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12 Commits

Author SHA1 Message Date
hagen-danswer
0c13c9a106 updates 2024-12-15 15:12:55 -08:00
hagen-danswer
24525ca3d8 all done 2024-12-13 12:18:16 -08:00
hagen-danswer
8b8030a61f Merge pull request #3379 from onyx-dot-app/hagen-initial-branch
refactor
2024-12-12 15:55:22 -08:00
hagen-danswer
f4e8ac1dde 2 graphs down 2024-12-12 15:54:13 -08:00
hagen-danswer
ad4df04159 done with exanded retrieval 2024-12-12 15:20:39 -08:00
hagen-danswer
f5e28e0f54 minor refactor 2024-12-09 11:34:11 -08:00
hagen-danswer
091cb136c4 got core qa graph working 2024-12-07 12:25:54 -08:00
hagen-danswer
56052c5b4b imports 2024-12-07 06:09:57 -08:00
hagen-danswer
617726207b all 3 graphs r done 2024-12-07 06:06:22 -08:00
hagen-danswer
1be58e74b3 Finished primary graph 2024-12-06 11:01:03 -08:00
hagen-danswer
a693c991d7 Merge remote-tracking branch 'origin/agent-search-a' into initial-implementation 2024-12-04 15:42:58 -08:00
hagen-danswer
4b28686721 Added Initial Implementation of the Agent Search Graph 2024-12-02 07:16:08 -08:00
1434 changed files with 34391 additions and 86015 deletions

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@@ -1,14 +1,29 @@
## Description
[Provide a brief description of the changes in this PR]
## How Has This Been Tested?
## How Has This Been Tested?
[Describe the tests you ran to verify your changes]
## Accepted Risk (provide if relevant)
N/A
## Related Issue(s) (provide if relevant)
N/A
## Mental Checklist:
- All of the automated tests pass
- All PR comments are addressed and marked resolved
- If there are migrations, they have been rebased to latest main
- If there are new dependencies, they are added to the requirements
- If there are new environment variables, they are added to all of the deployment methods
- If there are new APIs that don't require auth, they are added to PUBLIC_ENDPOINT_SPECS
- Docker images build and basic functionalities work
- Author has done a final read through of the PR right before merge
## Backporting (check the box to trigger backport action)
Note: You have to check that the action passes, otherwise resolve the conflicts manually and tag the patches.
- [ ] This PR should be backported (make sure to check that the backport attempt succeeds)
- [ ] [Optional] Override Linear Check

View File

@@ -6,7 +6,7 @@ on:
- "*"
env:
REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'onyxdotapp/onyx-backend-cloud' || 'onyxdotapp/onyx-backend' }}
REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'danswer/danswer-backend-cloud' || 'danswer/danswer-backend' }}
LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
jobs:
@@ -44,7 +44,7 @@ jobs:
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
build-args: |
ONYX_VERSION=${{ github.ref_name }}
DANSWER_VERSION=${{ github.ref_name }}
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
@@ -57,7 +57,7 @@ jobs:
TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
with:
# To run locally: trivy image --severity HIGH,CRITICAL onyxdotapp/onyx-backend
# To run locally: trivy image --severity HIGH,CRITICAL danswer/danswer-backend
image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
severity: "CRITICAL,HIGH"
trivyignores: ./backend/.trivyignore

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@@ -7,7 +7,7 @@ on:
- "*"
env:
REGISTRY_IMAGE: onyxdotapp/onyx-web-server-cloud
REGISTRY_IMAGE: danswer/danswer-web-server-cloud
LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
jobs:
@@ -60,15 +60,12 @@ jobs:
platforms: ${{ matrix.platform }}
push: true
build-args: |
ONYX_VERSION=${{ github.ref_name }}
DANSWER_VERSION=${{ github.ref_name }}
NEXT_PUBLIC_CLOUD_ENABLED=true
NEXT_PUBLIC_POSTHOG_KEY=${{ secrets.POSTHOG_KEY }}
NEXT_PUBLIC_POSTHOG_HOST=${{ secrets.POSTHOG_HOST }}
NEXT_PUBLIC_SENTRY_DSN=${{ secrets.SENTRY_DSN }}
NEXT_PUBLIC_GTM_ENABLED=true
NEXT_PUBLIC_FORGOT_PASSWORD_ENABLED=true
NEXT_PUBLIC_INCLUDE_ERROR_POPUP_SUPPORT_LINK=true
NODE_OPTIONS=--max-old-space-size=8192
# needed due to weird interactions with the builds for different platforms
no-cache: true
labels: ${{ steps.meta.outputs.labels }}

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@@ -6,31 +6,20 @@ on:
- "*"
env:
REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'onyxdotapp/onyx-model-server-cloud' || 'onyxdotapp/onyx-model-server' }}
REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'danswer/danswer-model-server-cloud' || 'danswer/danswer-model-server' }}
LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
DOCKER_BUILDKIT: 1
BUILDKIT_PROGRESS: plain
jobs:
build-amd64:
runs-on:
[runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-amd64"]
build-and-push:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: System Info
run: |
df -h
free -h
docker system prune -af --volumes
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
with:
driver-opts: |
image=moby/buildkit:latest
network=host
- name: Login to Docker Hub
uses: docker/login-action@v3
@@ -38,86 +27,29 @@ jobs:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Build and Push AMD64
- name: Model Server Image Docker Build and Push
uses: docker/build-push-action@v5
with:
context: ./backend
file: ./backend/Dockerfile.model_server
platforms: linux/amd64
platforms: linux/amd64,linux/arm64
push: true
tags: ${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}-amd64
tags: |
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
build-args: |
DANSWER_VERSION=${{ github.ref_name }}
outputs: type=registry
provenance: false
build-arm64:
runs-on:
[runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-arm64"]
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: System Info
run: |
df -h
free -h
docker system prune -af --volumes
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
with:
driver-opts: |
image=moby/buildkit:latest
network=host
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Build and Push ARM64
uses: docker/build-push-action@v5
with:
context: ./backend
file: ./backend/Dockerfile.model_server
platforms: linux/arm64
push: true
tags: ${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}-arm64
build-args: |
DANSWER_VERSION=${{ github.ref_name }}
outputs: type=registry
provenance: false
merge-and-scan:
needs: [build-amd64, build-arm64]
runs-on: ubuntu-latest
steps:
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Create and Push Multi-arch Manifest
run: |
docker buildx create --use
docker buildx imagetools create -t ${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }} \
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}-amd64 \
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}-arm64
if [[ "${{ env.LATEST_TAG }}" == "true" ]]; then
docker buildx imagetools create -t ${{ env.REGISTRY_IMAGE }}:latest \
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}-amd64 \
${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}-arm64
fi
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
env:
TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
with:
image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
image-ref: docker.io/danswer/danswer-model-server:${{ github.ref_name }}
severity: "CRITICAL,HIGH"
timeout: "10m"

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@@ -3,12 +3,12 @@ name: Build and Push Web Image on Tag
on:
push:
tags:
- "*"
- '*'
env:
REGISTRY_IMAGE: onyxdotapp/onyx-web-server
REGISTRY_IMAGE: danswer/danswer-web-server
LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
jobs:
build:
runs-on:
@@ -27,11 +27,11 @@ jobs:
- name: Prepare
run: |
platform=${{ matrix.platform }}
echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
- name: Checkout
uses: actions/checkout@v4
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
@@ -40,16 +40,16 @@ jobs:
tags: |
type=raw,value=${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
type=raw,value=${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Build and push by digest
id: build
uses: docker/build-push-action@v5
@@ -59,20 +59,18 @@ jobs:
platforms: ${{ matrix.platform }}
push: true
build-args: |
ONYX_VERSION=${{ github.ref_name }}
NODE_OPTIONS=--max-old-space-size=8192
# needed due to weird interactions with the builds for different platforms
DANSWER_VERSION=${{ github.ref_name }}
# needed due to weird interactions with the builds for different platforms
no-cache: true
labels: ${{ steps.meta.outputs.labels }}
outputs: type=image,name=${{ env.REGISTRY_IMAGE }},push-by-digest=true,name-canonical=true,push=true
- name: Export digest
run: |
mkdir -p /tmp/digests
digest="${{ steps.build.outputs.digest }}"
touch "/tmp/digests/${digest#sha256:}"
touch "/tmp/digests/${digest#sha256:}"
- name: Upload digest
uses: actions/upload-artifact@v4
with:
@@ -92,42 +90,42 @@ jobs:
path: /tmp/digests
pattern: digests-*
merge-multiple: true
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Docker meta
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY_IMAGE }}
- name: Login to Docker Hub
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Create manifest list and push
working-directory: /tmp/digests
run: |
docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
$(printf '${{ env.REGISTRY_IMAGE }}@sha256:%s ' *)
$(printf '${{ env.REGISTRY_IMAGE }}@sha256:%s ' *)
- name: Inspect image
run: |
docker buildx imagetools inspect ${{ env.REGISTRY_IMAGE }}:${{ steps.meta.outputs.version }}
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
# trivy has their own rate limiting issues causing this action to flake
# we worked around it by hardcoding to different db repos in env
# can re-enable when they figure it out
# https://github.com/aquasecurity/trivy/discussions/7538
# https://github.com/aquasecurity/trivy-action/issues/389
- name: Run Trivy vulnerability scanner
uses: aquasecurity/trivy-action@master
env:
TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
TRIVY_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
with:
image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
severity: "CRITICAL,HIGH"
severity: 'CRITICAL,HIGH'

View File

@@ -7,31 +7,31 @@ on:
workflow_dispatch:
inputs:
version:
description: "The version (ie v0.0.1) to tag as latest"
description: 'The version (ie v0.0.1) to tag as latest'
required: true
jobs:
tag:
# See https://runs-on.com/runners/linux/
# use a lower powered instance since this just does i/o to docker hub
runs-on: [runs-on, runner=2cpu-linux-x64, "run-id=${{ github.run_id }}"]
runs-on: [runs-on,runner=2cpu-linux-x64,"run-id=${{ github.run_id }}"]
steps:
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v1
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v1
- name: Login to Docker Hub
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Login to Docker Hub
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_TOKEN }}
- name: Enable Docker CLI experimental features
run: echo "DOCKER_CLI_EXPERIMENTAL=enabled" >> $GITHUB_ENV
- name: Enable Docker CLI experimental features
run: echo "DOCKER_CLI_EXPERIMENTAL=enabled" >> $GITHUB_ENV
- name: Pull, Tag and Push Web Server Image
run: |
docker buildx imagetools create -t onyxdotapp/onyx-web-server:latest onyxdotapp/onyx-web-server:${{ github.event.inputs.version }}
- name: Pull, Tag and Push Web Server Image
run: |
docker buildx imagetools create -t danswer/danswer-web-server:latest danswer/danswer-web-server:${{ github.event.inputs.version }}
- name: Pull, Tag and Push API Server Image
run: |
docker buildx imagetools create -t onyxdotapp/onyx-backend:latest onyxdotapp/onyx-backend:${{ github.event.inputs.version }}
- name: Pull, Tag and Push API Server Image
run: |
docker buildx imagetools create -t danswer/danswer-backend:latest danswer/danswer-backend:${{ github.event.inputs.version }}

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@@ -8,42 +8,43 @@ on:
workflow_dispatch:
inputs:
hotfix_commit:
description: "Hotfix commit hash"
description: 'Hotfix commit hash'
required: true
hotfix_suffix:
description: "Hotfix branch suffix (e.g. hotfix/v0.8-{suffix})"
description: 'Hotfix branch suffix (e.g. hotfix/v0.8-{suffix})'
required: true
release_branch_pattern:
description: "Release branch pattern (regex)"
description: 'Release branch pattern (regex)'
required: true
default: "release/.*"
default: 'release/.*'
auto_merge:
description: "Automatically merge the hotfix PRs"
description: 'Automatically merge the hotfix PRs'
required: true
type: choice
default: "true"
default: 'true'
options:
- true
- false
jobs:
hotfix_release_branches:
permissions: write-all
# See https://runs-on.com/runners/linux/
# use a lower powered instance since this just does i/o to docker hub
runs-on: [runs-on, runner=2cpu-linux-x64, "run-id=${{ github.run_id }}"]
runs-on: [runs-on,runner=2cpu-linux-x64,"run-id=${{ github.run_id }}"]
steps:
# needs RKUO_DEPLOY_KEY for write access to merge PR's
- name: Checkout Repository
uses: actions/checkout@v4
with:
ssh-key: "${{ secrets.RKUO_DEPLOY_KEY }}"
fetch-depth: 0
- name: Set up Git user
run: |
git config user.name "Richard Kuo [bot]"
git config user.email "rkuo[bot]@onyx.app"
git config user.email "rkuo[bot]@danswer.ai"
- name: Fetch All Branches
run: |
@@ -61,10 +62,10 @@ jobs:
echo "No release branches found matching pattern '${{ github.event.inputs.release_branch_pattern }}'."
exit 1
fi
echo "Found release branches:"
echo "$BRANCHES"
# Join the branches into a single line separated by commas
BRANCHES_JOINED=$(echo "$BRANCHES" | tr '\n' ',' | sed 's/,$//')
@@ -168,4 +169,4 @@ jobs:
echo "Failed to merge pull request #$PR_NUMBER."
fi
fi
done
done

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@@ -4,7 +4,7 @@ name: Backport on Merge
on:
pull_request:
types: [closed] # Later we check for merge so only PRs that go in can get backported
types: [closed] # Later we check for merge so only PRs that go in can get backported
permissions:
contents: write
@@ -26,9 +26,9 @@ jobs:
- name: Set up Git user
run: |
git config user.name "Richard Kuo [bot]"
git config user.email "rkuo[bot]@onyx.app"
git config user.email "rkuo[bot]@danswer.ai"
git fetch --prune
- name: Check for Backport Checkbox
id: checkbox-check
run: |
@@ -51,14 +51,14 @@ jobs:
# Fetch latest tags for beta and stable
LATEST_BETA_TAG=$(git tag -l "v[0-9]*.[0-9]*.[0-9]*-beta.[0-9]*" | grep -E "^v[0-9]+\.[0-9]+\.[0-9]+-beta\.[0-9]+$" | grep -v -- "-cloud" | sort -Vr | head -n 1)
LATEST_STABLE_TAG=$(git tag -l "v[0-9]*.[0-9]*.[0-9]*" | grep -E "^v[0-9]+\.[0-9]+\.[0-9]+$" | sort -Vr | head -n 1)
# Handle case where no beta tags exist
if [[ -z "$LATEST_BETA_TAG" ]]; then
NEW_BETA_TAG="v1.0.0-beta.1"
else
NEW_BETA_TAG=$(echo $LATEST_BETA_TAG | awk -F '[.-]' '{print $1 "." $2 "." $3 "-beta." ($NF+1)}')
fi
# Increment latest stable tag
NEW_STABLE_TAG=$(echo $LATEST_STABLE_TAG | awk -F '.' '{print $1 "." $2 "." ($3+1)}')
echo "latest_beta_tag=$LATEST_BETA_TAG" >> $GITHUB_OUTPUT
@@ -80,10 +80,10 @@ jobs:
run: |
set -e
echo "Backporting to beta ${{ steps.list-branches.outputs.beta }} and stable ${{ steps.list-branches.outputs.stable }}"
# Echo the merge commit SHA
echo "Merge commit SHA: ${{ github.event.pull_request.merge_commit_sha }}"
# Fetch all history for all branches and tags
git fetch --prune
@@ -98,7 +98,7 @@ jobs:
echo "Cherry-pick to beta failed due to conflicts."
exit 1
}
# Create new beta branch/tag
git tag ${{ steps.list-branches.outputs.new_beta_tag }}
# Push the changes and tag to the beta branch using PAT
@@ -110,13 +110,13 @@ jobs:
echo "Last 5 commits on stable branch:"
git log -n 5 --pretty=format:"%H"
echo "" # Newline for formatting
# Cherry-pick the merge commit from the merged PR
git cherry-pick -m 1 ${{ github.event.pull_request.merge_commit_sha }} || {
echo "Cherry-pick to stable failed due to conflicts."
exit 1
}
# Create new stable branch/tag
git tag ${{ steps.list-branches.outputs.new_stable_tag }}
# Push the changes and tag to the stable branch using PAT

