning(
+                "Failed to parse OpenAI-compatible model entry",
+                extra={"error": str(e), "item": str(model)[:1000]},
+            )
+
+    if not results:
+        raise OnyxError(
+            OnyxErrorCode.VALIDATION_ERROR,
+            "No compatible models found from OpenAI-compatible endpoint",
+        )
+
+    sorted_results = sorted(results, key=lambda m: m.name.lower())
+
+    # Sync new models to DB if provider_name is specified
+    if request.provider_name:
+        _sync_fetched_models(
+            db_session=db_session,
+            provider_name=request.provider_name,
+            models=[
+                SyncModelEntry(
+                    name=r.name,
+                    display_name=r.display_name,
+                    max_input_tokens=r.max_input_tokens,
+                    supports_image_input=r.supports_image_input,
+                )
+                for r in sorted_results
+            ],
+            source_label="OpenAI Compatible",
+        )
+
+    return sorted_results
+
+
+def _get_openai_compatible_server_response(
+    api_base: str, api_key: str | None = None
+) -> dict:
+    """Perform GET to an OpenAI-compatible /v1/models and return parsed JSON."""
+    cleaned_api_base = api_base.strip().rstrip("/")
+    # Ensure we hit /v1/models
+    if cleaned_api_base.endswith("/v1"):
+        url = f"{cleaned_api_base}/models"
+    else:
+        url = f"{cleaned_api_base}/v1/models"
+
+    return _get_openai_compatible_models_response(
+        url=url,
+        source_name="OpenAI Compatible",
+        api_key=api_key,
+    )

backend/onyx/server/manage/llm/models.py

@@ -464,3 +464,18 @@ class BifrostFinalModelResponse(BaseModel):
     max_input_tokens: int | None
     supports_image_input: bool
     supports_reasoning: bool
+
+
+# OpenAI Compatible dynamic models fetch
+class OpenAICompatibleModelsRequest(BaseModel):
+    api_base: str
+    api_key: str | None = None
+    provider_name: str | None = None  # Optional: to save models to existing provider
+
+
+class OpenAICompatibleFinalModelResponse(BaseModel):
+    name: str  # Model ID (e.g. "meta-llama/Llama-3-8B-Instruct")
+    display_name: str  # Human-readable name from API
+    max_input_tokens: int | None
+    supports_image_input: bool
+    supports_reasoning: bool

backend/onyx/server/manage/llm/utils.py

@@ -26,6 +26,7 @@ DYNAMIC_LLM_PROVIDERS = frozenset(
         LlmProviderNames.OLLAMA_CHAT,
         LlmProviderNames.LM_STUDIO,
         LlmProviderNames.BIFROST,
+        LlmProviderNames.OPENAI_COMPATIBLE,
     }
 )
 

backend/tests/unit/onyx/context/search/federated/test_build_thread_text.py

@@ -0,0 +1,67 @@
+"""Tests for _build_thread_text function."""
+
+from unittest.mock import MagicMock
+from unittest.mock import patch
+
+from onyx.context.search.federated.slack_search import _build_thread_text
+
+
+def _make_msg(user: str, text: str, ts: str) -> dict[str, str]:
+    return {"user": user, "text": text, "ts": ts}
+
+
+class TestBuildThreadText:
+    """Verify _build_thread_text includes full thread replies up to cap."""
+
+    @patch("onyx.context.search.federated.slack_search.batch_get_user_profiles")
+    def test_includes_all_replies(self, mock_profiles: MagicMock) -> None:
+        """All replies within cap are included in output."""
+        mock_profiles.return_value = {}
+        messages = [
+            _make_msg("U1", "parent msg", "1000.0"),
+            _make_msg("U2", "reply 1", "1001.0"),
+            _make_msg("U3", "reply 2", "1002.0"),
+            _make_msg("U4", "reply 3", "1003.0"),
+        ]
+        result = _build_thread_text(messages, "token", "T123", MagicMock())
+        assert "parent msg" in result
+        assert "reply 1" in result
+        assert "reply 2" in result
+        assert "reply 3" in result
+        assert "..." not in result
+
+    @patch("onyx.context.search.federated.slack_search.batch_get_user_profiles")
+    def test_non_thread_returns_parent_only(self, mock_profiles: MagicMock) -> None:
+        """Single message (no replies) returns just the parent text."""
+        mock_profiles.return_value = {}
+        messages = [_make_msg("U1", "just a message", "1000.0")]
+        result = _build_thread_text(messages, "token", "T123", MagicMock())
+        assert "just a message" in result
+        assert "Replies:" not in result
+
+    @patch("onyx.context.search.federated.slack_search.batch_get_user_profiles")
+    def test_parent_always_first(self, mock_profiles: MagicMock) -> None:
+        """Thread parent message is always the first line of output."""
+        mock_profiles.return_value = {}
+        messages = [
+            _make_msg("U1", "I am the parent", "1000.0"),
+            _make_msg("U2", "I am a reply", "1001.0"),
+        ]
+        result = _build_thread_text(messages, "token", "T123", MagicMock())
+        parent_pos = result.index("I am the parent")
+        reply_pos = result.index("I am a reply")
+        assert parent_pos < reply_pos
+
+    @patch("onyx.context.search.federated.slack_search.batch_get_user_profiles")
+    def test_user_profiles_resolved(self, mock_profiles: MagicMock) -> None:
+        """User IDs in thread text are replaced with display names."""
+        mock_profiles.return_value = {"U1": "Alice", "U2": "Bob"}
+        messages = [
+            _make_msg("U1", "hello", "1000.0"),
+            _make_msg("U2", "world", "1001.0"),
+        ]
+        result = _build_thread_text(messages, "token", "T123", MagicMock())
+        assert "Alice" in result
+        assert "Bob" in result
+        assert "<@U1>" not in result
+        assert "<@U2>" not in result

backend/tests/unit/onyx/context/search/federated/test_url_override.py

@@ -0,0 +1,108 @@
+"""Tests for Slack URL parsing and direct thread fetch via URL override."""
+
+from unittest.mock import MagicMock
+from unittest.mock import patch
+
+from onyx.context.search.federated.models import DirectThreadFetch
+from onyx.context.search.federated.slack_search import _fetch_thread_from_url
+from onyx.context.search.federated.slack_search_utils import extract_slack_message_urls
+
+
+class TestExtractSlackMessageUrls:
+    """Verify URL parsing extracts channel_id and timestamp correctly."""
+
+    def test_standard_url(self) -> None:
+        query = "summarize https://mycompany.slack.com/archives/C097NBWMY8Y/p1775491616524769"
+        results = extract_slack_message_urls(query)
+        assert len(results) == 1
+        assert results[0] == ("C097NBWMY8Y", "1775491616.524769")
+
+    def test_multiple_urls(self) -> None:
+        query = (
+            "compare https://co.slack.com/archives/C111/p1234567890123456 "
+            "and https://co.slack.com/archives/C222/p9876543210987654"
+        )
+        results = extract_slack_message_urls(query)
+        assert len(results) == 2
+        assert results[0] == ("C111", "1234567890.123456")
+        assert results[1] == ("C222", "9876543210.987654")
+
+    def test_no_urls(self) -> None:
+        query = "what happened in #general last week?"
+        results = extract_slack_message_urls(query)
+        assert len(results) == 0
+
+    def test_non_slack_url_ignored(self) -> None:
+        query = "check https://google.com/archives/C111/p1234567890123456"
+        results = extract_slack_message_urls(query)
+        assert len(results) == 0
+
+    def test_timestamp_conversion(self) -> None:
+        """p prefix removed, dot inserted after 10th digit."""
+        query = "https://x.slack.com/archives/CABC123/p1775491616524769"
+        results = extract_slack_message_urls(query)
+        channel_id, ts = results[0]
+        assert channel_id == "CABC123"
+        assert ts == "1775491616.524769"
+        assert not ts.startswith("p")
+        assert "." in ts
+
+
+class TestFetchThreadFromUrl:
+    """Verify _fetch_thread_from_url calls conversations.replies and returns SlackMessage."""
+
+    @patch("onyx.context.search.federated.slack_search._build_thread_text")
+    @patch("onyx.context.search.federated.slack_search.WebClient")
+    def test_successful_fetch(
+        self, mock_webclient_cls: MagicMock, mock_build_thread: MagicMock
+    ) -> None:
+        mock_client = MagicMock()
+        mock_webclient_cls.return_value = mock_client
+
+        # Mock conversations_replies
+        mock_response = MagicMock()
+        mock_response.get.return_value = [
+            {"user": "U1", "text": "parent", "ts": "1775491616.524769"},
+            {"user": "U2", "text": "reply 1", "ts": "1775491617.000000"},
+            {"user": "U3", "text": "reply 2", "ts": "1775491618.000000"},
+        ]
+        mock_client.conversations_replies.return_value = mock_response
+
+        # Mock channel info
+        mock_ch_response = MagicMock()
+        mock_ch_response.get.return_value = {"name": "general"}
+        mock_client.conversations_info.return_value = mock_ch_response
+
+        mock_build_thread.return_value = (
+            "U1: parent\n\nReplies:\n\nU2: reply 1\n\nU3: reply 2"
+        )
+
+        fetch = DirectThreadFetch(
+            channel_id="C097NBWMY8Y", thread_ts="1775491616.524769"
+        )
+        result = _fetch_thread_from_url(fetch, "xoxp-token")
+
+        assert len(result.messages) == 1
+        msg = result.messages[0]
+        assert msg.channel_id == "C097NBWMY8Y"
+        assert msg.thread_id is None  # Prevents double-enrichment
+        assert msg.slack_score == 100000.0
+        assert "parent" in msg.text
+        mock_client.conversations_replies.assert_called_once_with(
+            channel="C097NBWMY8Y", ts="1775491616.524769"
+        )
+
+    @patch("onyx.context.search.federated.slack_search.WebClient")
+    def test_api_error_returns_empty(self, mock_webclient_cls: MagicMock) -> None:
+        from slack_sdk.errors import SlackApiError
+
+        mock_client = MagicMock()
+        mock_webclient_cls.return_value = mock_client
+        mock_client.conversations_replies.side_effect = SlackApiError(
+            message="channel_not_found",
+            response=MagicMock(status_code=404),
+        )
+
+        fetch = DirectThreadFetch(channel_id="CBAD", thread_ts="1234567890.123456")
+        result = _fetch_thread_from_url(fetch, "xoxp-token")
+        assert len(result.messages) == 0

backend/tests/unit/onyx/file_processing/test_pdf.py

@@ -12,6 +12,10 @@ dependency on pypdf internals (pypdf.generic).
 from io import BytesIO
 from pathlib import Path
 
+import pytest
+
+from onyx.file_processing import extract_file_text
+from onyx.file_processing.extract_file_text import count_pdf_embedded_images
 from onyx.file_processing.extract_file_text import pdf_to_text
 from onyx.file_processing.extract_file_text import read_pdf_file
 from onyx.file_processing.password_validation import is_pdf_protected
@@ -96,6 +100,80 @@ class TestReadPdfFile:
         # Returned list is empty when callback is used
         assert images == []
 
+    def test_image_cap_skips_images_above_limit(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        """When the embedded-image cap is exceeded, remaining images are skipped.
+
+        The cap protects the user-file-processing worker from OOMing on PDFs
+        with thousands of embedded images. Setting the cap to 0 should yield
+        zero extracted images even though the fixture has one.
+        """
+        monkeypatch.setattr(extract_file_text, "MAX_EMBEDDED_IMAGES_PER_FILE", 0)
+        _, _, images = read_pdf_file(_load("with_image.pdf"), extract_images=True)
+        assert images == []
+
+    def test_image_cap_at_limit_extracts_up_to_cap(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        """A cap >= image count behaves identically to the uncapped path."""
+        monkeypatch.setattr(extract_file_text, "MAX_EMBEDDED_IMAGES_PER_FILE", 100)
+        _, _, images = read_pdf_file(_load("with_image.pdf"), extract_images=True)
+        assert len(images) == 1
+
+    def test_image_cap_with_callback_stops_streaming_at_limit(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        """The cap also short-circuits the streaming callback path."""
+        monkeypatch.setattr(extract_file_text, "MAX_EMBEDDED_IMAGES_PER_FILE", 0)
+        collected: list[tuple[bytes, str]] = []
+
+        def callback(data: bytes, name: str) -> None:
+            collected.append((data, name))
+
+        read_pdf_file(
+            _load("with_image.pdf"), extract_images=True, image_callback=callback
+        )
+        assert collected == []
+
+
+# ── count_pdf_embedded_images ────────────────────────────────────────────
+
+
+class TestCountPdfEmbeddedImages:
+    def test_returns_count_for_normal_pdf(self) -> None:
+        assert count_pdf_embedded_images(_load("with_image.pdf"), cap=10) == 1
+
+    def test_short_circuits_above_cap(self) -> None:
+        # with_image.pdf has 1 image. cap=0 means "anything > 0 is over cap" —
+        # function returns on first increment as the over-cap sentinel.
+        assert count_pdf_embedded_images(_load("with_image.pdf"), cap=0) == 1
+
+    def test_returns_zero_for_pdf_without_images(self) -> None:
+        assert count_pdf_embedded_images(_load("simple.pdf"), cap=10) == 0
+
+    def test_returns_zero_for_invalid_pdf(self) -> None:
+        assert count_pdf_embedded_images(BytesIO(b"not a pdf"), cap=10) == 0
+
+    def test_returns_zero_for_password_locked_pdf(self) -> None:
+        # encrypted.pdf has an open password; we can't inspect without it, so
+        # the helper returns 0 — callers rely on the password-protected check
+        # that runs earlier in the upload pipeline.
+        assert count_pdf_embedded_images(_load("encrypted.pdf"), cap=10) == 0
+
+    def test_inspects_owner_password_only_pdf(self) -> None:
+        # owner_protected.pdf is encrypted but has no open password. It should
+        # decrypt with an empty string and count images normally. The fixture
+        # has zero images, so 0 is a real count (not the "bail on encrypted"
+        # path).
+        assert count_pdf_embedded_images(_load("owner_protected.pdf"), cap=10) == 0
+
+    def test_preserves_file_position(self) -> None:
+        pdf = _load("with_image.pdf")
+        pdf.seek(42)
+        count_pdf_embedded_images(pdf, cap=10)
+        assert pdf.tell() == 42
+
 
 # ── pdf_to_text ──────────────────────────────────────────────────────────
 

backend/tests/unit/onyx/server/scim/test_user_endpoints.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+from typing import Any
 from unittest.mock import MagicMock
 from unittest.mock import patch
 from uuid import uuid4
@@ -9,7 +10,9 @@ from uuid import uuid4
 from fastapi import Response
 from sqlalchemy.exc import IntegrityError
 
+from ee.onyx.server.scim.api import _check_seat_availability
 from ee.onyx.server.scim.api import _scim_name_to_str
+from ee.onyx.server.scim.api import _seat_lock_id_for_tenant
 from ee.onyx.server.scim.api import create_user
 from ee.onyx.server.scim.api import delete_user
 from ee.onyx.server.scim.api import get_user
@@ -741,3 +744,80 @@ class TestEmailCasePreservation:
         resource = parse_scim_user(result)
         assert resource.userName == "Alice@Example.COM"
         assert resource.emails[0].value == "Alice@Example.COM"
+
+
+class TestSeatLock:
+    """Tests for the advisory lock in _check_seat_availability."""
+
+    @patch("ee.onyx.server.scim.api.get_current_tenant_id", return_value="tenant_abc")
+    def test_acquires_advisory_lock_before_checking(
+        self,
+        _mock_tenant: MagicMock,
+        mock_dal: MagicMock,
+    ) -> None:
+        """The advisory lock must be acquired before the seat check runs."""
+        call_order: list[str] = []
+
+        def track_execute(stmt: Any, _params: Any = None) -> None:
+            if "pg_advisory_xact_lock" in str(stmt):
+                call_order.append("lock")
+
+        mock_dal.session.execute.side_effect = track_execute
+
+        with patch(
+            "ee.onyx.server.scim.api.fetch_ee_implementation_or_noop"
+        ) as mock_fetch:
+            mock_result = MagicMock()
+            mock_result.available = True
+            mock_fn = MagicMock(return_value=mock_result)
+            mock_fetch.return_value = mock_fn
+
+            def track_check(*_args: Any, **_kwargs: Any) -> Any:
+                call_order.append("check")
+                return mock_result
+
+            mock_fn.side_effect = track_check
+
+            _check_seat_availability(mock_dal)
+
+        assert call_order == ["lock", "check"]
+
+    @patch("ee.onyx.server.scim.api.get_current_tenant_id", return_value="tenant_xyz")
+    def test_lock_uses_tenant_scoped_key(
+        self,
+        _mock_tenant: MagicMock,
+        mock_dal: MagicMock,
+    ) -> None:
+        """The lock id must be derived from the tenant via _seat_lock_id_for_tenant."""
+        mock_result = MagicMock()
+        mock_result.available = True
+        mock_check = MagicMock(return_value=mock_result)
+
+        with patch(
+            "ee.onyx.server.scim.api.fetch_ee_implementation_or_noop",
+            return_value=mock_check,
+        ):
+            _check_seat_availability(mock_dal)
+
+        mock_dal.session.execute.assert_called_once()
+        params = mock_dal.session.execute.call_args[0][1]
+        assert params["lock_id"] == _seat_lock_id_for_tenant("tenant_xyz")
+
+    def test_seat_lock_id_is_stable_and_tenant_scoped(self) -> None:
+        """Lock id must be deterministic and differ across tenants."""
+        assert _seat_lock_id_for_tenant("t1") == _seat_lock_id_for_tenant("t1")
+        assert _seat_lock_id_for_tenant("t1") != _seat_lock_id_for_tenant("t2")
+
+    def test_no_lock_when_ee_absent(
+        self,
+        mock_dal: MagicMock,
+    ) -> None:
+        """No advisory lock should be acquired when the EE check is absent."""
+        with patch(
+            "ee.onyx.server.scim.api.fetch_ee_implementation_or_noop",
+            return_value=None,
+        ):
+            result = _check_seat_availability(mock_dal)
+
+        assert result is None
+        mock_dal.session.execute.assert_not_called()

web/src/app/admin/configuration/llm/page.tsx

@@ -1,7 +1 @@
-"use client";
-
-import LLMConfigurationPage from "@/refresh-pages/admin/LLMConfigurationPage";
-
-export default function Page() {
-  return <LLMConfigurationPage />;
-}
+export { default } from "@/refresh-pages/admin/LLMProviderConfigurationPage";

web/src/app/admin/configuration/llm/utils.ts

@@ -32,8 +32,10 @@ import {
   OpenRouterFetchParams,
   LiteLLMProxyFetchParams,
   BifrostFetchParams,
+  OpenAICompatibleFetchParams,
+  OpenAICompatibleModelResponse,
 } from "@/interfaces/llm";
-import { SvgAws, SvgBifrost, SvgOpenrouter } from "@opal/icons";
+import { SvgAws, SvgBifrost, SvgOpenrouter, SvgPlug } from "@opal/icons";
 
 // Aggregator providers that host models from multiple vendors
 export const AGGREGATOR_PROVIDERS = new Set([
@@ -44,6 +46,7 @@ export const AGGREGATOR_PROVIDERS = new Set([
   "lm_studio",
   "litellm_proxy",
   "bifrost",
+  "openai_compatible",
   "vertex_ai",
 ]);
 
@@ -82,6 +85,7 @@ export const getProviderIcon = (
     openrouter: SvgOpenrouter,
     litellm_proxy: LiteLLMIcon,
     bifrost: SvgBifrost,
+    openai_compatible: SvgPlug,
     vertex_ai: GeminiIcon,
   };
 
@@ -411,6 +415,64 @@ export const fetchBifrostModels = async (
   }
 };
 
+/**
+ * Fetches models from a generic OpenAI-compatible server.
+ * Uses snake_case params to match API structure.
+ */
+export const fetchOpenAICompatibleModels = async (
+  params: OpenAICompatibleFetchParams
+): Promise<{ models: ModelConfiguration[]; error?: string }> => {
+  const apiBase = params.api_base;
+  if (!apiBase) {
+    return { models: [], error: "API Base is required" };
+  }
+
+  try {
+    const response = await fetch(
+      "/api/admin/llm/openai-compatible/available-models",
+      {
+        method: "POST",
+        headers: {
+          "Content-Type": "application/json",
+        },
+        body: JSON.stringify({
+          api_base: apiBase,
+          api_key: params.api_key,
+          provider_name: params.provider_name,
+        }),
+        signal: params.signal,
+      }
+    );
+
+    if (!response.ok) {
+      let errorMessage = "Failed to fetch models";
+      try {
+        const errorData = await response.json();
+        errorMessage = errorData.detail || errorData.message || errorMessage;
+      } catch {
+        // ignore JSON parsing errors
+      }
+      return { models: [], error: errorMessage };
+    }
+
+    const data: OpenAICompatibleModelResponse[] = await response.json();
+    const models: ModelConfiguration[] = data.map((modelData) => ({
+      name: modelData.name,
+      display_name: modelData.display_name,
+      is_visible: true,
+      max_input_tokens: modelData.max_input_tokens,
+      supports_image_input: modelData.supports_image_input,
+      supports_reasoning: modelData.supports_reasoning,
+    }));
+
+    return { models };
+  } catch (error) {
+    const errorMessage =
+      error instanceof Error ? error.message : "Unknown error";
+    return { models: [], error: errorMessage };
+  }
+};
+
 /**
  * Fetches LiteLLM Proxy models directly without any form state dependencies.
  * Uses snake_case params to match API structure.
@@ -531,6 +593,13 @@ export const fetchModels = async (
         provider_name: formValues.name,
         signal,
       });
+    case LLMProviderName.OPENAI_COMPATIBLE:
+      return fetchOpenAICompatibleModels({
+        api_base: formValues.api_base,
+        api_key: formValues.api_key,
+        provider_name: formValues.name,
+        signal,
+      });
     default:
       return { models: [], error: `Unknown provider: ${providerName}` };
   }
@@ -545,6 +614,7 @@ export function canProviderFetchModels(providerName?: string) {
     case LLMProviderName.OPENROUTER:
     case LLMProviderName.LITELLM_PROXY:
     case LLMProviderName.BIFROST:
+    case LLMProviderName.OPENAI_COMPATIBLE:
       return true;
     default:
       return false;

web/src/app/craft/onboarding/components/BuildOnboardingModal.tsx

@@ -24,7 +24,6 @@ import {
 } from "@/app/craft/onboarding/constants";
 import { LLMProviderDescriptor } from "@/interfaces/llm";
 import { LLM_PROVIDERS_ADMIN_URL } from "@/lib/llmConfig/constants";
-import { buildOnboardingInitialValues as buildInitialValues } from "@/sections/modals/llmConfig/utils";
 import { testApiKeyHelper } from "@/sections/modals/llmConfig/svc";
 import OnboardingInfoPages from "@/app/craft/onboarding/components/OnboardingInfoPages";
 import OnboardingUserInfo from "@/app/craft/onboarding/components/OnboardingUserInfo";
@@ -221,10 +220,8 @@ export default function BuildOnboardingModal({
     setConnectionStatus("testing");
     setErrorMessage("");
 
