mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-05-22 13:55:12 +02:00
Merge pull request #327 from trustgraph-ai/release/v0.21
0.21 to master
This commit is contained in:
cybermaggedon
GitHub
commit
6ceb926b69
238 changed files with 7339 additions and 2268 deletions
95
.github/workflows/release.yaml
vendored
95
.github/workflows/release.yaml
vendored
|
|
@ -5,17 +5,17 @@ on:
|
|||
workflow_dispatch:
|
||||
push:
|
||||
tags:
|
||||
- v0.18.*
|
||||
- v*
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
|
||||
deploy:
|
||||
python-packages:
|
||||
|
||||
name: Build everything
|
||||
runs-on: ubuntu-latest
|
||||
name: Release Python packages
|
||||
runs-on: ubuntu-24.04
|
||||
permissions:
|
||||
contents: write
|
||||
id-token: write
|
||||
|
|
@ -25,50 +25,73 @@ jobs:
|
|||
steps:
|
||||
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v3
|
||||
|
||||
- name: Log in to Docker Hub
|
||||
uses: docker/login-action@f4ef78c080cd8ba55a85445d5b36e214a81df20a
|
||||
with:
|
||||
username: ${{ vars.DOCKER_USERNAME }}
|
||||
password: ${{ secrets.DOCKER_SECRET }}
|
||||
|
||||
- name: Install build dependencies
|
||||
run: pip3 install jsonnet
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Get version
|
||||
id: version
|
||||
run: echo VERSION=$(git describe --exact-match --tags | sed 's/^v//') >> $GITHUB_OUTPUT
|
||||
|
||||
- run: echo ${{ steps.version.outputs.VERSION }}
|
||||
|
||||
- name: Build packages
|
||||
run: make packages VERSION=${{ steps.version.outputs.VERSION }}
|
||||
|
||||
- name: Publish release distributions to PyPI
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
|
||||
- name: Extract metadata for container
|
||||
id: meta
|
||||
uses: docker/metadata-action@v4
|
||||
with:
|
||||
images: trustgraph/trustgraph-flow
|
||||
tags: |
|
||||
type=ref,event=branch
|
||||
type=ref,event=pr
|
||||
type=semver,pattern={{version}}
|
||||
type=semver,pattern={{major}}.{{minor}}
|
||||
type=sha
|
||||
deploy-container-image:
|
||||
|
||||
- name: Build and push Docker image
|
||||
id: push
|
||||
uses: docker/build-push-action@3b5e8027fcad23fda98b2e3ac259d8d67585f671
|
||||
with:
|
||||
context: .
|
||||
file: ./Containerfile
|
||||
push: true
|
||||
tags: ${{ steps.meta.outputs.tags }}
|
||||
labels: ${{ steps.meta.outputs.labels }}
|
||||
name: Release container image
|
||||
runs-on: ubuntu-24.04
|
||||
permissions:
|
||||
contents: write
|
||||
id-token: write
|
||||
environment:
|
||||
name: release
|
||||
|
||||
steps:
|
||||
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Docker Hub token
|
||||
run: echo ${{ secrets.DOCKER_SECRET }} > docker-token.txt
|
||||
|
||||
- name: Authenticate with Docker hub
|
||||
run: make docker-hub-login
|
||||
|
||||
- name: Get version
|
||||
id: version
|
||||
run: echo VERSION=$(git describe --exact-match --tags | sed 's/^v//') >> $GITHUB_OUTPUT
|
||||
|
||||
- name: Put version into package manifests
|
||||
run: make update-package-versions VERSION=${{ steps.version.outputs.VERSION }}
|
||||
|
||||
- name: Build containers
|
||||
run: make container VERSION=${{ steps.version.outputs.VERSION }}
|
||||
|
||||
- name: Push containers
|
||||