View File

@@ -8,32 +8,24 @@ on: push
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
GEN_AI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
MOCK_LLM_RESPONSE: true
jobs:
playwright-tests:
name: Playwright Tests
# See https://runs-on.com/runners/linux/
runs-on:
[
runs-on,
runner=32cpu-linux-x64,
disk=large,
"run-id=${{ github.run_id }}",
]
runs-on: [runs-on,runner=8cpu-linux-x64,ram=16,"run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11"
cache: "pip"
python-version: '3.11'
cache: 'pip'
cache-dependency-path: |
backend/requirements/default.txt
backend/requirements/dev.txt
@@ -43,7 +35,7 @@ jobs:
pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
- name: Setup node
uses: actions/setup-node@v4
with:
@@ -56,7 +48,7 @@ jobs:
- name: Install playwright browsers
working-directory: ./web
run: npx playwright install --with-deps
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -68,13 +60,13 @@ jobs:
# tag every docker image with "test" so that we can spin up the correct set
# of images during testing
# we use the runs-on cache for docker builds
# in conjunction with runs-on runners, it has better speed and unlimited caching
# https://runs-on.com/caching/s3-cache-for-github-actions/
# https://runs-on.com/caching/docker/
# https://github.com/moby/buildkit#s3-cache-experimental
# images are built and run locally for testing purposes. Not pushed.
- name: Build Web Docker image
@@ -83,7 +75,7 @@ jobs:
context: ./web
file: ./web/Dockerfile
platforms: linux/amd64
tags: onyxdotapp/onyx-web-server:test
tags: danswer/danswer-web-server:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/web-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
@@ -95,7 +87,7 @@ jobs:
context: ./backend
file: ./backend/Dockerfile
platforms: linux/amd64
tags: onyxdotapp/onyx-backend:test
tags: danswer/danswer-backend:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
@@ -107,7 +99,7 @@ jobs:
context: ./backend
file: ./backend/Dockerfile.model_server
platforms: linux/amd64
tags: onyxdotapp/onyx-model-server:test
tags: danswer/danswer-model-server:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
@@ -118,7 +110,6 @@ jobs:
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
AUTH_TYPE=basic \
GEN_AI_API_KEY=${{ secrets.OPENAI_API_KEY }} \
REQUIRE_EMAIL_VERIFICATION=false \
DISABLE_TELEMETRY=true \
IMAGE_TAG=test \
@@ -128,12 +119,12 @@ jobs:
- name: Wait for service to be ready
run: |
echo "Starting wait-for-service script..."
docker logs -f danswer-stack-api_server-1 &
start_time=$(date +%s)
timeout=300 # 5 minutes in seconds
while true; do
current_time=$(date +%s)
elapsed_time=$((current_time - start_time))
@@ -161,7 +152,7 @@ jobs:
- name: Run pytest playwright test init
working-directory: ./backend
env:
env:
PYTEST_IGNORE_SKIP: true
run: pytest -s tests/integration/tests/playwright/test_playwright.py
@@ -177,7 +168,7 @@ jobs:
name: test-results
path: ./web/test-results
retention-days: 30
# save before stopping the containers so the logs can be captured
- name: Save Docker logs
if: success() || failure()
@@ -185,7 +176,7 @@ jobs:
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack logs > docker-compose.log
mv docker-compose.log ${{ github.workspace }}/docker-compose.log
- name: Upload logs
if: success() || failure()
uses: actions/upload-artifact@v4
@@ -200,41 +191,35 @@ jobs:
chromatic-tests:
name: Chromatic Tests
needs: playwright-tests
runs-on:
[
runs-on,
runner=32cpu-linux-x64,
disk=large,
"run-id=${{ github.run_id }}",
]
runs-on: [runs-on,runner=8cpu-linux-x64,ram=16,"run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Setup node
uses: actions/setup-node@v4
with:
node-version: 22
- name: Install node dependencies
working-directory: ./web
run: npm ci
- name: Download Playwright test results
uses: actions/download-artifact@v4
with:
name: test-results
path: ./web/test-results
- name: Run Chromatic
uses: chromaui/action@latest
with:
playwright: true
projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
workingDir: ./web
env:
env:
CHROMATIC_ARCHIVE_LOCATION: ./test-results

View File

@@ -21,10 +21,10 @@ jobs:
- name: Set up Helm
uses: azure/setup-helm@v4.2.0
with:
version: v3.17.0
version: v3.14.4
- name: Set up chart-testing
uses: helm/chart-testing-action@v2.7.0
uses: helm/chart-testing-action@v2.6.1
# even though we specify chart-dirs in ct.yaml, it isn't used by ct for the list-changed command...
- name: Run chart-testing (list-changed)
@@ -37,6 +37,22 @@ jobs:
echo "changed=true" >> "$GITHUB_OUTPUT"
fi
# rkuo: I don't think we need python?
# - name: Set up Python
# uses: actions/setup-python@v5
# with:
# python-version: '3.11'
# cache: 'pip'
# cache-dependency-path: |
# backend/requirements/default.txt
# backend/requirements/dev.txt
# backend/requirements/model_server.txt
# - run: |
# python -m pip install --upgrade pip
# pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
# pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
# pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
# lint all charts if any changes were detected
- name: Run chart-testing (lint)
if: steps.list-changed.outputs.changed == 'true'
@@ -46,7 +62,7 @@ jobs:
- name: Create kind cluster
if: steps.list-changed.outputs.changed == 'true'
uses: helm/kind-action@v1.12.0
uses: helm/kind-action@v1.10.0
- name: Run chart-testing (install)
if: steps.list-changed.outputs.changed == 'true'

View File

@@ -8,7 +8,7 @@ on:
pull_request:
branches:
- main
- "release/**"
- 'release/**'
env:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
@@ -16,11 +16,11 @@ env:
CONFLUENCE_TEST_SPACE_URL: ${{ secrets.CONFLUENCE_TEST_SPACE_URL }}
CONFLUENCE_USER_NAME: ${{ secrets.CONFLUENCE_USER_NAME }}
CONFLUENCE_ACCESS_TOKEN: ${{ secrets.CONFLUENCE_ACCESS_TOKEN }}
jobs:
integration-tests:
# See https://runs-on.com/runners/linux/
runs-on: [runs-on, runner=32cpu-linux-x64, "run-id=${{ github.run_id }}"]
runs-on: [runs-on,runner=8cpu-linux-x64,ram=16,"run-id=${{ github.run_id }}"]
steps:
- name: Checkout code
uses: actions/checkout@v4
@@ -36,21 +36,21 @@ jobs:
# tag every docker image with "test" so that we can spin up the correct set
# of images during testing
# We don't need to build the Web Docker image since it's not yet used
# in the integration tests. We have a separate action to verify that it builds
# in the integration tests. We have a separate action to verify that it builds
# successfully.
- name: Pull Web Docker image
run: |
docker pull onyxdotapp/onyx-web-server:latest
docker tag onyxdotapp/onyx-web-server:latest onyxdotapp/onyx-web-server:test
docker pull danswer/danswer-web-server:latest
docker tag danswer/danswer-web-server:latest danswer/danswer-web-server:test
# we use the runs-on cache for docker builds
# in conjunction with runs-on runners, it has better speed and unlimited caching
# https://runs-on.com/caching/s3-cache-for-github-actions/
# https://runs-on.com/caching/docker/
# https://github.com/moby/buildkit#s3-cache-experimental
# images are built and run locally for testing purposes. Not pushed.
- name: Build Backend Docker image
uses: ./.github/actions/custom-build-and-push
@@ -58,7 +58,7 @@ jobs:
context: ./backend
file: ./backend/Dockerfile
platforms: linux/amd64
tags: onyxdotapp/onyx-backend:test
tags: danswer/danswer-backend:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
@@ -70,19 +70,19 @@ jobs:
context: ./backend
file: ./backend/Dockerfile.model_server
platforms: linux/amd64
tags: onyxdotapp/onyx-model-server:test
tags: danswer/danswer-model-server:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
- name: Build integration test Docker image
uses: ./.github/actions/custom-build-and-push
with:
context: ./backend
file: ./backend/tests/integration/Dockerfile
platforms: linux/amd64
tags: onyxdotapp/onyx-integration:test
tags: danswer/danswer-integration:test
push: false
load: true
cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/integration/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
@@ -119,7 +119,7 @@ jobs:
-e TEST_WEB_HOSTNAME=test-runner \
-e AUTH_TYPE=cloud \
-e MULTI_TENANT=true \
onyxdotapp/onyx-integration:test \
danswer/danswer-integration:test \
/app/tests/integration/multitenant_tests
continue-on-error: true
id: run_multitenant_tests
@@ -131,14 +131,15 @@ jobs:
exit 1
else
echo "All integration tests passed successfully."
fi
fi
- name: Stop multi-tenant Docker containers
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
- name: Start Docker containers
- name: Start Docker containers
run: |
cd deployment/docker_compose
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
@@ -152,12 +153,12 @@ jobs:
- name: Wait for service to be ready
run: |
echo "Starting wait-for-service script..."
docker logs -f danswer-stack-api_server-1 &
start_time=$(date +%s)
timeout=300 # 5 minutes in seconds
while true; do
current_time=$(date +%s)
elapsed_time=$((current_time - start_time))
@@ -201,7 +202,7 @@ jobs:
-e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
-e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
-e TEST_WEB_HOSTNAME=test-runner \
onyxdotapp/onyx-integration:test \
danswer/danswer-integration:test \
/app/tests/integration/tests \
/app/tests/integration/connector_job_tests
continue-on-error: true
@@ -228,7 +229,7 @@ jobs:
run: |
cd deployment/docker_compose
docker compose -f docker-compose.dev.yml -p danswer-stack down -v
- name: Upload logs
if: success() || failure()
uses: actions/upload-artifact@v4

View File

@@ -1,29 +0,0 @@
name: Ensure PR references Linear
on:
pull_request:
types: [opened, edited, reopened, synchronize]
jobs:
linear-check:
runs-on: ubuntu-latest
steps:
- name: Check PR body for Linear link or override
env:
PR_BODY: ${{ github.event.pull_request.body }}
run: |
# Looking for "https://linear.app" in the body
if echo "$PR_BODY" | grep -qE "https://linear\.app"; then
echo "Found a Linear link. Check passed."
exit 0
fi
# Looking for a checked override: "[x] Override Linear Check"
if echo "$PR_BODY" | grep -q "\[x\].*Override Linear Check"; then
echo "Override box is checked. Check passed."
exit 0
fi
# Otherwise, fail the run
echo "No Linear link or override found in the PR description."
exit 1

View File

@@ -26,24 +26,6 @@ env:
GOOGLE_GMAIL_OAUTH_CREDENTIALS_JSON_STR: ${{ secrets.GOOGLE_GMAIL_OAUTH_CREDENTIALS_JSON_STR }}
# Slab
SLAB_BOT_TOKEN: ${{ secrets.SLAB_BOT_TOKEN }}
# Zendesk
ZENDESK_SUBDOMAIN: ${{ secrets.ZENDESK_SUBDOMAIN }}
ZENDESK_EMAIL: ${{ secrets.ZENDESK_EMAIL }}
ZENDESK_TOKEN: ${{ secrets.ZENDESK_TOKEN }}
# Salesforce
SF_USERNAME: ${{ secrets.SF_USERNAME }}
SF_PASSWORD: ${{ secrets.SF_PASSWORD }}
SF_SECURITY_TOKEN: ${{ secrets.SF_SECURITY_TOKEN }}
# Airtable
AIRTABLE_TEST_BASE_ID: ${{ secrets.AIRTABLE_TEST_BASE_ID }}
AIRTABLE_TEST_TABLE_ID: ${{ secrets.AIRTABLE_TEST_TABLE_ID }}
AIRTABLE_TEST_TABLE_NAME: ${{ secrets.AIRTABLE_TEST_TABLE_NAME }}
AIRTABLE_ACCESS_TOKEN: ${{ secrets.AIRTABLE_ACCESS_TOKEN }}
# Sharepoint
SHAREPOINT_CLIENT_ID: ${{ secrets.SHAREPOINT_CLIENT_ID }}
SHAREPOINT_CLIENT_SECRET: ${{ secrets.SHAREPOINT_CLIENT_SECRET }}
SHAREPOINT_CLIENT_DIRECTORY_ID: ${{ secrets.SHAREPOINT_CLIENT_DIRECTORY_ID }}
SHAREPOINT_SITE: ${{ secrets.SHAREPOINT_SITE }}
jobs:
connectors-check:

View File

@@ -2,52 +2,53 @@ name: Nightly Tag Push
on:
schedule:
- cron: "0 10 * * *" # Runs every day at 2 AM PST / 3 AM PDT / 10 AM UTC
- cron: '0 10 * * *' # Runs every day at 2 AM PST / 3 AM PDT / 10 AM UTC
permissions:
contents: write # Allows pushing tags to the repository
contents: write # Allows pushing tags to the repository
jobs:
create-and-push-tag:
runs-on: [runs-on, runner=2cpu-linux-x64, "run-id=${{ github.run_id }}"]
runs-on: [runs-on,runner=2cpu-linux-x64,"run-id=${{ github.run_id }}"]
steps:
# actions using GITHUB_TOKEN cannot trigger another workflow, but we do want this to trigger docker pushes
# see https://github.com/orgs/community/discussions/27028#discussioncomment-3254367 for the workaround we
# implement here which needs an actual user's deploy key
- name: Checkout code
uses: actions/checkout@v4
with:
ssh-key: "${{ secrets.RKUO_DEPLOY_KEY }}"
# actions using GITHUB_TOKEN cannot trigger another workflow, but we do want this to trigger docker pushes
# see https://github.com/orgs/community/discussions/27028#discussioncomment-3254367 for the workaround we
# implement here which needs an actual user's deploy key
- name: Checkout code
uses: actions/checkout@v4
with:
ssh-key: "${{ secrets.RKUO_DEPLOY_KEY }}"
- name: Set up Git user
run: |
git config user.name "Richard Kuo [bot]"
git config user.email "rkuo[bot]@onyx.app"
- name: Set up Git user
run: |
git config user.name "Richard Kuo [bot]"
git config user.email "rkuo[bot]@danswer.ai"
- name: Check for existing nightly tag
id: check_tag
run: |
if git tag --points-at HEAD --list "nightly-latest*" | grep -q .; then
echo "A tag starting with 'nightly-latest' already exists on HEAD."
echo "tag_exists=true" >> $GITHUB_OUTPUT
else
echo "No tag starting with 'nightly-latest' exists on HEAD."
echo "tag_exists=false" >> $GITHUB_OUTPUT
fi
- name: Check for existing nightly tag
id: check_tag
run: |
if git tag --points-at HEAD --list "nightly-latest*" | grep -q .; then
echo "A tag starting with 'nightly-latest' already exists on HEAD."
echo "tag_exists=true" >> $GITHUB_OUTPUT
else
echo "No tag starting with 'nightly-latest' exists on HEAD."
echo "tag_exists=false" >> $GITHUB_OUTPUT
fi
# don't tag again if HEAD already has a nightly-latest tag on it
- name: Create Nightly Tag
if: steps.check_tag.outputs.tag_exists == 'false'
env:
DATE: ${{ github.run_id }}
run: |
TAG_NAME="nightly-latest-$(date +'%Y%m%d')"
echo "Creating tag: $TAG_NAME"
git tag $TAG_NAME
# don't tag again if HEAD already has a nightly-latest tag on it
- name: Create Nightly Tag
if: steps.check_tag.outputs.tag_exists == 'false'
env:
DATE: ${{ github.run_id }}
run: |
TAG_NAME="nightly-latest-$(date +'%Y%m%d')"
echo "Creating tag: $TAG_NAME"
git tag $TAG_NAME
- name: Push Tag
if: steps.check_tag.outputs.tag_exists == 'false'
run: |
TAG_NAME="nightly-latest-$(date +'%Y%m%d')"
git push origin $TAG_NAME
- name: Push Tag
if: steps.check_tag.outputs.tag_exists == 'false'
run: |
TAG_NAME="nightly-latest-$(date +'%Y%m%d')"
git push origin $TAG_NAME

4
.gitignore vendored
View File

@@ -7,6 +7,4 @@
.vscode/
*.sw?
/backend/tests/regression/answer_quality/search_test_config.yaml
/web/test-results/
backend/onyx/agent_search/main/test_data.json
backend/tests/regression/answer_quality/test_data.json
/web/test-results/

View File

@@ -5,8 +5,6 @@
# For local dev, often user Authentication is not needed
AUTH_TYPE=disabled
# Skip warm up for dev
SKIP_WARM_UP=True
# Always keep these on for Dev
# Logs all model prompts to stdout
@@ -29,7 +27,6 @@ REQUIRE_EMAIL_VERIFICATION=False
# Set these so if you wipe the DB, you don't end up having to go through the UI every time
GEN_AI_API_KEY=<REPLACE THIS>
OPENAI_API_KEY=<REPLACE THIS>
# If answer quality isn't important for dev, use gpt-4o-mini since it's cheaper
GEN_AI_MODEL_VERSION=gpt-4o
FAST_GEN_AI_MODEL_VERSION=gpt-4o
@@ -52,9 +49,3 @@ BING_API_KEY=<REPLACE THIS>
# Enable the full set of Danswer Enterprise Edition features
# NOTE: DO NOT ENABLE THIS UNLESS YOU HAVE A PAID ENTERPRISE LICENSE (or if you are using this for local testing/development)
ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=False
# Agent Search configs # TODO: Remove give proper namings
AGENT_RETRIEVAL_STATS=False # Note: This setting will incur substantial re-ranking effort
AGENT_RERANKING_STATS=True
AGENT_MAX_QUERY_RETRIEVAL_RESULTS=20
AGENT_RERANKING_MAX_QUERY_RETRIEVAL_RESULTS=20