-    const baseValues = buildInitialValues();
     const providerName = `build-mode-${currentProviderConfig.providerName}`;
     const payload = {
-      ...baseValues,
       name: providerName,
       provider: currentProviderConfig.providerName,
       api_key: apiKey,

web/src/app/craft/v1/configure/components/UserLibraryModal.tsx

@@ -272,6 +272,22 @@ export default function UserLibraryModal({
                   </Disabled>
                 </Section>
 
+                {/* The exact cap is controlled by the backend env var
+                    MAX_EMBEDDED_IMAGES_PER_FILE (default 500). This copy is
+                    deliberately vague so it doesn't drift if the limit is
+                    tuned per-deployment; the precise number is surfaced in
+                    the rejection error the server returns. */}
+                <Section
+                  flexDirection="row"
+                  justifyContent="end"
+                  padding={0.5}
+                  height="fit"
+                >
+                  <Text secondaryBody text03>
+                    PDFs with many embedded images may be rejected.
+                  </Text>
+                </Section>
+
                 {isLoading ? (
                   <Section padding={2} height="fit">
                     <Text secondaryBody text03>

web/src/hooks/useLLMProviders.ts

@@ -4,6 +4,7 @@ import useSWR from "swr";
 import { errorHandlingFetcher } from "@/lib/fetcher";
 import {
   LLMProviderDescriptor,
+  LLMProviderName,
   LLMProviderResponse,
   LLMProviderView,
   WellKnownLLMProviderDescriptor,
@@ -136,14 +137,12 @@ export function useAdminLLMProviders() {
  * Used inside individual provider modals to pre-populate model lists
  * before the user has entered credentials.
  *
- * @param providerEndpoint - The provider's API endpoint name (e.g. "openai", "anthropic").
+ * @param providerName - The provider's API endpoint name (e.g. "openai", "anthropic").
  *   Pass `null` to suppress the request.
  */
-export function useWellKnownLLMProvider(providerEndpoint: string | null) {
+export function useWellKnownLLMProvider(providerName: LLMProviderName) {
   const { data, error, isLoading } = useSWR<WellKnownLLMProviderDescriptor>(
-    providerEndpoint
-      ? `/api/admin/llm/built-in/options/${providerEndpoint}`
-      : null,
+    providerName ? `/api/admin/llm/built-in/options/${providerName}` : null,
     errorHandlingFetcher,
     {
       revalidateOnFocus: false,

web/src/interfaces/llm.ts

@@ -14,6 +14,7 @@ export enum LLMProviderName {
   BEDROCK = "bedrock",
   LITELLM_PROXY = "litellm_proxy",
   BIFROST = "bifrost",
+  OPENAI_COMPATIBLE = "openai_compatible",
   CUSTOM = "custom",
 }
 
@@ -123,14 +124,11 @@ export interface LLMProviderFormProps {
   shouldMarkAsDefault?: boolean;
   open?: boolean;
   onOpenChange?: (open: boolean) => void;
-
-  /** The current default model name for this provider (from the global default). */
-  defaultModelName?: string;
+  /** Called after successful provider creation/update. */
+  onSuccess?: () => void | Promise<void>;
 
   // Onboarding-specific (only when variant === "onboarding")
-  onboardingState?: OnboardingState;
   onboardingActions?: OnboardingActions;
-  llmDescriptor?: WellKnownLLMProviderDescriptor;
 }
 
 // Param types for model fetching functions - use snake_case to match API structure
@@ -181,6 +179,21 @@ export interface BifrostModelResponse {
   supports_reasoning: boolean;
 }
 
+export interface OpenAICompatibleFetchParams {
+  api_base?: string;
+  api_key?: string;
+  provider_name?: string;
+  signal?: AbortSignal;
+}
+
+export interface OpenAICompatibleModelResponse {
+  name: string;
+  display_name: string;
+  max_input_tokens: number | null;
+  supports_image_input: boolean;
+  supports_reasoning: boolean;
+}
+
 export interface VertexAIFetchParams {
   model_configurations?: ModelConfiguration[];
 }
@@ -199,5 +212,6 @@ export type FetchModelsParams =
   | OpenRouterFetchParams
   | LiteLLMProxyFetchParams
   | BifrostFetchParams
+  | OpenAICompatibleFetchParams
   | VertexAIFetchParams
   | LMStudioFetchParams;

web/src/layouts/input-layouts.tsx

@@ -1,8 +1,9 @@
 "use client";
 
-import type { RichStr } from "@opal/types";
+import type { RichStr, WithoutStyles } from "@opal/types";
 import { resolveStr } from "@opal/components/text/InlineMarkdown";
 import Text from "@/refresh-components/texts/Text";
+import Separator from "@/refresh-components/Separator";
 import { SvgXOctagon, SvgAlertCircle } from "@opal/icons";
 import { useField, useFormikContext } from "formik";
 import { Section } from "@/layouts/general-layouts";
@@ -234,9 +235,27 @@ function ErrorTextLayout({ children, type = "error" }: ErrorTextLayoutProps) {
   );
 }
 
+/**
+ * FieldSeparator - A horizontal rule with inline padding, used to visually separate field groups.
+ */
+function FieldSeparator() {
+  return <Separator noPadding className="p-2" />;
+}
+
+/**
+ * FieldPadder -  Wraps a field in standard horizontal + vertical padding (`p-2 w-full`).
+ */
+type FieldPadderProps = WithoutStyles<React.HTMLAttributes<HTMLDivElement>>;
+function FieldPadder(props: FieldPadderProps) {
+  return <div {...props} className="p-2 w-full" />;
+}
+
 export {
   VerticalInputLayout as Vertical,
   HorizontalInputLayout as Horizontal,
   ErrorLayout as Error,
   ErrorTextLayout,
+  FieldSeparator,
+  FieldPadder,
+  type FieldPadderProps,
 };

web/src/lib/llmConfig/providers.ts

@@ -8,6 +8,7 @@ import {
   SvgCloud,
   SvgAws,
   SvgOpenrouter,
+  SvgPlug,
   SvgServer,
   SvgAzure,
   SvgGemini,
@@ -28,6 +29,7 @@ const PROVIDER_ICONS: Record<string, IconFunctionComponent> = {
   [LLMProviderName.OPENROUTER]: SvgOpenrouter,
   [LLMProviderName.LM_STUDIO]: SvgLmStudio,
   [LLMProviderName.BIFROST]: SvgBifrost,
+  [LLMProviderName.OPENAI_COMPATIBLE]: SvgPlug,
 
   // fallback
   [LLMProviderName.CUSTOM]: SvgServer,
@@ -45,6 +47,7 @@ const PROVIDER_PRODUCT_NAMES: Record<string, string> = {
   [LLMProviderName.OPENROUTER]: "OpenRouter",
   [LLMProviderName.LM_STUDIO]: "LM Studio",
   [LLMProviderName.BIFROST]: "Bifrost",
+  [LLMProviderName.OPENAI_COMPATIBLE]: "OpenAI Compatible",
 
   // fallback
   [LLMProviderName.CUSTOM]: "Custom Models",
@@ -62,6 +65,7 @@ const PROVIDER_DISPLAY_NAMES: Record<string, string> = {
   [LLMProviderName.OPENROUTER]: "OpenRouter",
   [LLMProviderName.LM_STUDIO]: "LM Studio",
   [LLMProviderName.BIFROST]: "Bifrost",
+  [LLMProviderName.OPENAI_COMPATIBLE]: "OpenAI Compatible",
 
   // fallback
   [LLMProviderName.CUSTOM]: "Other providers or self-hosted",

web/src/refresh-pages/admin/LLMProviderConfigurationPage.tsx

@@ -31,6 +31,7 @@ import ConfirmationModalLayout from "@/refresh-components/layouts/ConfirmationMo
 import { useCreateModal } from "@/refresh-components/contexts/ModalContext";
 import Separator from "@/refresh-components/Separator";
 import {
+  LLMProviderName,
   LLMProviderView,
   WellKnownLLMProviderDescriptor,
 } from "@/interfaces/llm";
@@ -43,9 +44,10 @@ import BedrockModal from "@/sections/modals/llmConfig/BedrockModal";
 import VertexAIModal from "@/sections/modals/llmConfig/VertexAIModal";
 import OpenRouterModal from "@/sections/modals/llmConfig/OpenRouterModal";
 import CustomModal from "@/sections/modals/llmConfig/CustomModal";
-import LMStudioForm from "@/sections/modals/llmConfig/LMStudioForm";
+import LMStudioModal from "@/sections/modals/llmConfig/LMStudioModal";
 import LiteLLMProxyModal from "@/sections/modals/llmConfig/LiteLLMProxyModal";
 import BifrostModal from "@/sections/modals/llmConfig/BifrostModal";
+import OpenAICompatibleModal from "@/sections/modals/llmConfig/OpenAICompatibleModal";
 import { Section } from "@/layouts/general-layouts";
 
 const route = ADMIN_ROUTES.LLM_MODELS;
@@ -57,16 +59,18 @@ const route = ADMIN_ROUTES.LLM_MODELS;
 // Client-side ordering for the "Add Provider" cards. The backend may return
 // wellKnownLLMProviders in an arbitrary order, so we sort explicitly here.
 const PROVIDER_DISPLAY_ORDER: string[] = [
-  "openai",
-  "anthropic",
-  "vertex_ai",
-  "bedrock",
-  "azure",
-  "litellm_proxy",
-  "ollama_chat",
-  "openrouter",
-  "lm_studio",
-  "bifrost",
+  LLMProviderName.OPENAI,
+  LLMProviderName.ANTHROPIC,
+  LLMProviderName.VERTEX_AI,
+  LLMProviderName.BEDROCK,
+  LLMProviderName.AZURE,
+  "litellm",
+  LLMProviderName.LITELLM_PROXY,
+  LLMProviderName.OLLAMA_CHAT,
+  LLMProviderName.OPENROUTER,
+  LLMProviderName.LM_STUDIO,
+  LLMProviderName.BIFROST,
+  LLMProviderName.OPENAI_COMPATIBLE,
 ];
 
 const PROVIDER_MODAL_MAP: Record<
@@ -127,7 +131,7 @@ const PROVIDER_MODAL_MAP: Record<
     />
   ),
   lm_studio: (d, open, onOpenChange) => (
-    <LMStudioForm
+    <LMStudioModal
       shouldMarkAsDefault={d}
       open={open}
       onOpenChange={onOpenChange}
@@ -147,6 +151,13 @@ const PROVIDER_MODAL_MAP: Record<
       onOpenChange={onOpenChange}
     />
   ),
+  openai_compatible: (d, open, onOpenChange) => (
+    <OpenAICompatibleModal
+      shouldMarkAsDefault={d}
+      open={open}
+      onOpenChange={onOpenChange}
+    />
+  ),
 };
 
 // ============================================================================
@@ -341,7 +352,7 @@ function NewCustomProviderCard({
 // LLMConfigurationPage — main page component
 // ============================================================================
 
-export default function LLMConfigurationPage() {
+export default function LLMProviderConfigurationPage() {
   const { mutate } = useSWRConfig();
   const { llmProviders: existingLlmProviders, defaultText } =
     useAdminLLMProviders();

web/src/sections/modals/llmConfig/AnthropicModal.tsx

@@ -1,33 +1,23 @@
 "use client";
 
-import { useState } from "react";
 import { useSWRConfig } from "swr";
-import { Formik } from "formik";
-import { LLMProviderFormProps } from "@/interfaces/llm";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
+import { LLMProviderFormProps, LLMProviderName } from "@/interfaces/llm";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
 } from "@/sections/modals/llmConfig/utils";
-import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
   APIKeyField,
-  ModelsField,
+  ModelSelectionField,
   DisplayNameField,
-  ModelsAccessField,
-  FieldSeparator,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
-
-const ANTHROPIC_PROVIDER_NAME = "anthropic";
-const DEFAULT_DEFAULT_MODEL_NAME = "claude-sonnet-4-5";
+import * as InputLayouts from "@/layouts/input-layouts";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
+import { toast } from "@/hooks/useToast";
 
 export default function AnthropicModal({
   variant = "llm-configuration",
@@ -35,143 +25,78 @@ export default function AnthropicModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
   const isOnboarding = variant === "onboarding";
-  const [isTesting, setIsTesting] = useState(false);
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(
-    ANTHROPIC_PROVIDER_NAME
+
+  const initialValues = useInitialValues(
+    isOnboarding,
+    LLMProviderName.ANTHROPIC,
+    existingLlmProvider
   );
 
-  if (open === false) return null;
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiKey: true,
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues = isOnboarding
-    ? {
-        ...buildOnboardingInitialValues(),
-        name: ANTHROPIC_PROVIDER_NAME,
-        provider: ANTHROPIC_PROVIDER_NAME,
-        api_key: "",
-        default_model_name: DEFAULT_DEFAULT_MODEL_NAME,
-      }
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_key: existingLlmProvider?.api_key ?? "",
-        api_base: existingLlmProvider?.api_base ?? undefined,
-        default_model_name:
-          (defaultModelName &&
-          modelConfigurations.some((m) => m.name === defaultModelName)
-            ? defaultModelName
-            : undefined) ??
-          wellKnownLLMProvider?.recommended_default_model?.name ??
-          DEFAULT_DEFAULT_MODEL_NAME,
-        is_auto_mode: existingLlmProvider?.is_auto_mode ?? true,
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_key: Yup.string().required("API Key is required"),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_key: Yup.string().required("API Key is required"),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.ANTHROPIC}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            (wellKnownLLMProvider ?? llmDescriptor)?.known_models ?? [];
-
-          await submitOnboardingProvider({
-            providerName: ANTHROPIC_PROVIDER_NAME,
-            payload: {
-              ...values,
-              model_configurations: modelConfigsToUse,
-              is_auto_mode:
-                values.default_model_name === DEFAULT_DEFAULT_MODEL_NAME,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: ANTHROPIC_PROVIDER_NAME,
-            values,
-            initialValues,
-            modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.ANTHROPIC,
+          values,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <LLMConfigurationModalWrapper
-          providerEndpoint={ANTHROPIC_PROVIDER_NAME}
-          existingProviderName={existingLlmProvider?.name}
-          onClose={onClose}
-          isFormValid={formikProps.isValid}
-          isDirty={formikProps.dirty}
-          isTesting={isTesting}
-          isSubmitting={formikProps.isSubmitting}
-        >
-          <APIKeyField providerName="Anthropic" />
+      <APIKeyField providerName="Anthropic" />
 
-          {!isOnboarding && (
-            <>
-              <FieldSeparator />
-              <DisplayNameField disabled={!!existingLlmProvider} />
-            </>
-          )}
-
-          <FieldSeparator />
-          {isOnboarding ? (
-            <SingleDefaultModelField placeholder="E.g. claude-sonnet-4-5" />
-          ) : (
-            <ModelsField
-              modelConfigurations={modelConfigurations}
-              formikProps={formikProps}
-              recommendedDefaultModel={
-                wellKnownLLMProvider?.recommended_default_model ?? null
-              }
-              shouldShowAutoUpdateToggle={true}
-            />
-          )}
-
-          {!isOnboarding && (
-            <>
-              <FieldSeparator />
-              <ModelsAccessField formikProps={formikProps} />
-            </>
-          )}
-        </LLMConfigurationModalWrapper>
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <DisplayNameField disabled={!!existingLlmProvider} />
+        </>
       )}
-    </Formik>
+
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField shouldShowAutoUpdateToggle={true} />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
+        </>
+      )}
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/AzureModal.tsx

@@ -1,41 +1,35 @@
 "use client";
 
-import { useState } from "react";
 import { useSWRConfig } from "swr";
-import { Formik } from "formik";
+import { useFormikContext } from "formik";
 import InputTypeInField from "@/refresh-components/form/InputTypeInField";
 import * as InputLayouts from "@/layouts/input-layouts";
-import { LLMProviderFormProps, LLMProviderView } from "@/interfaces/llm";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  LLMProviderFormProps,
+  LLMProviderName,
+  LLMProviderView,
+} from "@/interfaces/llm";
+import * as Yup from "yup";
+import {
+  useInitialValues,
+  buildValidationSchema,
   BaseLLMFormValues,
 } from "@/sections/modals/llmConfig/utils";
-import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
   APIKeyField,
   DisplayNameField,
-  FieldSeparator,
-  FieldWrapper,
-  ModelsAccessField,
-  ModelsField,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModelSelectionField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
 import {
   isValidAzureTargetUri,
   parseAzureTargetUri,
 } from "@/lib/azureTargetUri";
 import { toast } from "@/hooks/useToast";
-
-const AZURE_PROVIDER_NAME = "azure";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
 
 interface AzureModalValues extends BaseLLMFormValues {
   api_key: string;
@@ -45,6 +39,33 @@ interface AzureModalValues extends BaseLLMFormValues {
   deployment_name?: string;
 }
 
+function AzureModelSelection() {
+  const formikProps = useFormikContext<AzureModalValues>();
+  return (
+    <ModelSelectionField
+      shouldShowAutoUpdateToggle={false}
+      onAddModel={(modelName) => {
+        const current = formikProps.values.model_configurations;
+        if (current.some((m) => m.name === modelName)) return;
+        const updated = [
+          ...current,
+          {
+            name: modelName,
+            is_visible: true,
+            max_input_tokens: null,
+            supports_image_input: false,
+            supports_reasoning: false,
+          },
+        ];
+        formikProps.setFieldValue("model_configurations", updated);
+        if (!formikProps.values.test_model_name) {
+          formikProps.setFieldValue("test_model_name", modelName);
+        }
+      }}
+    />
+  );
+}
+
 function buildTargetUri(existingLlmProvider?: LLMProviderView): string {
   if (!existingLlmProvider?.api_base || !existingLlmProvider?.api_version) {
     return "";
@@ -81,160 +102,105 @@ export default function AzureModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
   const isOnboarding = variant === "onboarding";
-  const [isTesting, setIsTesting] = useState(false);
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(AZURE_PROVIDER_NAME);
 
-  if (open === false) return null;
+  const initialValues: AzureModalValues = {
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.AZURE,
+      existingLlmProvider
+    ),
+    target_uri: buildTargetUri(existingLlmProvider),
+  } as AzureModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiKey: true,
+    extra: {
+      target_uri: Yup.string()
+        .required("Target URI is required")
+        .test(
+          "valid-target-uri",
+          "Target URI must be a valid URL with api-version query parameter and either a deployment name in the path or /openai/responses",
+          (value) => (value ? isValidAzureTargetUri(value) : false)
+        ),
+    },
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: AzureModalValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: AZURE_PROVIDER_NAME,
-        provider: AZURE_PROVIDER_NAME,
-        api_key: "",
-        target_uri: "",
-        default_model_name: "",
-      } as AzureModalValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_key: existingLlmProvider?.api_key ?? "",
-        target_uri: buildTargetUri(existingLlmProvider),
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_key: Yup.string().required("API Key is required"),
-        target_uri: Yup.string()
-          .required("Target URI is required")
-          .test(
-            "valid-target-uri",
-            "Target URI must be a valid URL with api-version query parameter and either a deployment name in the path or /openai/responses",
-            (value) => (value ? isValidAzureTargetUri(value) : false)
-          ),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_key: Yup.string().required("API Key is required"),
-        target_uri: Yup.string()
-          .required("Target URI is required")
-          .test(
-            "valid-target-uri",
-            "Target URI must be a valid URL with api-version query parameter and either a deployment name in the path or /openai/responses",
-            (value) => (value ? isValidAzureTargetUri(value) : false)
-          ),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.AZURE}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
         const processedValues = processValues(values);
 
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            (wellKnownLLMProvider ?? llmDescriptor)?.known_models ?? [];
-
-          await submitOnboardingProvider({
-            providerName: AZURE_PROVIDER_NAME,
-            payload: {
-              ...processedValues,
-              model_configurations: modelConfigsToUse,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: AZURE_PROVIDER_NAME,
-            values: processedValues,
-            initialValues,
-            modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.AZURE,
+          values: processedValues,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <LLMConfigurationModalWrapper
-          providerEndpoint={AZURE_PROVIDER_NAME}
-          existingProviderName={existingLlmProvider?.name}
-          onClose={onClose}
-          isFormValid={formikProps.isValid}
-          isDirty={formikProps.dirty}
-          isTesting={isTesting}
-          isSubmitting={formikProps.isSubmitting}
+      <InputLayouts.FieldPadder>
+        <InputLayouts.Vertical
+          name="target_uri"
+          title="Target URI"
+          subDescription="Paste your endpoint target URI from Azure OpenAI (including API endpoint base, deployment name, and API version)."
         >
-          <FieldWrapper>
-            <InputLayouts.Vertical
-              name="target_uri"
-              title="Target URI"
-              subDescription="Paste your endpoint target URI from Azure OpenAI (including API endpoint base, deployment name, and API version)."
-            >
-              <InputTypeInField
-                name="target_uri"
-                placeholder="https://your-resource.cognitiveservices.azure.com/openai/deployments/deployment-name/chat/completions?api-version=2025-01-01-preview"
-              />
-            </InputLayouts.Vertical>
-          </FieldWrapper>
+          <InputTypeInField
+            name="target_uri"
+            placeholder="https://your-resource.cognitiveservices.azure.com/openai/deployments/deployment-name/chat/completions?api-version=2025-01-01-preview"
+          />
+        </InputLayouts.Vertical>
+      </InputLayouts.FieldPadder>
 
-          <APIKeyField providerName="Azure" />
+      <APIKeyField providerName="Azure" />
 
-          {!isOnboarding && (
-            <>
-              <FieldSeparator />
-              <DisplayNameField disabled={!!existingLlmProvider} />
-            </>
-          )}
-
-          <FieldSeparator />
-
-          {isOnboarding ? (
-            <SingleDefaultModelField placeholder="E.g. gpt-4o" />
-          ) : (
-            <ModelsField
-              modelConfigurations={modelConfigurations}
-              formikProps={formikProps}
-              recommendedDefaultModel={null}
-              shouldShowAutoUpdateToggle={false}
-            />
-          )}
-
-          {!isOnboarding && (
-            <>
-              <FieldSeparator />
-              <ModelsAccessField formikProps={formikProps} />
-            </>
-          )}
-        </LLMConfigurationModalWrapper>
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <DisplayNameField disabled={!!existingLlmProvider} />
+        </>
       )}
-    </Formik>
+
+      <InputLayouts.FieldSeparator />
+      <AzureModelSelection />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
+        </>
+      )}
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/BedrockModal.tsx

@@ -1,8 +1,8 @@
 "use client";
 
-import { useState, useEffect } from "react";
+import { useEffect } from "react";
 import { useSWRConfig } from "swr";
-import { Formik, FormikProps } from "formik";
+import { useFormikContext } from "formik";
 import InputTypeInField from "@/refresh-components/form/InputTypeInField";
 import InputSelectField from "@/refresh-components/form/InputSelectField";
 import InputSelect from "@/refresh-components/inputs/InputSelect";
@@ -10,30 +10,22 @@ import * as InputLayouts from "@/layouts/input-layouts";
 import PasswordInputTypeInField from "@/refresh-components/form/PasswordInputTypeInField";
 import {
   LLMProviderFormProps,
+  LLMProviderName,
   LLMProviderView,
-  ModelConfiguration,
 } from "@/interfaces/llm";
 import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
   BaseLLMFormValues,
 } from "@/sections/modals/llmConfig/utils";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
-import {
-  ModelsField,
+  ModelSelectionField,
   DisplayNameField,
-  FieldSeparator,
-  FieldWrapper,
-  ModelsAccessField,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
 import { fetchBedrockModels } from "@/app/admin/configuration/llm/utils";
 import { Card } from "@opal/components";
@@ -41,9 +33,9 @@ import { Section } from "@/layouts/general-layouts";
 import { SvgAlertCircle } from "@opal/icons";
 import { Content } from "@opal/layouts";
 import { toast } from "@/hooks/useToast";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
 import useOnMount from "@/hooks/useOnMount";
 