run: make push VERSION=${{ steps.version.outputs.VERSION }}
|
||||
|
||||
release-bundle:
|
||||
|
||||
name: Upload release bundle
|
||||
runs-on: ubuntu-24.04
|
||||
permissions:
|
||||
contents: write
|
||||
id-token: write
|
||||
environment:
|
||||
name: release
|
||||
|
||||
steps:
|
||||
|
||||
- name: Checkout
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Install build dependencies
|
||||
run: pip3 install jsonnet
|
||||
|
||||
- name: Get version
|
||||
id: version
|
||||
run: echo VERSION=$(git describe --exact-match --tags | sed 's/^v//') >> $GITHUB_OUTPUT
|
||||
|
||||
- name: Create deploy bundle
|
||||
run: templates/generate-all deploy.zip ${{ steps.version.outputs.VERSION }}
|
||||
|
|
|
|||
1
.gitignore
vendored
1
.gitignore
vendored
|
|
@ -9,6 +9,7 @@ trustgraph-base/trustgraph/base_version.py
|
|||
trustgraph-bedrock/trustgraph/bedrock_version.py
|
||||
trustgraph-embeddings-hf/trustgraph/embeddings_hf_version.py
|
||||
trustgraph-flow/trustgraph/flow_version.py
|
||||
trustgraph-ocr/trustgraph/ocr_version.py
|
||||
trustgraph-parquet/trustgraph/parquet_version.py
|
||||
trustgraph-vertexai/trustgraph/vertexai_version.py
|
||||
trustgraph-cli/trustgraph/
|
||||
|
|
|
|||
|
|
@ -11,15 +11,26 @@ ENV PIP_BREAK_SYSTEM_PACKAGES=1
|
|||
RUN dnf install -y python3 python3-pip python3-wheel python3-aiohttp \
|
||||
python3-rdflib
|
||||
|
||||
RUN pip3 install torch --index-url https://download.pytorch.org/whl/cpu
|
||||
RUN pip3 install torch==2.5.1+cpu \
|
||||
--index-url https://download.pytorch.org/whl/cpu
|
||||
|
||||
RUN pip3 install anthropic boto3 cohere openai google-cloud-aiplatform ollama google-generativeai \
|
||||
langchain langchain-core langchain-huggingface langchain-text-splitters \
|
||||
langchain-community pymilvus sentence-transformers transformers \
|
||||
huggingface-hub pulsar-client cassandra-driver pyyaml \
|
||||
RUN pip3 install \
|
||||
anthropic boto3 cohere mistralai openai google-cloud-aiplatform \
|
||||
ollama google-generativeai \
|
||||
langchain==0.3.13 langchain-core==0.3.28 langchain-huggingface==0.1.2 \
|
||||
langchain-text-splitters==0.3.4 \
|
||||
langchain-community==0.3.13 \
|
||||
sentence-transformers==3.4.0 transformers==4.47.1 \
|
||||
huggingface-hub==0.27.0 \
|
||||
pymilvus \
|
||||
pulsar-client==3.5.0 cassandra-driver pyyaml \
|
||||
neo4j tiktoken falkordb && \
|
||||
pip3 cache purge
|
||||
|
||||
# Most commonly used embeddings model, just build it into the container
|
||||
# image
|
||||
RUN huggingface-cli download sentence-transformers/all-MiniLM-L6-v2
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build a container which contains the built Python packages. The build
|
||||
# creates a bunch of left-over cruft, a separate phase means this is only
|
||||
|
|
@ -34,6 +45,7 @@ COPY trustgraph-vertexai/ /root/build/trustgraph-vertexai/
|
|||
COPY trustgraph-bedrock/ /root/build/trustgraph-bedrock/
|
||||
COPY trustgraph-embeddings-hf/ /root/build/trustgraph-embeddings-hf/
|
||||
COPY trustgraph-cli/ /root/build/trustgraph-cli/
|
||||
COPY trustgraph-ocr/ /root/build/trustgraph-ocr/
|
||||
|
||||
WORKDIR /root/build/
|
||||
|
||||
|
|