View File

@@ -17,7 +17,7 @@
}
},
{
"name": "Run All Onyx Services",
"name": "Run All Danswer Services",
"configurations": [
"Web Server",
"Model Server",
@@ -28,7 +28,6 @@
"Celery heavy",
"Celery indexing",
"Celery beat",
"Celery monitoring",
],
"presentation": {
"group": "1",
@@ -52,8 +51,7 @@
"Celery light",
"Celery heavy",
"Celery indexing",
"Celery beat",
"Celery monitoring",
"Celery beat"
],
"presentation": {
"group": "1",
@@ -124,7 +122,7 @@
"PYTHONUNBUFFERED": "1"
},
"args": [
"onyx.main:app",
"danswer.main:app",
"--reload",
"--port",
"8080"
@@ -141,7 +139,7 @@
"consoleName": "Slack Bot",
"type": "debugpy",
"request": "launch",
"program": "onyx/onyxbot/slack/listener.py",
"program": "danswer/danswerbot/slack/listener.py",
"cwd": "${workspaceFolder}/backend",
"envFile": "${workspaceFolder}/.vscode/.env",
"env": {
@@ -168,7 +166,7 @@
},
"args": [
"-A",
"onyx.background.celery.versioned_apps.primary",
"danswer.background.celery.versioned_apps.primary",
"worker",
"--pool=threads",
"--concurrency=4",
@@ -197,7 +195,7 @@
},
"args": [
"-A",
"onyx.background.celery.versioned_apps.light",
"danswer.background.celery.versioned_apps.light",
"worker",
"--pool=threads",
"--concurrency=64",
@@ -226,7 +224,7 @@
},
"args": [
"-A",
"onyx.background.celery.versioned_apps.heavy",
"danswer.background.celery.versioned_apps.heavy",
"worker",
"--pool=threads",
"--concurrency=4",
@@ -256,7 +254,7 @@
},
"args": [
"-A",
"onyx.background.celery.versioned_apps.indexing",
"danswer.background.celery.versioned_apps.indexing",
"worker",
"--pool=threads",
"--concurrency=1",
@@ -271,31 +269,6 @@
},
"consoleTitle": "Celery indexing Console"
},
{
"name": "Celery monitoring",
"type": "debugpy",
"request": "launch",
"module": "celery",
"cwd": "${workspaceFolder}/backend",
"envFile": "${workspaceFolder}/.vscode/.env",
"env": {},
"args": [
"-A",
"onyx.background.celery.versioned_apps.monitoring",
"worker",
"--pool=solo",
"--concurrency=1",
"--prefetch-multiplier=1",
"--loglevel=INFO",
"--hostname=monitoring@%n",
"-Q",
"monitoring",
],
"presentation": {
"group": "2",
},
"consoleTitle": "Celery monitoring Console"
},
{
"name": "Celery beat",
"type": "debugpy",
@@ -310,7 +283,7 @@
},
"args": [
"-A",
"onyx.background.celery.versioned_apps.beat",
"danswer.background.celery.versioned_apps.beat",
"beat",
"--loglevel=INFO",
],
@@ -335,7 +308,7 @@
"args": [
"-v"
// Specify a sepcific module/test to run or provide nothing to run all tests
//"tests/unit/onyx/llm/answering/test_prune_and_merge.py"
//"tests/unit/danswer/llm/answering/test_prune_and_merge.py"
],
"presentation": {
"group": "2",
@@ -382,20 +355,5 @@
"PYTHONPATH": "."
},
},
{
"name": "Install Python Requirements",
"type": "node",
"request": "launch",
"runtimeExecutable": "bash",
"runtimeArgs": [
"-c",
"pip install -r backend/requirements/default.txt && pip install -r backend/requirements/dev.txt && pip install -r backend/requirements/ee.txt && pip install -r backend/requirements/model_server.txt"
],
"cwd": "${workspaceFolder}",
"console": "integratedTerminal",
"presentation": {
"group": "3"
}
},
]
}

View File

@@ -1,38 +1,32 @@
<!-- DANSWER_METADATA={"link": "https://github.com/onyx-dot-app/onyx/blob/main/CONTRIBUTING.md"} -->
<!-- DANSWER_METADATA={"link": "https://github.com/danswer-ai/danswer/blob/main/CONTRIBUTING.md"} -->
# Contributing to Onyx
Hey there! We are so excited that you're interested in Onyx.
# Contributing to Danswer
Hey there! We are so excited that you're interested in Danswer.
As an open source project in a rapidly changing space, we welcome all contributions.
## 💃 Guidelines
### Contribution Opportunities
The [GitHub Issues](https://github.com/onyx-dot-app/onyx/issues) page is a great place to start for contribution ideas.
To ensure that your contribution is aligned with the project's direction, please reach out to Hagen (or any other maintainer) on the Onyx team
via [Slack](https://join.slack.com/t/onyx-dot-app/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA) /
[Discord](https://discord.gg/TDJ59cGV2X) or [email](mailto:founders@onyx.app).
The [GitHub Issues](https://github.com/danswer-ai/danswer/issues) page is a great place to start for contribution ideas.
Issues that have been explicitly approved by the maintainers (aligned with the direction of the project)
will be marked with the `approved by maintainers` label.
Issues marked `good first issue` are an especially great place to start.
**Connectors** to other tools are another great place to contribute. For details on how, refer to this
[README.md](https://github.com/onyx-dot-app/onyx/blob/main/backend/onyx/connectors/README.md).
[README.md](https://github.com/danswer-ai/danswer/blob/main/backend/danswer/connectors/README.md).
If you have a new/different contribution in mind, we'd love to hear about it!
Your input is vital to making sure that Onyx moves in the right direction.
Your input is vital to making sure that Danswer moves in the right direction.
Before starting on implementation, please raise a GitHub issue.
Also, always feel free to message the founders (Chris Weaver / Yuhong Sun) on
[Slack](https://join.slack.com/t/onyx-dot-app/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA) /
[Discord](https://discord.gg/TDJ59cGV2X) directly about anything at all.
And always feel free to message us (Chris Weaver / Yuhong Sun) on
[Slack](https://join.slack.com/t/danswer/shared_invite/zt-2lcmqw703-071hBuZBfNEOGUsLa5PXvQ) /
[Discord](https://discord.gg/TDJ59cGV2X) directly about anything at all.
### Contributing Code
To contribute to this project, please follow the
["fork and pull request"](https://docs.github.com/en/get-started/quickstart/contributing-to-projects) workflow.
When opening a pull request, mention related issues and feel free to tag relevant maintainers.
@@ -40,78 +34,72 @@ When opening a pull request, mention related issues and feel free to tag relevan
Before creating a pull request please make sure that the new changes conform to the formatting and linting requirements.
See the [Formatting and Linting](#formatting-and-linting) section for how to run these checks locally.
### Getting Help 🙋
### Getting Help 🙋
Our goal is to make contributing as easy as possible. If you run into any issues please don't hesitate to reach out.
That way we can help future contributors and users can avoid the same issue.
We also have support channels and generally interesting discussions on our
[Slack](https://join.slack.com/t/onyx-dot-app/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA)
and
[Slack](https://join.slack.com/t/danswer/shared_invite/zt-2afut44lv-Rw3kSWu6_OmdAXRpCv80DQ)
and
[Discord](https://discord.gg/TDJ59cGV2X).
We would love to see you there!
## Get Started 🚀
Onyx being a fully functional app, relies on some external software, specifically:
Danswer being a fully functional app, relies on some external software, specifically:
- [Postgres](https://www.postgresql.org/) (Relational DB)
- [Vespa](https://vespa.ai/) (Vector DB/Search Engine)
- [Redis](https://redis.io/) (Cache)
- [Nginx](https://nginx.org/) (Not needed for development flows generally)
> **Note:**
> This guide provides instructions to build and run Onyx locally from source with Docker containers providing the above external software. We believe this combination is easier for
> development purposes. If you prefer to use pre-built container images, we provide instructions on running the full Onyx stack within Docker below.
> This guide provides instructions to build and run Danswer locally from source with Docker containers providing the above external software. We believe this combination is easier for
> development purposes. If you prefer to use pre-built container images, we provide instructions on running the full Danswer stack within Docker below.
### Local Set Up
Be sure to use Python version 3.11. For instructions on installing Python 3.11 on macOS, refer to the [CONTRIBUTING_MACOS.md](./CONTRIBUTING_MACOS.md) readme.
If using a lower version, modifications will have to be made to the code.
If using a higher version, sometimes some libraries will not be available (i.e. we had problems with Tensorflow in the past with higher versions of python).
#### Backend: Python requirements
#### Backend: Python requirements
Currently, we use pip and recommend creating a virtual environment.
For convenience here's a command for it:
```bash
python -m venv .venv
source .venv/bin/activate
```
> **Note:**
> This virtual environment MUST NOT be set up WITHIN the onyx directory if you plan on using mypy within certain IDEs.
> For simplicity, we recommend setting up the virtual environment outside of the onyx directory.
> This virtual environment MUST NOT be set up WITHIN the danswer directory if you plan on using mypy within certain IDEs.
> For simplicity, we recommend setting up the virtual environment outside of the danswer directory.
_For Windows, activate the virtual environment using Command Prompt:_
```bash
.venv\Scripts\activate
```
If using PowerShell, the command slightly differs:
```powershell
.venv\Scripts\Activate.ps1
```
Install the required python dependencies:
```bash
pip install -r onyx/backend/requirements/default.txt
pip install -r onyx/backend/requirements/dev.txt
pip install -r onyx/backend/requirements/ee.txt
pip install -r onyx/backend/requirements/model_server.txt
pip install -r danswer/backend/requirements/default.txt
pip install -r danswer/backend/requirements/dev.txt
pip install -r danswer/backend/requirements/ee.txt
pip install -r danswer/backend/requirements/model_server.txt
```
Install Playwright for Python (headless browser required by the Web Connector)
In the activated Python virtualenv, install Playwright for Python by running:
```bash
playwright install
```
@@ -121,90 +109,42 @@ You may have to deactivate and reactivate your virtualenv for `playwright` to ap
#### Frontend: Node dependencies
Install [Node.js and npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) for the frontend.
Once the above is done, navigate to `onyx/web` run:
Once the above is done, navigate to `danswer/web` run:
```bash
npm i
```
## Formatting and Linting
### Backend
For the backend, you'll need to setup pre-commit hooks (black / reorder-python-imports).
First, install pre-commit (if you don't have it already) following the instructions
[here](https://pre-commit.com/#installation).
With the virtual environment active, install the pre-commit library with:
```bash
pip install pre-commit
```
Then, from the `onyx/backend` directory, run:
```bash
pre-commit install
```
Additionally, we use `mypy` for static type checking.
Onyx is fully type-annotated, and we want to keep it that way!
To run the mypy checks manually, run `python -m mypy .` from the `onyx/backend` directory.
### Web
We use `prettier` for formatting. The desired version (2.8.8) will be installed via a `npm i` from the `onyx/web` directory.
To run the formatter, use `npx prettier --write .` from the `onyx/web` directory.
Please double check that prettier passes before creating a pull request.
# Running the application for development
## Developing using VSCode Debugger (recommended)
We highly recommend using VSCode debugger for development.
See [CONTRIBUTING_VSCODE.md](./CONTRIBUTING_VSCODE.md) for more details.
Otherwise, you can follow the instructions below to run the application for development.
## Manually running the application for development
### Docker containers for external software
#### Docker containers for external software
You will need Docker installed to run these containers.
First navigate to `onyx/deployment/docker_compose`, then start up Postgres/Vespa/Redis with:
First navigate to `danswer/deployment/docker_compose`, then start up Postgres/Vespa/Redis with:
```bash
docker compose -f docker-compose.dev.yml -p onyx-stack up -d index relational_db cache
docker compose -f docker-compose.dev.yml -p danswer-stack up -d index relational_db cache
```
(index refers to Vespa, relational_db refers to Postgres, and cache refers to Redis)
### Running Onyx locally
To start the frontend, navigate to `onyx/web` and run:
#### Running Danswer locally
To start the frontend, navigate to `danswer/web` and run:
```bash
npm run dev
```
Next, start the model server which runs the local NLP models.
Navigate to `onyx/backend` and run:
Navigate to `danswer/backend` and run:
```bash
uvicorn model_server.main:app --reload --port 9000
```
_For Windows (for compatibility with both PowerShell and Command Prompt):_
```bash
powershell -Command "uvicorn model_server.main:app --reload --port 9000"
```
The first time running Onyx, you will need to run the DB migrations for Postgres.
The first time running Danswer, you will need to run the DB migrations for Postgres.
After the first time, this is no longer required unless the DB models change.
Navigate to `onyx/backend` and with the venv active, run:
Navigate to `danswer/backend` and with the venv active, run:
```bash
alembic upgrade head
```
@@ -212,24 +152,21 @@ alembic upgrade head
Next, start the task queue which orchestrates the background jobs.
Jobs that take more time are run async from the API server.
Still in `onyx/backend`, run:
Still in `danswer/backend`, run:
```bash
python ./scripts/dev_run_background_jobs.py
```
To run the backend API server, navigate back to `onyx/backend` and run:
To run the backend API server, navigate back to `danswer/backend` and run:
```bash
AUTH_TYPE=disabled uvicorn onyx.main:app --reload --port 8080
AUTH_TYPE=disabled uvicorn danswer.main:app --reload --port 8080
```
_For Windows (for compatibility with both PowerShell and Command Prompt):_
```bash
powershell -Command "
$env:AUTH_TYPE='disabled'
uvicorn onyx.main:app --reload --port 8080
uvicorn danswer.main:app --reload --port 8080
"
```
@@ -245,32 +182,57 @@ You should now have 4 servers running:
- Model server
- Background jobs
Now, visit `http://localhost:3000` in your browser. You should see the Onyx onboarding wizard where you can connect your external LLM provider to Onyx.
Now, visit `http://localhost:3000` in your browser. You should see the Danswer onboarding wizard where you can connect your external LLM provider to Danswer.
You've successfully set up a local Onyx instance! 🏁
You've successfully set up a local Danswer instance! 🏁
#### Running the Onyx application in a container
#### Running the Danswer application in a container
You can run the full Onyx application stack from pre-built images including all external software dependencies.
You can run the full Danswer application stack from pre-built images including all external software dependencies.
Navigate to `onyx/deployment/docker_compose` and run:
Navigate to `danswer/deployment/docker_compose` and run:
```bash
docker compose -f docker-compose.dev.yml -p onyx-stack up -d
docker compose -f docker-compose.dev.yml -p danswer-stack up -d
```
After Docker pulls and starts these containers, navigate to `http://localhost:3000` to use Onyx.
After Docker pulls and starts these containers, navigate to `http://localhost:3000` to use Danswer.
If you want to make changes to Onyx and run those changes in Docker, you can also build a local version of the Onyx container images that incorporates your changes like so:
If you want to make changes to Danswer and run those changes in Docker, you can also build a local version of the Danswer container images that incorporates your changes like so:
```bash
docker compose -f docker-compose.dev.yml -p onyx-stack up -d --build
docker compose -f docker-compose.dev.yml -p danswer-stack up -d --build
```
### Formatting and Linting
#### Backend
For the backend, you'll need to setup pre-commit hooks (black / reorder-python-imports).
First, install pre-commit (if you don't have it already) following the instructions
[here](https://pre-commit.com/#installation).
With the virtual environment active, install the pre-commit library with:
```bash
pip install pre-commit
```
Then, from the `danswer/backend` directory, run:
```bash
pre-commit install
```
Additionally, we use `mypy` for static type checking.
Danswer is fully type-annotated, and we want to keep it that way!
To run the mypy checks manually, run `python -m mypy .` from the `danswer/backend` directory.
#### Web
We use `prettier` for formatting. The desired version (2.8.8) will be installed via a `npm i` from the `danswer/web` directory.
To run the formatter, use `npx prettier --write .` from the `danswer/web` directory.
Please double check that prettier passes before creating a pull request.
### Release Process
Onyx loosely follows the SemVer versioning standard.
Danswer loosely follows the SemVer versioning standard.
Major changes are released with a "minor" version bump. Currently we use patch release versions to indicate small feature changes.
A set of Docker containers will be pushed automatically to DockerHub with every tag.
You can see the containers [here](https://hub.docker.com/search?q=onyx%2F).
You can see the containers [here](https://hub.docker.com/search?q=danswer%2F).