-const BEDROCK_PROVIDER_NAME = "bedrock";
 const AWS_REGION_OPTIONS = [
   { name: "us-east-1", value: "us-east-1" },
   { name: "us-east-2", value: "us-east-2" },
@@ -79,26 +71,15 @@ interface BedrockModalValues extends BaseLLMFormValues {
 }
 
 interface BedrockModalInternalsProps {
-  formikProps: FormikProps<BedrockModalValues>;
   existingLlmProvider: LLMProviderView | undefined;
-  fetchedModels: ModelConfiguration[];
-  setFetchedModels: (models: ModelConfiguration[]) => void;
-  modelConfigurations: ModelConfiguration[];
-  isTesting: boolean;
-  onClose: () => void;
   isOnboarding: boolean;
 }
 
 function BedrockModalInternals({
-  formikProps,
   existingLlmProvider,
-  fetchedModels,
-  setFetchedModels,
-  modelConfigurations,
-  isTesting,
-  onClose,
   isOnboarding,
 }: BedrockModalInternalsProps) {
+  const formikProps = useFormikContext<BedrockModalValues>();
   const authMethod = formikProps.values.custom_config?.BEDROCK_AUTH_METHOD;
 
   useEffect(() => {
@@ -115,11 +96,6 @@ function BedrockModalInternals({
     // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [authMethod]);
 
-  const currentModels =
-    fetchedModels.length > 0
-      ? fetchedModels
-      : existingLlmProvider?.model_configurations || modelConfigurations;
-
   const isAuthComplete =
     authMethod === AUTH_METHOD_IAM ||
     (authMethod === AUTH_METHOD_ACCESS_KEY &&
@@ -139,12 +115,12 @@ function BedrockModalInternals({
         formikProps.values.custom_config?.AWS_SECRET_ACCESS_KEY,
       aws_bearer_token_bedrock:
         formikProps.values.custom_config?.AWS_BEARER_TOKEN_BEDROCK,
-      provider_name: existingLlmProvider?.name,
+      provider_name: LLMProviderName.BEDROCK,
     });
     if (error) {
       throw new Error(error);
     }
-    setFetchedModels(models);
+    formikProps.setFieldValue("model_configurations", models);
   };
 
   // Auto-fetch models on initial load when editing an existing provider
@@ -159,16 +135,8 @@ function BedrockModalInternals({
   });
 
   return (
-    <LLMConfigurationModalWrapper
-      providerEndpoint={BEDROCK_PROVIDER_NAME}
-      existingProviderName={existingLlmProvider?.name}
-      onClose={onClose}
-      isFormValid={formikProps.isValid}
-      isDirty={formikProps.dirty}
-      isTesting={isTesting}
-      isSubmitting={formikProps.isSubmitting}
-    >
-      <FieldWrapper>
+    <>
+      <InputLayouts.FieldPadder>
         <Section gap={1}>
           <InputLayouts.Vertical
             name={FIELD_AWS_REGION_NAME}
@@ -222,7 +190,7 @@ function BedrockModalInternals({
             </InputSelect>
           </InputLayouts.Vertical>
         </Section>
-      </FieldWrapper>
+      </InputLayouts.FieldPadder>
 
       {authMethod === AUTH_METHOD_ACCESS_KEY && (
         <Card backgroundVariant="light" borderVariant="none" sizeVariant="lg">
@@ -250,7 +218,7 @@ function BedrockModalInternals({
       )}
 
       {authMethod === AUTH_METHOD_IAM && (
-        <FieldWrapper>
+        <InputLayouts.FieldPadder>
           <Card backgroundVariant="none" borderVariant="solid">
             <Content
               icon={SvgAlertCircle}
@@ -259,7 +227,7 @@ function BedrockModalInternals({
               sizePreset="main-ui"
             />
           </Card>
-        </FieldWrapper>
+        </InputLayouts.FieldPadder>
       )}
 
       {authMethod === AUTH_METHOD_LONG_TERM_API_KEY && (
@@ -280,32 +248,24 @@ function BedrockModalInternals({
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
+          <InputLayouts.FieldSeparator />
           <DisplayNameField disabled={!!existingLlmProvider} />
         </>
       )}
 
-      <FieldSeparator />
-
-      {isOnboarding ? (
-        <SingleDefaultModelField placeholder="E.g. us.anthropic.claude-sonnet-4-5-v1" />
-      ) : (
-        <ModelsField
-          modelConfigurations={currentModels}
-          formikProps={formikProps}
-          recommendedDefaultModel={null}
-          shouldShowAutoUpdateToggle={false}
-          onRefetch={isFetchDisabled ? undefined : handleFetchModels}
-        />
-      )}
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField
+        shouldShowAutoUpdateToggle={false}
+        onRefetch={isFetchDisabled ? undefined : handleFetchModels}
+      />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
-          <ModelsAccessField formikProps={formikProps} />
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
         </>
       )}
-    </LLMConfigurationModalWrapper>
+    </>
   );
 }
 
@@ -315,86 +275,54 @@ export default function BedrockModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
-  const [fetchedModels, setFetchedModels] = useState<ModelConfiguration[]>([]);
-  const [isTesting, setIsTesting] = useState(false);
   const isOnboarding = variant === "onboarding";
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(
-    BEDROCK_PROVIDER_NAME
-  );
 
-  if (open === false) return null;
+  const initialValues: BedrockModalValues = {
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.BEDROCK,
+      existingLlmProvider
+    ),
+    custom_config: {
+      AWS_REGION_NAME:
+        (existingLlmProvider?.custom_config?.AWS_REGION_NAME as string) ?? "",
+      BEDROCK_AUTH_METHOD:
+        (existingLlmProvider?.custom_config?.BEDROCK_AUTH_METHOD as string) ??
+        "access_key",
+      AWS_ACCESS_KEY_ID:
+        (existingLlmProvider?.custom_config?.AWS_ACCESS_KEY_ID as string) ?? "",
+      AWS_SECRET_ACCESS_KEY:
+        (existingLlmProvider?.custom_config?.AWS_SECRET_ACCESS_KEY as string) ??
+        "",
+      AWS_BEARER_TOKEN_BEDROCK:
+        (existingLlmProvider?.custom_config
+          ?.AWS_BEARER_TOKEN_BEDROCK as string) ?? "",
+    },
+  } as BedrockModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    extra: {
+      custom_config: Yup.object({
+        AWS_REGION_NAME: Yup.string().required("AWS Region is required"),
+      }),
+    },
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: BedrockModalValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: BEDROCK_PROVIDER_NAME,
-        provider: BEDROCK_PROVIDER_NAME,
-        default_model_name: "",
-        custom_config: {
-          AWS_REGION_NAME: "",
-          BEDROCK_AUTH_METHOD: "access_key",
-          AWS_ACCESS_KEY_ID: "",
-          AWS_SECRET_ACCESS_KEY: "",
-          AWS_BEARER_TOKEN_BEDROCK: "",
-        },
-      } as BedrockModalValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        custom_config: {
-          AWS_REGION_NAME:
-            (existingLlmProvider?.custom_config?.AWS_REGION_NAME as string) ??
-            "",
-          BEDROCK_AUTH_METHOD:
-            (existingLlmProvider?.custom_config
-              ?.BEDROCK_AUTH_METHOD as string) ?? "access_key",
-          AWS_ACCESS_KEY_ID:
-            (existingLlmProvider?.custom_config?.AWS_ACCESS_KEY_ID as string) ??
-            "",
-          AWS_SECRET_ACCESS_KEY:
-            (existingLlmProvider?.custom_config
-              ?.AWS_SECRET_ACCESS_KEY as string) ?? "",
-          AWS_BEARER_TOKEN_BEDROCK:
-            (existingLlmProvider?.custom_config
-              ?.AWS_BEARER_TOKEN_BEDROCK as string) ?? "",
-        },
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        default_model_name: Yup.string().required("Model name is required"),
-        custom_config: Yup.object({
-          AWS_REGION_NAME: Yup.string().required("AWS Region is required"),
-        }),
-      })
-    : buildDefaultValidationSchema().shape({
-        custom_config: Yup.object({
-          AWS_REGION_NAME: Yup.string().required("AWS Region is required"),
-        }),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.BEDROCK}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
         const filteredCustomConfig = Object.fromEntries(
           Object.entries(values.custom_config || {}).filter(([, v]) => v !== "")
         );
@@ -407,51 +335,37 @@ export default function BedrockModal({
               : undefined,
         };
 
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            fetchedModels.length > 0 ? fetchedModels : [];
-
-          await submitOnboardingProvider({
-            providerName: BEDROCK_PROVIDER_NAME,
-            payload: {
-              ...submitValues,
-              model_configurations: modelConfigsToUse,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: BEDROCK_PROVIDER_NAME,
-            values: submitValues,
-            initialValues,
-            modelConfigurations:
-              fetchedModels.length > 0 ? fetchedModels : modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.BEDROCK,
+          values: submitValues,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <BedrockModalInternals
-          formikProps={formikProps}
-          existingLlmProvider={existingLlmProvider}
-          fetchedModels={fetchedModels}
-          setFetchedModels={setFetchedModels}
-          modelConfigurations={modelConfigurations}
-          isTesting={isTesting}
-          onClose={onClose}
-          isOnboarding={isOnboarding}
-        />
-      )}
-    </Formik>
+      <BedrockModalInternals
+        existingLlmProvider={existingLlmProvider}
+        isOnboarding={isOnboarding}
+      />
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/BifrostModal.tsx

@@ -1,45 +1,33 @@
 "use client";
 
-import { useState, useEffect } from "react";
+import { useEffect } from "react";
 import { markdown } from "@opal/utils";
 import { useSWRConfig } from "swr";
-import { Formik, FormikProps } from "formik";
-import InputTypeInField from "@/refresh-components/form/InputTypeInField";
-import PasswordInputTypeInField from "@/refresh-components/form/PasswordInputTypeInField";
+import { useFormikContext } from "formik";
 import * as InputLayouts from "@/layouts/input-layouts";
 import {
   LLMProviderFormProps,
   LLMProviderName,
   LLMProviderView,
-  ModelConfiguration,
 } from "@/interfaces/llm";
 import { fetchBifrostModels } from "@/app/admin/configuration/llm/utils";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
   BaseLLMFormValues,
 } from "@/sections/modals/llmConfig/utils";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
-import {
-  ModelsField,
+  APIBaseField,
+  APIKeyField,
+  ModelSelectionField,
   DisplayNameField,
-  ModelsAccessField,
-  FieldSeparator,
-  FieldWrapper,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
 import { toast } from "@/hooks/useToast";
-
-const BIFROST_PROVIDER_NAME = LLMProviderName.BIFROST;
-const DEFAULT_API_BASE = "";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
 
 interface BifrostModalValues extends BaseLLMFormValues {
   api_key: string;
@@ -47,30 +35,15 @@ interface BifrostModalValues extends BaseLLMFormValues {
 }
 
 interface BifrostModalInternalsProps {
-  formikProps: FormikProps<BifrostModalValues>;
   existingLlmProvider: LLMProviderView | undefined;
-  fetchedModels: ModelConfiguration[];
-  setFetchedModels: (models: ModelConfiguration[]) => void;
-  modelConfigurations: ModelConfiguration[];
-  isTesting: boolean;
-  onClose: () => void;
   isOnboarding: boolean;
 }
 
 function BifrostModalInternals({
-  formikProps,
   existingLlmProvider,
-  fetchedModels,
-  setFetchedModels,
-  modelConfigurations,
-  isTesting,
-  onClose,
   isOnboarding,
 }: BifrostModalInternalsProps) {
-  const currentModels =
-    fetchedModels.length > 0
-      ? fetchedModels
-      : existingLlmProvider?.model_configurations || modelConfigurations;
+  const formikProps = useFormikContext<BifrostModalValues>();
 
   const isFetchDisabled = !formikProps.values.api_base;
 
@@ -78,12 +51,12 @@ function BifrostModalInternals({
     const { models, error } = await fetchBifrostModels({
       api_base: formikProps.values.api_base,
       api_key: formikProps.values.api_key || undefined,
-      provider_name: existingLlmProvider?.name,
+      provider_name: LLMProviderName.BIFROST,
     });
     if (error) {
       throw new Error(error);
     }
-    setFetchedModels(models);
+    formikProps.setFieldValue("model_configurations", models);
   };
 
   // Auto-fetch models on initial load when editing an existing provider
@@ -100,69 +73,39 @@ function BifrostModalInternals({
   }, []);
 
   return (
-    <LLMConfigurationModalWrapper
-      providerEndpoint={LLMProviderName.BIFROST}
-      existingProviderName={existingLlmProvider?.name}
-      onClose={onClose}
-      isFormValid={formikProps.isValid}
-      isDirty={formikProps.dirty}
-      isTesting={isTesting}
-      isSubmitting={formikProps.isSubmitting}
-    >
-      <FieldWrapper>
-        <InputLayouts.Vertical
-          name="api_base"
-          title="API Base URL"
-          subDescription="Paste your Bifrost gateway endpoint URL (including API version)."
-        >
-          <InputTypeInField
-            name="api_base"
-            placeholder="https://your-bifrost-gateway.com/v1"
-          />
-        </InputLayouts.Vertical>
-      </FieldWrapper>
+    <>
+      <APIBaseField
+        subDescription="Paste your Bifrost gateway endpoint URL (including API version)."
+        placeholder="https://your-bifrost-gateway.com/v1"
+      />
 
-      <FieldWrapper>
-        <InputLayouts.Vertical
-          name="api_key"
-          title="API Key"
-          optional={true}
-          subDescription={markdown(
-            "Paste your API key from [Bifrost](https://docs.getbifrost.ai/overview) to access your models."
-          )}
-        >
-          <PasswordInputTypeInField name="api_key" placeholder="API Key" />
-        </InputLayouts.Vertical>
-      </FieldWrapper>
+      <APIKeyField
+        optional
+        subDescription={markdown(
+          "Paste your API key from [Bifrost](https://docs.getbifrost.ai/overview) to access your models."
+        )}
+      />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
+          <InputLayouts.FieldSeparator />
           <DisplayNameField disabled={!!existingLlmProvider} />
         </>
       )}
 
-      <FieldSeparator />
-
-      {isOnboarding ? (
-        <SingleDefaultModelField placeholder="E.g. anthropic/claude-sonnet-4-6" />
-      ) : (
-        <ModelsField
-          modelConfigurations={currentModels}
-          formikProps={formikProps}
-          recommendedDefaultModel={null}
-          shouldShowAutoUpdateToggle={false}
-          onRefetch={isFetchDisabled ? undefined : handleFetchModels}
-        />
-      )}
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField
+        shouldShowAutoUpdateToggle={false}
+        onRefetch={isFetchDisabled ? undefined : handleFetchModels}
+      />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
-          <ModelsAccessField formikProps={formikProps} />
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
         </>
       )}
-    </LLMConfigurationModalWrapper>
+    </>
   );
 }
 
@@ -172,107 +115,64 @@ export default function BifrostModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
-  const [fetchedModels, setFetchedModels] = useState<ModelConfiguration[]>([]);
-  const [isTesting, setIsTesting] = useState(false);
   const isOnboarding = variant === "onboarding";
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(
-    BIFROST_PROVIDER_NAME
-  );
 
-  if (open === false) return null;
+  const initialValues: BifrostModalValues = useInitialValues(
+    isOnboarding,
+    LLMProviderName.BIFROST,
+    existingLlmProvider
+  ) as BifrostModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiBase: true,
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: BifrostModalValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: BIFROST_PROVIDER_NAME,
-        provider: BIFROST_PROVIDER_NAME,
-        api_key: "",
-        api_base: DEFAULT_API_BASE,
-        default_model_name: "",
-      } as BifrostModalValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_key: existingLlmProvider?.api_key ?? "",
-        api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_base: Yup.string().required("API Base URL is required"),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_base: Yup.string().required("API Base URL is required"),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.BIFROST}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            fetchedModels.length > 0 ? fetchedModels : [];
-
-          await submitOnboardingProvider({
-            providerName: BIFROST_PROVIDER_NAME,
-            payload: {
-              ...values,
-              model_configurations: modelConfigsToUse,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: BIFROST_PROVIDER_NAME,
-            values,
-            initialValues,
-            modelConfigurations:
-              fetchedModels.length > 0 ? fetchedModels : modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.BIFROST,
+          values,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <BifrostModalInternals
-          formikProps={formikProps}
-          existingLlmProvider={existingLlmProvider}
-          fetchedModels={fetchedModels}
-          setFetchedModels={setFetchedModels}
-          modelConfigurations={modelConfigurations}
-          isTesting={isTesting}
-          onClose={onClose}
-          isOnboarding={isOnboarding}
-        />
-      )}
-    </Formik>
+      <BifrostModalInternals
+        existingLlmProvider={existingLlmProvider}
+        isOnboarding={isOnboarding}
+      />
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/CustomModal.test.tsx

@@ -70,7 +70,9 @@ describe("Custom LLM Provider Configuration Workflow", () => {
     }
   ) {
     const nameInput = screen.getByPlaceholderText("Display Name");
-    const providerInput = screen.getByPlaceholderText("Provider Name");
+    const providerInput = screen.getByPlaceholderText(
+      "Provider Name as shown on LiteLLM"
+    );
 
     await user.type(nameInput, options.name);
     await user.type(providerInput, options.provider);
@@ -498,7 +500,9 @@ describe("Custom LLM Provider Configuration Workflow", () => {
     const nameInput = screen.getByPlaceholderText("Display Name");
     await user.type(nameInput, "Cloudflare Provider");
 
-    const providerInput = screen.getByPlaceholderText("Provider Name");
+    const providerInput = screen.getByPlaceholderText(
+      "Provider Name as shown on LiteLLM"
+    );
     await user.type(providerInput, "cloudflare");
 
     // Click "Add Line" button for custom config (aria-label from KeyValueInput)

web/src/sections/modals/llmConfig/CustomModal.tsx

@@ -1,24 +1,23 @@
 "use client";
 
-import { useState } from "react";
+import { markdown } from "@opal/utils";
 import { useSWRConfig } from "swr";
-import { Formik, FormikProps } from "formik";
-import { LLMProviderFormProps, ModelConfiguration } from "@/interfaces/llm";
+import { useFormikContext } from "formik";
+import {
+  LLMProviderFormProps,
+  LLMProviderName,
+  ModelConfiguration,
+} from "@/interfaces/llm";
 import * as Yup from "yup";
+import { useInitialValues } from "@/sections/modals/llmConfig/utils";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
-  buildDefaultInitialValues,
-  buildOnboardingInitialValues,
-} from "@/sections/modals/llmConfig/utils";
-import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
-import {
+  APIKeyField,
+  APIBaseField,
   DisplayNameField,
-  FieldSeparator,
-  ModelsAccessField,
-  LLMConfigurationModalWrapper,
-  FieldWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
 import InputTypeInField from "@/refresh-components/form/InputTypeInField";
 import * as InputLayouts from "@/layouts/input-layouts";
@@ -32,6 +31,7 @@ import { Button, Card, EmptyMessageCard } from "@opal/components";
 import { Disabled } from "@opal/core";
 import { SvgMinusCircle, SvgPlusCircle } from "@opal/icons";
 import { toast } from "@/hooks/useToast";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
 import { Content } from "@opal/layouts";
 import { Section } from "@/layouts/general-layouts";
 
@@ -109,13 +109,10 @@ function ModelConfigurationItem({
   );
 }
 
-interface ModelConfigurationListProps {
-  formikProps: FormikProps<{
+function ModelConfigurationList() {
+  const formikProps = useFormikContext<{
     model_configurations: CustomModelConfiguration[];
-  }>;
-}
-
-function ModelConfigurationList({ formikProps }: ModelConfigurationListProps) {
+  }>();
   const models = formikProps.values.model_configurations;
 
   function handleChange(index: number, next: CustomModelConfiguration) {
@@ -181,6 +178,19 @@ function ModelConfigurationList({ formikProps }: ModelConfigurationListProps) {
   );
 }
 
+function CustomConfigKeyValue() {
+  const formikProps = useFormikContext<{ custom_config_list: KeyValue[] }>();
+  return (
+    <KeyValueInput
+      items={formikProps.values.custom_config_list}
+      onChange={(items) =>
+        formikProps.setFieldValue("custom_config_list", items)
+      }
+      addButtonLabel="Add Line"
+    />
+  );
+}
+
 // ─── Custom Config Processing ─────────────────────────────────────────────────
 
 function customConfigProcessing(items: KeyValue[]) {
@@ -197,39 +207,36 @@ export default function CustomModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
+  onSuccess,
 }: LLMProviderFormProps) {
   const isOnboarding = variant === "onboarding";
-  const [isTesting, setIsTesting] = useState(false);
   const { mutate } = useSWRConfig();
 
-  if (open === false) return null;
-
-  const onClose = () => onOpenChange?.(false);
-
   const initialValues = {
-    ...buildDefaultInitialValues(
-      existingLlmProvider,
-      undefined,
-      defaultModelName
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.CUSTOM,
+      existingLlmProvider
     ),
-    ...(isOnboarding ? buildOnboardingInitialValues() : {}),
     provider: existingLlmProvider?.provider ?? "",
+    api_version: existingLlmProvider?.api_version ?? "",
     model_configurations: existingLlmProvider?.model_configurations.map(
       (mc) => ({
         name: mc.name,
         display_name: mc.display_name ?? "",
+        is_visible: mc.is_visible,
         max_input_tokens: mc.max_input_tokens ?? null,
         supports_image_input: mc.supports_image_input,
+        supports_reasoning: mc.supports_reasoning,
       })
     ) ?? [
       {
         name: "",
         display_name: "",
+        is_visible: true,
         max_input_tokens: null,
         supports_image_input: false,
+        supports_reasoning: false,
       },
     ],
     custom_config_list: existingLlmProvider?.custom_config
@@ -260,12 +267,18 @@ export default function CustomModal({
         model_configurations: Yup.array(modelConfigurationSchema),
       });
 
+  const onClose = () => onOpenChange?.(false);
+
+  if (open === false) return null;
+
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.CUSTOM}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
         setSubmitting(true);
 
         const modelConfigurations = values.model_configurations
@@ -285,127 +298,123 @@ export default function CustomModal({
           return;
         }
 
-        if (isOnboarding && onboardingState && onboardingActions) {
-          await submitOnboardingProvider({
-            providerName: values.provider,
-            payload: {
-              ...values,
-              model_configurations: modelConfigurations,
-              custom_config: customConfigProcessing(values.custom_config_list),
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: true,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          const selectedModelNames = modelConfigurations.map(
-            (config) => config.name
-          );
+        // Always send custom_config as a dict (even empty) so the backend
+        // preserves it as non-null — this is the signal that the provider was
+        // created via CustomModal.
+        const customConfig = customConfigProcessing(values.custom_config_list);
 