@ -43,6 +55,7 @@ RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-vertexai/
|
|||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-bedrock/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-embeddings-hf/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-cli/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-ocr/
|
||||
|
||||
RUN ls /root/wheels
|
||||
|
||||
|
|
@ -61,6 +74,7 @@ RUN \
|
|||
pip3 install /root/wheels/trustgraph_bedrock-* && \
|
||||
pip3 install /root/wheels/trustgraph_embeddings_hf-* && \
|
||||
pip3 install /root/wheels/trustgraph_cli-* && \
|
||||
pip3 install /root/wheels/trustgraph_ocr-* && \
|
||||
pip3 cache purge && \
|
||||
rm -rf /root/wheels
|
||||
|
||||
|
|
|
|||
38
Makefile
38
Makefile
|
|
@ -16,6 +16,7 @@ wheels:
|
|||
pip3 wheel --no-deps --wheel-dir dist trustgraph-bedrock/
|
||||
pip3 wheel --no-deps --wheel-dir dist trustgraph-embeddings-hf/
|
||||
pip3 wheel --no-deps --wheel-dir dist trustgraph-cli/
|
||||
pip3 wheel --no-deps --wheel-dir dist trustgraph-ocr/
|
||||
|
||||
packages: update-package-versions
|
||||
rm -rf dist/
|
||||
|
|
@ -26,11 +27,12 @@ packages: update-package-versions
|
|||
cd trustgraph-bedrock && python3 setup.py sdist --dist-dir ../dist/
|
||||
cd trustgraph-embeddings-hf && python3 setup.py sdist --dist-dir ../dist/
|
||||
cd trustgraph-cli && python3 setup.py sdist --dist-dir ../dist/
|
||||
cd trustgraph-ocr && python3 setup.py sdist --dist-dir ../dist/
|
||||
|
||||
pypi-upload:
|
||||
twine upload dist/*-${VERSION}.*
|
||||
|
||||
CONTAINER=docker.io/trustgraph/trustgraph-flow
|
||||
CONTAINER_BASE=docker.io/trustgraph
|
||||
|
||||
update-package-versions:
|
||||
mkdir -p trustgraph-cli/trustgraph
|
||||
|
|
@ -41,14 +43,34 @@ update-package-versions:
|
|||
echo __version__ = \"${VERSION}\" > trustgraph-bedrock/trustgraph/bedrock_version.py
|
||||
echo __version__ = \"${VERSION}\" > trustgraph-embeddings-hf/trustgraph/embeddings_hf_version.py
|
||||
echo __version__ = \"${VERSION}\" > trustgraph-cli/trustgraph/cli_version.py
|
||||
echo __version__ = \"${VERSION}\" > trustgraph-ocr/trustgraph/ocr_version.py
|
||||
echo __version__ = \"${VERSION}\" > trustgraph/trustgraph/trustgraph_version.py
|
||||
|
||||
container: update-package-versions
|
||||
${DOCKER} build -f Containerfile -t ${CONTAINER}:${VERSION} \
|
||||
--format docker
|
||||
${DOCKER} build -f containers/Containerfile.base \
|
||||
-t ${CONTAINER_BASE}/trustgraph-base:${VERSION} .
|
||||
${DOCKER} build -f containers/Containerfile.flow \
|
||||
-t ${CONTAINER_BASE}/trustgraph-flow:${VERSION} .
|
||||
${DOCKER} build -f containers/Containerfile.bedrock \
|
||||
-t ${CONTAINER_BASE}/trustgraph-bedrock:${VERSION} .
|
||||
${DOCKER} build -f containers/Containerfile.vertexai \
|
||||
-t ${CONTAINER_BASE}/trustgraph-vertexai:${VERSION} .
|
||||
${DOCKER} build -f containers/Containerfile.hf \
|
||||
-t ${CONTAINER_BASE}/trustgraph-hf:${VERSION} .
|
||||
${DOCKER} build -f containers/Containerfile.ocr \
|
||||
-t ${CONTAINER_BASE}/trustgraph-ocr:${VERSION} .
|
||||
|
||||
container.ocr:
|
||||
${DOCKER} build -f containers/Containerfile.ocr \
|
||||
-t ${CONTAINER_BASE}/trustgraph-ocr:${VERSION} .