View File

@@ -1,19 +1,15 @@
## Some additional notes for Mac Users
The base instructions to set up the development environment are located in [CONTRIBUTING.md](https://github.com/onyx-dot-app/onyx/blob/main/CONTRIBUTING.md).
The base instructions to set up the development environment are located in [CONTRIBUTING.md](https://github.com/danswer-ai/danswer/blob/main/CONTRIBUTING.md).
### Setting up Python
Ensure [Homebrew](https://brew.sh/) is already set up.
Then install python 3.11.
```bash
brew install python@3.11
```
Add python 3.11 to your path: add the following line to ~/.zshrc
```
export PATH="$(brew --prefix)/opt/python@3.11/libexec/bin:$PATH"
```
@@ -21,16 +17,15 @@ export PATH="$(brew --prefix)/opt/python@3.11/libexec/bin:$PATH"
> **Note:**
> You will need to open a new terminal for the path change above to take effect.
### Setting up Docker
On macOS, you will need to install [Docker Desktop](https://www.docker.com/products/docker-desktop/) and
### Setting up Docker
On macOS, you will need to install [Docker Desktop](https://www.docker.com/products/docker-desktop/) and
ensure it is running before continuing with the docker commands.
### Formatting and Linting
### Formatting and Linting
MacOS will likely require you to remove some quarantine attributes on some of the hooks for them to execute properly.
After installing pre-commit, run the following command:
```bash
sudo xattr -r -d com.apple.quarantine ~/.cache/pre-commit
```
```

View File

@@ -1,30 +0,0 @@
# VSCode Debugging Setup
This guide explains how to set up and use VSCode's debugging capabilities with this project.
## Initial Setup
1. **Environment Setup**:
- Copy `.vscode/.env.template` to `.vscode/.env`
- Fill in the necessary environment variables in `.vscode/.env`
2. **launch.json**:
- Copy `.vscode/launch.template.jsonc` to `.vscode/launch.json`
## Using the Debugger
Before starting, make sure the Docker Daemon is running.
1. Open the Debug view in VSCode (Cmd+Shift+D on macOS)
2. From the dropdown at the top, select "Clear and Restart External Volumes and Containers" and press the green play button
3. From the dropdown at the top, select "Run All Onyx Services" and press the green play button
4. CD into web, run "npm i" followed by npm run dev.
5. Now, you can navigate to onyx in your browser (default is http://localhost:3000) and start using the app
6. You can set breakpoints by clicking to the left of line numbers to help debug while the app is running
7. Use the debug toolbar to step through code, inspect variables, etc.
## Features
- Hot reload is enabled for the web server and API servers
- Python debugging is configured with debugpy
- Environment variables are loaded from `.vscode/.env`
- Console output is organized in the integrated terminal with labeled tabs

View File

@@ -2,9 +2,9 @@ Copyright (c) 2023-present DanswerAI, Inc.
Portions of this software are licensed as follows:
- All content that resides under "ee" directories of this repository, if that directory exists, is licensed under the license defined in "backend/ee/LICENSE". Specifically all content under "backend/ee" and "web/src/app/ee" is licensed under the license defined in "backend/ee/LICENSE".
- All third party components incorporated into the Onyx Software are licensed under the original license provided by the owner of the applicable component.
- Content outside of the above mentioned directories or restrictions above is available under the "MIT Expat" license as defined below.
* All content that resides under "ee" directories of this repository, if that directory exists, is licensed under the license defined in "backend/ee/LICENSE". Specifically all content under "backend/ee" and "web/src/app/ee" is licensed under the license defined in "backend/ee/LICENSE".
* All third party components incorporated into the Danswer Software are licensed under the original license provided by the owner of the applicable component.
* Content outside of the above mentioned directories or restrictions above is available under the "MIT Expat" license as defined below.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

169
README.md
View File

@@ -1,135 +1,146 @@
<!-- DANSWER_METADATA={"link": "https://github.com/onyx-dot-app/onyx/blob/main/README.md"} -->
<!-- DANSWER_METADATA={"link": "https://github.com/danswer-ai/danswer/blob/main/README.md"} -->
<a name="readme-top"></a>
<h2 align="center">
<a href="https://www.onyx.app/"> <img width="50%" src="https://github.com/onyx-dot-app/onyx/blob/logo/OnyxLogoCropped.jpg?raw=true)" /></a>
<a href="https://www.danswer.ai/"> <img width="50%" src="https://github.com/danswer-owners/danswer/blob/1fabd9372d66cd54238847197c33f091a724803b/DanswerWithName.png?raw=true)" /></a>
</h2>
<p align="center">
<p align="center">Open Source Gen-AI + Enterprise Search.</p>
<p align="center">Open Source Gen-AI Chat + Unified Search.</p>
<p align="center">
<a href="https://docs.onyx.app/" target="_blank">
<a href="https://docs.danswer.dev/" target="_blank">
<img src="https://img.shields.io/badge/docs-view-blue" alt="Documentation">
</a>
<a href="https://join.slack.com/t/onyx-dot-app/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA" target="_blank">
<a href="https://join.slack.com/t/danswer/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA" target="_blank">
<img src="https://img.shields.io/badge/slack-join-blue.svg?logo=slack" alt="Slack">
</a>
<a href="https://discord.gg/TDJ59cGV2X" target="_blank">
<img src="https://img.shields.io/badge/discord-join-blue.svg?logo=discord&logoColor=white" alt="Discord">
</a>
<a href="https://github.com/onyx-dot-app/onyx/blob/main/README.md" target="_blank">
<a href="https://github.com/danswer-ai/danswer/blob/main/README.md" target="_blank">
<img src="https://img.shields.io/static/v1?label=license&message=MIT&color=blue" alt="License">
</a>
</p>
<strong>[Onyx](https://www.onyx.app/)</strong> (formerly Danswer) is the AI Assistant connected to your company's docs, apps, and people.
Onyx provides a Chat interface and plugs into any LLM of your choice. Onyx can be deployed anywhere and for any
scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your
own control. Onyx is dual Licensed with most of it under MIT license and designed to be modular and easily extensible. The system also comes fully ready
for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for
configuring AI Assistants.
<strong>[Danswer](https://www.danswer.ai/)</strong> is the AI Assistant connected to your company's docs, apps, and people.
Danswer provides a Chat interface and plugs into any LLM of your choice. Danswer can be deployed anywhere and for any
scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your
own control. Danswer is MIT licensed and designed to be modular and easily extensible. The system also comes fully ready
for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for
configuring Personas (AI Assistants) and their Prompts.
Onyx also serves as a Enterprise Search across all common workplace tools such as Slack, Google Drive, Confluence, etc.
By combining LLMs and team specific knowledge, Onyx becomes a subject matter expert for the team. Imagine ChatGPT if
Danswer also serves as a Unified Search across all common workplace tools such as Slack, Google Drive, Confluence, etc.
By combining LLMs and team specific knowledge, Danswer becomes a subject matter expert for the team. Imagine ChatGPT if
it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already
supported?" or "Where's the pull request for feature Y?"
<h3>Usage</h3>
Onyx Web App:
Danswer Web App:
https://github.com/onyx-dot-app/onyx/assets/32520769/563be14c-9304-47b5-bf0a-9049c2b6f410
https://github.com/danswer-ai/danswer/assets/32520769/563be14c-9304-47b5-bf0a-9049c2b6f410
Or, plug Onyx into your existing Slack workflows (more integrations to come 😁):
https://github.com/onyx-dot-app/onyx/assets/25087905/3e19739b-d178-4371-9a38-011430bdec1b
Or, plug Danswer into your existing Slack workflows (more integrations to come 😁):
For more details on the Admin UI to manage connectors and users, check out our
https://github.com/danswer-ai/danswer/assets/25087905/3e19739b-d178-4371-9a38-011430bdec1b
For more details on the Admin UI to manage connectors and users, check out our
<strong><a href="https://www.youtube.com/watch?v=geNzY1nbCnU">Full Video Demo</a></strong>!
## Deployment
Onyx can easily be run locally (even on a laptop) or deployed on a virtual machine with a single
`docker compose` command. Checkout our [docs](https://docs.onyx.app/quickstart) to learn more.
Danswer can easily be run locally (even on a laptop) or deployed on a virtual machine with a single
`docker compose` command. Checkout our [docs](https://docs.danswer.dev/quickstart) to learn more.
We also have built-in support for deployment on Kubernetes. Files for that can be found [here](https://github.com/onyx-dot-app/onyx/tree/main/deployment/kubernetes).
We also have built-in support for deployment on Kubernetes. Files for that can be found [here](https://github.com/danswer-ai/danswer/tree/main/deployment/kubernetes).
## 💃 Main Features
- Chat UI with the ability to select documents to chat with.
- Create custom AI Assistants with different prompts and backing knowledge sets.
- Connect Onyx with LLM of your choice (self-host for a fully airgapped solution).
- Document Search + AI Answers for natural language queries.
- Connectors to all common workplace tools like Google Drive, Confluence, Slack, etc.
- Slack integration to get answers and search results directly in Slack.
## 💃 Main Features
* Chat UI with the ability to select documents to chat with.
* Create custom AI Assistants with different prompts and backing knowledge sets.
* Connect Danswer with LLM of your choice (self-host for a fully airgapped solution).
* Document Search + AI Answers for natural language queries.
* Connectors to all common workplace tools like Google Drive, Confluence, Slack, etc.
* Slack integration to get answers and search results directly in Slack.
## 🚧 Roadmap
* Chat/Prompt sharing with specific teammates and user groups.
* Multimodal model support, chat with images, video etc.
* Choosing between LLMs and parameters during chat session.
* Tool calling and agent configurations options.
* Organizational understanding and ability to locate and suggest experts from your team.
- Chat/Prompt sharing with specific teammates and user groups.
- Multimodal model support, chat with images, video etc.
- Choosing between LLMs and parameters during chat session.
- Tool calling and agent configurations options.
- Organizational understanding and ability to locate and suggest experts from your team.
## Other Notable Benefits of Onyx
## Other Notable Benefits of Danswer
* User Authentication with document level access management.
* Best in class Hybrid Search across all sources (BM-25 + prefix aware embedding models).
* Admin Dashboard to configure connectors, document-sets, access, etc.
* Custom deep learning models + learn from user feedback.
* Easy deployment and ability to host Danswer anywhere of your choosing.
- User Authentication with document level access management.
- Best in class Hybrid Search across all sources (BM-25 + prefix aware embedding models).
- Admin Dashboard to configure connectors, document-sets, access, etc.
- Custom deep learning models + learn from user feedback.
- Easy deployment and ability to host Onyx anywhere of your choosing.
## 🔌 Connectors
Efficiently pulls the latest changes from:
- Slack
- GitHub
- Google Drive
- Confluence
- Jira
- Zendesk
- Gmail
- Notion
- Gong
- Slab
- Linear
- Productboard
- Guru
- Bookstack
- Document360
- Sharepoint
- Hubspot
- Local Files
- Websites
- And more ...
* Slack
* GitHub
* Google Drive
* Confluence
* Jira
* Zendesk
* Gmail
* Notion
* Gong
* Slab
* Linear
* Productboard
* Guru
* Bookstack
* Document360
* Sharepoint
* Hubspot
* Local Files
* Websites
* And more ...
## 📚 Editions
There are two editions of Onyx:
There are two editions of Danswer:
- Onyx Community Edition (CE) is available freely under the MIT Expat license. This version has ALL the core features discussed above. This is the version of Onyx you will get if you follow the Deployment guide above.
- Onyx Enterprise Edition (EE) includes extra features that are primarily useful for larger organizations. Specifically, this includes:
- Single Sign-On (SSO), with support for both SAML and OIDC
- Role-based access control
- Document permission inheritance from connected sources
- Usage analytics and query history accessible to admins
- Whitelabeling
- API key authentication
- Encryption of secrets
- And many more! Checkout [our website](https://www.onyx.app/) for the latest.
* Danswer Community Edition (CE) is available freely under the MIT Expat license. This version has ALL the core features discussed above. This is the version of Danswer you will get if you follow the Deployment guide above.
* Danswer Enterprise Edition (EE) includes extra features that are primarily useful for larger organizations. Specifically, this includes:
* Single Sign-On (SSO), with support for both SAML and OIDC
* Role-based access control
* Document permission inheritance from connected sources
* Usage analytics and query history accessible to admins
* Whitelabeling
* API key authentication
* Encryption of secrets
* Any many more! Checkout [our website](https://www.danswer.ai/) for the latest.
To try the Onyx Enterprise Edition:
To try the Danswer Enterprise Edition:
1. Checkout our [Cloud product](https://cloud.onyx.app/signup).
2. For self-hosting, contact us at [founders@onyx.app](mailto:founders@onyx.app) or book a call with us on our [Cal](https://cal.com/team/onyx/founders).
1. Checkout our [Cloud product](https://app.danswer.ai/signup).
2. For self-hosting, contact us at [founders@danswer.ai](mailto:founders@danswer.ai) or book a call with us on our [Cal](https://cal.com/team/danswer/founders).
## 💡 Contributing
Looking to contribute? Please check out the [Contribution Guide](CONTRIBUTING.md) for more details.
## ⭐Star History
[![Star History Chart](https://api.star-history.com/svg?repos=onyx-dot-app/onyx&type=Date)](https://star-history.com/#onyx-dot-app/onyx&Date)
[![Star History Chart](https://api.star-history.com/svg?repos=danswer-ai/danswer&type=Date)](https://star-history.com/#danswer-ai/danswer&Date)
## ✨Contributors
<a href="https://github.com/danswer-ai/danswer/graphs/contributors">
<img alt="contributors" src="https://contrib.rocks/image?repo=danswer-ai/danswer"/>
</a>
<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
<a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
↑ Back to Top ↑
</a>
</p>

1
backend/.gitignore vendored
View File

@@ -9,4 +9,3 @@ api_keys.py
vespa-app.zip
dynamic_config_storage/
celerybeat-schedule*
onyx/connectors/salesforce/data/

View File

@@ -1,21 +1,19 @@
FROM python:3.11.7-slim-bookworm
LABEL com.danswer.maintainer="founders@onyx.app"
LABEL com.danswer.description="This image is the web/frontend container of Onyx which \
contains code for both the Community and Enterprise editions of Onyx. If you do not \
LABEL com.danswer.maintainer="founders@danswer.ai"
LABEL com.danswer.description="This image is the web/frontend container of Danswer which \
contains code for both the Community and Enterprise editions of Danswer. If you do not \
have a contract or agreement with DanswerAI, you are not permitted to use the Enterprise \
Edition features outside of personal development or testing purposes. Please reach out to \
founders@onyx.app for more information. Please visit https://github.com/onyx-dot-app/onyx"
founders@danswer.ai for more information. Please visit https://github.com/danswer-ai/danswer"
# Default ONYX_VERSION, typically overriden during builds by GitHub Actions.
ARG ONYX_VERSION=0.8-dev
# DO_NOT_TRACK is used to disable telemetry for Unstructured
ENV ONYX_VERSION=${ONYX_VERSION} \
DANSWER_RUNNING_IN_DOCKER="true" \
DO_NOT_TRACK="true"
# Default DANSWER_VERSION, typically overriden during builds by GitHub Actions.
ARG DANSWER_VERSION=0.8-dev
ENV DANSWER_VERSION=${DANSWER_VERSION} \
DANSWER_RUNNING_IN_DOCKER="true"
RUN echo "ONYX_VERSION: ${ONYX_VERSION}"
RUN echo "DANSWER_VERSION: ${DANSWER_VERSION}"
# Install system dependencies
# cmake needed for psycopg (postgres)
# libpq-dev needed for psycopg (postgres)
@@ -58,7 +56,7 @@ RUN pip install --no-cache-dir --upgrade \
# Cleanup for CVEs and size reduction
# https://github.com/tornadoweb/tornado/issues/3107
# xserver-common and xvfb included by playwright installation but not needed after
# perl-base is part of the base Python Debian image but not needed for Onyx functionality
# perl-base is part of the base Python Debian image but not needed for Danswer functionality
# perl-base could only be removed with --allow-remove-essential
RUN apt-get update && \
apt-get remove -y --allow-remove-essential \
@@ -94,15 +92,14 @@ COPY ./ee /app/ee
COPY supervisord.conf /etc/supervisor/conf.d/supervisord.conf
# Set up application files
COPY ./onyx /app/onyx
COPY ./danswer /app/danswer
COPY ./shared_configs /app/shared_configs
COPY ./alembic /app/alembic
COPY ./alembic_tenants /app/alembic_tenants
COPY ./alembic.ini /app/alembic.ini
COPY supervisord.conf /usr/etc/supervisord.conf
# Escape hatch scripts
COPY ./scripts/debugging /app/scripts/debugging
# Escape hatch
COPY ./scripts/force_delete_connector_by_id.py /app/scripts/force_delete_connector_by_id.py
# Put logo in assets

View File

@@ -1,18 +1,18 @@
FROM python:3.11.7-slim-bookworm
LABEL com.danswer.maintainer="founders@onyx.app"
LABEL com.danswer.description="This image is for the Onyx model server which runs all of the \