-          await submitLLMProvider({
-            providerName: values.provider,
-            values: {
-              ...values,
-              selected_model_names: selectedModelNames,
-              custom_config: customConfigProcessing(values.custom_config_list),
-            },
-            initialValues: {
-              ...initialValues,
-              custom_config: customConfigProcessing(
-                initialValues.custom_config_list
-              ),
-            },
-            modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: (values as Record<string, unknown>).provider as string,
+          values: {
+            ...values,
+            model_configurations: modelConfigurations,
+            custom_config: customConfig,
+          },
+          initialValues: {
+            ...initialValues,
+            custom_config: customConfigProcessing(
+              initialValues.custom_config_list
+            ),
+          },
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          isCustomProvider: true,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <LLMConfigurationModalWrapper
-          providerEndpoint="custom"
-          existingProviderName={existingLlmProvider?.name}
-          onClose={onClose}
-          isFormValid={formikProps.isValid}
-          isDirty={formikProps.dirty}
-          isTesting={isTesting}
-          isSubmitting={formikProps.isSubmitting}
+      <InputLayouts.FieldPadder>
+        <InputLayouts.Vertical
+          name="provider"
+          title="Provider Name"
+          subDescription={markdown(
+            "Should be one of the providers listed at [LiteLLM](https://docs.litellm.ai/docs/providers)."
+          )}
         >
-          {!isOnboarding && (
-            <Section gap={0}>
-              <DisplayNameField disabled={!!existingLlmProvider} />
+          <InputTypeInField
+            name="provider"
+            placeholder="Provider Name as shown on LiteLLM"
+            variant={existingLlmProvider ? "disabled" : undefined}
+          />
+        </InputLayouts.Vertical>
+      </InputLayouts.FieldPadder>
 
-              <FieldWrapper>
-                <InputLayouts.Vertical
-                  name="provider"
-                  title="Provider Name"
-                  subDescription="Should be one of the providers listed at https://docs.litellm.ai/docs/providers."
-                >
-                  <InputTypeInField
-                    name="provider"
-                    placeholder="Provider Name"
-                    variant={existingLlmProvider ? "disabled" : undefined}
-                  />
-                </InputLayouts.Vertical>
-              </FieldWrapper>
-            </Section>
-          )}
+      <APIBaseField optional />
 
-          <FieldSeparator />
+      <InputLayouts.FieldPadder>
+        <InputLayouts.Vertical name="api_version" title="API Version" optional>
+          <InputTypeInField name="api_version" />
+        </InputLayouts.Vertical>
+      </InputLayouts.FieldPadder>
 
-          <FieldWrapper>
-            <Section gap={0.75}>
-              <Content
-                title="Provider Configs"
-                description="Add properties as needed by the model provider. This is passed to LiteLLM completion() call as arguments in the environment variable. See LiteLLM documentation for more instructions."
-                widthVariant="full"
-                variant="section"
-                sizePreset="main-content"
-              />
+      <APIKeyField
+        optional
+        subDescription="Paste your API key if your model provider requires authentication."
+      />
 
-              <KeyValueInput
-                items={formikProps.values.custom_config_list}
-                onChange={(items) =>
-                  formikProps.setFieldValue("custom_config_list", items)
-                }
-                addButtonLabel="Add Line"
-              />
-            </Section>
-          </FieldWrapper>
+      <InputLayouts.FieldPadder>
+        <Section gap={0.75}>
+          <Content
+            title="Additional Configs"
+            description={markdown(
+              "Add extra properties as needed by the model provider. These are passed to LiteLLM's `completion()` call as [environment variables](https://docs.litellm.ai/docs/set_keys#environment-variables). See [documentation](https://docs.onyx.app/admins/ai_models/custom_inference_provider) for more instructions."
+            )}
+            widthVariant="full"
+            variant="section"
+            sizePreset="main-content"
+          />
 
-          <FieldSeparator />
+          <CustomConfigKeyValue />
+        </Section>
+      </InputLayouts.FieldPadder>
 
-          <Section gap={0.5}>
-            <FieldWrapper>
-              <Content
-                title="Models"
-                description="List LLM models you wish to use and their configurations for this provider. See full list of models at LiteLLM."
-                variant="section"
-                sizePreset="main-content"
-                widthVariant="full"
-              />
-            </FieldWrapper>
-
-            <Card>
-              <ModelConfigurationList formikProps={formikProps as any} />
-            </Card>
-          </Section>
-
-          {!isOnboarding && (
-            <>
-              <FieldSeparator />
-              <ModelsAccessField formikProps={formikProps} />
-            </>
-          )}
-        </LLMConfigurationModalWrapper>
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <DisplayNameField disabled={!!existingLlmProvider} />
+        </>
       )}
-    </Formik>
+
+      <InputLayouts.FieldSeparator />
+      <Section gap={0.5}>
+        <InputLayouts.FieldPadder>
+          <Content
+            title="Models"
+            description="List LLM models you wish to use and their configurations for this provider. See full list of models at LiteLLM."
+            variant="section"
+            sizePreset="main-content"
+            widthVariant="full"
+          />
+        </InputLayouts.FieldPadder>
+
+        <Card sizeVariant="lg">
+          <ModelConfigurationList />
+        </Card>
+      </Section>
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
+        </>
+      )}
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/LMStudioForm.tsx

@@ -1,315 +0,0 @@
-"use client";
-
-import { useCallback, useEffect, useMemo, useState } from "react";
-import { useSWRConfig } from "swr";
-import { Formik, FormikProps } from "formik";
-import InputTypeInField from "@/refresh-components/form/InputTypeInField";
-import * as InputLayouts from "@/layouts/input-layouts";
-import PasswordInputTypeInField from "@/refresh-components/form/PasswordInputTypeInField";
-import {
-  LLMProviderFormProps,
-  LLMProviderName,
-  LLMProviderView,
-  ModelConfiguration,
-} from "@/interfaces/llm";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
-import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
-  BaseLLMFormValues,
-} from "@/sections/modals/llmConfig/utils";
-import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
-import {
-  ModelsField,
-  DisplayNameField,
-  ModelsAccessField,
-  FieldSeparator,
-  FieldWrapper,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
-} from "@/sections/modals/llmConfig/shared";
-import { fetchModels } from "@/app/admin/configuration/llm/utils";
-import debounce from "lodash/debounce";
-import { toast } from "@/hooks/useToast";
-
-const DEFAULT_API_BASE = "http://localhost:1234";
-
-interface LMStudioFormValues extends BaseLLMFormValues {
-  api_base: string;
-  custom_config: {
-    LM_STUDIO_API_KEY?: string;
-  };
-}
-
-interface LMStudioFormInternalsProps {
-  formikProps: FormikProps<LMStudioFormValues>;
-  existingLlmProvider: LLMProviderView | undefined;
-  fetchedModels: ModelConfiguration[];
-  setFetchedModels: (models: ModelConfiguration[]) => void;
-  isTesting: boolean;
-  onClose: () => void;
-  isOnboarding: boolean;
-}
-
-function LMStudioFormInternals({
-  formikProps,
-  existingLlmProvider,
-  fetchedModels,
-  setFetchedModels,
-  isTesting,
-  onClose,
-  isOnboarding,
-}: LMStudioFormInternalsProps) {
-  const initialApiKey =
-    (existingLlmProvider?.custom_config?.LM_STUDIO_API_KEY as string) ?? "";
-
-  const doFetchModels = useCallback(
-    (apiBase: string, apiKey: string | undefined, signal: AbortSignal) => {
-      fetchModels(
-        LLMProviderName.LM_STUDIO,
-        {
-          api_base: apiBase,
-          custom_config: apiKey ? { LM_STUDIO_API_KEY: apiKey } : {},
-          api_key_changed: apiKey !== initialApiKey,
-          name: existingLlmProvider?.name,
-        },
-        signal
-      ).then((data) => {
-        if (signal.aborted) return;
-        if (data.error) {
-          toast.error(data.error);
-          setFetchedModels([]);
-          return;
-        }
-        setFetchedModels(data.models);
-      });
-    },
-    [existingLlmProvider?.name, initialApiKey, setFetchedModels]
-  );
-
-  const debouncedFetchModels = useMemo(
-    () => debounce(doFetchModels, 500),
-    [doFetchModels]
-  );
-
-  const apiBase = formikProps.values.api_base;
-  const apiKey = formikProps.values.custom_config?.LM_STUDIO_API_KEY;
-
-  useEffect(() => {
-    if (apiBase) {
-      const controller = new AbortController();
-      debouncedFetchModels(apiBase, apiKey, controller.signal);
-      return () => {
-        debouncedFetchModels.cancel();
-        controller.abort();
-      };
-    } else {
-      setFetchedModels([]);
-    }
-  }, [apiBase, apiKey, debouncedFetchModels, setFetchedModels]);
-
-  const currentModels =
-    fetchedModels.length > 0
-      ? fetchedModels
-      : existingLlmProvider?.model_configurations || [];
-
-  return (
-    <LLMConfigurationModalWrapper
-      providerEndpoint={LLMProviderName.LM_STUDIO}
-      existingProviderName={existingLlmProvider?.name}
-      onClose={onClose}
-      isFormValid={formikProps.isValid}
-      isDirty={formikProps.dirty}
-      isTesting={isTesting}
-      isSubmitting={formikProps.isSubmitting}
-    >
-      <FieldWrapper>
-        <InputLayouts.Vertical
-          name="api_base"
-          title="API Base URL"
-          subDescription="The base URL for your LM Studio server."
-        >
-          <InputTypeInField
-            name="api_base"
-            placeholder="Your LM Studio API base URL"
-          />
-        </InputLayouts.Vertical>
-      </FieldWrapper>
-
-      <FieldWrapper>
-        <InputLayouts.Vertical
-          name="custom_config.LM_STUDIO_API_KEY"
-          title="API Key"
-          subDescription="Optional API key if your LM Studio server requires authentication."
-          optional
-        >
-          <PasswordInputTypeInField
-            name="custom_config.LM_STUDIO_API_KEY"
-            placeholder="API Key"
-          />
-        </InputLayouts.Vertical>
-      </FieldWrapper>
-
-      {!isOnboarding && (
-        <>
-          <FieldSeparator />
-          <DisplayNameField disabled={!!existingLlmProvider} />
-        </>
-      )}
-
-      <FieldSeparator />
-
-      {isOnboarding ? (
-        <SingleDefaultModelField placeholder="E.g. llama3.1" />
-      ) : (
-        <ModelsField
-          modelConfigurations={currentModels}
-          formikProps={formikProps}
-          recommendedDefaultModel={null}
-          shouldShowAutoUpdateToggle={false}
-        />
-      )}
-
-      {!isOnboarding && (
-        <>
-          <FieldSeparator />
-          <ModelsAccessField formikProps={formikProps} />
-        </>
-      )}
-    </LLMConfigurationModalWrapper>
-  );
-}
-
-export default function LMStudioForm({
-  variant = "llm-configuration",
-  existingLlmProvider,
-  shouldMarkAsDefault,
-  open,
-  onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
-}: LLMProviderFormProps) {
-  const [fetchedModels, setFetchedModels] = useState<ModelConfiguration[]>([]);
-  const [isTesting, setIsTesting] = useState(false);
-  const isOnboarding = variant === "onboarding";
-  const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(
-    LLMProviderName.LM_STUDIO
-  );
-
-  if (open === false) return null;
-
-  const onClose = () => onOpenChange?.(false);
-
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: LMStudioFormValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: LLMProviderName.LM_STUDIO,
-        provider: LLMProviderName.LM_STUDIO,
-        api_base: DEFAULT_API_BASE,
-        default_model_name: "",
-        custom_config: {
-          LM_STUDIO_API_KEY: "",
-        },
-      } as LMStudioFormValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
-        custom_config: {
-          LM_STUDIO_API_KEY:
-            (existingLlmProvider?.custom_config?.LM_STUDIO_API_KEY as string) ??
-            "",
-        },
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_base: Yup.string().required("API Base URL is required"),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_base: Yup.string().required("API Base URL is required"),
-      });
-
-  return (
-    <Formik
-      initialValues={initialValues}
-      validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
-        const filteredCustomConfig = Object.fromEntries(
-          Object.entries(values.custom_config || {}).filter(([, v]) => v !== "")
-        );
-
-        const submitValues = {
-          ...values,
-          custom_config:
-            Object.keys(filteredCustomConfig).length > 0
-              ? filteredCustomConfig
-              : undefined,
-        };
-
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            fetchedModels.length > 0 ? fetchedModels : [];
-
-          await submitOnboardingProvider({
-            providerName: LLMProviderName.LM_STUDIO,
-            payload: {
-              ...submitValues,
-              model_configurations: modelConfigsToUse,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: LLMProviderName.LM_STUDIO,
-            values: submitValues,
-            initialValues,
-            modelConfigurations:
-              fetchedModels.length > 0 ? fetchedModels : modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
-      }}
-    >
-      {(formikProps) => (
-        <LMStudioFormInternals
-          formikProps={formikProps}
-          existingLlmProvider={existingLlmProvider}
-          fetchedModels={fetchedModels}
-          setFetchedModels={setFetchedModels}
-          isTesting={isTesting}
-          onClose={onClose}
-          isOnboarding={isOnboarding}
-        />
-      )}
-    </Formik>
-  );
-}

web/src/sections/modals/llmConfig/LMStudioModal.tsx

@@ -0,0 +1,217 @@
+"use client";
+
+import { useCallback, useEffect, useMemo } from "react";
+import { useSWRConfig } from "swr";
+import { useFormikContext } from "formik";
+import * as InputLayouts from "@/layouts/input-layouts";
+import {
+  LLMProviderFormProps,
+  LLMProviderName,
+  LLMProviderView,
+} from "@/interfaces/llm";
+import {
+  useInitialValues,
+  buildValidationSchema,
+  BaseLLMFormValues as BaseLLMModalValues,
+} from "@/sections/modals/llmConfig/utils";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
+import {
+  APIKeyField,
+  APIBaseField,
+  ModelSelectionField,
+  DisplayNameField,
+  ModelAccessField,
+  ModalWrapper,
+} from "@/sections/modals/llmConfig/shared";
+import { fetchModels } from "@/app/admin/configuration/llm/utils";
+import debounce from "lodash/debounce";
+import { toast } from "@/hooks/useToast";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
+
+const DEFAULT_API_BASE = "http://localhost:1234";
+
+interface LMStudioModalValues extends BaseLLMModalValues {
+  api_base: string;
+  custom_config: {
+    LM_STUDIO_API_KEY?: string;
+  };
+}
+
+interface LMStudioModalInternalsProps {
+  existingLlmProvider: LLMProviderView | undefined;
+  isOnboarding: boolean;
+}
+
+function LMStudioModalInternals({
+  existingLlmProvider,
+  isOnboarding,
+}: LMStudioModalInternalsProps) {
+  const formikProps = useFormikContext<LMStudioModalValues>();
+  const initialApiKey = existingLlmProvider?.custom_config?.LM_STUDIO_API_KEY;
+
+  const doFetchModels = useCallback(
+    (apiBase: string, apiKey: string | undefined, signal: AbortSignal) => {
+      fetchModels(
+        LLMProviderName.LM_STUDIO,
+        {
+          api_base: apiBase,
+          custom_config: apiKey ? { LM_STUDIO_API_KEY: apiKey } : {},
+          api_key_changed: apiKey !== initialApiKey,
+          name: existingLlmProvider?.name,
+        },
+        signal
+      ).then((data) => {
+        if (signal.aborted) return;
+        if (data.error) {
+          toast.error(data.error);
+          formikProps.setFieldValue("model_configurations", []);
+          return;
+        }
+        formikProps.setFieldValue("model_configurations", data.models);
+      });
+    },
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+    [existingLlmProvider?.name, initialApiKey]
+  );
+
+  const debouncedFetchModels = useMemo(
+    () => debounce(doFetchModels, 500),
+    [doFetchModels]
+  );
+
+  const apiBase = formikProps.values.api_base;
+  const apiKey = formikProps.values.custom_config?.LM_STUDIO_API_KEY;
+
+  useEffect(() => {
+    if (apiBase) {
+      const controller = new AbortController();
+      debouncedFetchModels(apiBase, apiKey, controller.signal);
+      return () => {
+        debouncedFetchModels.cancel();
+        controller.abort();
+      };
+    } else {
+      formikProps.setFieldValue("model_configurations", []);
+    }
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [apiBase, apiKey, debouncedFetchModels]);
+
+  return (
+    <>
+      <APIBaseField
+        subDescription="The base URL for your LM Studio server."
+        placeholder="Your LM Studio API base URL"
+      />
+
+      <APIKeyField
+        name="custom_config.LM_STUDIO_API_KEY"
+        optional
+        subDescription="Optional API key if your LM Studio server requires authentication."
+      />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <DisplayNameField disabled={!!existingLlmProvider} />
+        </>
+      )}
+
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField shouldShowAutoUpdateToggle={false} />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
+        </>
+      )}
+    </>
+  );
+}
+
+export default function LMStudioModal({
+  variant = "llm-configuration",
+  existingLlmProvider,
+  shouldMarkAsDefault,
+  open,
+  onOpenChange,
+  onSuccess,
+}: LLMProviderFormProps) {
+  const isOnboarding = variant === "onboarding";
+  const { mutate } = useSWRConfig();
+
+  const initialValues: LMStudioModalValues = {
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.LM_STUDIO,
+      existingLlmProvider
+    ),
+    api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
+    custom_config: {
+      LM_STUDIO_API_KEY: existingLlmProvider?.custom_config?.LM_STUDIO_API_KEY,
+    },
+  } as LMStudioModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiBase: true,
+  });
+
+  const onClose = () => onOpenChange?.(false);
+
+  if (open === false) return null;
+
+  return (
+    <ModalWrapper
+      providerName={LLMProviderName.LM_STUDIO}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
+      initialValues={initialValues}
+      validationSchema={validationSchema}
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
+        const filteredCustomConfig = Object.fromEntries(
+          Object.entries(values.custom_config || {}).filter(([, v]) => v !== "")
+        );
+
+        const submitValues = {
+          ...values,
+          custom_config:
+            Object.keys(filteredCustomConfig).length > 0
+              ? filteredCustomConfig
+              : undefined,
+        };
+
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.LM_STUDIO,
+          values: submitValues,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
+      }}
+    >
+      <LMStudioModalInternals
+        existingLlmProvider={existingLlmProvider}
+        isOnboarding={isOnboarding}
+      />
+    </ModalWrapper>
+  );
+}

web/src/sections/modals/llmConfig/LiteLLMProxyModal.tsx

@@ -1,41 +1,32 @@
 "use client";
 
-import { useState, useEffect } from "react";
+import { useEffect } from "react";
 import { useSWRConfig } from "swr";
-import { Formik, FormikProps } from "formik";
-import InputTypeInField from "@/refresh-components/form/InputTypeInField";
+import { useFormikContext } from "formik";
 import * as InputLayouts from "@/layouts/input-layouts";
 import {
   LLMProviderFormProps,
   LLMProviderName,
   LLMProviderView,
-  ModelConfiguration,
 } from "@/interfaces/llm";
 import { fetchLiteLLMProxyModels } from "@/app/admin/configuration/llm/utils";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
   BaseLLMFormValues,
 } from "@/sections/modals/llmConfig/utils";
-import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
   APIKeyField,
-  ModelsField,
+  APIBaseField,
+  ModelSelectionField,
   DisplayNameField,
-  ModelsAccessField,
-  FieldSeparator,
-  FieldWrapper,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
 import { toast } from "@/hooks/useToast";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
 
 const DEFAULT_API_BASE = "http://localhost:4000";
 
@@ -45,30 +36,15 @@ interface LiteLLMProxyModalValues extends BaseLLMFormValues {
 }
 
 interface LiteLLMProxyModalInternalsProps {
-  formikProps: FormikProps<LiteLLMProxyModalValues>;
   existingLlmProvider: LLMProviderView | undefined;
-  fetchedModels: ModelConfiguration[];
-  setFetchedModels: (models: ModelConfiguration[]) => void;
-  modelConfigurations: ModelConfiguration[];
-  isTesting: boolean;
-  onClose: () => void;
   isOnboarding: boolean;
 }
 
 function LiteLLMProxyModalInternals({
-  formikProps,
   existingLlmProvider,
-  fetchedModels,
-  setFetchedModels,
-  modelConfigurations,
-  isTesting,
-  onClose,
   isOnboarding,
 }: LiteLLMProxyModalInternalsProps) {
-  const currentModels =
-    fetchedModels.length > 0
-      ? fetchedModels
-      : existingLlmProvider?.model_configurations || modelConfigurations;
+  const formikProps = useFormikContext<LiteLLMProxyModalValues>();
 
   const isFetchDisabled =
     !formikProps.values.api_base || !formikProps.values.api_key;
@@ -77,12 +53,12 @@ function LiteLLMProxyModalInternals({
     const { models, error } = await fetchLiteLLMProxyModels({
       api_base: formikProps.values.api_base,
       api_key: formikProps.values.api_key,
-      provider_name: existingLlmProvider?.name,
+      provider_name: LLMProviderName.LITELLM_PROXY,
     });
     if (error) {
       throw new Error(error);
     }
-    setFetchedModels(models);
+    formikProps.setFieldValue("model_configurations", models);
   };
 
   // Auto-fetch models on initial load when editing an existing provider
@@ -98,58 +74,34 @@ function LiteLLMProxyModalInternals({
   }, []);
 
   return (
-    <LLMConfigurationModalWrapper
-      providerEndpoint={LLMProviderName.LITELLM_PROXY}
-      existingProviderName={existingLlmProvider?.name}
-      onClose={onClose}
-      isFormValid={formikProps.isValid}
-      isDirty={formikProps.dirty}
-      isTesting={isTesting}
-      isSubmitting={formikProps.isSubmitting}
-    >
-      <FieldWrapper>
-        <InputLayouts.Vertical
-          name="api_base"
-          title="API Base URL"
-          subDescription="The base URL for your LiteLLM Proxy server."
-        >
-          <InputTypeInField
-            name="api_base"
-            placeholder="https://your-litellm-proxy.com"
-          />
-        </InputLayouts.Vertical>
-      </FieldWrapper>
+    <>
+      <APIBaseField
+        subDescription="The base URL for your LiteLLM Proxy server."
+        placeholder="https://your-litellm-proxy.com"
+      />
 
       <APIKeyField providerName="LiteLLM Proxy" />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
+          <InputLayouts.FieldSeparator />
           <DisplayNameField disabled={!!existingLlmProvider} />
         </>
       )}
 
-      <FieldSeparator />
-
-      {isOnboarding ? (
-        <SingleDefaultModelField placeholder="E.g. gpt-4o" />
-      ) : (
-        <ModelsField
-          modelConfigurations={currentModels}
-          formikProps={formikProps}
-          recommendedDefaultModel={null}
-          shouldShowAutoUpdateToggle={false}
-          onRefetch={isFetchDisabled ? undefined : handleFetchModels}
-        />
-      )}
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField
+        shouldShowAutoUpdateToggle={false}
+        onRefetch={isFetchDisabled ? undefined : handleFetchModels}
+      />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
-          <ModelsAccessField formikProps={formikProps} />
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
         </>
       )}
-    </LLMConfigurationModalWrapper>
+    </>
   );
 }
 
@@ -159,109 +111,68 @@ export default function LiteLLMProxyModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
-  const [fetchedModels, setFetchedModels] = useState<ModelConfiguration[]>([]);
-  const [isTesting, setIsTesting] = useState(false);
   const isOnboarding = variant === "onboarding";
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(
-    LLMProviderName.LITELLM_PROXY
-  );
 