|
||||
|
||||
push:
|
||||
${DOCKER} push ${CONTAINER}:${VERSION}
|
||||
${DOCKER} push ${CONTAINER_BASE}/trustgraph-base:${VERSION}
|
||||
${DOCKER} push ${CONTAINER_BASE}/trustgraph-flow:${VERSION}
|
||||
${DOCKER} push ${CONTAINER_BASE}/trustgraph-bedrock:${VERSION}
|
||||
${DOCKER} push ${CONTAINER_BASE}/trustgraph-vertexai:${VERSION}
|
||||
${DOCKER} push ${CONTAINER_BASE}/trustgraph-hf:${VERSION}
|
||||
${DOCKER} push ${CONTAINER_BASE}/trustgraph-ocr:${VERSION}
|
||||
|
||||
clean:
|
||||
rm -rf wheels/
|
||||
|
|
@ -56,13 +78,13 @@ clean:
|
|||
set-version:
|
||||
echo '"${VERSION}"' > templates/values/version.jsonnet
|
||||
|
||||
TEMPLATES=azure bedrock claude cohere mix llamafile ollama openai vertexai \
|
||||
TEMPLATES=azure bedrock claude cohere mix llamafile mistral ollama openai vertexai \
|
||||
openai-neo4j storage
|
||||
|
||||
DCS=$(foreach template,${TEMPLATES},${template:%=tg-launch-%.yaml})
|
||||
|
||||
MODELS=azure bedrock claude cohere llamafile ollama openai vertexai
|
||||
GRAPHS=cassandra neo4j falkordb
|
||||
MODELS=azure bedrock claude cohere llamafile mistral ollama openai vertexai
|
||||
GRAPHS=cassandra neo4j falkordb memgraph
|
||||
|
||||
# tg-launch-%.yaml: templates/%.jsonnet templates/components/version.jsonnet
|
||||
# jsonnet -Jtemplates \
|
||||
|
|
@ -104,5 +126,5 @@ update-dcs: set-version
|
|||
|
||||
docker-hub-login:
|
||||
cat docker-token.txt | \
|
||||
docker login -u trustgraph --password-stdin registry-1.docker.io
|
||||
${DOCKER} login -u trustgraph --password-stdin registry-1.docker.io
|
||||
|
||||
|
|
|
|||
48
containers/Containerfile.base
Normal file
48
containers/Containerfile.base
Normal file
|
|
@ -0,0 +1,48 @@
|
|||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build an AI container. This does the torch install which is huge, and I
|
||||
# like to avoid re-doing this.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM docker.io/fedora:40 AS base
|
||||
|
||||
ENV PIP_BREAK_SYSTEM_PACKAGES=1
|
||||
|
||||
RUN dnf install -y python3 python3-pip python3-wheel python3-aiohttp && \
|
||||
dnf clean all
|
||||
|
||||
RUN pip3 install --no-cache-dir pulsar-client==3.5.0
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build a container which contains the built Python packages. The build
|
||||
# creates a bunch of left-over cruft, a separate phase means this is only
|
||||
# needed to support package build
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base AS build
|
||||
|
||||
COPY trustgraph-base/ /root/build/trustgraph-base/
|
||||
COPY trustgraph-cli/ /root/build/trustgraph-cli/
|
||||
|
||||
WORKDIR /root/build/
|
||||
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-base/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-cli/
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Finally, the target container. Start with base and add the package.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base
|
||||
|
||||
COPY --from=build /root/wheels /root/wheels
|
||||
|
||||
RUN \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_base-* && \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_cli-* && \
|
||||
rm -rf /root/wheels
|
||||
|
||||
WORKDIR /
|
||||
|
||||
|
||||
|
||||
48
containers/Containerfile.bedrock
Normal file
48
containers/Containerfile.bedrock
Normal file
|
|
@ -0,0 +1,48 @@
|
|||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build an AI container. This does the torch install which is huge, and I
|
||||
# like to avoid re-doing this.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM docker.io/fedora:40 AS base
|
||||
|
||||
ENV PIP_BREAK_SYSTEM_PACKAGES=1
|
||||
|
||||
RUN dnf install -y python3 python3-pip python3-wheel python3-aiohttp \
|
||||
python3-rdflib
|
||||
|
||||
RUN pip3 install --no-cache-dir boto3 pulsar-client==3.5.0
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build a container which contains the built Python packages. The build
|
||||
# creates a bunch of left-over cruft, a separate phase means this is only
|
||||
# needed to support package build
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base AS build
|
||||
|
||||
COPY trustgraph-base/ /root/build/trustgraph-base/
|
||||
COPY trustgraph-bedrock/ /root/build/trustgraph-bedrock/
|
||||
|
||||
WORKDIR /root/build/
|
||||
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-base/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-bedrock/
|
||||
|
||||
RUN ls /root/wheels