AI models for Onyx. This container and all the code is MIT Licensed and free for all to use. \
You can find it at https://hub.docker.com/r/onyx/onyx-model-server. For more details, \
visit https://github.com/onyx-dot-app/onyx."
LABEL com.danswer.maintainer="founders@danswer.ai"
LABEL com.danswer.description="This image is for the Danswer model server which runs all of the \
AI models for Danswer. This container and all the code is MIT Licensed and free for all to use. \
You can find it at https://hub.docker.com/r/danswer/danswer-model-server. For more details, \
visit https://github.com/danswer-ai/danswer."
# Default ONYX_VERSION, typically overriden during builds by GitHub Actions.
ARG ONYX_VERSION=0.8-dev
ENV ONYX_VERSION=${ONYX_VERSION} \
# Default DANSWER_VERSION, typically overriden during builds by GitHub Actions.
ARG DANSWER_VERSION=0.8-dev
ENV DANSWER_VERSION=${DANSWER_VERSION} \
DANSWER_RUNNING_IN_DOCKER="true"
RUN echo "ONYX_VERSION: ${ONYX_VERSION}"
RUN echo "DANSWER_VERSION: ${DANSWER_VERSION}"
COPY ./requirements/model_server.txt /tmp/requirements.txt
RUN pip install --no-cache-dir --upgrade \
@@ -20,11 +20,11 @@ RUN pip install --no-cache-dir --upgrade \
--timeout 30 \
-r /tmp/requirements.txt
RUN apt-get remove -y --allow-remove-essential perl-base && \
RUN apt-get remove -y --allow-remove-essential perl-base && \
apt-get autoremove -y
# Pre-downloading models for setups with limited egress
# Download tokenizers, distilbert for the Onyx model
# Download tokenizers, distilbert for the Danswer model
# Download model weights
# Run Nomic to pull in the custom architecture and have it cached locally
RUN python -c "from transformers import AutoTokenizer; \
@@ -38,18 +38,18 @@ from sentence_transformers import SentenceTransformer; \
SentenceTransformer(model_name_or_path='nomic-ai/nomic-embed-text-v1', trust_remote_code=True);"
# In case the user has volumes mounted to /root/.cache/huggingface that they've downloaded while
# running Onyx, don't overwrite it with the built in cache folder
# running Danswer, don't overwrite it with the built in cache folder
RUN mv /root/.cache/huggingface /root/.cache/temp_huggingface
WORKDIR /app
# Utils used by model server
COPY ./onyx/utils/logger.py /app/onyx/utils/logger.py
COPY ./danswer/utils/logger.py /app/danswer/utils/logger.py
# Place to fetch version information
COPY ./onyx/__init__.py /app/onyx/__init__.py
COPY ./danswer/__init__.py /app/danswer/__init__.py
# Shared between Onyx Backend and Model Server
# Shared between Danswer Backend and Model Server
COPY ./shared_configs /app/shared_configs
# Model Server main code

View File

@@ -1,22 +1,19 @@
<!-- DANSWER_METADATA={"link": "https://github.com/onyx-dot-app/onyx/blob/main/backend/alembic/README.md"} -->
<!-- DANSWER_METADATA={"link": "https://github.com/danswer-ai/danswer/blob/main/backend/alembic/README.md"} -->
# Alembic DB Migrations
These files are for creating/updating the tables in the Relational DB (Postgres).
Onyx migrations use a generic single-database configuration with an async dbapi.
Danswer migrations use a generic single-database configuration with an async dbapi.
## To generate new migrations:
run from onyx/backend:
## To generate new migrations:
run from danswer/backend:
`alembic revision --autogenerate -m <DESCRIPTION_OF_MIGRATION>`
More info can be found here: https://alembic.sqlalchemy.org/en/latest/autogenerate.html
## Running migrations
To run all un-applied migrations:
`alembic upgrade head`
To undo migrations:
`alembic downgrade -X`
`alembic downgrade -X`
where X is the number of migrations you want to undo from the current state

View File

@@ -1,48 +1,38 @@
from typing import Any, Literal
from onyx.db.engine import get_iam_auth_token
from onyx.configs.app_configs import USE_IAM_AUTH
from onyx.configs.app_configs import POSTGRES_HOST
from onyx.configs.app_configs import POSTGRES_PORT
from onyx.configs.app_configs import POSTGRES_USER
from onyx.configs.app_configs import AWS_REGION_NAME
from onyx.db.engine import build_connection_string
from onyx.db.engine import get_all_tenant_ids
from sqlalchemy import event
from sqlalchemy import pool
from sqlalchemy import text
from sqlalchemy.engine.base import Connection
import os
import ssl
from typing import Literal
import asyncio
import logging
from logging.config import fileConfig
import logging
from alembic import context
from sqlalchemy import pool
from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy.sql import text
from sqlalchemy.sql.schema import SchemaItem
from onyx.configs.constants import SSL_CERT_FILE
from shared_configs.configs import MULTI_TENANT, POSTGRES_DEFAULT_SCHEMA
from onyx.db.models import Base
from shared_configs.configs import MULTI_TENANT
from danswer.db.engine import build_connection_string
from danswer.db.models import Base
from celery.backends.database.session import ResultModelBase # type: ignore
from danswer.db.engine import get_all_tenant_ids
from shared_configs.configs import POSTGRES_DEFAULT_SCHEMA
# Alembic Config object
config = context.config
# Interpret the config file for Python logging.
if config.config_file_name is not None and config.attributes.get(
"configure_logger", True
):
fileConfig(config.config_file_name)
# Add your model's MetaData object here for 'autogenerate' support
target_metadata = [Base.metadata, ResultModelBase.metadata]
EXCLUDE_TABLES = {"kombu_queue", "kombu_message"}
logger = logging.getLogger(__name__)
ssl_context: ssl.SSLContext | None = None
if USE_IAM_AUTH:
if not os.path.exists(SSL_CERT_FILE):
raise FileNotFoundError(f"Expected {SSL_CERT_FILE} when USE_IAM_AUTH is true.")
ssl_context = ssl.create_default_context(cafile=SSL_CERT_FILE)
# Set up logging
logger = logging.getLogger(__name__)
def include_object(
@@ -59,12 +49,20 @@ def include_object(
reflected: bool,
compare_to: SchemaItem | None,
) -> bool:
"""
Determines whether a database object should be included in migrations.
Excludes specified tables from migrations.
"""
if type_ == "table" and name in EXCLUDE_TABLES:
return False
return True
def get_schema_options() -> tuple[str, bool, bool]:
"""
Parses command-line options passed via '-x' in Alembic commands.
Recognizes 'schema', 'create_schema', and 'upgrade_all_tenants' options.
"""
x_args_raw = context.get_x_argument()
x_args = {}
for arg in x_args_raw:
@@ -92,12 +90,16 @@ def get_schema_options() -> tuple[str, bool, bool]:
def do_run_migrations(
connection: Connection, schema_name: str, create_schema: bool
) -> None:
"""
Executes migrations in the specified schema.
"""
logger.info(f"About to migrate schema: {schema_name}")
if create_schema:
connection.execute(text(f'CREATE SCHEMA IF NOT EXISTS "{schema_name}"'))
connection.execute(text("COMMIT"))
# Set search_path to the target schema
connection.execute(text(f'SET search_path TO "{schema_name}"'))
context.configure(
@@ -115,25 +117,11 @@ def do_run_migrations(
context.run_migrations()
def provide_iam_token_for_alembic(
dialect: Any, conn_rec: Any, cargs: Any, cparams: Any
) -> None:
if USE_IAM_AUTH:
# Database connection settings
region = AWS_REGION_NAME
host = POSTGRES_HOST
port = POSTGRES_PORT
user = POSTGRES_USER
# Get IAM authentication token
token = get_iam_auth_token(host, port, user, region)
# For Alembic / SQLAlchemy in this context, set SSL and password
cparams["password"] = token
cparams["ssl"] = ssl_context
async def run_async_migrations() -> None:
"""
Determines whether to run migrations for a single schema or all schemas,
and executes migrations accordingly.
"""
schema_name, create_schema, upgrade_all_tenants = get_schema_options()
engine = create_async_engine(
@@ -141,16 +129,10 @@ async def run_async_migrations() -> None:
poolclass=pool.NullPool,
)
if USE_IAM_AUTH:
@event.listens_for(engine.sync_engine, "do_connect")
def event_provide_iam_token_for_alembic(
dialect: Any, conn_rec: Any, cargs: Any, cparams: Any
) -> None:
provide_iam_token_for_alembic(dialect, conn_rec, cargs, cparams)
if upgrade_all_tenants:
# Run migrations for all tenant schemas sequentially
tenant_schemas = get_all_tenant_ids()
for schema in tenant_schemas:
try:
logger.info(f"Migrating schema: {schema}")
@@ -180,20 +162,15 @@ async def run_async_migrations() -> None:
def run_migrations_offline() -> None:
"""
Run migrations in 'offline' mode.
"""
schema_name, _, upgrade_all_tenants = get_schema_options()
url = build_connection_string()
if upgrade_all_tenants:
# Run offline migrations for all tenant schemas
engine = create_async_engine(url)
if USE_IAM_AUTH:
@event.listens_for(engine.sync_engine, "do_connect")
def event_provide_iam_token_for_alembic_offline(
dialect: Any, conn_rec: Any, cargs: Any, cparams: Any
) -> None:
provide_iam_token_for_alembic(dialect, conn_rec, cargs, cparams)
tenant_schemas = get_all_tenant_ids()
engine.sync_engine.dispose()
@@ -230,6 +207,9 @@ def run_migrations_offline() -> None:
def run_migrations_online() -> None:
"""
Runs migrations in 'online' mode using an asynchronous engine.
"""
asyncio.run(run_async_migrations())

View File

@@ -1,29 +0,0 @@
"""add shortcut option for users
Revision ID: 027381bce97c
Revises: 6fc7886d665d
Create Date: 2025-01-14 12:14:00.814390
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "027381bce97c"
down_revision = "6fc7886d665d"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"user",
sa.Column(
"shortcut_enabled", sa.Boolean(), nullable=False, server_default="false"
),
)
def downgrade() -> None:
op.drop_column("user", "shortcut_enabled")

View File

@@ -11,7 +11,7 @@ from sqlalchemy.sql import table
from sqlalchemy.dialects import postgresql
import json
from onyx.utils.encryption import encrypt_string_to_bytes
from danswer.utils.encryption import encrypt_string_to_bytes
# revision identifiers, used by Alembic.
revision = "0a98909f2757"

View File

@@ -1,36 +0,0 @@
"""add index to index_attempt.time_created
Revision ID: 0f7ff6d75b57
Revises: 369644546676
Create Date: 2025-01-10 14:01:14.067144
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "0f7ff6d75b57"
down_revision = "fec3db967bf7"
branch_labels: None = None
depends_on: None = None
def upgrade() -> None:
op.create_index(
op.f("ix_index_attempt_status"),
"index_attempt",
["status"],
unique=False,
)
op.create_index(
op.f("ix_index_attempt_time_created"),
"index_attempt",
["time_created"],
unique=False,
)
def downgrade() -> None:
op.drop_index(op.f("ix_index_attempt_time_created"), table_name="index_attempt")
op.drop_index(op.f("ix_index_attempt_status"), table_name="index_attempt")

View File

@@ -1,4 +1,4 @@
"""Introduce Onyx APIs
"""Introduce Danswer APIs
Revision ID: 15326fcec57e
Revises: 77d07dffae64
@@ -8,7 +8,7 @@ Create Date: 2023-11-11 20:51:24.228999
from alembic import op
import sqlalchemy as sa
from onyx.configs.constants import DocumentSource
from danswer.configs.constants import DocumentSource
# revision identifiers, used by Alembic.
revision = "15326fcec57e"

View File

@@ -10,7 +10,7 @@ from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
from onyx.configs.chat_configs import NUM_POSTPROCESSED_RESULTS
from danswer.configs.chat_configs import NUM_POSTPROCESSED_RESULTS
# revision identifiers, used by Alembic.
revision = "1f60f60c3401"

View File

@@ -1,24 +0,0 @@
"""add chunk count to document
Revision ID: 2955778aa44c
Revises: c0aab6edb6dd
Create Date: 2025-01-04 11:39:43.268612
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "2955778aa44c"
down_revision = "c0aab6edb6dd"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("document", sa.Column("chunk_count", sa.Integer(), nullable=True))
def downgrade() -> None:
op.drop_column("document", "chunk_count")

View File

@@ -1,36 +0,0 @@
"""add chat session specific temperature override
Revision ID: 2f80c6a2550f
Revises: 33ea50e88f24
Create Date: 2025-01-31 10:30:27.289646
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "2f80c6a2550f"
down_revision = "33ea50e88f24"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"chat_session", sa.Column("temperature_override", sa.Float(), nullable=True)
)
op.add_column(
"user",
sa.Column(
"temperature_override_enabled",
sa.Boolean(),
nullable=False,
server_default=sa.false(),
),
)
def downgrade() -> None:
op.drop_column("chat_session", "temperature_override")
op.drop_column("user", "temperature_override_enabled")

View File

@@ -1,80 +0,0 @@
"""foreign key input prompts
Revision ID: 33ea50e88f24
Revises: a6df6b88ef81
Create Date: 2025-01-29 10:54:22.141765
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "33ea50e88f24"
down_revision = "a6df6b88ef81"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Safely drop constraints if exists
op.execute(
"""
ALTER TABLE inputprompt__user
DROP CONSTRAINT IF EXISTS inputprompt__user_input_prompt_id_fkey
"""
)
op.execute(
"""
ALTER TABLE inputprompt__user
DROP CONSTRAINT IF EXISTS inputprompt__user_user_id_fkey
"""
)
# Recreate with ON DELETE CASCADE
op.create_foreign_key(
"inputprompt__user_input_prompt_id_fkey",
"inputprompt__user",
"inputprompt",
["input_prompt_id"],
["id"],
ondelete="CASCADE",
)
op.create_foreign_key(
"inputprompt__user_user_id_fkey",
"inputprompt__user",
"user",
["user_id"],
["id"],
ondelete="CASCADE",
)
def downgrade() -> None:
# Drop the new FKs with ondelete
op.drop_constraint(
"inputprompt__user_input_prompt_id_fkey",
"inputprompt__user",
type_="foreignkey",
)
op.drop_constraint(
"inputprompt__user_user_id_fkey",
"inputprompt__user",
type_="foreignkey",
)
# Recreate them without cascading
op.create_foreign_key(
"inputprompt__user_input_prompt_id_fkey",
"inputprompt__user",
"inputprompt",
["input_prompt_id"],
["id"],
)
op.create_foreign_key(
"inputprompt__user_user_id_fkey",
"inputprompt__user",
"user",
["user_id"],
["id"],
)

View File

@@ -1,121 +0,0 @@
"""properly_cascade
Revision ID: 35e518e0ddf4
Revises: 91a0a4d62b14
Create Date: 2024-09-20 21:24:04.891018
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "35e518e0ddf4"
down_revision = "91a0a4d62b14"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Update chat_message foreign key constraint
op.drop_constraint(
"chat_message_chat_session_id_fkey", "chat_message", type_="foreignkey"
)
op.create_foreign_key(
"chat_message_chat_session_id_fkey",
"chat_message",
"chat_session",
["chat_session_id"],
["id"],
ondelete="CASCADE",
)
# Update chat_message__search_doc foreign key constraints
op.drop_constraint(
"chat_message__search_doc_chat_message_id_fkey",
"chat_message__search_doc",
type_="foreignkey",
)
op.drop_constraint(
"chat_message__search_doc_search_doc_id_fkey",
"chat_message__search_doc",
type_="foreignkey",
)
op.create_foreign_key(
"chat_message__search_doc_chat_message_id_fkey",
"chat_message__search_doc",
"chat_message",
["chat_message_id"],
["id"],
ondelete="CASCADE",
)
op.create_foreign_key(
"chat_message__search_doc_search_doc_id_fkey",
"chat_message__search_doc",
"search_doc",
["search_doc_id"],
["id"],
ondelete="CASCADE",
)
# Add CASCADE delete for tool_call foreign key
op.drop_constraint("tool_call_message_id_fkey", "tool_call", type_="foreignkey")
op.create_foreign_key(
"tool_call_message_id_fkey",
"tool_call",
"chat_message",
["message_id"],
["id"],
ondelete="CASCADE",
)
def downgrade() -> None:
# Revert chat_message foreign key constraint
op.drop_constraint(
"chat_message_chat_session_id_fkey", "chat_message", type_="foreignkey"
)
op.create_foreign_key(
"chat_message_chat_session_id_fkey",
"chat_message",
"chat_session",
["chat_session_id"],
["id"],
)
# Revert chat_message__search_doc foreign key constraints
op.drop_constraint(
"chat_message__search_doc_chat_message_id_fkey",
"chat_message__search_doc",
type_="foreignkey",
)
op.drop_constraint(
"chat_message__search_doc_search_doc_id_fkey",
"chat_message__search_doc",
type_="foreignkey",
)
op.create_foreign_key(
"chat_message__search_doc_chat_message_id_fkey",
"chat_message__search_doc",
"chat_message",
["chat_message_id"],
["id"],
)
op.create_foreign_key(
"chat_message__search_doc_search_doc_id_fkey",
"chat_message__search_doc",
"search_doc",
["search_doc_id"],
["id"],
)
# Revert tool_call foreign key constraint
op.drop_constraint("tool_call_message_id_fkey", "tool_call", type_="foreignkey")
op.create_foreign_key(
"tool_call_message_id_fkey",
"tool_call",
"chat_message",
["message_id"],
["id"],
)

View File

@@ -1,35 +0,0 @@
"""add composite index for index attempt time updated
Revision ID: 369644546676
Revises: 2955778aa44c
Create Date: 2025-01-08 15:38:17.224380
"""
from alembic import op
from sqlalchemy import text
# revision identifiers, used by Alembic.
revision = "369644546676"
down_revision = "2955778aa44c"
branch_labels: None = None
depends_on: None = None
def upgrade() -> None:
op.create_index(
"ix_index_attempt_ccpair_search_settings_time_updated",
"index_attempt",
[
"connector_credential_pair_id",
"search_settings_id",
text("time_updated DESC"),
],
unique=False,
)
def downgrade() -> None:
op.drop_index(
"ix_index_attempt_ccpair_search_settings_time_updated",
table_name="index_attempt",
)

View File

@@ -1,59 +0,0 @@
"""add back input prompts
Revision ID: 3c6531f32351
Revises: aeda5f2df4f6
Create Date: 2025-01-13 12:49:51.705235
"""
from alembic import op
import sqlalchemy as sa
import fastapi_users_db_sqlalchemy
# revision identifiers, used by Alembic.
revision = "3c6531f32351"
down_revision = "aeda5f2df4f6"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"inputprompt",
sa.Column("id", sa.Integer(), autoincrement=True, nullable=False),
sa.Column("prompt", sa.String(), nullable=False),
sa.Column("content", sa.String(), nullable=False),
sa.Column("active", sa.Boolean(), nullable=False),
sa.Column("is_public", sa.Boolean(), nullable=False),
sa.Column(
"user_id",