-  if (open === false) return null;
+  const initialValues: LiteLLMProxyModalValues = {
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.LITELLM_PROXY,
+      existingLlmProvider
+    ),
+    api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
+  } as LiteLLMProxyModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiKey: true,
+    apiBase: true,
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: LiteLLMProxyModalValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: LLMProviderName.LITELLM_PROXY,
-        provider: LLMProviderName.LITELLM_PROXY,
-        api_key: "",
-        api_base: DEFAULT_API_BASE,
-        default_model_name: "",
-      } as LiteLLMProxyModalValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_key: existingLlmProvider?.api_key ?? "",
-        api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_key: Yup.string().required("API Key is required"),
-        api_base: Yup.string().required("API Base URL is required"),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_key: Yup.string().required("API Key is required"),
-        api_base: Yup.string().required("API Base URL is required"),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.LITELLM_PROXY}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            fetchedModels.length > 0 ? fetchedModels : [];
-
-          await submitOnboardingProvider({
-            providerName: LLMProviderName.LITELLM_PROXY,
-            payload: {
-              ...values,
-              model_configurations: modelConfigsToUse,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: LLMProviderName.LITELLM_PROXY,
-            values,
-            initialValues,
-            modelConfigurations:
-              fetchedModels.length > 0 ? fetchedModels : modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.LITELLM_PROXY,
+          values,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <LiteLLMProxyModalInternals
-          formikProps={formikProps}
-          existingLlmProvider={existingLlmProvider}
-          fetchedModels={fetchedModels}
-          setFetchedModels={setFetchedModels}
-          modelConfigurations={modelConfigurations}
-          isTesting={isTesting}
-          onClose={onClose}
-          isOnboarding={isOnboarding}
-        />
-      )}
-    </Formik>
+      <LiteLLMProxyModalInternals
+        existingLlmProvider={existingLlmProvider}
+        isOnboarding={isOnboarding}
+      />
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/OllamaModal.tsx

@@ -1,47 +1,44 @@
 "use client";
 
-import { useCallback, useEffect, useMemo, useRef, useState } from "react";
+import * as Yup from "yup";
+import { Dispatch, SetStateAction, useMemo, useState } from "react";
 import { useSWRConfig } from "swr";
-import { Formik, FormikProps } from "formik";
-import InputTypeInField from "@/refresh-components/form/InputTypeInField";
+import { useFormikContext } from "formik";
 import * as InputLayouts from "@/layouts/input-layouts";
 import PasswordInputTypeInField from "@/refresh-components/form/PasswordInputTypeInField";
 import {
   LLMProviderFormProps,
+  LLMProviderName,
   LLMProviderView,
-  ModelConfiguration,
 } from "@/interfaces/llm";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
   BaseLLMFormValues,
 } from "@/sections/modals/llmConfig/utils";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
-import {
-  ModelsField,
+  ModelSelectionField,
   DisplayNameField,
-  ModelsAccessField,
-  FieldSeparator,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
 import { fetchOllamaModels } from "@/app/admin/configuration/llm/utils";
-import debounce from "lodash/debounce";
 import Tabs from "@/refresh-components/Tabs";
 import { Card } from "@opal/components";
 import { toast } from "@/hooks/useToast";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
+import InputTypeInField from "@/refresh-components/form/InputTypeInField";
+import useOnMount from "@/hooks/useOnMount";
 
-const OLLAMA_PROVIDER_NAME = "ollama_chat";
 const DEFAULT_API_BASE = "http://127.0.0.1:11434";
-const TAB_SELF_HOSTED = "self-hosted";
-const TAB_CLOUD = "cloud";
+const CLOUD_API_BASE = "https://ollama.com";
+
+enum Tab {
+  TAB_SELF_HOSTED = "self-hosted",
+  TAB_CLOUD = "cloud",
+}
 
 interface OllamaModalValues extends BaseLLMFormValues {
   api_base: string;
@@ -51,104 +48,65 @@ interface OllamaModalValues extends BaseLLMFormValues {
 }
 
 interface OllamaModalInternalsProps {
-  formikProps: FormikProps<OllamaModalValues>;
   existingLlmProvider: LLMProviderView | undefined;
-  fetchedModels: ModelConfiguration[];
-  setFetchedModels: (models: ModelConfiguration[]) => void;
-  isTesting: boolean;
-  onClose: () => void;
   isOnboarding: boolean;
+  tab: Tab;
+  setTab: Dispatch<SetStateAction<Tab>>;
 }
 
 function OllamaModalInternals({
-  formikProps,
   existingLlmProvider,
-  fetchedModels,
-  setFetchedModels,
-  isTesting,
-  onClose,
   isOnboarding,
+  tab,
+  setTab,
 }: OllamaModalInternalsProps) {
-  const isInitialMount = useRef(true);
+  const formikProps = useFormikContext<OllamaModalValues>();
 
-  const doFetchModels = useCallback(
-    (apiBase: string, signal: AbortSignal) => {
-      fetchOllamaModels({
-        api_base: apiBase,
-        provider_name: existingLlmProvider?.name,
-        signal,
-      }).then((data) => {
-        if (signal.aborted) return;
-        if (data.error) {
-          toast.error(data.error);
-          setFetchedModels([]);
-          return;
-        }
-        setFetchedModels(data.models);
+  const isFetchDisabled = useMemo(
+    () =>
+      tab === Tab.TAB_SELF_HOSTED
+        ? !formikProps.values.api_base
+        : !formikProps.values.custom_config.OLLAMA_API_KEY,
+    [tab, formikProps]
+  );
+
+  const handleFetchModels = async () => {
+    // Only Ollama cloud accepts API key
+    const apiBase = formikProps.values.custom_config?.OLLAMA_API_KEY
+      ? CLOUD_API_BASE
+      : formikProps.values.api_base;
+    const { models, error } = await fetchOllamaModels({
+      api_base: apiBase,
+      provider_name: existingLlmProvider?.name,
+    });
+    if (error) {
+      throw new Error(error);
+    }
+    formikProps.setFieldValue("model_configurations", models);
+  };
+
+  // Auto-fetch models on initial load when editing an existing provider
+  useOnMount(() => {
+    if (existingLlmProvider) {
+      handleFetchModels().catch((err) => {
+        toast.error(
+          err instanceof Error ? err.message : "Failed to fetch models"
+        );
       });
-    },
-    [existingLlmProvider?.name, setFetchedModels]
-  );
-
-  const debouncedFetchModels = useMemo(
-    () => debounce(doFetchModels, 500),
-    [doFetchModels]
-  );
-
-  // Skip the initial fetch for new providers — api_base starts with a default
-  // value, which would otherwise trigger a fetch before the user has done
-  // anything. Existing providers should still auto-fetch on mount.
-  useEffect(() => {
-    if (isInitialMount.current) {
-      isInitialMount.current = false;
-      if (!existingLlmProvider) return;
     }
-
-    if (formikProps.values.api_base) {
-      const controller = new AbortController();
-      debouncedFetchModels(formikProps.values.api_base, controller.signal);
-      return () => {
-        debouncedFetchModels.cancel();
-        controller.abort();
-      };
-    } else {
-      setFetchedModels([]);
-    }
-  }, [
-    formikProps.values.api_base,
-    debouncedFetchModels,
-    setFetchedModels,
-    existingLlmProvider,
-  ]);
-
-  const currentModels =
-    fetchedModels.length > 0
-      ? fetchedModels
-      : existingLlmProvider?.model_configurations || [];
-
-  const hasApiKey = !!formikProps.values.custom_config?.OLLAMA_API_KEY;
-  const defaultTab =
-    existingLlmProvider && hasApiKey ? TAB_CLOUD : TAB_SELF_HOSTED;
+  });
 
   return (
-    <LLMConfigurationModalWrapper
-      providerEndpoint={OLLAMA_PROVIDER_NAME}
-      existingProviderName={existingLlmProvider?.name}
-      onClose={onClose}
-      isFormValid={formikProps.isValid}
-      isDirty={formikProps.dirty}
-      isTesting={isTesting}
-      isSubmitting={formikProps.isSubmitting}
-    >
+    <>
       <Card backgroundVariant="light" borderVariant="none" sizeVariant="lg">
-        <Tabs defaultValue={defaultTab}>
+        <Tabs value={tab} onValueChange={(value) => setTab(value as Tab)}>
           <Tabs.List>
-            <Tabs.Trigger value={TAB_SELF_HOSTED}>
+            <Tabs.Trigger value={Tab.TAB_SELF_HOSTED}>
               Self-hosted Ollama
             </Tabs.Trigger>
-            <Tabs.Trigger value={TAB_CLOUD}>Ollama Cloud</Tabs.Trigger>
+            <Tabs.Trigger value={Tab.TAB_CLOUD}>Ollama Cloud</Tabs.Trigger>
           </Tabs.List>
-          <Tabs.Content value={TAB_SELF_HOSTED}>
+          <Tabs.Content value={Tab.TAB_SELF_HOSTED} padding={0}>
             <InputLayouts.Vertical
               name="api_base"
               title="API Base URL"
@@ -161,7 +119,7 @@ function OllamaModalInternals({
             </InputLayouts.Vertical>
           </Tabs.Content>
 
-          <Tabs.Content value={TAB_CLOUD}>
+          <Tabs.Content value={Tab.TAB_CLOUD}>
             <InputLayouts.Vertical
               name="custom_config.OLLAMA_API_KEY"
               title="API Key"
@@ -178,31 +136,24 @@ function OllamaModalInternals({
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
+          <InputLayouts.FieldSeparator />
           <DisplayNameField disabled={!!existingLlmProvider} />
         </>
       )}
 
-      <FieldSeparator />
-
-      {isOnboarding ? (
-        <SingleDefaultModelField placeholder="E.g. llama3.1" />
-      ) : (
-        <ModelsField
-          modelConfigurations={currentModels}
-          formikProps={formikProps}
-          recommendedDefaultModel={null}
-          shouldShowAutoUpdateToggle={false}
-        />
-      )}
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField
+        shouldShowAutoUpdateToggle={false}
+        onRefetch={isFetchDisabled ? undefined : handleFetchModels}
+      />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
-          <ModelsAccessField formikProps={formikProps} />
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
         </>
       )}
-    </LLMConfigurationModalWrapper>
+    </>
   );
 }
 
@@ -212,67 +163,55 @@ export default function OllamaModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
-  const [fetchedModels, setFetchedModels] = useState<ModelConfiguration[]>([]);
-  const [isTesting, setIsTesting] = useState(false);
   const isOnboarding = variant === "onboarding";
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } =
-    useWellKnownLLMProvider(OLLAMA_PROVIDER_NAME);
+  const apiKey = existingLlmProvider?.custom_config?.OLLAMA_API_KEY;
+  const defaultTab =
+    existingLlmProvider && !!apiKey ? Tab.TAB_CLOUD : Tab.TAB_SELF_HOSTED;
+  const [tab, setTab] = useState<Tab>(defaultTab);
 
-  if (open === false) return null;
+  const initialValues: OllamaModalValues = {
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.OLLAMA_CHAT,
+      existingLlmProvider
+    ),
+    api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
+    custom_config: {
+      OLLAMA_API_KEY: apiKey,
+    },
+  } as OllamaModalValues;
+
+  const validationSchema = useMemo(
+    () =>
+      buildValidationSchema(isOnboarding, {
+        apiBase: tab === Tab.TAB_SELF_HOSTED,
+        extra:
+          tab === Tab.TAB_CLOUD
+            ? {
+                custom_config: Yup.object({
+                  OLLAMA_API_KEY: Yup.string().required("API Key is required"),
+                }),
+              }
+            : undefined,
+      }),
+    [tab, isOnboarding]
+  );
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: OllamaModalValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: OLLAMA_PROVIDER_NAME,
-        provider: OLLAMA_PROVIDER_NAME,
-        api_base: DEFAULT_API_BASE,
-        default_model_name: "",
-        custom_config: {
-          OLLAMA_API_KEY: "",
-        },
-      } as OllamaModalValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
-        custom_config: {
-          OLLAMA_API_KEY:
-            (existingLlmProvider?.custom_config?.OLLAMA_API_KEY as string) ??
-            "",
-        },
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_base: Yup.string().required("API Base URL is required"),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_base: Yup.string().required("API Base URL is required"),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.OLLAMA_CHAT}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
         const filteredCustomConfig = Object.fromEntries(
           Object.entries(values.custom_config || {}).filter(([, v]) => v !== "")
         );
@@ -285,50 +224,39 @@ export default function OllamaModal({
               : undefined,
         };
 
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            fetchedModels.length > 0 ? fetchedModels : [];
-
-          await submitOnboardingProvider({
-            providerName: OLLAMA_PROVIDER_NAME,
-            payload: {
-              ...submitValues,
-              model_configurations: modelConfigsToUse,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: OLLAMA_PROVIDER_NAME,
-            values: submitValues,
-            initialValues,
-            modelConfigurations:
-              fetchedModels.length > 0 ? fetchedModels : modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.OLLAMA_CHAT,
+          values: submitValues,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <OllamaModalInternals
-          formikProps={formikProps}
-          existingLlmProvider={existingLlmProvider}
-          fetchedModels={fetchedModels}
-          setFetchedModels={setFetchedModels}
-          isTesting={isTesting}
-          onClose={onClose}
-          isOnboarding={isOnboarding}
-        />
-      )}
-    </Formik>
+      <OllamaModalInternals
+        existingLlmProvider={existingLlmProvider}
+        isOnboarding={isOnboarding}
+        tab={tab}
+        setTab={setTab}
+      />
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/OpenAICompatibleModal.tsx

@@ -0,0 +1,177 @@
+"use client";
+
+import { useEffect } from "react";
+import { markdown } from "@opal/utils";
+import { useSWRConfig } from "swr";
+import { useFormikContext } from "formik";
+import * as InputLayouts from "@/layouts/input-layouts";
+import {
+  LLMProviderFormProps,
+  LLMProviderName,
+  LLMProviderView,
+} from "@/interfaces/llm";
+import { fetchOpenAICompatibleModels } from "@/app/admin/configuration/llm/utils";
+import {
+  useInitialValues,
+  buildValidationSchema,
+  BaseLLMFormValues,
+} from "@/sections/modals/llmConfig/utils";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
+import {
+  APIBaseField,
+  APIKeyField,
+  ModelSelectionField,
+  DisplayNameField,
+  ModelAccessField,
+  ModalWrapper,
+} from "@/sections/modals/llmConfig/shared";
+import { toast } from "@/hooks/useToast";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
+
+interface OpenAICompatibleModalValues extends BaseLLMFormValues {
+  api_key: string;
+  api_base: string;
+}
+
+interface OpenAICompatibleModalInternalsProps {
+  existingLlmProvider: LLMProviderView | undefined;
+  isOnboarding: boolean;
+}
+
+function OpenAICompatibleModalInternals({
+  existingLlmProvider,
+  isOnboarding,
+}: OpenAICompatibleModalInternalsProps) {
+  const formikProps = useFormikContext<OpenAICompatibleModalValues>();
+
+  const isFetchDisabled = !formikProps.values.api_base;
+
+  const handleFetchModels = async () => {
+    const { models, error } = await fetchOpenAICompatibleModels({
+      api_base: formikProps.values.api_base,
+      api_key: formikProps.values.api_key || undefined,
+      provider_name: existingLlmProvider?.name,
+    });
+    if (error) {
+      throw new Error(error);
+    }
+    formikProps.setFieldValue("model_configurations", models);
+  };
+
+  // Auto-fetch models on initial load when editing an existing provider
+  useEffect(() => {
+    if (existingLlmProvider && !isFetchDisabled) {
+      handleFetchModels().catch((err) => {
+        toast.error(
+          err instanceof Error ? err.message : "Failed to fetch models"
+        );
+      });
+    }
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, []);
+
+  return (
+    <>
+      <APIBaseField
+        subDescription="The base URL of your OpenAI-compatible server."
+        placeholder="http://localhost:8000/v1"
+      />
+
+      <APIKeyField
+        optional
+        subDescription={markdown(
+          "Provide an API key if your server requires authentication."
+        )}
+      />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <DisplayNameField disabled={!!existingLlmProvider} />
+        </>
+      )}
+
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField
+        shouldShowAutoUpdateToggle={false}
+        onRefetch={isFetchDisabled ? undefined : handleFetchModels}
+      />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
+        </>
+      )}
+    </>
+  );
+}
+
+export default function OpenAICompatibleModal({
+  variant = "llm-configuration",
+  existingLlmProvider,
+  shouldMarkAsDefault,
+  open,
+  onOpenChange,
+  onSuccess,
+}: LLMProviderFormProps) {
+  const isOnboarding = variant === "onboarding";
+  const { mutate } = useSWRConfig();
+
+  const initialValues = useInitialValues(
+    isOnboarding,
+    LLMProviderName.OPENAI_COMPATIBLE,
+    existingLlmProvider
+  ) as OpenAICompatibleModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiBase: true,
+  });
+
+  const onClose = () => onOpenChange?.(false);
+
+  if (open === false) return null;
+
+  return (
+    <ModalWrapper
+      providerName={LLMProviderName.OPENAI_COMPATIBLE}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
+      initialValues={initialValues}
+      validationSchema={validationSchema}
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.OPENAI_COMPATIBLE,
+          values,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
+      }}
+    >
+      <OpenAICompatibleModalInternals
+        existingLlmProvider={existingLlmProvider}
+        isOnboarding={isOnboarding}
+      />
+    </ModalWrapper>
+  );
+}

web/src/sections/modals/llmConfig/OpenAIModal.tsx

@@ -1,33 +1,23 @@
 "use client";
 
-import { useState } from "react";
 import { useSWRConfig } from "swr";
-import { Formik } from "formik";
-import { LLMProviderFormProps } from "@/interfaces/llm";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
+import { LLMProviderFormProps, LLMProviderName } from "@/interfaces/llm";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
 } from "@/sections/modals/llmConfig/utils";
-import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
   APIKeyField,
-  ModelsField,
+  ModelSelectionField,
   DisplayNameField,
-  FieldSeparator,
-  ModelsAccessField,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
-
-const OPENAI_PROVIDER_NAME = "openai";
-const DEFAULT_DEFAULT_MODEL_NAME = "gpt-5.2";
+import * as InputLayouts from "@/layouts/input-layouts";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
+import { toast } from "@/hooks/useToast";
 
 export default function OpenAIModal({
   variant = "llm-configuration",
@@ -35,141 +25,78 @@ export default function OpenAIModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
   const isOnboarding = variant === "onboarding";
-  const [isTesting, setIsTesting] = useState(false);
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } =
-    useWellKnownLLMProvider(OPENAI_PROVIDER_NAME);
 
-  if (open === false) return null;
+  const initialValues = useInitialValues(
+    isOnboarding,
+    LLMProviderName.OPENAI,
+    existingLlmProvider
+  );
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiKey: true,
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues = isOnboarding
-    ? {
-        ...buildOnboardingInitialValues(),
-        name: OPENAI_PROVIDER_NAME,
-        provider: OPENAI_PROVIDER_NAME,
-        api_key: "",
-        default_model_name: DEFAULT_DEFAULT_MODEL_NAME,
-      }
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_key: existingLlmProvider?.api_key ?? "",
-        default_model_name:
-          (defaultModelName &&
-          modelConfigurations.some((m) => m.name === defaultModelName)
-            ? defaultModelName
-            : undefined) ??
-          wellKnownLLMProvider?.recommended_default_model?.name ??
-          DEFAULT_DEFAULT_MODEL_NAME,
-        is_auto_mode: existingLlmProvider?.is_auto_mode ?? true,
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_key: Yup.string().required("API Key is required"),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_key: Yup.string().required("API Key is required"),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.OPENAI}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            (wellKnownLLMProvider ?? llmDescriptor)?.known_models ?? [];
-
-          await submitOnboardingProvider({
-            providerName: OPENAI_PROVIDER_NAME,
-            payload: {
-              ...values,
-              model_configurations: modelConfigsToUse,
-              is_auto_mode:
-                values.default_model_name === DEFAULT_DEFAULT_MODEL_NAME,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: OPENAI_PROVIDER_NAME,
-            values,
-            initialValues,
-            modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.OPENAI,
+          values,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <LLMConfigurationModalWrapper
-          providerEndpoint={OPENAI_PROVIDER_NAME}
-          existingProviderName={existingLlmProvider?.name}
-          onClose={onClose}
-          isFormValid={formikProps.isValid}
-          isDirty={formikProps.dirty}
-          isTesting={isTesting}
-          isSubmitting={formikProps.isSubmitting}
-        >
-          <APIKeyField providerName="OpenAI" />
+      <APIKeyField providerName="OpenAI" />
 
-          {!isOnboarding && (
-            <>
-              <FieldSeparator />
-              <DisplayNameField disabled={!!existingLlmProvider} />
-            </>
-          )}
-
-          <FieldSeparator />
-          {isOnboarding ? (
-            <SingleDefaultModelField placeholder="E.g. gpt-5.2" />
-          ) : (
-            <ModelsField
-              modelConfigurations={modelConfigurations}
-              formikProps={formikProps}
-              recommendedDefaultModel={
-                wellKnownLLMProvider?.recommended_default_model ?? null
-              }
-              shouldShowAutoUpdateToggle={true}
-            />
-          )}
-
-          {!isOnboarding && (
-            <>
-              <FieldSeparator />
-              <ModelsAccessField formikProps={formikProps} />
-            </>
-          )}
-        </LLMConfigurationModalWrapper>
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <DisplayNameField disabled={!!existingLlmProvider} />
+        </>
       )}
-    </Formik>
+
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField shouldShowAutoUpdateToggle={true} />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
+        </>
+      )}
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/OpenRouterModal.tsx

@@ -1,73 +1,50 @@
 "use client";
 
-import { useState, useEffect } from "react";
+import { useEffect } from "react";
 import { useSWRConfig } from "swr";
-import { Formik, FormikProps } from "formik";
-import InputTypeInField from "@/refresh-components/form/InputTypeInField";
+import { useFormikContext } from "formik";
 import * as InputLayouts from "@/layouts/input-layouts";
 import {
   LLMProviderFormProps,
+  LLMProviderName,
   LLMProviderView,
-  ModelConfiguration,
 } from "@/interfaces/llm";
 import { fetchOpenRouterModels } from "@/app/admin/configuration/llm/utils";
-import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
   BaseLLMFormValues,
 } from "@/sections/modals/llmConfig/utils";
-import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
   APIKeyField,
-  ModelsField,
+  APIBaseField,
+  ModelSelectionField,
   DisplayNameField,
-  ModelsAccessField,
-  FieldSeparator,
-  FieldWrapper,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
 import { toast } from "@/hooks/useToast";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
 