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Finally, the target container. Start with base and add the package.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base
|
||||
|
||||
COPY --from=build /root/wheels /root/wheels
|
||||
|
||||
RUN \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_base-* && \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_bedrock-* && \
|
||||
rm -rf /root/wheels
|
||||
|
||||
WORKDIR /
|
||||
|
||||
60
containers/Containerfile.flow
Normal file
60
containers/Containerfile.flow
Normal file
|
|
@ -0,0 +1,60 @@
|
|||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build an AI container. This does the torch install which is huge, and I
|
||||
# like to avoid re-doing this.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM docker.io/fedora:40 AS base
|
||||
|
||||
ENV PIP_BREAK_SYSTEM_PACKAGES=1
|
||||
|
||||
RUN dnf install -y python3 python3-pip python3-wheel python3-aiohttp \
|
||||
python3-rdflib
|
||||
|
||||
RUN pip3 install --no-cache-dir \
|
||||
anthropic cohere mistralai openai google-generativeai \
|
||||
ollama \
|
||||
langchain==0.3.13 langchain-core==0.3.28 \
|
||||
langchain-text-splitters==0.3.4 \
|
||||
langchain-community==0.3.13 \
|
||||
pymilvus \
|
||||
pulsar-client==3.5.0 cassandra-driver pyyaml \
|
||||
neo4j tiktoken falkordb && \
|
||||
pip3 cache purge
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build a container which contains the built Python packages. The build
|
||||
# creates a bunch of left-over cruft, a separate phase means this is only
|
||||
# needed to support package build
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base AS build
|
||||
|
||||
COPY trustgraph-base/ /root/build/trustgraph-base/
|
||||
COPY trustgraph-flow/ /root/build/trustgraph-flow/
|
||||
COPY trustgraph-cli/ /root/build/trustgraph-cli/
|
||||
|
||||
WORKDIR /root/build/
|
||||
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-base/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-flow/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-cli/
|
||||
|
||||
RUN ls /root/wheels
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Finally, the target container. Start with base and add the package.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base
|
||||
|
||||
COPY --from=build /root/wheels /root/wheels
|
||||
|
||||
RUN \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_base-* && \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_flow-* && \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_cli-* && \
|
||||
rm -rf /root/wheels
|
||||
|
||||
WORKDIR /
|
||||
|
||||
75
containers/Containerfile.hf
Normal file
75
containers/Containerfile.hf
Normal file
|
|
@ -0,0 +1,75 @@
|
|||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build an AI container. This does the torch install which is huge, and I
|
||||
# like to avoid re-doing this.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM docker.io/fedora:40 AS ai
|
||||
|
||||
ENV PIP_BREAK_SYSTEM_PACKAGES=1
|
||||
|
||||
RUN dnf install -y python3 python3-pip python3-wheel python3-aiohttp \
|
||||
python3-rdflib
|
||||
|
||||
RUN pip3 install torch==2.5.1+cpu \
|
||||
--index-url https://download.pytorch.org/whl/cpu
|
||||
|
||||
RUN pip3 install --no-cache-dir \
|
||||
langchain==0.3.13 langchain-core==0.3.28 langchain-huggingface==0.1.2 \
|
||||
langchain-community==0.3.13 \
|
||||
sentence-transformers==3.4.0 transformers==4.47.1 \
|
||||
huggingface-hub==0.27.0 \
|
||||
pulsar-client==3.5.0
|
||||
|
||||
# Most commonly used embeddings model, just build it into the container
|
||||
# image
|
||||
RUN huggingface-cli download sentence-transformers/all-MiniLM-L6-v2
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build a container which contains the built Python packages. The build
|
||||
# creates a bunch of left-over cruft, a separate phase means this is only
|
||||
# needed to support package build
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM ai AS build
|
||||
|
||||
COPY trustgraph-base/ /root/build/trustgraph-base/
|
||||
COPY trustgraph-flow/ /root/build/trustgraph-flow/
|
||||
COPY trustgraph-vertexai/ /root/build/trustgraph-vertexai/
|
||||
COPY trustgraph-bedrock/ /root/build/trustgraph-bedrock/
|
||||
COPY trustgraph-embeddings-hf/ /root/build/trustgraph-embeddings-hf/
|
||||
COPY trustgraph-cli/ /root/build/trustgraph-cli/
|
||||
|
||||
WORKDIR /root/build/
|
||||