fastapi_users_db_sqlalchemy.generics.GUID(),
nullable=True,
),
sa.ForeignKeyConstraint(
["user_id"],
["user.id"],
),
sa.PrimaryKeyConstraint("id"),
)
op.create_table(
"inputprompt__user",
sa.Column("input_prompt_id", sa.Integer(), nullable=False),
sa.Column(
"user_id", fastapi_users_db_sqlalchemy.generics.GUID(), nullable=False
),
sa.Column("disabled", sa.Boolean(), nullable=False, default=False),
sa.ForeignKeyConstraint(
["input_prompt_id"],
["inputprompt.id"],
),
sa.ForeignKeyConstraint(
["user_id"],
["user.id"],
),
sa.PrimaryKeyConstraint("input_prompt_id", "user_id"),
)
def downgrade() -> None:
op.drop_table("inputprompt__user")
op.drop_table("inputprompt")

View File

@@ -17,7 +17,7 @@ depends_on: None = None
def upgrade() -> None:
# At this point, we directly changed some previous migrations,
# https://github.com/onyx-dot-app/onyx/pull/637
# https://github.com/danswer-ai/danswer/pull/637
# Due to using Postgres native Enums, it caused some complications for first time users.
# To remove those complications, all Enums are only handled application side moving forward.
# This migration exists to ensure that existing users don't run into upgrade issues.

View File

@@ -40,6 +40,6 @@ def upgrade() -> None:
def downgrade() -> None:
op.drop_constraint("persona_category_id_fkey", "persona", type_="foreignkey")
op.drop_constraint("fk_persona_category", "persona", type_="foreignkey")
op.drop_column("persona", "category_id")
op.drop_table("persona_category")

View File

@@ -1,37 +0,0 @@
"""lowercase_user_emails
Revision ID: 4d58345da04a
Revises: f1ca58b2f2ec
Create Date: 2025-01-29 07:48:46.784041
"""
from alembic import op
from sqlalchemy.sql import text
# revision identifiers, used by Alembic.
revision = "4d58345da04a"
down_revision = "f1ca58b2f2ec"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Get database connection
connection = op.get_bind()
# Update all user emails to lowercase
connection.execute(
text(
"""
UPDATE "user"
SET email = LOWER(email)
WHERE email != LOWER(email)
"""
)
)
def downgrade() -> None:
# Cannot restore original case of emails
pass

View File

@@ -10,8 +10,8 @@ from typing import cast
from alembic import op
import sqlalchemy as sa
from sqlalchemy.orm import Session
from onyx.key_value_store.factory import get_kv_store
from onyx.db.models import SlackBot
from danswer.key_value_store.factory import get_kv_store
from danswer.db.models import SlackBot
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.

View File

@@ -1,23 +0,0 @@
"""danswerbot -> onyxbot
Revision ID: 54a74a0417fc
Revises: 94dc3d0236f8
Create Date: 2024-12-11 18:05:05.490737
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "54a74a0417fc"
down_revision = "94dc3d0236f8"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.alter_column("chat_session", "danswerbot_flow", new_column_name="onyxbot_flow")
def downgrade() -> None:
op.alter_column("chat_session", "onyxbot_flow", new_column_name="danswerbot_flow")

View File

@@ -1,4 +1,4 @@
"""Track Onyxbot Explicitly
"""Track Danswerbot Explicitly
Revision ID: 570282d33c49
Revises: 7547d982db8f

View File

@@ -1,80 +0,0 @@
"""make categories labels and many to many
Revision ID: 6fc7886d665d
Revises: 3c6531f32351
Create Date: 2025-01-13 18:12:18.029112
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "6fc7886d665d"
down_revision = "3c6531f32351"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Rename persona_category table to persona_label
op.rename_table("persona_category", "persona_label")
# Create the new association table
op.create_table(
"persona__persona_label",
sa.Column("persona_id", sa.Integer(), nullable=False),
sa.Column("persona_label_id", sa.Integer(), nullable=False),
sa.ForeignKeyConstraint(
["persona_id"],
["persona.id"],
),
sa.ForeignKeyConstraint(
["persona_label_id"],
["persona_label.id"],
ondelete="CASCADE",
),
sa.PrimaryKeyConstraint("persona_id", "persona_label_id"),
)
# Copy existing relationships to the new table
op.execute(
"""
INSERT INTO persona__persona_label (persona_id, persona_label_id)
SELECT id, category_id FROM persona WHERE category_id IS NOT NULL
"""
)
# Remove the old category_id column from persona table
op.drop_column("persona", "category_id")
def downgrade() -> None:
# Rename persona_label table back to persona_category
op.rename_table("persona_label", "persona_category")
# Add back the category_id column to persona table
op.add_column("persona", sa.Column("category_id", sa.Integer(), nullable=True))
op.create_foreign_key(
"persona_category_id_fkey",
"persona",
"persona_category",
["category_id"],
["id"],
)
# Copy the first label relationship back to the persona table
op.execute(
"""
UPDATE persona
SET category_id = (
SELECT persona_label_id
FROM persona__persona_label
WHERE persona__persona_label.persona_id = persona.id
LIMIT 1
)
"""
)
# Drop the association table
op.drop_table("persona__persona_label")

View File

@@ -9,7 +9,7 @@ import json
from typing import cast
from alembic import op
import sqlalchemy as sa
from onyx.key_value_store.factory import get_kv_store
from danswer.key_value_store.factory import get_kv_store
# revision identifiers, used by Alembic.
revision = "703313b75876"

View File

@@ -8,9 +8,9 @@ Create Date: 2024-03-22 21:34:27.629444
from alembic import op
import sqlalchemy as sa
from onyx.db.models import IndexModelStatus
from onyx.context.search.enums import RecencyBiasSetting
from onyx.context.search.enums import SearchType
from danswer.db.models import IndexModelStatus
from danswer.context.search.enums import RecencyBiasSetting
from danswer.context.search.enums import SearchType
# revision identifiers, used by Alembic.
revision = "776b3bbe9092"

View File

@@ -18,7 +18,7 @@ depends_on: None = None
def upgrade() -> None:
# In a PR:
# https://github.com/onyx-dot-app/onyx/pull/397/files#diff-f05fb341f6373790b91852579631b64ca7645797a190837156a282b67e5b19c2
# https://github.com/danswer-ai/danswer/pull/397/files#diff-f05fb341f6373790b91852579631b64ca7645797a190837156a282b67e5b19c2
# we directly changed some previous migrations. This caused some users to have native enums
# while others wouldn't. This has caused some issues when adding new fields to these enums.
# This migration manually changes the enum types to ensure that nobody uses native enums.

View File

@@ -1,45 +0,0 @@
"""Milestone
Revision ID: 91a0a4d62b14
Revises: dab04867cd88
Create Date: 2024-12-13 19:03:30.947551
"""
from alembic import op
import sqlalchemy as sa
import fastapi_users_db_sqlalchemy
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "91a0a4d62b14"
down_revision = "dab04867cd88"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"milestone",
sa.Column("id", sa.UUID(), nullable=False),
sa.Column("tenant_id", sa.String(), nullable=True),
sa.Column(
"user_id",
fastapi_users_db_sqlalchemy.generics.GUID(),
nullable=True,
),
sa.Column("event_type", sa.String(), nullable=False),
sa.Column(
"time_created",
sa.DateTime(timezone=True),
server_default=sa.text("now()"),
nullable=False,
),
sa.Column("event_tracker", postgresql.JSONB(), nullable=True),
sa.ForeignKeyConstraint(["user_id"], ["user.id"], ondelete="CASCADE"),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint("event_type", name="uq_milestone_event_type"),
)
def downgrade() -> None:
op.drop_table("milestone")

View File

@@ -7,7 +7,7 @@ Create Date: 2024-03-21 12:05:23.956734
"""
from alembic import op
import sqlalchemy as sa
from onyx.configs.constants import DocumentSource
from danswer.configs.constants import DocumentSource
# revision identifiers, used by Alembic.
revision = "91fd3b470d1a"

View File

@@ -10,7 +10,7 @@ from sqlalchemy.orm import Session
from sqlalchemy import text
# Import your models and constants
from onyx.db.models import (
from danswer.db.models import (
Connector,
ConnectorCredentialPair,
Credential,

View File

@@ -1,30 +0,0 @@
"""make document set description optional
Revision ID: 94dc3d0236f8
Revises: bf7a81109301
Create Date: 2024-12-11 11:26:10.616722
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "94dc3d0236f8"
down_revision = "bf7a81109301"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Make document_set.description column nullable
op.alter_column(
"document_set", "description", existing_type=sa.String(), nullable=True
)
def downgrade() -> None:
# Revert document_set.description column to non-nullable
op.alter_column(
"document_set", "description", existing_type=sa.String(), nullable=False
)

View File

@@ -1,72 +0,0 @@
"""Add SyncRecord
Revision ID: 97dbb53fa8c8
Revises: 369644546676
Create Date: 2025-01-11 19:39:50.426302
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "97dbb53fa8c8"
down_revision = "be2ab2aa50ee"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"sync_record",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("entity_id", sa.Integer(), nullable=False),
sa.Column(
"sync_type",
sa.Enum(
"DOCUMENT_SET",
"USER_GROUP",
"CONNECTOR_DELETION",
name="synctype",
native_enum=False,
length=40,
),
nullable=False,
),
sa.Column(
"sync_status",
sa.Enum(
"IN_PROGRESS",
"SUCCESS",
"FAILED",
"CANCELED",
name="syncstatus",
native_enum=False,
length=40,
),
nullable=False,
),
sa.Column("num_docs_synced", sa.Integer(), nullable=False),
sa.Column("sync_start_time", sa.DateTime(timezone=True), nullable=False),
sa.Column("sync_end_time", sa.DateTime(timezone=True), nullable=True),
sa.PrimaryKeyConstraint("id"),
)
# Add index for fetch_latest_sync_record query
op.create_index(
"ix_sync_record_entity_id_sync_type_sync_start_time",
"sync_record",
["entity_id", "sync_type", "sync_start_time"],
)
# Add index for cleanup_sync_records query
op.create_index(
"ix_sync_record_entity_id_sync_type_sync_status",
"sync_record",
["entity_id", "sync_type", "sync_status"],
)
def downgrade() -> None:
op.drop_index("ix_sync_record_entity_id_sync_type_sync_status")
op.drop_index("ix_sync_record_entity_id_sync_type_sync_start_time")
op.drop_table("sync_record")

View File

@@ -1,107 +0,0 @@
"""agent_tracking
Revision ID: 98a5008d8711
Revises: 2f80c6a2550f
Create Date: 2025-01-29 17:00:00.000001
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
from sqlalchemy.dialects.postgresql import UUID
# revision identifiers, used by Alembic.
revision = "98a5008d8711"
down_revision = "2f80c6a2550f"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"agent__search_metrics",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("user_id", postgresql.UUID(as_uuid=True), nullable=True),
sa.Column("persona_id", sa.Integer(), nullable=True),
sa.Column("agent_type", sa.String(), nullable=False),
sa.Column("start_time", sa.DateTime(timezone=True), nullable=False),
sa.Column("base_duration_s", sa.Float(), nullable=False),
sa.Column("full_duration_s", sa.Float(), nullable=False),
sa.Column("base_metrics", postgresql.JSONB(), nullable=True),
sa.Column("refined_metrics", postgresql.JSONB(), nullable=True),
sa.Column("all_metrics", postgresql.JSONB(), nullable=True),
sa.ForeignKeyConstraint(
["persona_id"],
["persona.id"],
),
sa.ForeignKeyConstraint(["user_id"], ["user.id"], ondelete="CASCADE"),
sa.PrimaryKeyConstraint("id"),
)
# Create sub_question table
op.create_table(
"agent__sub_question",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column("primary_question_id", sa.Integer, sa.ForeignKey("chat_message.id")),
sa.Column(
"chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
),
sa.Column("sub_question", sa.Text),
sa.Column(
"time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
),
sa.Column("sub_answer", sa.Text),
sa.Column("sub_question_doc_results", postgresql.JSONB(), nullable=True),
sa.Column("level", sa.Integer(), nullable=False),
sa.Column("level_question_num", sa.Integer(), nullable=False),
)
# Create sub_query table
op.create_table(
"agent__sub_query",
sa.Column("id", sa.Integer, primary_key=True),
sa.Column(
"parent_question_id", sa.Integer, sa.ForeignKey("agent__sub_question.id")
),
sa.Column(
"chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
),
sa.Column("sub_query", sa.Text),
sa.Column(
"time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
),
)
# Create sub_query__search_doc association table
op.create_table(
"agent__sub_query__search_doc",
sa.Column(
"sub_query_id",
sa.Integer,
sa.ForeignKey("agent__sub_query.id"),
primary_key=True,
),
sa.Column(
"search_doc_id",
sa.Integer,
sa.ForeignKey("search_doc.id"),
primary_key=True,
),
)
op.add_column(
"chat_message",
sa.Column(
"refined_answer_improvement",
sa.Boolean(),
nullable=True,
),
)
def downgrade() -> None:
op.drop_column("chat_message", "refined_answer_improvement")
op.drop_table("agent__sub_query__search_doc")
op.drop_table("agent__sub_query")
op.drop_table("agent__sub_question")
op.drop_table("agent__search_metrics")

View File

@@ -1,29 +0,0 @@
"""remove recent assistants
Revision ID: a6df6b88ef81
Revises: 4d58345da04a
Create Date: 2025-01-29 10:25:52.790407
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "a6df6b88ef81"
down_revision = "4d58345da04a"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.drop_column("user", "recent_assistants")
def downgrade() -> None:
op.add_column(
"user",
sa.Column(
"recent_assistants", postgresql.JSONB(), server_default="[]", nullable=False
),
)

View File

@@ -1,27 +0,0 @@
"""add pinned assistants
Revision ID: aeda5f2df4f6
Revises: c5eae4a75a1b
Create Date: 2025-01-09 16:04:10.770636
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "aeda5f2df4f6"
down_revision = "c5eae4a75a1b"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"user", sa.Column("pinned_assistants", postgresql.JSONB(), nullable=True)
)
op.execute('UPDATE "user" SET pinned_assistants = chosen_assistants')
def downgrade() -> None:
op.drop_column("user", "pinned_assistants")

View File

@@ -10,7 +10,7 @@ from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
from sqlalchemy.dialects.postgresql import ENUM
from onyx.configs.constants import DocumentSource
from danswer.configs.constants import DocumentSource
# revision identifiers, used by Alembic.
revision = "b156fa702355"

View File

@@ -1,38 +0,0 @@
"""fix_capitalization
Revision ID: be2ab2aa50ee
Revises: 369644546676
Create Date: 2025-01-10 13:13:26.228960
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "be2ab2aa50ee"
down_revision = "369644546676"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.execute(
"""
UPDATE document
SET
external_user_group_ids = ARRAY(
SELECT LOWER(unnest(external_user_group_ids))
),
last_modified = NOW()
WHERE
external_user_group_ids IS NOT NULL
AND external_user_group_ids::text[] <> ARRAY(
SELECT LOWER(unnest(external_user_group_ids))
)::text[]
"""
)
def downgrade() -> None:
# No way to cleanly persist the bad state through an upgrade/downgrade
# cycle, so we just pass
pass

View File

@@ -1,57 +0,0 @@
"""delete_input_prompts
Revision ID: bf7a81109301
Revises: f7a894b06d02
Create Date: 2024-12-09 12:00:49.884228
"""
from alembic import op
import sqlalchemy as sa
import fastapi_users_db_sqlalchemy
# revision identifiers, used by Alembic.
revision = "bf7a81109301"
down_revision = "f7a894b06d02"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.drop_table("inputprompt__user")
op.drop_table("inputprompt")
def downgrade() -> None:
op.create_table(
"inputprompt",
sa.Column("id", sa.Integer(), autoincrement=True, nullable=False),
sa.Column("prompt", sa.String(), nullable=False),
sa.Column("content", sa.String(), nullable=False),
sa.Column("active", sa.Boolean(), nullable=False),
sa.Column("is_public", sa.Boolean(), nullable=False),
sa.Column(
"user_id",
fastapi_users_db_sqlalchemy.generics.GUID(),
nullable=True,
),
sa.ForeignKeyConstraint(
["user_id"],
["user.id"],
),
sa.PrimaryKeyConstraint("id"),
)
op.create_table(
"inputprompt__user",
sa.Column("input_prompt_id", sa.Integer(), nullable=False),
sa.Column("user_id", sa.Integer(), nullable=False),
sa.ForeignKeyConstraint(
["input_prompt_id"],
["inputprompt.id"],
),
sa.ForeignKeyConstraint(
["user_id"],
["inputprompt.id"],
),
sa.PrimaryKeyConstraint("input_prompt_id", "user_id"),
)

View File

@@ -1,87 +0,0 @@
"""delete workspace
Revision ID: c0aab6edb6dd
Revises: 35e518e0ddf4
Create Date: 2024-12-17 14:37:07.660631
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "c0aab6edb6dd"
down_revision = "35e518e0ddf4"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.execute(
"""
UPDATE connector
SET connector_specific_config = connector_specific_config - 'workspace'
WHERE source = 'SLACK'
"""
)
def downgrade() -> None:
import json
from sqlalchemy import text
from slack_sdk import WebClient
conn = op.get_bind()
# Fetch all Slack credentials
creds_result = conn.execute(
text("SELECT id, credential_json FROM credential WHERE source = 'SLACK'")
)
all_slack_creds = creds_result.fetchall()
if not all_slack_creds:
return
for cred_row in all_slack_creds:
credential_id, credential_json = cred_row
credential_json = (
credential_json.tobytes().decode("utf-8")
if isinstance(credential_json, memoryview)
else credential_json.decode("utf-8")
)
credential_data = json.loads(credential_json)
slack_bot_token = credential_data.get("slack_bot_token")
if not slack_bot_token:
print(
f"No slack_bot_token found for credential {credential_id}. "
"Your Slack connector will not function until you upgrade and provide a valid token."
)
continue
client = WebClient(token=slack_bot_token)
try:
auth_response = client.auth_test()
workspace = auth_response["url"].split("//")[1].split(".")[0]
# Update only the connectors linked to this credential
# (and which are Slack connectors).
op.execute(
f"""
UPDATE connector AS c
SET connector_specific_config = jsonb_set(
connector_specific_config,
'{{workspace}}',
to_jsonb('{workspace}'::text)
)
FROM connector_credential_pair AS ccp