-const OPENROUTER_PROVIDER_NAME = "openrouter";
 const DEFAULT_API_BASE = "https://openrouter.ai/api/v1";
+
 interface OpenRouterModalValues extends BaseLLMFormValues {
   api_key: string;
   api_base: string;
 }
 
 interface OpenRouterModalInternalsProps {
-  formikProps: FormikProps<OpenRouterModalValues>;
   existingLlmProvider: LLMProviderView | undefined;
-  fetchedModels: ModelConfiguration[];
-  setFetchedModels: (models: ModelConfiguration[]) => void;
-  modelConfigurations: ModelConfiguration[];
-  isTesting: boolean;
-  onClose: () => void;
   isOnboarding: boolean;
 }
 
 function OpenRouterModalInternals({
-  formikProps,
   existingLlmProvider,
-  fetchedModels,
-  setFetchedModels,
-  modelConfigurations,
-  isTesting,
-  onClose,
   isOnboarding,
 }: OpenRouterModalInternalsProps) {
-  const currentModels =
-    fetchedModels.length > 0
-      ? fetchedModels
-      : existingLlmProvider?.model_configurations || modelConfigurations;
+  const formikProps = useFormikContext<OpenRouterModalValues>();
 
   const isFetchDisabled =
     !formikProps.values.api_base || !formikProps.values.api_key;
@@ -76,12 +53,12 @@ function OpenRouterModalInternals({
     const { models, error } = await fetchOpenRouterModels({
       api_base: formikProps.values.api_base,
       api_key: formikProps.values.api_key,
-      provider_name: existingLlmProvider?.name,
+      provider_name: LLMProviderName.OPENROUTER,
     });
     if (error) {
       throw new Error(error);
     }
-    setFetchedModels(models);
+    formikProps.setFieldValue("model_configurations", models);
   };
 
   // Auto-fetch models on initial load when editing an existing provider
@@ -97,58 +74,34 @@ function OpenRouterModalInternals({
   }, []);
 
   return (
-    <LLMConfigurationModalWrapper
-      providerEndpoint={OPENROUTER_PROVIDER_NAME}
-      existingProviderName={existingLlmProvider?.name}
-      onClose={onClose}
-      isFormValid={formikProps.isValid}
-      isDirty={formikProps.dirty}
-      isTesting={isTesting}
-      isSubmitting={formikProps.isSubmitting}
-    >
-      <FieldWrapper>
-        <InputLayouts.Vertical
-          name="api_base"
-          title="API Base URL"
-          subDescription="Paste your OpenRouter-compatible endpoint URL or use OpenRouter API directly."
-        >
-          <InputTypeInField
-            name="api_base"
-            placeholder="Your OpenRouter base URL"
-          />
-        </InputLayouts.Vertical>
-      </FieldWrapper>
+    <>
+      <APIBaseField
+        subDescription="Paste your OpenRouter-compatible endpoint URL or use OpenRouter API directly."
+        placeholder="Your OpenRouter base URL"
+      />
 
       <APIKeyField providerName="OpenRouter" />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
+          <InputLayouts.FieldSeparator />
           <DisplayNameField disabled={!!existingLlmProvider} />
         </>
       )}
 
-      <FieldSeparator />
-
-      {isOnboarding ? (
-        <SingleDefaultModelField placeholder="E.g. openai/gpt-4o" />
-      ) : (
-        <ModelsField
-          modelConfigurations={currentModels}
-          formikProps={formikProps}
-          recommendedDefaultModel={null}
-          shouldShowAutoUpdateToggle={false}
-          onRefetch={isFetchDisabled ? undefined : handleFetchModels}
-        />
-      )}
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField
+        shouldShowAutoUpdateToggle={false}
+        onRefetch={isFetchDisabled ? undefined : handleFetchModels}
+      />
 
       {!isOnboarding && (
         <>
-          <FieldSeparator />
-          <ModelsAccessField formikProps={formikProps} />
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
         </>
       )}
-    </LLMConfigurationModalWrapper>
+    </>
   );
 }
 
@@ -158,109 +111,68 @@ export default function OpenRouterModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
-  const [fetchedModels, setFetchedModels] = useState<ModelConfiguration[]>([]);
-  const [isTesting, setIsTesting] = useState(false);
   const isOnboarding = variant === "onboarding";
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(
-    OPENROUTER_PROVIDER_NAME
-  );
 
-  if (open === false) return null;
+  const initialValues: OpenRouterModalValues = {
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.OPENROUTER,
+      existingLlmProvider
+    ),
+    api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
+  } as OpenRouterModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    apiKey: true,
+    apiBase: true,
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: OpenRouterModalValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: OPENROUTER_PROVIDER_NAME,
-        provider: OPENROUTER_PROVIDER_NAME,
-        api_key: "",
-        api_base: DEFAULT_API_BASE,
-        default_model_name: "",
-      } as OpenRouterModalValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        api_key: existingLlmProvider?.api_key ?? "",
-        api_base: existingLlmProvider?.api_base ?? DEFAULT_API_BASE,
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        api_key: Yup.string().required("API Key is required"),
-        api_base: Yup.string().required("API Base URL is required"),
-        default_model_name: Yup.string().required("Model name is required"),
-      })
-    : buildDefaultValidationSchema().shape({
-        api_key: Yup.string().required("API Key is required"),
-        api_base: Yup.string().required("API Base URL is required"),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.OPENROUTER}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            fetchedModels.length > 0 ? fetchedModels : [];
-
-          await submitOnboardingProvider({
-            providerName: OPENROUTER_PROVIDER_NAME,
-            payload: {
-              ...values,
-              model_configurations: modelConfigsToUse,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: OPENROUTER_PROVIDER_NAME,
-            values,
-            initialValues,
-            modelConfigurations:
-              fetchedModels.length > 0 ? fetchedModels : modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.OPENROUTER,
+          values,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <OpenRouterModalInternals
-          formikProps={formikProps}
-          existingLlmProvider={existingLlmProvider}
-          fetchedModels={fetchedModels}
-          setFetchedModels={setFetchedModels}
-          modelConfigurations={modelConfigurations}
-          isTesting={isTesting}
-          onClose={onClose}
-          isOnboarding={isOnboarding}
-        />
-      )}
-    </Formik>
+      <OpenRouterModalInternals
+        existingLlmProvider={existingLlmProvider}
+        isOnboarding={isOnboarding}
+      />
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/VertexAIModal.tsx

@@ -1,38 +1,27 @@
 "use client";
 
-import { useState } from "react";
 import { useSWRConfig } from "swr";
-import { Formik } from "formik";
 import { FileUploadFormField } from "@/components/Field";
 import InputTypeInField from "@/refresh-components/form/InputTypeInField";
 import * as InputLayouts from "@/layouts/input-layouts";
-import { LLMProviderFormProps } from "@/interfaces/llm";
+import { LLMProviderFormProps, LLMProviderName } from "@/interfaces/llm";
 import * as Yup from "yup";
-import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 import {
-  buildDefaultInitialValues,
-  buildDefaultValidationSchema,
-  buildAvailableModelConfigurations,
-  buildOnboardingInitialValues,
+  useInitialValues,
+  buildValidationSchema,
   BaseLLMFormValues,
 } from "@/sections/modals/llmConfig/utils";
+import { submitProvider } from "@/sections/modals/llmConfig/svc";
+import { LLMProviderConfiguredSource } from "@/lib/analytics";
 import {
-  submitLLMProvider,
-  submitOnboardingProvider,
-} from "@/sections/modals/llmConfig/svc";
-import {
-  ModelsField,
+  ModelSelectionField,
   DisplayNameField,
-  FieldSeparator,
-  FieldWrapper,
-  ModelsAccessField,
-  SingleDefaultModelField,
-  LLMConfigurationModalWrapper,
+  ModelAccessField,
+  ModalWrapper,
 } from "@/sections/modals/llmConfig/shared";
+import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
+import { toast } from "@/hooks/useToast";
 
-const VERTEXAI_PROVIDER_NAME = "vertex_ai";
-const VERTEXAI_DISPLAY_NAME = "Google Cloud Vertex AI";
-const VERTEXAI_DEFAULT_MODEL = "gemini-2.5-pro";
 const VERTEXAI_DEFAULT_LOCATION = "global";
 
 interface VertexAIModalValues extends BaseLLMFormValues {
@@ -48,87 +37,50 @@ export default function VertexAIModal({
   shouldMarkAsDefault,
   open,
   onOpenChange,
-  defaultModelName,
-  onboardingState,
-  onboardingActions,
-  llmDescriptor,
+  onSuccess,
 }: LLMProviderFormProps) {
   const isOnboarding = variant === "onboarding";
-  const [isTesting, setIsTesting] = useState(false);
   const { mutate } = useSWRConfig();
-  const { wellKnownLLMProvider } = useWellKnownLLMProvider(
-    VERTEXAI_PROVIDER_NAME
-  );
 
-  if (open === false) return null;
+  const initialValues: VertexAIModalValues = {
+    ...useInitialValues(
+      isOnboarding,
+      LLMProviderName.VERTEX_AI,
+      existingLlmProvider
+    ),
+    custom_config: {
+      vertex_credentials:
+        (existingLlmProvider?.custom_config?.vertex_credentials as string) ??
+        "",
+      vertex_location:
+        (existingLlmProvider?.custom_config?.vertex_location as string) ??
+        VERTEXAI_DEFAULT_LOCATION,
+    },
+  } as VertexAIModalValues;
+
+  const validationSchema = buildValidationSchema(isOnboarding, {
+    extra: {
+      custom_config: Yup.object({
+        vertex_credentials: Yup.string().required(
+          "Credentials file is required"
+        ),
+        vertex_location: Yup.string(),
+      }),
+    },
+  });
 
   const onClose = () => onOpenChange?.(false);
 
-  const modelConfigurations = buildAvailableModelConfigurations(
-    existingLlmProvider,
-    wellKnownLLMProvider ?? llmDescriptor
-  );
-
-  const initialValues: VertexAIModalValues = isOnboarding
-    ? ({
-        ...buildOnboardingInitialValues(),
-        name: VERTEXAI_PROVIDER_NAME,
-        provider: VERTEXAI_PROVIDER_NAME,
-        default_model_name: VERTEXAI_DEFAULT_MODEL,
-        custom_config: {
-          vertex_credentials: "",
-          vertex_location: VERTEXAI_DEFAULT_LOCATION,
-        },
-      } as VertexAIModalValues)
-    : {
-        ...buildDefaultInitialValues(
-          existingLlmProvider,
-          modelConfigurations,
-          defaultModelName
-        ),
-        default_model_name:
-          (defaultModelName &&
-          modelConfigurations.some((m) => m.name === defaultModelName)
-            ? defaultModelName
-            : undefined) ??
-          wellKnownLLMProvider?.recommended_default_model?.name ??
-          VERTEXAI_DEFAULT_MODEL,
-        is_auto_mode: existingLlmProvider?.is_auto_mode ?? true,
-        custom_config: {
-          vertex_credentials:
-            (existingLlmProvider?.custom_config
-              ?.vertex_credentials as string) ?? "",
-          vertex_location:
-            (existingLlmProvider?.custom_config?.vertex_location as string) ??
-            VERTEXAI_DEFAULT_LOCATION,
-        },
-      };
-
-  const validationSchema = isOnboarding
-    ? Yup.object().shape({
-        default_model_name: Yup.string().required("Model name is required"),
-        custom_config: Yup.object({
-          vertex_credentials: Yup.string().required(
-            "Credentials file is required"
-          ),
-          vertex_location: Yup.string(),
-        }),
-      })
-    : buildDefaultValidationSchema().shape({
-        custom_config: Yup.object({
-          vertex_credentials: Yup.string().required(
-            "Credentials file is required"
-          ),
-          vertex_location: Yup.string(),
-        }),
-      });
+  if (open === false) return null;
 
   return (
-    <Formik
+    <ModalWrapper
+      providerName={LLMProviderName.VERTEX_AI}
+      llmProvider={existingLlmProvider}
+      onClose={onClose}
       initialValues={initialValues}
       validationSchema={validationSchema}
-      validateOnMount={true}
-      onSubmit={async (values, { setSubmitting }) => {
+      onSubmit={async (values, { setSubmitting, setStatus }) => {
         const filteredCustomConfig = Object.fromEntries(
           Object.entries(values.custom_config || {}).filter(
             ([key, v]) => key === "vertex_credentials" || v !== ""
@@ -143,101 +95,75 @@ export default function VertexAIModal({
               : undefined,
         };
 
-        if (isOnboarding && onboardingState && onboardingActions) {
-          const modelConfigsToUse =
-            (wellKnownLLMProvider ?? llmDescriptor)?.known_models ?? [];
-
-          await submitOnboardingProvider({
-            providerName: VERTEXAI_PROVIDER_NAME,
-            payload: {
-              ...submitValues,
-              model_configurations: modelConfigsToUse,
-              is_auto_mode:
-                values.default_model_name === VERTEXAI_DEFAULT_MODEL,
-            },
-            onboardingState,
-            onboardingActions,
-            isCustomProvider: false,
-            onClose,
-            setIsSubmitting: setSubmitting,
-          });
-        } else {
-          await submitLLMProvider({
-            providerName: VERTEXAI_PROVIDER_NAME,
-            values: submitValues,
-            initialValues,
-            modelConfigurations,
-            existingLlmProvider,
-            shouldMarkAsDefault,
-            setIsTesting,
-            mutate,
-            onClose,
-            setSubmitting,
-          });
-        }
+        await submitProvider({
+          analyticsSource: isOnboarding
+            ? LLMProviderConfiguredSource.CHAT_ONBOARDING
+            : LLMProviderConfiguredSource.ADMIN_PAGE,
+          providerName: LLMProviderName.VERTEX_AI,
+          values: submitValues,
+          initialValues,
+          existingLlmProvider,
+          shouldMarkAsDefault,
+          setStatus,
+          setSubmitting,
+          onClose,
+          onSuccess: async () => {
+            if (onSuccess) {
+              await onSuccess();
+            } else {
+              await refreshLlmProviderCaches(mutate);
+              toast.success(
+                existingLlmProvider
+                  ? "Provider updated successfully!"
+                  : "Provider enabled successfully!"
+              );
+            }
+          },
+        });
       }}
     >
-      {(formikProps) => (
-        <LLMConfigurationModalWrapper
-          providerEndpoint={VERTEXAI_PROVIDER_NAME}
-          providerName={VERTEXAI_DISPLAY_NAME}
-          existingProviderName={existingLlmProvider?.name}
-          onClose={onClose}
-          isFormValid={formikProps.isValid}
-          isDirty={formikProps.dirty}
-          isTesting={isTesting}
-          isSubmitting={formikProps.isSubmitting}
+      <InputLayouts.FieldPadder>
+        <InputLayouts.Vertical
+          name="custom_config.vertex_location"
+          title="Google Cloud Region Name"
+          subDescription="Region where your Google Vertex AI models are hosted. See full list of regions supported at Google Cloud."
         >
-          <FieldWrapper>
-            <InputLayouts.Vertical
-              name="custom_config.vertex_location"
-              title="Google Cloud Region Name"
-              subDescription="Region where your Google Vertex AI models are hosted. See full list of regions supported at Google Cloud."
-            >
-              <InputTypeInField
-                name="custom_config.vertex_location"
-                placeholder={VERTEXAI_DEFAULT_LOCATION}
-              />
-            </InputLayouts.Vertical>
-          </FieldWrapper>
+          <InputTypeInField
+            name="custom_config.vertex_location"
+            placeholder={VERTEXAI_DEFAULT_LOCATION}
+          />
+        </InputLayouts.Vertical>
+      </InputLayouts.FieldPadder>
 
-          <FieldWrapper>
-            <InputLayouts.Vertical
-              name="custom_config.vertex_credentials"
-              title="API Key"
-              subDescription="Attach your API key JSON from Google Cloud to access your models."
-            >
-              <FileUploadFormField
-                name="custom_config.vertex_credentials"
-                label=""
-              />
-            </InputLayouts.Vertical>
-          </FieldWrapper>
+      <InputLayouts.FieldPadder>
+        <InputLayouts.Vertical
+          name="custom_config.vertex_credentials"
+          title="API Key"
+          subDescription="Attach your API key JSON from Google Cloud to access your models."
+        >
+          <FileUploadFormField
+            name="custom_config.vertex_credentials"
+            label=""
+          />
+        </InputLayouts.Vertical>
+      </InputLayouts.FieldPadder>
 
-          <FieldSeparator />
-
-          {!isOnboarding && (
-            <DisplayNameField disabled={!!existingLlmProvider} />
-          )}
-
-          <FieldSeparator />
-
-          {isOnboarding ? (
-            <SingleDefaultModelField placeholder="E.g. gemini-2.5-pro" />
-          ) : (
-            <ModelsField
-              modelConfigurations={modelConfigurations}
-              formikProps={formikProps}
-              recommendedDefaultModel={
-                wellKnownLLMProvider?.recommended_default_model ?? null
-              }
-              shouldShowAutoUpdateToggle={true}
-            />
-          )}
-
-          {!isOnboarding && <ModelsAccessField formikProps={formikProps} />}
-        </LLMConfigurationModalWrapper>
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <DisplayNameField disabled={!!existingLlmProvider} />
+        </>
       )}
-    </Formik>
+
+      <InputLayouts.FieldSeparator />
+      <ModelSelectionField shouldShowAutoUpdateToggle={true} />
+
+      {!isOnboarding && (
+        <>
+          <InputLayouts.FieldSeparator />
+          <ModelAccessField />
+        </>
+      )}
+    </ModalWrapper>
   );
 }

web/src/sections/modals/llmConfig/getModal.tsx

@@ -7,9 +7,10 @@ import VertexAIModal from "@/sections/modals/llmConfig/VertexAIModal";
 import OpenRouterModal from "@/sections/modals/llmConfig/OpenRouterModal";
 import CustomModal from "@/sections/modals/llmConfig/CustomModal";
 import BedrockModal from "@/sections/modals/llmConfig/BedrockModal";
-import LMStudioForm from "@/sections/modals/llmConfig/LMStudioForm";
+import LMStudioModal from "@/sections/modals/llmConfig/LMStudioModal";
 import LiteLLMProxyModal from "@/sections/modals/llmConfig/LiteLLMProxyModal";
 import BifrostModal from "@/sections/modals/llmConfig/BifrostModal";
+import OpenAICompatibleModal from "@/sections/modals/llmConfig/OpenAICompatibleModal";
 
 function detectIfRealOpenAIProvider(provider: LLMProviderView) {
   return (
@@ -54,11 +55,13 @@ export function getModalForExistingProvider(
     case LLMProviderName.OPENROUTER:
       return <OpenRouterModal {...props} />;
     case LLMProviderName.LM_STUDIO:
-      return <LMStudioForm {...props} />;
+      return <LMStudioModal {...props} />;
     case LLMProviderName.LITELLM_PROXY:
       return <LiteLLMProxyModal {...props} />;
     case LLMProviderName.BIFROST:
       return <BifrostModal {...props} />;
+    case LLMProviderName.OPENAI_COMPATIBLE:
+      return <OpenAICompatibleModal {...props} />;
     default:
       return <CustomModal {...props} />;
   }

web/src/sections/modals/llmConfig/shared.tsx

@@ -1,30 +1,31 @@
 "use client";
 
-import { ReactNode } from "react";
-import { Form, FormikProps } from "formik";
+import React, { useEffect, useRef, useState } from "react";
+import { Formik, Form, useFormikContext } from "formik";
+import type { FormikConfig } from "formik";
 import { usePaidEnterpriseFeaturesEnabled } from "@/components/settings/usePaidEnterpriseFeaturesEnabled";
 import { useAgents } from "@/hooks/useAgents";
 import { useUserGroups } from "@/lib/hooks";
-import { ModelConfiguration, SimpleKnownModel } from "@/interfaces/llm";
+import { LLMProviderView, ModelConfiguration } from "@/interfaces/llm";
 import * as InputLayouts from "@/layouts/input-layouts";
 import Checkbox from "@/refresh-components/inputs/Checkbox";
 import InputTypeInField from "@/refresh-components/form/InputTypeInField";
 import InputComboBox from "@/refresh-components/inputs/InputComboBox";
 import InputSelect from "@/refresh-components/inputs/InputSelect";
+import InputTypeIn from "@/refresh-components/inputs/InputTypeIn";
 import PasswordInputTypeInField from "@/refresh-components/form/PasswordInputTypeInField";
 import Switch from "@/refresh-components/inputs/Switch";
 import Text from "@/refresh-components/texts/Text";
-import { Button, LineItemButton, Tag } from "@opal/components";
+import { Button, LineItemButton } from "@opal/components";
 import { BaseLLMFormValues } from "@/sections/modals/llmConfig/utils";
-import { WithoutStyles } from "@opal/types";
-import Separator from "@/refresh-components/Separator";
+import type { RichStr } from "@opal/types";
 import { Section } from "@/layouts/general-layouts";
-import { Disabled, Hoverable } from "@opal/core";
 import { Content } from "@opal/layouts";
 import {
   SvgArrowExchange,
   SvgOnyxOctagon,
   SvgOrganization,
+  SvgPlusCircle,
   SvgRefreshCw,
   SvgSparkle,
   SvgUserManage,
@@ -46,27 +47,14 @@ import {
   getProviderProductName,
 } from "@/lib/llmConfig/providers";
 
-export function FieldSeparator() {
-  return <Separator noPadding className="px-2" />;
-}
-
-export type FieldWrapperProps = WithoutStyles<
-  React.HTMLAttributes<HTMLDivElement>
->;
-
-export function FieldWrapper(props: FieldWrapperProps) {
-  return <div {...props} className="p-2 w-full" />;
-}
-
 // ─── DisplayNameField ────────────────────────────────────────────────────────
 
 export interface DisplayNameFieldProps {
   disabled?: boolean;
 }
-
 export function DisplayNameField({ disabled = false }: DisplayNameFieldProps) {
   return (
-    <FieldWrapper>
+    <InputLayouts.FieldPadder>
       <InputLayouts.Vertical
         name="name"
         title="Display Name"
@@ -78,56 +66,68 @@ export function DisplayNameField({ disabled = false }: DisplayNameFieldProps) {
           variant={disabled ? "disabled" : undefined}
         />
       </InputLayouts.Vertical>
-    </FieldWrapper>
+    </InputLayouts.FieldPadder>
   );
 }
 
 // ─── APIKeyField ─────────────────────────────────────────────────────────────
 
 export interface APIKeyFieldProps {
+  /** Formik field name. @default "api_key" */
+  name?: string;
   optional?: boolean;
   providerName?: string;
+  subDescription?: string | RichStr;
 }
-
 export function APIKeyField({
+  name = "api_key",
   optional = false,
   providerName,
+  subDescription,
 }: APIKeyFieldProps) {
   return (
-    <FieldWrapper>
+    <InputLayouts.FieldPadder>
       <InputLayouts.Vertical
-        name="api_key"
+        name={name}
         title="API Key"
         subDescription={
-          providerName
-            ? `Paste your API key from ${providerName} to access your models.`
-            : "Paste your API key to access your models."
+          subDescription
+            ? subDescription
+            : providerName
+              ? `Paste your API key from ${providerName} to access your models.`
+              : "Paste your API key to access your models."
         }
         optional={optional}
       >
-        <PasswordInputTypeInField name="api_key" placeholder="API Key" />
+        <PasswordInputTypeInField name={name} />
       </InputLayouts.Vertical>
-    </FieldWrapper>
+    </InputLayouts.FieldPadder>
   );
 }
 
-// ─── SingleDefaultModelField ─────────────────────────────────────────────────
+// ─── APIBaseField ───────────────────────────────────────────────────────────
 
-export interface SingleDefaultModelFieldProps {
+export interface APIBaseFieldProps {
+  optional?: boolean;
+  subDescription?: string | RichStr;
   placeholder?: string;
 }
-
-export function SingleDefaultModelField({
-  placeholder = "E.g. gpt-4o",
-}: SingleDefaultModelFieldProps) {
+export function APIBaseField({
+  optional = false,
+  subDescription,
+  placeholder = "https://",
+}: APIBaseFieldProps) {
   return (
-    <InputLayouts.Vertical
-      name="default_model_name"
-      title="Default Model"
-      description="The model to use by default for this provider unless otherwise specified."
-    >
-      <InputTypeInField name="default_model_name" placeholder={placeholder} />
-    </InputLayouts.Vertical>
+    <InputLayouts.FieldPadder>
+      <InputLayouts.Vertical
+        name="api_base"
+        title="API Base URL"
+        subDescription={subDescription}
+        optional={optional}
+      >
+        <InputTypeInField name="api_base" placeholder={placeholder} />
+      </InputLayouts.Vertical>
+    </InputLayouts.FieldPadder>
   );
 }
 
@@ -137,13 +137,8 @@ export function SingleDefaultModelField({
 const GROUP_PREFIX = "group:";
 const AGENT_PREFIX = "agent:";
 
-interface ModelsAccessFieldProps<T> {
-  formikProps: FormikProps<T>;
-}
-
-export function ModelsAccessField<T extends BaseLLMFormValues>({
-  formikProps,
-}: ModelsAccessFieldProps<T>) {
+export function ModelAccessField() {
+  const formikProps = useFormikContext<BaseLLMFormValues>();
   const { agents } = useAgents();
   const { data: userGroups, isLoading: userGroupsIsLoading } = useUserGroups();
   const { data: usersData } = useUsers({ includeApiKeys: false });
@@ -229,7 +224,7 @@ export function ModelsAccessField<T extends BaseLLMFormValues>({
 
   return (
     <div className="flex flex-col w-full">
-      <FieldWrapper>
+      <InputLayouts.FieldPadder>
         <InputLayouts.Horizontal
           name="is_public"
           title="Models Access"
@@ -250,7 +245,7 @@ export function ModelsAccessField<T extends BaseLLMFormValues>({
             </InputSelect.Content>
           </InputSelect>
         </InputLayouts.Horizontal>
-      </FieldWrapper>
+      </InputLayouts.FieldPadder>
 
       {!isPublic && (
         <Card backgroundVariant="light" borderVariant="none" sizeVariant="lg">
@@ -316,7 +311,7 @@ export function ModelsAccessField<T extends BaseLLMFormValues>({
               </div>
             )}
 
-            <FieldSeparator />
+            <InputLayouts.FieldSeparator />
 
             {selectedAgentIds.length > 0 ? (
               <div className="grid grid-cols-2 gap-1 w-full">
@@ -371,84 +366,73 @@ export function ModelsAccessField<T extends BaseLLMFormValues>({
 
 // ─── ModelsField ─────────────────────────────────────────────────────
 
-export interface ModelsFieldProps<T> {
-  formikProps: FormikProps<T>;
-  modelConfigurations: ModelConfiguration[];
-  recommendedDefaultModel: SimpleKnownModel | null;
+export interface ModelSelectionFieldProps {
   shouldShowAutoUpdateToggle: boolean;
   /** Called when the user clicks the refresh button to re-fetch models. */
   onRefetch?: () => Promise<void> | void;
+  /** Called when the user adds a custom model name (e.g. for Azure). */
+  onAddModel?: (modelName: string) => void;
 }
-
-export function ModelsField<T extends BaseLLMFormValues>({
-  formikProps,
-  modelConfigurations,
-  recommendedDefaultModel,
+export function ModelSelectionField({
   shouldShowAutoUpdateToggle,
   onRefetch,
-}: ModelsFieldProps<T>) {
-  const isAutoMode = formikProps.values.is_auto_mode;
-  const selectedModels = formikProps.values.selected_model_names ?? [];
-  const defaultModel = formikProps.values.default_model_name;
+  onAddModel,
+}: ModelSelectionFieldProps) {
+  const formikProps = useFormikContext<BaseLLMFormValues>();
+  const [newModelName, setNewModelName] = useState("");
+  // When the auto-update toggle is hidden, auto mode should have no effect —
+  // otherwise models can't be deselected and "Select All" stays disabled.
+  const isAutoMode =
+    shouldShowAutoUpdateToggle && formikProps.values.is_auto_mode;
+  const models = formikProps.values.model_configurations;
 
-  function handleCheckboxChange(modelName: string, checked: boolean) {
-    // Read current values inside the handler to avoid stale closure issues
-    const currentSelected = formikProps.values.selected_model_names ?? [];
-    const currentDefault = formikProps.values.default_model_name;
-
-    if (checked) {
-      const newSelected = [...currentSelected, modelName];
-      formikProps.setFieldValue("selected_model_names", newSelected);
-      // If this is the first model, set it as default
-      if (currentSelected.length === 0) {
-        formikProps.setFieldValue("default_model_name", modelName);
-      }
-    } else {
-      const newSelected = currentSelected.filter((name) => name !== modelName);
-      formikProps.setFieldValue("selected_model_names", newSelected);
-      // If removing the default, set the first remaining model as default
-      if (currentDefault === modelName && newSelected.length > 0) {
-        formikProps.setFieldValue("default_model_name", newSelected[0]);
-      } else if (newSelected.length === 0) {
-        formikProps.setFieldValue("default_model_name", undefined);
-      }
+  // Snapshot the original model visibility so we can restore it when
+  // toggling auto mode back on.
+  const originalModelsRef = useRef(models);
+  useEffect(() => {
+    if (originalModelsRef.current.length === 0 && models.length > 0) {
+      originalModelsRef.current = models;
     }
-  }
+  }, [models]);
 
-  function handleSetDefault(modelName: string) {
-    formikProps.setFieldValue("default_model_name", modelName);
+  // Automatically derive test_model_name from model_configurations.
+  // Any change to visibility or the model list syncs this automatically.
+  useEffect(() => {
+    const firstVisible = models.find((m) => m.is_visible)?.name;
+    if (firstVisible !== formikProps.values.test_model_name) {
+      formikProps.setFieldValue("test_model_name", firstVisible);
+    }
+  }, [models]); // eslint-disable-line react-hooks/exhaustive-deps
+
+  function setVisibility(modelName: string, visible: boolean) {
+    const updated = models.map((m) =>
+      m.name === modelName ? { ...m, is_visible: visible } : m
+    );
+    formikProps.setFieldValue("model_configurations", updated);
   }
 
   function handleToggleAutoMode(nextIsAutoMode: boolean) {
     formikProps.setFieldValue("is_auto_mode", nextIsAutoMode);
-    formikProps.setFieldValue(
-      "selected_model_names",
-      modelConfigurations.filter((m) => m.is_visible).map((m) => m.name)
-    );
-    formikProps.setFieldValue(
-      "default_model_name",
-      recommendedDefaultModel?.name ?? undefined
-    );
-  }
-
-  const allSelected =
-    modelConfigurations.length > 0 &&
-    modelConfigurations.every((m) => selectedModels.includes(m.name));
-
-  function handleToggleSelectAll() {
-    if (allSelected) {
-      formikProps.setFieldValue("selected_model_names", []);
-      formikProps.setFieldValue("default_model_name", undefined);
-    } else {
-      const allNames = modelConfigurations.map((m) => m.name);
-      formikProps.setFieldValue("selected_model_names", allNames);
-      if (!formikProps.values.default_model_name && allNames.length > 0) {
-        formikProps.setFieldValue("default_model_name", allNames[0]);
-      }
+    if (nextIsAutoMode) {
+      formikProps.setFieldValue(
+        "model_configurations",
+        originalModelsRef.current
+      );
     }
   }
 
-  const visibleModels = modelConfigurations.filter((m) => m.is_visible);
+  const allSelected = models.length > 0 && models.every((m) => m.is_visible);
+
+  function handleToggleSelectAll() {
+    const nextVisible = !allSelected;
+    const updated = models.map((m) => ({
+      ...m,
+      is_visible: nextVisible,
+    }));
+    formikProps.setFieldValue("model_configurations", updated);
+  }
+
+  const visibleModels = models.filter((m) => m.is_visible);
 
   return (
     <Card backgroundVariant="light" borderVariant="none" sizeVariant="lg">
@@ -460,15 +444,14 @@ export function ModelsField<T extends BaseLLMFormValues>({
           center
         >
           <Section flexDirection="row" gap={0}>
-            <Disabled disabled={isAutoMode || modelConfigurations.length === 0}>
-              <Button
-                prominence="tertiary"
-                size="md"
-                onClick={handleToggleSelectAll}
-              >
-                {allSelected ? "Unselect All" : "Select All"}
-              </Button>
-            </Disabled>
+            <Button
+              disabled={isAutoMode || models.length === 0}
+              prominence="tertiary"
+              size="md"
+              onClick={handleToggleSelectAll}
+            >
+              {allSelected ? "Unselect All" : "Select All"}
+            </Button>
             {onRefetch && (
               <Button
                 prominence="tertiary"
@@ -489,91 +472,75 @@ export function ModelsField<T extends BaseLLMFormValues>({
           </Section>
         </InputLayouts.Horizontal>
 
-        {modelConfigurations.length === 0 ? (
+        {models.length === 0 ? (
           <EmptyMessageCard title="No models available." />
         ) : (
           <Section gap={0.25}>
             {isAutoMode
-              ? // Auto mode: read-only display
-                visibleModels.map((model) => (
-                  <Hoverable.Root
+              ? visibleModels.map((model) => (
+                  <LineItemButton
                     key={model.name}
-                    group="LLMConfigurationButton"
-                    widthVariant="full"
-                  >
-                    <LineItemButton
-                      variant="section"
-                      sizePreset="main-ui"
-                      selectVariant="select-heavy"
-                      state="selected"
-                      icon={() => <Checkbox checked />}
-                      title={model.display_name || model.name}
-                      rightChildren={
-                        model.name === defaultModel ? (
-                          <Section>
-                            <Tag title="Default Model" color="blue" />
-                          </Section>
-                        ) : undefined
-                      }
-                    />
-                  </Hoverable.Root>
+                    variant="section"
+                    sizePreset="main-ui"
+                    selectVariant="select-heavy"
+                    state="selected"
+                    icon={() => <Checkbox checked />}
+                    title={model.display_name || model.name}
+                  />
                 ))
-              : // Manual mode: checkbox selection
-                modelConfigurations.map((modelConfiguration) => {
-                  const isSelected = selectedModels.includes(
-                    modelConfiguration.name
-                  );
-                  const isDefault = defaultModel === modelConfiguration.name;
+              : models.map((model) => (
+                  <LineItemButton
+                    key={model.name}
+                    variant="section"
+                    sizePreset="main-ui"
+                    selectVariant="select-heavy"
+                    state={model.is_visible ? "selected" : "empty"}
+                    icon={() => <Checkbox checked={model.is_visible} />}
+                    title={model.name}
+                    onClick={() => setVisibility(model.name, !model.is_visible)}
+                  />
+                ))}
+          </Section>
+        )}
 
-                  return (
-                    <Hoverable.Root
-                      key={modelConfiguration.name}
-                      group="LLMConfigurationButton"
-                      widthVariant="full"
-                    >
-                      <LineItemButton
-                        variant="section"
-                        sizePreset="main-ui"
-                        selectVariant="select-heavy"
-                        state={isSelected ? "selected" : "empty"}
-                        icon={() => <Checkbox checked={isSelected} />}
-                        title={modelConfiguration.name}
-                        onClick={() =>
-                          handleCheckboxChange(
-                            modelConfiguration.name,
-                            !isSelected
-                          )
-                        }
-                        rightChildren={
-                          isSelected ? (
-                            isDefault ? (
-                              <Section>
-                                <Tag color="blue" title="Default Model" />
-                              </Section>
-                            ) : (
-                              <Hoverable.Item
-                                group="LLMConfigurationButton"
-                                variant="opacity-on-hover"
-                              >
-                                <Button
-                                  size="sm"
-                                  prominence="internal"
-                                  onClick={(e) => {
-                                    e.stopPropagation();
-                                    handleSetDefault(modelConfiguration.name);
-                                  }}
-                                  type="button"
-                                >
-                                  Set as default
-                                </Button>
-                              </Hoverable.Item>
-                            )
-                          ) : undefined
-                        }
-                      />
-                    </Hoverable.Root>
-                  );
-                })}
+        {onAddModel && !isAutoMode && (
+          <Section flexDirection="row" gap={0.5}>
+            <div className="flex-1">
+              <InputTypeIn
+                placeholder="Enter model name"
+                value={newModelName}
+                onChange={(e) => setNewModelName(e.target.value)}
+                onKeyDown={(e) => {
+                  if (e.key === "Enter" && newModelName.trim()) {
+                    e.preventDefault();
+                    const trimmed = newModelName.trim();
+                    if (!models.some((m) => m.name === trimmed)) {
+                      onAddModel(trimmed);
+                      setNewModelName("");
+                    }
+                  }
+                }}
+                showClearButton={false}
+              />
+            </div>
+            <Button
+              prominence="secondary"
+              icon={SvgPlusCircle}
+              type="button"
+              disabled={
+                !newModelName.trim() ||
+                models.some((m) => m.name === newModelName.trim())
+              }
+              onClick={() => {
+                const trimmed = newModelName.trim();
+                if (trimmed && !models.some((m) => m.name === trimmed)) {
+                  onAddModel(trimmed);
+                  setNewModelName("");
+                }
+              }}
+            >
+              Add Model
+            </Button>
           </Section>
         )}
 
@@ -593,41 +560,96 @@ export function ModelsField<T extends BaseLLMFormValues>({
   );
 }
 
-// ============================================================================
-// LLMConfigurationModalWrapper
-// ============================================================================
+// ─── ModalWrapper ─────────────────────────────────────────────────────
 
-interface LLMConfigurationModalWrapperProps {
-  providerEndpoint: string;
-  providerName?: string;
-  existingProviderName?: string;
+export interface ModalWrapperProps<
+  T extends BaseLLMFormValues = BaseLLMFormValues,
+> {
+  providerName: string;
+  llmProvider?: LLMProviderView;
   onClose: () => void;
-  isFormValid: boolean;
-  isDirty?: boolean;
-  isTesting?: boolean;
-  isSubmitting?: boolean;
-  children: ReactNode;
+  initialValues: T;
+  validationSchema: FormikConfig<T>["validationSchema"];
+  onSubmit: FormikConfig<T>["onSubmit"];
+  children: React.ReactNode;
+}
+export function ModalWrapper<T extends BaseLLMFormValues = BaseLLMFormValues>({
+  providerName,
+  llmProvider,
+  onClose,
+  initialValues,
+  validationSchema,
+  onSubmit,
+  children,
+}: ModalWrapperProps<T>) {
+  return (
+    <Formik
+      initialValues={initialValues}
+      validationSchema={validationSchema}
+      validateOnMount
+      onSubmit={onSubmit}
+    >
+      {() => (
+        <ModalWrapperInner
+          providerName={providerName}
+          llmProvider={llmProvider}
+          onClose={onClose}
+          modelConfigurations={initialValues.model_configurations}
+        >
+          {children}
+        </ModalWrapperInner>
+      )}
+    </Formik>
+  );
 }
 
-export function LLMConfigurationModalWrapper({
-  providerEndpoint,
+interface ModalWrapperInnerProps {
+  providerName: string;
+  llmProvider?: LLMProviderView;
+  onClose: () => void;
+  modelConfigurations?: ModelConfiguration[];
+  children: React.ReactNode;
+}
+function ModalWrapperInner({
   providerName,
-  existingProviderName,
+  llmProvider,
   onClose,
-  isFormValid,
-  isDirty,
-  isTesting,
-  isSubmitting,
+  modelConfigurations,
   children,
-}: LLMConfigurationModalWrapperProps) {
-  const busy = isTesting || isSubmitting;
-  const providerIcon = getProviderIcon(providerEndpoint);
-  const providerDisplayName =
-    providerName ?? getProviderDisplayName(providerEndpoint);
-  const providerProductName = getProviderProductName(providerEndpoint);
+}: ModalWrapperInnerProps) {
+  const { isValid, dirty, isSubmitting, status, setFieldValue, values } =
+    useFormikContext<BaseLLMFormValues>();
 
-  const title = existingProviderName
-    ? `Configure "${existingProviderName}"`
+  // When SWR resolves after mount, populate model_configurations if still
+  // empty. test_model_name is then derived automatically by
+  // ModelSelectionField's useEffect.
+  useEffect(() => {
+    if (
+      modelConfigurations &&
+      modelConfigurations.length > 0 &&
+      values.model_configurations.length === 0
+    ) {
+      setFieldValue("model_configurations", modelConfigurations);
+    }
+  }, [modelConfigurations]); // eslint-disable-line react-hooks/exhaustive-deps
+
+  const isTesting = status?.isTesting === true;
+  const busy = isTesting || isSubmitting;
+
+  const disabledTooltip = busy
+    ? undefined
+    : !isValid
+      ? "Please fill in all required fields."
+      : !dirty
+        ? "No changes to save."
+        : undefined;
+
+  const providerIcon = getProviderIcon(providerName);
+  const providerDisplayName = getProviderDisplayName(providerName);
+  const providerProductName = getProviderProductName(providerName);
+
+  const title = llmProvider
+    ? `Configure "${llmProvider.name}"`
     : `Set up ${providerProductName}`;
   const description = `Connect to ${providerDisplayName} and set up your ${providerProductName} models.`;
 
@@ -650,21 +672,20 @@ export function LLMConfigurationModalWrapper({
             <Button prominence="secondary" onClick={onClose} type="button">
               Cancel
             </Button>
-            <Disabled
-              disabled={
-                !isFormValid || busy || (!!existingProviderName && !isDirty)
-              }
+            <Button
+              disabled={!isValid || !dirty || busy}
+              type="submit"
+              icon={busy ? SimpleLoader : undefined}
+              tooltip={disabledTooltip}
             >
-              <Button type="submit" icon={busy ? SimpleLoader : undefined}>
-                {existingProviderName
-                  ? busy
-                    ? "Updating"
-                    : "Update"
-                  : busy
-                    ? "Connecting"
-                    : "Connect"}
-              </Button>
-            </Disabled>
+              {llmProvider?.name
+                ? busy
+                  ? "Updating"
+                  : "Update"
+                : busy
+                  ? "Connecting"
+                  : "Connect"}
+            </Button>
           </Modal.Footer>
         </Form>
       </Modal.Content>

web/src/sections/modals/llmConfig/svc.ts

@@ -1,13 +1,8 @@
-import {
-  LLMProviderName,
-  LLMProviderView,
-  ModelConfiguration,
-} from "@/interfaces/llm";
+import { LLMProviderName, LLMProviderView } from "@/interfaces/llm";
 import {
   LLM_ADMIN_URL,
   LLM_PROVIDERS_ADMIN_URL,
 } from "@/lib/llmConfig/constants";
-import { refreshLlmProviderCaches } from "@/lib/llmConfig/cache";
 import { toast } from "@/hooks/useToast";
 import isEqual from "lodash/isEqual";
 import { parseAzureTargetUri } from "@/lib/azureTargetUri";
@@ -18,13 +13,11 @@ import {
 } from "@/lib/analytics";
 import {
   BaseLLMFormValues,
-  SubmitLLMProviderParams,
-  SubmitOnboardingProviderParams,
   TestApiKeyResult,
-  filterModelConfigurations,
-  getAutoModeModelConfigurations,
 } from "@/sections/modals/llmConfig/utils";
 
+// ─── Test helpers ─────────────────────────────────────────────────────────
+
 const submitLlmTestRequest = async (
   payload: Record<string, unknown>,
   fallbackErrorMessage: string
@@ -50,161 +43,6 @@ const submitLlmTestRequest = async (
   }
 };
 
-export const submitLLMProvider = async <T extends BaseLLMFormValues>({
-  providerName,
-  values,
-  initialValues,
-  modelConfigurations,
-  existingLlmProvider,
-  shouldMarkAsDefault,
-  hideSuccess,
-  setIsTesting,
-  mutate,
-  onClose,
-  setSubmitting,
-}: SubmitLLMProviderParams<T>): Promise<void> => {
-  setSubmitting(true);
-
-  const { selected_model_names: visibleModels, api_key, ...rest } = values;
-
-  // In auto mode, use recommended models from descriptor
-  // In manual mode, use user's selection
-  let filteredModelConfigurations: ModelConfiguration[];
-  let finalDefaultModelName = rest.default_model_name;
-
-  if (values.is_auto_mode) {
-    filteredModelConfigurations =
-      getAutoModeModelConfigurations(modelConfigurations);
-
-    // In auto mode, use the first recommended model as default if current default isn't in the list
-    const visibleModelNames = new Set(
-      filteredModelConfigurations.map((m) => m.name)
-    );
-    if (
-      finalDefaultModelName &&
-      !visibleModelNames.has(finalDefaultModelName)
-    ) {
-      finalDefaultModelName = filteredModelConfigurations[0]?.name ?? "";
-    }
-  } else {
-    filteredModelConfigurations = filterModelConfigurations(
-      modelConfigurations,
-      visibleModels,
-      rest.default_model_name as string | undefined
-    );
-  }
-
-  const customConfigChanged = !isEqual(
-    values.custom_config,
-    initialValues.custom_config
-  );
-
-  const normalizedApiBase =
-    typeof rest.api_base === "string" && rest.api_base.trim() === ""
-      ? undefined
-      : rest.api_base;
-
-  const finalValues = {
-    ...rest,
-    api_base: normalizedApiBase,
-    default_model_name: finalDefaultModelName,
-    api_key,
-    api_key_changed: api_key !== (initialValues.api_key as string | undefined),
-    custom_config_changed: customConfigChanged,
-    model_configurations: filteredModelConfigurations,
-  };
-
-  // Test the configuration
-  if (!isEqual(finalValues, initialValues)) {
-    setIsTesting(true);
-
-    const response = await fetch("/api/admin/llm/test", {
-      method: "POST",
-      headers: {
-        "Content-Type": "application/json",
-      },
-      body: JSON.stringify({
-        provider: providerName,
-        ...finalValues,
-        model: finalDefaultModelName,
-        id: existingLlmProvider?.id,
-      }),
-    });
-    setIsTesting(false);
-
-    if (!response.ok) {
-      const errorMsg = (await response.json()).detail;
-      toast.error(errorMsg);
-      setSubmitting(false);
-      return;
-    }
-  }
-
-  const response = await fetch(
-    `${LLM_PROVIDERS_ADMIN_URL}${
-      existingLlmProvider ? "" : "?is_creation=true"
-    }`,
-    {
-      method: "PUT",
-      headers: {
-        "Content-Type": "application/json",
-      },
-      body: JSON.stringify({
-        provider: providerName,
-        ...finalValues,
-        id: existingLlmProvider?.id,
-      }),
-    }
-  );
-
-  if (!response.ok) {
-    const errorMsg = (await response.json()).detail;
-    const fullErrorMsg = existingLlmProvider
-      ? `Failed to update provider: ${errorMsg}`
-      : `Failed to enable provider: ${errorMsg}`;
-    toast.error(fullErrorMsg);
-    return;
-  }
-
-  if (shouldMarkAsDefault) {
-    const newLlmProvider = (await response.json()) as LLMProviderView;
-    const setDefaultResponse = await fetch(`${LLM_ADMIN_URL}/default`, {
-      method: "POST",
-      headers: {
-        "Content-Type": "application/json",
-      },
-      body: JSON.stringify({
-        provider_id: newLlmProvider.id,
-        model_name: finalDefaultModelName,
-      }),
-    });
-    if (!setDefaultResponse.ok) {
-      const errorMsg = (await setDefaultResponse.json()).detail;
-      toast.error(`Failed to set provider as default: ${errorMsg}`);
-      return;
-    }
-  }
-
-  await refreshLlmProviderCaches(mutate);
-  onClose();
-
-  if (!hideSuccess) {
-    const successMsg = existingLlmProvider
-      ? "Provider updated successfully!"
-      : "Provider enabled successfully!";
-    toast.success(successMsg);
-  }
-
-  const knownProviders = new Set<string>(Object.values(LLMProviderName));
-  track(AnalyticsEvent.CONFIGURED_LLM_PROVIDER, {
-    provider: knownProviders.has(providerName) ? providerName : "custom",
-    is_creation: !existingLlmProvider,
-    source: LLMProviderConfiguredSource.ADMIN_PAGE,
-  });
-
-  setSubmitting(false);
-};
-
 export const testApiKeyHelper = async (
   providerName: string,
   formValues: Record<string, unknown>,
@@ -241,7 +79,7 @@ export const testApiKeyHelper = async (
       ...((formValues?.custom_config as Record<string, unknown>) ?? {}),
       ...(customConfigOverride ?? {}),
     },
-    model: modelName ?? (formValues?.default_model_name as string) ?? "",
+    model: modelName ?? (formValues?.test_model_name as string) ?? "",
   };
 
   return await submitLlmTestRequest(
@@ -259,96 +97,148 @@ export const testCustomProvider = async (
   );
 };
 