WHERE ccp.connector_id = c.id
AND c.source = 'SLACK'
AND ccp.credential_id = {credential_id}
"""
)
except Exception:
print(
f"We were unable to get the workspace url for your Slack Connector with id {credential_id}."
)
print("This connector will no longer work until you upgrade.")
continue

View File

@@ -1,36 +0,0 @@
"""Add chat_message__standard_answer table
Revision ID: c5eae4a75a1b
Revises: 0f7ff6d75b57
Create Date: 2025-01-15 14:08:49.688998
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "c5eae4a75a1b"
down_revision = "0f7ff6d75b57"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"chat_message__standard_answer",
sa.Column("chat_message_id", sa.Integer(), nullable=False),
sa.Column("standard_answer_id", sa.Integer(), nullable=False),
sa.ForeignKeyConstraint(
["chat_message_id"],
["chat_message.id"],
),
sa.ForeignKeyConstraint(
["standard_answer_id"],
["standard_answer.id"],
),
sa.PrimaryKeyConstraint("chat_message_id", "standard_answer_id"),
)
def downgrade() -> None:
op.drop_table("chat_message__standard_answer")

View File

@@ -1,48 +0,0 @@
"""Add has_been_indexed to DocumentByConnectorCredentialPair
Revision ID: c7bf5721733e
Revises: fec3db967bf7
Create Date: 2025-01-13 12:39:05.831693
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "c7bf5721733e"
down_revision = "027381bce97c"
branch_labels = None
depends_on = None
def upgrade() -> None:
# assume all existing rows have been indexed, no better approach
op.add_column(
"document_by_connector_credential_pair",
sa.Column("has_been_indexed", sa.Boolean(), nullable=True),
)
op.execute(
"UPDATE document_by_connector_credential_pair SET has_been_indexed = TRUE"
)
op.alter_column(
"document_by_connector_credential_pair",
"has_been_indexed",
nullable=False,
)
# Add index to optimize get_document_counts_for_cc_pairs query pattern
op.create_index(
"idx_document_cc_pair_counts",
"document_by_connector_credential_pair",
["connector_id", "credential_id", "has_been_indexed"],
unique=False,
)
def downgrade() -> None:
# Remove the index first before removing the column
op.drop_index(
"idx_document_cc_pair_counts",
table_name="document_by_connector_credential_pair",
)
op.drop_column("document_by_connector_credential_pair", "has_been_indexed")

View File

@@ -1,32 +0,0 @@
"""Add composite index to document_by_connector_credential_pair
Revision ID: dab04867cd88
Revises: 54a74a0417fc
Create Date: 2024-12-13 22:43:20.119990
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "dab04867cd88"
down_revision = "54a74a0417fc"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Composite index on (connector_id, credential_id)
op.create_index(
"idx_document_cc_pair_connector_credential",
"document_by_connector_credential_pair",
["connector_id", "credential_id"],
unique=False,
)
def downgrade() -> None:
op.drop_index(
"idx_document_cc_pair_connector_credential",
table_name="document_by_connector_credential_pair",
)

View File

@@ -1,4 +1,4 @@
"""Onyx Custom Tool Flow
"""Danswer Custom Tool Flow
Revision ID: dba7f71618f5
Revises: d5645c915d0e

View File

@@ -9,12 +9,12 @@ from alembic import op
import sqlalchemy as sa
from sqlalchemy import table, column, String, Integer, Boolean
from onyx.db.search_settings import (
from danswer.db.search_settings import (
get_new_default_embedding_model,
get_old_default_embedding_model,
user_has_overridden_embedding_model,
)
from onyx.db.models import IndexModelStatus
from danswer.db.models import IndexModelStatus
# revision identifiers, used by Alembic.
revision = "dbaa756c2ccf"

View File

@@ -8,7 +8,7 @@ Create Date: 2024-03-14 18:06:08.523106
from alembic import op
import sqlalchemy as sa
from onyx.configs.constants import DocumentSource
from danswer.configs.constants import DocumentSource
# revision identifiers, used by Alembic.
revision = "e50154680a5c"

View File

@@ -1,80 +0,0 @@
"""add default slack channel config
Revision ID: eaa3b5593925
Revises: 98a5008d8711
Create Date: 2025-02-03 18:07:56.552526
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "eaa3b5593925"
down_revision = "98a5008d8711"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Add is_default column
op.add_column(
"slack_channel_config",
sa.Column("is_default", sa.Boolean(), nullable=False, server_default="false"),
)
op.create_index(
"ix_slack_channel_config_slack_bot_id_default",
"slack_channel_config",
["slack_bot_id", "is_default"],
unique=True,
postgresql_where=sa.text("is_default IS TRUE"),
)
# Create default channel configs for existing slack bots without one
conn = op.get_bind()
slack_bots = conn.execute(sa.text("SELECT id FROM slack_bot")).fetchall()
for slack_bot in slack_bots:
slack_bot_id = slack_bot[0]
existing_default = conn.execute(
sa.text(
"SELECT id FROM slack_channel_config WHERE slack_bot_id = :bot_id AND is_default = TRUE"
),
{"bot_id": slack_bot_id},
).fetchone()
if not existing_default:
conn.execute(
sa.text(
"""
INSERT INTO slack_channel_config (
slack_bot_id, persona_id, channel_config, enable_auto_filters, is_default
) VALUES (
:bot_id, NULL,
'{"channel_name": null, '
'"respond_member_group_list": [], '
'"answer_filters": [], '
'"follow_up_tags": [], '
'"respond_tag_only": true}',
FALSE, TRUE
)
"""
),
{"bot_id": slack_bot_id},
)
def downgrade() -> None:
# Delete default slack channel configs
conn = op.get_bind()
conn.execute(sa.text("DELETE FROM slack_channel_config WHERE is_default = TRUE"))
# Remove index
op.drop_index(
"ix_slack_channel_config_slack_bot_id_default",
table_name="slack_channel_config",
)
# Remove is_default column
op.drop_column("slack_channel_config", "is_default")

View File

@@ -1,33 +0,0 @@
"""add passthrough auth to tool
Revision ID: f1ca58b2f2ec
Revises: c7bf5721733e
Create Date: 2024-03-19
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = "f1ca58b2f2ec"
down_revision: Union[str, None] = "c7bf5721733e"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# Add passthrough_auth column to tool table with default value of False
op.add_column(
"tool",
sa.Column(
"passthrough_auth", sa.Boolean(), nullable=False, server_default=sa.false()
),
)
def downgrade() -> None:
# Remove passthrough_auth column from tool table
op.drop_column("tool", "passthrough_auth")

View File

@@ -1,53 +0,0 @@
"""delete non-search assistants
Revision ID: f5437cc136c5
Revises: eaa3b5593925
Create Date: 2025-02-04 16:17:15.677256
"""
from alembic import op
# revision identifiers, used by Alembic.
revision = "f5437cc136c5"
down_revision = "eaa3b5593925"
branch_labels = None
depends_on = None
def upgrade() -> None:
pass
def downgrade() -> None:
# Fix: split the statements into multiple op.execute() calls
op.execute(
"""
WITH personas_without_search AS (
SELECT p.id
FROM persona p
LEFT JOIN persona__tool pt ON p.id = pt.persona_id
LEFT JOIN tool t ON pt.tool_id = t.id
GROUP BY p.id
HAVING COUNT(CASE WHEN t.in_code_tool_id = 'run_search' THEN 1 END) = 0
)
UPDATE slack_channel_config
SET persona_id = NULL
WHERE is_default = TRUE AND persona_id IN (SELECT id FROM personas_without_search)
"""
)
op.execute(
"""
WITH personas_without_search AS (
SELECT p.id
FROM persona p
LEFT JOIN persona__tool pt ON p.id = pt.persona_id
LEFT JOIN tool t ON pt.tool_id = t.id
GROUP BY p.id
HAVING COUNT(CASE WHEN t.in_code_tool_id = 'run_search' THEN 1 END) = 0
)
DELETE FROM slack_channel_config
WHERE is_default = FALSE AND persona_id IN (SELECT id FROM personas_without_search)
"""
)

View File

@@ -1,40 +0,0 @@
"""non-nullbale slack bot id in channel config
Revision ID: f7a894b06d02
Revises: 9f696734098f
Create Date: 2024-12-06 12:55:42.845723
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "f7a894b06d02"
down_revision = "9f696734098f"
branch_labels = None
depends_on = None
def upgrade() -> None:
# Delete all rows with null slack_bot_id
op.execute("DELETE FROM slack_channel_config WHERE slack_bot_id IS NULL")
# Make slack_bot_id non-nullable
op.alter_column(
"slack_channel_config",
"slack_bot_id",
existing_type=sa.Integer(),
nullable=False,
)
def downgrade() -> None:
# Make slack_bot_id nullable again
op.alter_column(
"slack_channel_config",
"slack_bot_id",
existing_type=sa.Integer(),
nullable=True,
)

View File

@@ -1,41 +0,0 @@
"""Add time_updated to UserGroup and DocumentSet
Revision ID: fec3db967bf7
Revises: 97dbb53fa8c8
Create Date: 2025-01-12 15:49:02.289100
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "fec3db967bf7"
down_revision = "97dbb53fa8c8"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"document_set",
sa.Column(
"time_last_modified_by_user",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.func.now(),
),
)
op.add_column(
"user_group",
sa.Column(
"time_last_modified_by_user",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.func.now(),
),
)
def downgrade() -> None:
op.drop_column("user_group", "time_last_modified_by_user")
op.drop_column("document_set", "time_last_modified_by_user")

View File

@@ -1,3 +1,3 @@
These files are for public table migrations when operating with multi tenancy.
If you are not a Onyx developer, you can ignore this directory entirely.
If you are not a Danswer developer, you can ignore this directory entirely.

View File

@@ -8,8 +8,8 @@ from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy.schema import SchemaItem
from alembic import context
from onyx.db.engine import build_connection_string
from onyx.db.models import PublicBase
from danswer.db.engine import build_connection_string
from danswer.db.models import PublicBase
# this is the Alembic Config object, which provides
# access to the values within the .ini file in use.

View File

@@ -1,31 +0,0 @@
"""mapping for anonymous user path
Revision ID: a4f6ee863c47
Revises: 14a83a331951
Create Date: 2025-01-04 14:16:58.697451
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "a4f6ee863c47"
down_revision = "14a83a331951"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"tenant_anonymous_user_path",
sa.Column("tenant_id", sa.String(), primary_key=True, nullable=False),
sa.Column("anonymous_user_path", sa.String(), nullable=False),
sa.PrimaryKeyConstraint("tenant_id"),
sa.UniqueConstraint("anonymous_user_path"),
)
def downgrade() -> None:
op.drop_table("tenant_anonymous_user_path")

View File

@@ -0,0 +1,3 @@
import os
__version__ = os.environ.get("DANSWER_VERSION", "") or "Development"

View File

@@ -1,12 +1,12 @@
from sqlalchemy.orm import Session
from onyx.access.models import DocumentAccess
from onyx.access.utils import prefix_user_email
from onyx.configs.constants import PUBLIC_DOC_PAT
from onyx.db.document import get_access_info_for_document
from onyx.db.document import get_access_info_for_documents
from onyx.db.models import User
from onyx.utils.variable_functionality import fetch_versioned_implementation
from danswer.access.models import DocumentAccess
from danswer.access.utils import prefix_user_email
from danswer.configs.constants import PUBLIC_DOC_PAT
from danswer.db.document import get_access_info_for_document
from danswer.db.document import get_access_info_for_documents
from danswer.db.models import User
from danswer.utils.variable_functionality import fetch_versioned_implementation
def _get_access_for_document(
@@ -32,7 +32,7 @@ def get_access_for_document(
db_session: Session,
) -> DocumentAccess:
versioned_get_access_for_document_fn = fetch_versioned_implementation(
"onyx.access.access", "_get_access_for_document"
"danswer.access.access", "_get_access_for_document"
)
return versioned_get_access_for_document_fn(document_id, db_session) # type: ignore
@@ -83,7 +83,7 @@ def get_access_for_documents(
) -> dict[str, DocumentAccess]:
"""Fetches all access information for the given documents."""
versioned_get_access_for_documents_fn = fetch_versioned_implementation(
"onyx.access.access", "_get_access_for_documents"
"danswer.access.access", "_get_access_for_documents"
)
return versioned_get_access_for_documents_fn(
document_ids, db_session
@@ -103,6 +103,6 @@ def _get_acl_for_user(user: User | None, db_session: Session) -> set[str]:
def get_acl_for_user(user: User | None, db_session: Session | None = None) -> set[str]:
versioned_acl_for_user_fn = fetch_versioned_implementation(
"onyx.access.access", "_get_acl_for_user"
"danswer.access.access", "_get_acl_for_user"
)
return versioned_acl_for_user_fn(user, db_session) # type: ignore

View File

@@ -1,9 +1,9 @@
from dataclasses import dataclass
from onyx.access.utils import prefix_external_group
from onyx.access.utils import prefix_user_email
from onyx.access.utils import prefix_user_group
from onyx.configs.constants import PUBLIC_DOC_PAT
from danswer.access.utils import prefix_external_group
from danswer.access.utils import prefix_user_email
from danswer.access.utils import prefix_user_group
from danswer.configs.constants import PUBLIC_DOC_PAT
@dataclass(frozen=True)
@@ -12,7 +12,7 @@ class ExternalAccess:
external_user_emails: set[str]
# Names or external IDs of groups with access to the doc
external_user_group_ids: set[str]
# Whether the document is public in the external system or Onyx
# Whether the document is public in the external system or Danswer
is_public: bool
@@ -58,7 +58,7 @@ class DocExternalAccess:
@dataclass(frozen=True)
class DocumentAccess(ExternalAccess):
# User emails for Onyx users, None indicates admin
# User emails for Danswer users, None indicates admin
user_emails: set[str | None]
# Names of user groups associated with this document
user_groups: set[str]

View File

@@ -1,9 +1,9 @@
from onyx.configs.constants import DocumentSource
from danswer.configs.constants import DocumentSource
def prefix_user_email(user_email: str) -> str:
"""Prefixes a user email to eliminate collision with group names.
This applies to both a Onyx user and an External user, this is to make the query time
This applies to both a Danswer user and an External user, this is to make the query time
more efficient"""
return f"user_email:{user_email}"
@@ -15,13 +15,10 @@ def prefix_user_group(user_group_name: str) -> str:
def prefix_external_group(ext_group_name: str) -> str:
"""Prefixes an external group name to eliminate collision with user emails / Onyx groups."""
"""Prefixes an external group name to eliminate collision with user emails / Danswer groups."""
return f"external_group:{ext_group_name}"
def build_ext_group_name_for_onyx(ext_group_name: str, source: DocumentSource) -> str:
"""
External groups may collide across sources, every source needs its own prefix.
NOTE: the name is lowercased to handle case sensitivity for group names
"""
return f"{source.value}_{ext_group_name}".lower()
def prefix_group_w_source(ext_group_name: str, source: DocumentSource) -> str:
"""External groups may collide across sources, every source needs its own prefix."""
return f"{source.value.upper()}_{ext_group_name}"

View File

@@ -0,0 +1,100 @@
from langgraph.graph import END
from langgraph.graph import START
from langgraph.graph import StateGraph
from danswer.agent_search.answer_query.nodes.answer_check import answer_check
from danswer.agent_search.answer_query.nodes.answer_generation import answer_generation
from danswer.agent_search.answer_query.nodes.format_answer import format_answer
from danswer.agent_search.answer_query.states import AnswerQueryInput
from danswer.agent_search.answer_query.states import AnswerQueryOutput
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.expanded_retrieval.graph_builder import (
expanded_retrieval_graph_builder,
)
def answer_query_graph_builder() -> StateGraph:
graph = StateGraph(
state_schema=AnswerQueryState,
input=AnswerQueryInput,
output=AnswerQueryOutput,
)
### Add nodes ###
expanded_retrieval = expanded_retrieval_graph_builder().compile()
graph.add_node(
node="expanded_retrieval_for_initial_decomp",
action=expanded_retrieval,
)
graph.add_node(
node="answer_check",
action=answer_check,
)
graph.add_node(
node="answer_generation",
action=answer_generation,
)
graph.add_node(
node="format_answer",
action=format_answer,
)
### Add edges ###
graph.add_edge(
start_key=START,
end_key="expanded_retrieval_for_initial_decomp",
)
graph.add_edge(
start_key="expanded_retrieval_for_initial_decomp",
end_key="answer_generation",
)
graph.add_edge(
start_key="answer_generation",
end_key="answer_check",
)
graph.add_edge(
start_key="answer_check",
end_key="format_answer",
)
graph.add_edge(
start_key="format_answer",
end_key=END,
)
return graph
if __name__ == "__main__":
from danswer.db.engine import get_session_context_manager
from danswer.llm.factory import get_default_llms
from danswer.context.search.models import SearchRequest
graph = answer_query_graph_builder()
compiled_graph = graph.compile()
primary_llm, fast_llm = get_default_llms()
search_request = SearchRequest(
query="Who made Excel and what other products did they make?",
)
with get_session_context_manager() as db_session:
inputs = AnswerQueryInput(
search_request=search_request,
primary_llm=primary_llm,
fast_llm=fast_llm,
db_session=db_session,
query_to_answer="Who made Excel?",
)
output = compiled_graph.invoke(
input=inputs,
# debug=True,
# subgraphs=True,
)
print(output)
# for namespace, chunk in compiled_graph.stream(
# input=inputs,
# # debug=True,
# subgraphs=True,
# ):
# print(namespace)
# print(chunk)

View File

@@ -0,0 +1,30 @@
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.answer_query.states import QACheckOutput
from danswer.agent_search.shared_graph_utils.prompts import BASE_CHECK_PROMPT
def answer_check(state: AnswerQueryState) -> QACheckOutput:
msg = [
HumanMessage(
content=BASE_CHECK_PROMPT.format(
question=state["search_request"].query,
base_answer=state["answer"],
)
)
]
fast_llm = state["fast_llm"]
response = list(
fast_llm.stream(
prompt=msg,
)
)
response_str = merge_message_runs(response, chunk_separator="")[0].content