-export const submitOnboardingProvider = async ({
+// ─── Submit provider ──────────────────────────────────────────────────────
+
+export interface SubmitProviderParams<
+  T extends BaseLLMFormValues = BaseLLMFormValues,
+> {
+  providerName: string;
+  values: T;
+  initialValues: T;
+  existingLlmProvider?: LLMProviderView;
+  shouldMarkAsDefault?: boolean;
+  isCustomProvider?: boolean;
+  setStatus: (status: Record<string, unknown>) => void;
+  setSubmitting: (submitting: boolean) => void;
+  onClose: () => void;
+  /** Called after successful create/update + set-default. Use for cache refresh, state updates, toasts, etc. */
+  onSuccess?: () => void | Promise<void>;
+  /** Analytics source for tracking. @default LLMProviderConfiguredSource.ADMIN_PAGE */
+  analyticsSource?: LLMProviderConfiguredSource;
+}
+
+export async function submitProvider<T extends BaseLLMFormValues>({
   providerName,
-  payload,
-  onboardingState,
-  onboardingActions,
+  values,
+  initialValues,
+  existingLlmProvider,
+  shouldMarkAsDefault,
   isCustomProvider,
+  setStatus,
+  setSubmitting,
   onClose,
-  setIsSubmitting,
-}: SubmitOnboardingProviderParams): Promise<void> => {
-  setIsSubmitting(true);
+  onSuccess,
+  analyticsSource = LLMProviderConfiguredSource.ADMIN_PAGE,
+}: SubmitProviderParams<T>): Promise<void> {
+  setSubmitting(true);
 
-  // Test credentials
-  let result: TestApiKeyResult;
-  if (isCustomProvider) {
-    result = await testCustomProvider(payload);
-  } else {
-    result = await testApiKeyHelper(providerName, payload);
+  const { test_model_name, api_key, ...rest } = values;
+  const testModelName =
+    test_model_name ||
+    values.model_configurations.find((m) => m.is_visible)?.name ||
+    "";
+
+  // ── Test credentials ────────────────────────────────────────────────
+  const customConfigChanged = !isEqual(
+    values.custom_config,
+    initialValues.custom_config
+  );
+
+  const normalizedApiBase =
+    typeof rest.api_base === "string" && rest.api_base.trim() === ""
+      ? undefined
+      : rest.api_base;
+
+  const finalValues = {
+    ...rest,
+    api_base: normalizedApiBase,
+    api_key,
+    api_key_changed: api_key !== (initialValues.api_key as string | undefined),
+    custom_config_changed: customConfigChanged,
+  };
+
+  if (!isEqual(finalValues, initialValues)) {
+    setStatus({ isTesting: true });
+
+    const testResult = await submitLlmTestRequest(
+      {
+        provider: providerName,
+        ...finalValues,
+        model: testModelName,
+        id: existingLlmProvider?.id,
+      },
+      "An error occurred while testing the provider."
+    );
+    setStatus({ isTesting: false });
+
+    if (!testResult.ok) {
+      toast.error(testResult.errorMessage);
+      setSubmitting(false);
+      return;
+    }
   }
 
-  if (!result.ok) {
-    toast.error(result.errorMessage);
-    setIsSubmitting(false);
-    return;
-  }
-
-  // Create provider
-  const response = await fetch(`${LLM_PROVIDERS_ADMIN_URL}?is_creation=true`, {
-    method: "PUT",
-    headers: { "Content-Type": "application/json" },
-    body: JSON.stringify(payload),
-  });
+  // ── Create/update provider ──────────────────────────────────────────
+  const response = await fetch(
+    `${LLM_PROVIDERS_ADMIN_URL}${
+      existingLlmProvider ? "" : "?is_creation=true"
+    }`,
+    {
+      method: "PUT",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({
+        provider: providerName,
+        ...finalValues,
+        id: existingLlmProvider?.id,
+      }),
+    }
+  );
 
   if (!response.ok) {
     const errorMsg = (await response.json()).detail;
-    toast.error(errorMsg);
-    setIsSubmitting(false);
+    const fullErrorMsg = existingLlmProvider
+      ? `Failed to update provider: ${errorMsg}`
+      : `Failed to enable provider: ${errorMsg}`;
+    toast.error(fullErrorMsg);
+    setSubmitting(false);
     return;
   }
 
-  // Set as default if first provider
-  if (
-    onboardingState?.data?.llmProviders == null ||
-    onboardingState.data.llmProviders.length === 0
-  ) {
+  // ── Set as default ──────────────────────────────────────────────────
+  if (shouldMarkAsDefault && testModelName) {
     try {
       const newLlmProvider = await response.json();
       if (newLlmProvider?.id != null) {
-        const defaultModelName =
-          (payload as Record<string, string>).default_model_name ??
-          (payload as Record<string, ModelConfiguration[]>)
-            .model_configurations?.[0]?.name ??
-          "";
-
-        if (defaultModelName) {
-          const setDefaultResponse = await fetch(`${LLM_ADMIN_URL}/default`, {
-            method: "POST",
-            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
-              provider_id: newLlmProvider.id,
-              model_name: defaultModelName,
-            }),
-          });
-          if (!setDefaultResponse.ok) {
-            const err = await setDefaultResponse.json().catch(() => ({}));
-            toast.error(err?.detail ?? "Failed to set provider as default");
-            setIsSubmitting(false);
-            return;
-          }
+        const setDefaultResponse = await fetch(`${LLM_ADMIN_URL}/default`, {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({
+            provider_id: newLlmProvider.id,
+            model_name: testModelName,
+          }),
+        });
+        if (!setDefaultResponse.ok) {
+          const err = await setDefaultResponse.json().catch(() => ({}));
+          toast.error(err?.detail ?? "Failed to set provider as default");
+          setSubmitting(false);
+          return;
         }
       }
-    } catch (_e) {
+    } catch {
       toast.error("Failed to set new provider as default");
     }
   }
 
+  // ── Post-success ────────────────────────────────────────────────────
+  const knownProviders = new Set<string>(Object.values(LLMProviderName));
   track(AnalyticsEvent.CONFIGURED_LLM_PROVIDER, {
-    provider: isCustomProvider ? "custom" : providerName,
-    is_creation: true,
-    source: LLMProviderConfiguredSource.CHAT_ONBOARDING,
+    provider: knownProviders.has(providerName) ? providerName : "custom",
+    is_creation: !existingLlmProvider,
+    source: analyticsSource,
   });
 
-  // Update onboarding state
-  onboardingActions.updateData({
-    llmProviders: [
-      ...(onboardingState?.data.llmProviders ?? []),
-      isCustomProvider ? "custom" : providerName,
-    ],
-  });
-  onboardingActions.setButtonActive(true);
+  if (onSuccess) await onSuccess();
 
-  setIsSubmitting(false);
+  setSubmitting(false);
   onClose();
-};
+}

web/src/sections/modals/llmConfig/utils.ts

@@ -1,197 +1,130 @@
 import {
+  LLMProviderName,
   LLMProviderView,
   ModelConfiguration,
   WellKnownLLMProviderDescriptor,
 } from "@/interfaces/llm";
 import * as Yup from "yup";
-import { ScopedMutator } from "swr";
-import { OnboardingActions, OnboardingState } from "@/interfaces/onboarding";
+import { useWellKnownLLMProvider } from "@/hooks/useLLMProviders";
 
-// Common class names for the Form component across all LLM provider forms
-export const LLM_FORM_CLASS_NAME = "flex flex-col gap-y-4 items-stretch mt-6";
+// ─── useInitialValues ─────────────────────────────────────────────────────
 
-export const buildDefaultInitialValues = (
+/** Builds the merged model list from existing + well-known, deduped by name. */
+function buildModelConfigurations(
   existingLlmProvider?: LLMProviderView,
-  modelConfigurations?: ModelConfiguration[],
-  currentDefaultModelName?: string
-) => {
-  const defaultModelName =
-    (currentDefaultModelName &&
-    existingLlmProvider?.model_configurations?.some(
-      (m) => m.name === currentDefaultModelName
-    )
-      ? currentDefaultModelName
-      : undefined) ??
-    existingLlmProvider?.model_configurations?.[0]?.name ??
-    modelConfigurations?.[0]?.name ??
-    "";
+  wellKnownLLMProvider?: WellKnownLLMProviderDescriptor
+): ModelConfiguration[] {
+  const existingModels = existingLlmProvider?.model_configurations ?? [];
+  const wellKnownModels = wellKnownLLMProvider?.known_models ?? [];
 
-  // Auto mode must be explicitly enabled by the user
-  // Default to false for new providers, preserve existing value when editing
-  const isAutoMode = existingLlmProvider?.is_auto_mode ?? false;
+  const modelMap = new Map<string, ModelConfiguration>();
+  wellKnownModels.forEach((m) => modelMap.set(m.name, m));
+  existingModels.forEach((m) => modelMap.set(m.name, m));
+
+  return Array.from(modelMap.values());
+}
+
+/** Shared initial values for all LLM provider forms (both onboarding and admin). */
+export function useInitialValues(
+  isOnboarding: boolean,
+  providerName: LLMProviderName,
+  existingLlmProvider?: LLMProviderView
+) {
+  const { wellKnownLLMProvider } = useWellKnownLLMProvider(providerName);
+
+  const modelConfigurations = buildModelConfigurations(
+    existingLlmProvider,
+    wellKnownLLMProvider ?? undefined
+  );
+
+  const testModelName =
+    modelConfigurations.find((m) => m.is_visible)?.name ??
+    wellKnownLLMProvider?.recommended_default_model?.name;
 
   return {
-    name: existingLlmProvider?.name || "",
-    default_model_name: defaultModelName,
+    provider: existingLlmProvider?.provider ?? providerName,
+    name: isOnboarding ? providerName : existingLlmProvider?.name ?? "",
+    api_key: existingLlmProvider?.api_key ?? undefined,
+    api_base: existingLlmProvider?.api_base ?? undefined,
     is_public: existingLlmProvider?.is_public ?? true,
-    is_auto_mode: isAutoMode,
+    is_auto_mode: existingLlmProvider?.is_auto_mode ?? true,
     groups: existingLlmProvider?.groups ?? [],
     personas: existingLlmProvider?.personas ?? [],
-    selected_model_names: existingLlmProvider
-      ? existingLlmProvider.model_configurations
-          .filter((modelConfiguration) => modelConfiguration.is_visible)
-          .map((modelConfiguration) => modelConfiguration.name)
-      : modelConfigurations
-          ?.filter((modelConfiguration) => modelConfiguration.is_visible)
-          .map((modelConfiguration) => modelConfiguration.name) ?? [],
+    model_configurations: modelConfigurations,
+    test_model_name: testModelName,
   };
-};
+}
+
+// ─── buildValidationSchema ────────────────────────────────────────────────
+
+interface ValidationSchemaOptions {
+  apiKey?: boolean;
+  apiBase?: boolean;
+  extra?: Yup.ObjectShape;
+}
+
+/**
+ * Builds the validation schema for a modal.
+ *
+ * @param isOnboarding — controls the base schema:
+ *   - `true`:  minimal (only `test_model_name`).
+ *   - `false`: full admin schema (display name, access, models, etc.).
+ * @param options.apiKey — require `api_key`.
+ * @param options.apiBase — require `api_base`.
+ * @param options.extra — arbitrary Yup fields for provider-specific validation.
+ */
+export function buildValidationSchema(
+  isOnboarding: boolean,
+  { apiKey, apiBase, extra }: ValidationSchemaOptions = {}
+) {
+  const providerFields: Yup.ObjectShape = {
+    ...(apiKey && {
+      api_key: Yup.string().required("API Key is required"),
+    }),
+    ...(apiBase && {
+      api_base: Yup.string().required("API Base URL is required"),
+    }),
+    ...extra,
+  };
+
+  if (isOnboarding) {
+    return Yup.object().shape({
+      test_model_name: Yup.string().required("Model name is required"),
+      ...providerFields,
+    });
+  }
 
-export const buildDefaultValidationSchema = () => {
   return Yup.object({
     name: Yup.string().required("Display Name is required"),
-    default_model_name: Yup.string().required("Model name is required"),
     is_public: Yup.boolean().required(),
     is_auto_mode: Yup.boolean().required(),
     groups: Yup.array().of(Yup.number()),
     personas: Yup.array().of(Yup.number()),
-    selected_model_names: Yup.array().of(Yup.string()),
+    test_model_name: Yup.string().required("Model name is required"),
+    ...providerFields,
   });
-};
+}
 
-export const buildAvailableModelConfigurations = (
-  existingLlmProvider?: LLMProviderView,
-  wellKnownLLMProvider?: WellKnownLLMProviderDescriptor
-): ModelConfiguration[] => {
-  const existingModels = existingLlmProvider?.model_configurations ?? [];
-  const wellKnownModels = wellKnownLLMProvider?.known_models ?? [];
+// ─── Form value types ─────────────────────────────────────────────────────
 
-  // Create a map to deduplicate by model name, preferring existing models
-  const modelMap = new Map<string, ModelConfiguration>();
-
-  // Add well-known models first
-  wellKnownModels.forEach((model) => {
-    modelMap.set(model.name, model);
-  });
-
-  // Override with existing models (they take precedence)
-  existingModels.forEach((model) => {
-    modelMap.set(model.name, model);
-  });
-
-  return Array.from(modelMap.values());
-};
-
-// Base form values that all provider forms share
+/** Base form values that all provider forms share. */
 export interface BaseLLMFormValues {
   name: string;
   api_key?: string;
   api_base?: string;
-  default_model_name?: string;
+  /** Model name used for the test request — automatically derived. */
+  test_model_name?: string;
   is_public: boolean;
   is_auto_mode: boolean;
   groups: number[];
   personas: number[];
-  selected_model_names: string[];
+  /** The full model list with is_visible set directly by user interaction. */
+  model_configurations: ModelConfiguration[];
   custom_config?: Record<string, string>;
 }
 
-export interface SubmitLLMProviderParams<
-  T extends BaseLLMFormValues = BaseLLMFormValues,
-> {
-  providerName: string;
-  values: T;
-  initialValues: T;
-  modelConfigurations: ModelConfiguration[];
-  existingLlmProvider?: LLMProviderView;
-  shouldMarkAsDefault?: boolean;
-  hideSuccess?: boolean;
-  setIsTesting: (testing: boolean) => void;
-  mutate: ScopedMutator;
-  onClose: () => void;
-  setSubmitting: (submitting: boolean) => void;
-}
-
-export const filterModelConfigurations = (
-  currentModelConfigurations: ModelConfiguration[],
-  visibleModels: string[],
-  defaultModelName?: string
-): ModelConfiguration[] => {
-  return currentModelConfigurations
-    .map(
-      (modelConfiguration): ModelConfiguration => ({
-        name: modelConfiguration.name,
-        is_visible: visibleModels.includes(modelConfiguration.name),
-        max_input_tokens: modelConfiguration.max_input_tokens ?? null,
-        supports_image_input: modelConfiguration.supports_image_input,
-        supports_reasoning: modelConfiguration.supports_reasoning,
-        display_name: modelConfiguration.display_name,
-      })
-    )
-    .filter(
-      (modelConfiguration) =>
-        modelConfiguration.name === defaultModelName ||
-        modelConfiguration.is_visible
-    );
-};
-
-// Helper to get model configurations for auto mode
-// In auto mode, we include ALL models but preserve their visibility status
-// Models in the auto config are visible, others are created but not visible
-export const getAutoModeModelConfigurations = (
-  modelConfigurations: ModelConfiguration[]
-): ModelConfiguration[] => {
-  return modelConfigurations.map(
-    (modelConfiguration): ModelConfiguration => ({
-      name: modelConfiguration.name,
-      is_visible: modelConfiguration.is_visible,
-      max_input_tokens: modelConfiguration.max_input_tokens ?? null,
-      supports_image_input: modelConfiguration.supports_image_input,
-      supports_reasoning: modelConfiguration.supports_reasoning,
-      display_name: modelConfiguration.display_name,
-    })
-  );
-};
+// ─── Misc ─────────────────────────────────────────────────────────────────
 
 export type TestApiKeyResult =
   | { ok: true }
   | { ok: false; errorMessage: string };
-
-export const getModelOptions = (
-  fetchedModelConfigurations: Array<{ name: string }>
-) => {
-  return fetchedModelConfigurations.map((model) => ({
-    label: model.name,
-    value: model.name,
-  }));
-};
-
-/** Initial values used by onboarding forms (flat shape, always creating new). */
-export const buildOnboardingInitialValues = () => ({
-  name: "",
-  provider: "",
-  api_key: "",
-  api_base: "",
-  api_version: "",
-  default_model_name: "",
-  model_configurations: [] as ModelConfiguration[],
-  custom_config: {} as Record<string, string>,
-  api_key_changed: true,
-  groups: [] as number[],
-  is_public: true,
-  is_auto_mode: false,
-  personas: [] as number[],
-  selected_model_names: [] as string[],
-  deployment_name: "",
-  target_uri: "",
-});
-
-export interface SubmitOnboardingProviderParams {
-  providerName: string;
-  payload: Record<string, unknown>;
-  onboardingState: OnboardingState;
-  onboardingActions: OnboardingActions;
-  isCustomProvider: boolean;
-  onClose: () => void;
-  setIsSubmitting: (submitting: boolean) => void;
-}

web/src/sections/onboarding/forms/getOnboardingForm.tsx

@@ -2,6 +2,7 @@ import React from "react";
 import {
   WellKnownLLMProviderDescriptor,
   LLMProviderName,
+  LLMProviderFormProps,
 } from "@/interfaces/llm";
 import { OnboardingActions, OnboardingState } from "@/interfaces/onboarding";
 import OpenAIModal from "@/sections/modals/llmConfig/OpenAIModal";
@@ -12,8 +13,9 @@ import BedrockModal from "@/sections/modals/llmConfig/BedrockModal";
 import VertexAIModal from "@/sections/modals/llmConfig/VertexAIModal";
 import OpenRouterModal from "@/sections/modals/llmConfig/OpenRouterModal";
 import CustomModal from "@/sections/modals/llmConfig/CustomModal";
-import LMStudioForm from "@/sections/modals/llmConfig/LMStudioForm";
+import LMStudioModal from "@/sections/modals/llmConfig/LMStudioModal";
 import LiteLLMProxyModal from "@/sections/modals/llmConfig/LiteLLMProxyModal";
+import OpenAICompatibleModal from "@/sections/modals/llmConfig/OpenAICompatibleModal";
 
 // Display info for LLM provider cards - title is the product name, displayName is the company/platform
 const PROVIDER_DISPLAY_INFO: Record<
@@ -47,6 +49,10 @@ const PROVIDER_DISPLAY_INFO: Record<
     title: "LiteLLM Proxy",
     displayName: "LiteLLM Proxy",
   },
+  [LLMProviderName.OPENAI_COMPATIBLE]: {
+    title: "OpenAI Compatible",
+    displayName: "OpenAI Compatible",
+  },
 };
 
 export function getProviderDisplayInfo(providerName: string): {
@@ -78,12 +84,26 @@ export function getOnboardingForm({
   open,
   onOpenChange,
 }: OnboardingFormProps): React.ReactNode {
-  const sharedProps = {
+  const providerName = isCustomProvider
+    ? "custom"
+    : llmDescriptor?.name ?? "custom";
+
+  const sharedProps: LLMProviderFormProps = {
     variant: "onboarding" as const,
-    onboardingState,
+    shouldMarkAsDefault:
+      (onboardingState?.data.llmProviders ?? []).length === 0,
     onboardingActions,
     open,
     onOpenChange,
+    onSuccess: () => {
+      onboardingActions.updateData({
+        llmProviders: [
+          ...(onboardingState?.data.llmProviders ?? []),
+          providerName,
+        ],
+      });
+      onboardingActions.setButtonActive(true);
+    },
   };
 
   // Handle custom provider
@@ -91,38 +111,36 @@ export function getOnboardingForm({
     return <CustomModal {...sharedProps} />;
   }
 
-  const providerProps = {
-    ...sharedProps,
-    llmDescriptor,
-  };
-
   switch (llmDescriptor.name) {
     case LLMProviderName.OPENAI:
-      return <OpenAIModal {...providerProps} />;
+      return <OpenAIModal {...sharedProps} />;
 
     case LLMProviderName.ANTHROPIC:
-      return <AnthropicModal {...providerProps} />;
+      return <AnthropicModal {...sharedProps} />;
 
     case LLMProviderName.OLLAMA_CHAT:
-      return <OllamaModal {...providerProps} />;
+      return <OllamaModal {...sharedProps} />;
 
     case LLMProviderName.AZURE:
-      return <AzureModal {...providerProps} />;
+      return <AzureModal {...sharedProps} />;
 
     case LLMProviderName.BEDROCK:
-      return <BedrockModal {...providerProps} />;
+      return <BedrockModal {...sharedProps} />;
 
     case LLMProviderName.VERTEX_AI:
-      return <VertexAIModal {...providerProps} />;
+      return <VertexAIModal {...sharedProps} />;
 
     case LLMProviderName.OPENROUTER:
-      return <OpenRouterModal {...providerProps} />;
+      return <OpenRouterModal {...sharedProps} />;
 
     case LLMProviderName.LM_STUDIO:
-      return <LMStudioForm {...providerProps} />;
+      return <LMStudioModal {...sharedProps} />;
 
     case LLMProviderName.LITELLM_PROXY:
-      return <LiteLLMProxyModal {...providerProps} />;
+      return <LiteLLMProxyModal {...sharedProps} />;
+
+    case LLMProviderName.OPENAI_COMPATIBLE:
+      return <OpenAICompatibleModal {...sharedProps} />;
 
     default:
       return <CustomModal {...sharedProps} />;