return QACheckOutput(
answer_quality=response_str,
)

View File

@@ -0,0 +1,32 @@
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.answer_query.states import QAGenerationOutput
from danswer.agent_search.shared_graph_utils.prompts import BASE_RAG_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_docs
def answer_generation(state: AnswerQueryState) -> QAGenerationOutput:
query = state["query_to_answer"]
docs = state["reordered_documents"]
print(f"Number of verified retrieval docs: {len(docs)}")
msg = [
HumanMessage(
content=BASE_RAG_PROMPT.format(question=query, context=format_docs(docs))
)
]
fast_llm = state["fast_llm"]
response = list(
fast_llm.stream(
prompt=msg,
)
)
answer_str = merge_message_runs(response, chunk_separator="")[0].content
return QAGenerationOutput(
answer=answer_str,
)

View File

@@ -0,0 +1,16 @@
from danswer.agent_search.answer_query.states import AnswerQueryOutput
from danswer.agent_search.answer_query.states import AnswerQueryState
from danswer.agent_search.answer_query.states import SearchAnswerResults
def format_answer(state: AnswerQueryState) -> AnswerQueryOutput:
return AnswerQueryOutput(
decomp_answer_results=[
SearchAnswerResults(
query=state["query_to_answer"],
quality=state["answer_quality"],
answer=state["answer"],
documents=state["reordered_documents"],
)
],
)

View File

@@ -0,0 +1,45 @@
from typing import Annotated
from typing import TypedDict
from pydantic import BaseModel
from danswer.agent_search.core_state import PrimaryState
from danswer.agent_search.shared_graph_utils.operators import dedup_inference_sections
from danswer.context.search.models import InferenceSection
class SearchAnswerResults(BaseModel):
query: str
answer: str
quality: str
documents: Annotated[list[InferenceSection], dedup_inference_sections]
class QACheckOutput(TypedDict, total=False):
answer_quality: str
class QAGenerationOutput(TypedDict, total=False):
answer: str
class ExpandedRetrievalOutput(TypedDict):
reordered_documents: Annotated[list[InferenceSection], dedup_inference_sections]
class AnswerQueryState(
PrimaryState,
QACheckOutput,
QAGenerationOutput,
ExpandedRetrievalOutput,
total=True,
):
query_to_answer: str
class AnswerQueryInput(PrimaryState, total=True):
query_to_answer: str
class AnswerQueryOutput(TypedDict):
decomp_answer_results: list[SearchAnswerResults]

View File

@@ -0,0 +1,15 @@
from typing import TypedDict
from sqlalchemy.orm import Session
from danswer.context.search.models import SearchRequest
from danswer.llm.interfaces import LLM
class PrimaryState(TypedDict, total=False):
search_request: SearchRequest
primary_llm: LLM
fast_llm: LLM
# a single session for the entire agent search
# is fine if we are only reading
db_session: Session

View File

@@ -0,0 +1,114 @@
from typing import Any
from langchain_core.messages import HumanMessage
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import COMBINED_CONTEXT
from danswer.agent_search.shared_graph_utils.prompts import MODIFIED_RAG_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_docs
from danswer.agent_search.shared_graph_utils.utils import normalize_whitespace
# aggregate sub questions and answers
def deep_answer_generation(state: MainState) -> dict[str, Any]:
"""
Generate answer
Args:
state (messages): The current state
Returns:
dict: The updated state with re-phrased question
"""
print("---DEEP GENERATE---")
question = state["original_question"]
docs = state["deduped_retrieval_docs"]
deep_answer_context = state["core_answer_dynamic_context"]
print(f"Number of verified retrieval docs - deep: {len(docs)}")
combined_context = normalize_whitespace(
COMBINED_CONTEXT.format(
deep_answer_context=deep_answer_context, formated_docs=format_docs(docs)
)
)
msg = [
HumanMessage(
content=MODIFIED_RAG_PROMPT.format(
question=question, combined_context=combined_context
)
)
]
# Grader
model = state["fast_llm"]
response = model.invoke(msg)
return {
"deep_answer": response.content,
}
def final_stuff(state: MainState) -> dict[str, Any]:
"""
Invokes the agent model to generate a response based on the current state. Given
the question, it will decide to retrieve using the retriever tool, or simply end.
Args:
state (messages): The current state
Returns:
dict: The updated state with the agent response appended to messages
"""
print("---FINAL---")
messages = state["log_messages"]
time_ordered_messages = [x.pretty_repr() for x in messages]
time_ordered_messages.sort()
print("Message Log:")
print("\n".join(time_ordered_messages))
initial_sub_qas = state["initial_sub_qas"]
initial_sub_qa_list = []
for initial_sub_qa in initial_sub_qas:
if initial_sub_qa["sub_answer_check"] == "yes":
initial_sub_qa_list.append(
f' Question:\n {initial_sub_qa["sub_question"]}\n --\n Answer:\n {initial_sub_qa["sub_answer"]}\n -----'
)
initial_sub_qa_context = "\n".join(initial_sub_qa_list)
base_answer = state["base_answer"]
print(f"Final Base Answer:\n{base_answer}")
print("--------------------------------")
print(f"Initial Answered Sub Questions:\n{initial_sub_qa_context}")
print("--------------------------------")
if not state.get("deep_answer"):
print("No Deep Answer was required")
return {}
deep_answer = state["deep_answer"]
sub_qas = state["sub_qas"]
sub_qa_list = []
for sub_qa in sub_qas:
if sub_qa["sub_answer_check"] == "yes":
sub_qa_list.append(
f' Question:\n {sub_qa["sub_question"]}\n --\n Answer:\n {sub_qa["sub_answer"]}\n -----'
)
sub_qa_context = "\n".join(sub_qa_list)
print(f"Final Base Answer:\n{base_answer}")
print("--------------------------------")
print(f"Final Deep Answer:\n{deep_answer}")
print("--------------------------------")
print("Sub Questions and Answers:")
print(sub_qa_context)
return {}

View File

@@ -0,0 +1,78 @@
import json
import re
from datetime import datetime
from typing import Any
from langchain_core.messages import HumanMessage
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import DEEP_DECOMPOSE_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_entity_term_extraction
from danswer.agent_search.shared_graph_utils.utils import generate_log_message
def decompose(state: MainState) -> dict[str, Any]:
""" """
node_start_time = datetime.now()
question = state["original_question"]
base_answer = state["base_answer"]
# get the entity term extraction dict and properly format it
entity_term_extraction_dict = state["retrieved_entities_relationships"][
"retrieved_entities_relationships"
]
entity_term_extraction_str = format_entity_term_extraction(
entity_term_extraction_dict
)
initial_question_answers = state["initial_sub_qas"]
addressed_question_list = [
x["sub_question"]
for x in initial_question_answers
if x["sub_answer_check"] == "yes"
]
failed_question_list = [
x["sub_question"]
for x in initial_question_answers
if x["sub_answer_check"] == "no"
]
msg = [
HumanMessage(
content=DEEP_DECOMPOSE_PROMPT.format(
question=question,
entity_term_extraction_str=entity_term_extraction_str,
base_answer=base_answer,
answered_sub_questions="\n - ".join(addressed_question_list),
failed_sub_questions="\n - ".join(failed_question_list),
),
)
]
# Grader
model = state["fast_llm"]
response = model.invoke(msg)
cleaned_response = re.sub(r"```json\n|\n```", "", response.pretty_repr())
parsed_response = json.loads(cleaned_response)
sub_questions_dict = {}
for sub_question_nr, sub_question_dict in enumerate(
parsed_response["sub_questions"]
):
sub_question_dict["answered"] = False
sub_question_dict["verified"] = False
sub_questions_dict[sub_question_nr] = sub_question_dict
return {
"decomposed_sub_questions_dict": sub_questions_dict,
"log_messages": generate_log_message(
message="deep - decompose",
node_start_time=node_start_time,
graph_start_time=state["graph_start_time"],
),
}

View File

@@ -0,0 +1,40 @@
import json
import re
from typing import Any
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.main.states import MainState
from danswer.agent_search.shared_graph_utils.prompts import ENTITY_TERM_PROMPT
from danswer.agent_search.shared_graph_utils.utils import format_docs
def entity_term_extraction(state: MainState) -> dict[str, Any]:
"""Extract entities and terms from the question and context"""
question = state["original_question"]
docs = state["deduped_retrieval_docs"]
doc_context = format_docs(docs)
msg = [
HumanMessage(
content=ENTITY_TERM_PROMPT.format(question=question, context=doc_context),
)
]
fast_llm = state["fast_llm"]
# Grader
llm_response_list = list(
fast_llm.stream(
prompt=msg,
)
)
llm_response = merge_message_runs(llm_response_list, chunk_separator="")[0].content
cleaned_response = re.sub(r"```json\n|\n```", "", llm_response)
parsed_response = json.loads(cleaned_response)
return {
"retrieved_entities_relationships": parsed_response,
}

View File

@@ -0,0 +1,30 @@
from typing import Any
from danswer.agent_search.main.states import MainState
# aggregate sub questions and answers
def sub_qa_level_aggregator(state: MainState) -> dict[str, Any]:
sub_qas = state["sub_qas"]
dynamic_context_list = [
"Below you will find useful information to answer the original question:"
]
checked_sub_qas = []
for core_answer_sub_qa in sub_qas:
question = core_answer_sub_qa["sub_question"]
answer = core_answer_sub_qa["sub_answer"]
verified = core_answer_sub_qa["sub_answer_check"]
if verified == "yes":
dynamic_context_list.append(
f"Question:\n{question}\n\nAnswer:\n{answer}\n\n---\n\n"
)
checked_sub_qas.append({"sub_question": question, "sub_answer": answer})
dynamic_context = "\n".join(dynamic_context_list)
return {
"core_answer_dynamic_context": dynamic_context,
"checked_sub_qas": checked_sub_qas,
}

View File

@@ -0,0 +1,19 @@
from typing import Any
from danswer.agent_search.main.states import MainState
def sub_qa_manager(state: MainState) -> dict[str, Any]:
""" """
sub_questions_dict = state["decomposed_sub_questions_dict"]
sub_questions = {}
for sub_question_nr, sub_question_dict in sub_questions_dict.items():
sub_questions[sub_question_nr] = sub_question_dict["sub_question"]
return {
"sub_questions": sub_questions,
"num_new_question_iterations": 0,
}

View File

@@ -0,0 +1,44 @@
from collections.abc import Hashable
from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from langgraph.types import Send
from danswer.agent_search.expanded_retrieval.nodes.doc_retrieval import RetrieveInput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalInput
from danswer.agent_search.shared_graph_utils.prompts import REWRITE_PROMPT_MULTI
from danswer.llm.interfaces import LLM
def parallel_retrieval_edge(state: ExpandedRetrievalInput) -> list[Send | Hashable]:
print(f"parallel_retrieval_edge state: {state.keys()}")
# This should be better...
question = state.get("query_to_answer") or state["search_request"].query
llm: LLM = state["fast_llm"]
msg = [
HumanMessage(
content=REWRITE_PROMPT_MULTI.format(question=question),
)
]
llm_response_list = list(
llm.stream(
prompt=msg,
)
)
llm_response = merge_message_runs(llm_response_list, chunk_separator="")[0].content
print(f"llm_response: {llm_response}")
rewritten_queries = llm_response.split("\n")
print(f"rewritten_queries: {rewritten_queries}")
return [
Send(
"doc_retrieval",
RetrieveInput(query_to_retrieve=query, **state),
)
for query in rewritten_queries
]

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from langgraph.graph import END
from langgraph.graph import START
from langgraph.graph import StateGraph
from danswer.agent_search.expanded_retrieval.edges import parallel_retrieval_edge
from danswer.agent_search.expanded_retrieval.nodes.doc_reranking import doc_reranking
from danswer.agent_search.expanded_retrieval.nodes.doc_retrieval import doc_retrieval
from danswer.agent_search.expanded_retrieval.nodes.doc_verification import (
doc_verification,
)
from danswer.agent_search.expanded_retrieval.nodes.verification_kickoff import (
verification_kickoff,
)
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalInput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
def expanded_retrieval_graph_builder() -> StateGraph:
graph = StateGraph(
state_schema=ExpandedRetrievalState,
input=ExpandedRetrievalInput,
output=ExpandedRetrievalOutput,
)
### Add nodes ###
graph.add_node(
node="doc_retrieval",
action=doc_retrieval,
)
graph.add_node(
node="verification_kickoff",
action=verification_kickoff,
)
graph.add_node(
node="doc_verification",
action=doc_verification,
)
graph.add_node(
node="doc_reranking",
action=doc_reranking,
)
### Add edges ###
graph.add_conditional_edges(
source=START,
path=parallel_retrieval_edge,
path_map=["doc_retrieval"],
)
graph.add_edge(
start_key="doc_retrieval",
end_key="verification_kickoff",
)
graph.add_edge(
start_key="doc_verification",
end_key="doc_reranking",
)
graph.add_edge(
start_key="doc_reranking",
end_key=END,
)
return graph
if __name__ == "__main__":
from danswer.db.engine import get_session_context_manager
from danswer.llm.factory import get_default_llms
from danswer.context.search.models import SearchRequest
graph = expanded_retrieval_graph_builder()
compiled_graph = graph.compile()
primary_llm, fast_llm = get_default_llms()
search_request = SearchRequest(
query="Who made Excel and what other products did they make?",
)
with get_session_context_manager() as db_session:
inputs = ExpandedRetrievalInput(
search_request=search_request,
primary_llm=primary_llm,
fast_llm=fast_llm,
db_session=db_session,
query_to_answer="Who made Excel?",
)
for thing in compiled_graph.stream(inputs, debug=True):
print(thing)

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from danswer.agent_search.expanded_retrieval.states import DocRerankingOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
def doc_reranking(state: ExpandedRetrievalState) -> DocRerankingOutput:
print(f"doc_reranking state: {state.keys()}")
verified_documents = state["verified_documents"]
reranked_documents = verified_documents
return DocRerankingOutput(reranked_documents=reranked_documents)

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from danswer.agent_search.expanded_retrieval.states import DocRetrievalOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
from danswer.context.search.models import InferenceSection
from danswer.context.search.models import SearchRequest
from danswer.context.search.pipeline import SearchPipeline
from danswer.db.engine import get_session_context_manager
class RetrieveInput(ExpandedRetrievalState):
query_to_retrieve: str
def doc_retrieval(state: RetrieveInput) -> DocRetrievalOutput:
# def doc_retrieval(state: RetrieveInput) -> Command[Literal["doc_verification"]]:
"""
Retrieve documents
Args:
state (dict): The current graph state
Returns:
state (dict): New key added to state, documents, that contains retrieved documents
"""
print(f"doc_retrieval state: {state.keys()}")
state["query_to_retrieve"]
documents: list[InferenceSection] = []
llm = state["primary_llm"]
fast_llm = state["fast_llm"]
# db_session = state["db_session"]
query_to_retrieve = state["search_request"].query
with get_session_context_manager() as db_session1:
documents = SearchPipeline(
search_request=SearchRequest(
query=query_to_retrieve,
),
user=None,
llm=llm,
fast_llm=fast_llm,
db_session=db_session1,
).reranked_sections
print(f"retrieved documents: {len(documents)}")
return DocRetrievalOutput(
retrieved_documents=documents,
)

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from langchain_core.messages import HumanMessage
from langchain_core.messages import merge_message_runs
from danswer.agent_search.expanded_retrieval.states import DocVerificationOutput
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
from danswer.agent_search.shared_graph_utils.models import BinaryDecision
from danswer.agent_search.shared_graph_utils.prompts import VERIFIER_PROMPT
from danswer.context.search.models import InferenceSection
class DocVerificationInput(ExpandedRetrievalState, total=True):
doc_to_verify: InferenceSection
def doc_verification(state: DocVerificationInput) -> DocVerificationOutput:
"""
Check whether the document is relevant for the original user question
Args:
state (VerifierState): The current state
Returns:
dict: ict: The updated state with the final decision
"""
print(f"doc_verification state: {state.keys()}")
original_query = state["search_request"].query
doc_to_verify = state["doc_to_verify"]
document_content = doc_to_verify.combined_content
msg = [
HumanMessage(
content=VERIFIER_PROMPT.format(
question=original_query, document_content=document_content
)
)
]
fast_llm = state["fast_llm"]
response = list(
fast_llm.stream(
prompt=msg,
)
)
response_string = merge_message_runs(response, chunk_separator="")[0].content
# Convert string response to proper dictionary format
decision_dict = {"decision": response_string.lower()}
formatted_response = BinaryDecision.model_validate(decision_dict)
print(f"Verdict: {formatted_response.decision}")
verified_documents = []
if formatted_response.decision == "yes":
verified_documents.append(doc_to_verify)
return DocVerificationOutput(
verified_documents=verified_documents,
)

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from typing import Literal
from langgraph.types import Command
from langgraph.types import Send
from danswer.agent_search.expanded_retrieval.nodes.doc_verification import (
DocVerificationInput,
)
from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
def verification_kickoff(
state: ExpandedRetrievalState,
) -> Command[Literal["doc_verification"]]:
print(f"verification_kickoff state: {state.keys()}")
documents = state["retrieved_documents"]
return Command(
update={},
goto=[
Send(
node="doc_verification",
arg=DocVerificationInput(doc_to_verify=doc, **state),
)
for doc in documents
],
)

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