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-base/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-flow/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-vertexai/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-bedrock/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-embeddings-hf/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-cli/
|
||||
|
||||
RUN ls /root/wheels
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Finally, the target container. Start with base and add the package.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM ai
|
||||
|
||||
COPY --from=build /root/wheels /root/wheels
|
||||
|
||||
RUN \
|
||||
pip3 install /root/wheels/trustgraph_base-* && \
|
||||
pip3 install /root/wheels/trustgraph_flow-* && \
|
||||
pip3 install /root/wheels/trustgraph_vertexai-* && \
|
||||
pip3 install /root/wheels/trustgraph_bedrock-* && \
|
||||
pip3 install /root/wheels/trustgraph_embeddings_hf-* && \
|
||||
pip3 install /root/wheels/trustgraph_cli-* && \
|
||||
pip3 cache purge && \
|
||||
rm -rf /root/wheels
|
||||
|
||||
WORKDIR /
|
||||
|
||||
CMD sleep 1000000
|
||||
|
||||
48
containers/Containerfile.ocr
Normal file
48
containers/Containerfile.ocr
Normal file
|
|
@ -0,0 +1,48 @@
|
|||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build an AI container. This does the torch install which is huge, and I
|
||||
# like to avoid re-doing this.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM docker.io/fedora:40 AS base
|
||||
|
||||
ENV PIP_BREAK_SYSTEM_PACKAGES=1
|
||||
|
||||
RUN dnf install -y python3 python3-pip python3-wheel python3-aiohttp \
|
||||
python3-rdflib tesseract poppler poppler-utils
|
||||
|
||||
RUN pip3 install --no-cache-dir pytesseract pulsar-client==3.5.0
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build a container which contains the built Python packages. The build
|
||||
# creates a bunch of left-over cruft, a separate phase means this is only
|
||||
# needed to support package build
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base AS build
|
||||
|
||||
COPY trustgraph-base/ /root/build/trustgraph-base/
|
||||
COPY trustgraph-ocr/ /root/build/trustgraph-ocr/
|
||||
|
||||
WORKDIR /root/build/
|
||||
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-base/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-ocr/
|
||||
|
||||
RUN ls /root/wheels
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Finally, the target container. Start with base and add the package.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base
|
||||
|
||||
COPY --from=build /root/wheels /root/wheels
|
||||
|
||||
RUN \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_base-* && \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_ocr-* && \
|
||||
rm -rf /root/wheels
|
||||
|
||||
WORKDIR /
|
||||
|
||||
51
containers/Containerfile.vertexai
Normal file
51
containers/Containerfile.vertexai
Normal file
|
|
@ -0,0 +1,51 @@
|
|||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build an AI container. This does the torch install which is huge, and I
|
||||
# like to avoid re-doing this.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM docker.io/fedora:40 AS base
|
||||
|
||||
ENV PIP_BREAK_SYSTEM_PACKAGES=1
|
||||
|
||||
RUN dnf install -y python3 python3-pip python3-wheel python3-aiohttp \
|
||||
python3-rdflib
|
||||
|
||||
RUN pip3 install --no-cache-dir \
|
||||
google-cloud-aiplatform pulsar-client==3.5.0
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Build a container which contains the built Python packages. The build
|
||||
# creates a bunch of left-over cruft, a separate phase means this is only
|
||||
# needed to support package build
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base AS build
|
||||
|
||||
COPY trustgraph-base/ /root/build/trustgraph-base/
|
||||
COPY trustgraph-vertexai/ /root/build/trustgraph-vertexai/
|
||||
|
||||
WORKDIR /root/build/
|
||||
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-base/
|
||||
RUN pip3 wheel -w /root/wheels/ --no-deps ./trustgraph-vertexai/
|
||||
|
||||
RUN ls /root/wheels
|
||||
|
||||
# ----------------------------------------------------------------------------
|
||||
# Finally, the target container. Start with base and add the package.
|
||||
# ----------------------------------------------------------------------------
|
||||
|
||||
FROM base
|
||||
|
||||
COPY --from=build /root/wheels /root/wheels
|
||||
|
||||
RUN \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_base-* && \
|
||||
pip3 install --no-cache-dir /root/wheels/trustgraph_vertexai-* && \
|
||||
rm -rf /root/wheels
|
||||
|
||||
WORKDIR /
|
||||
|
||||
|
||||
|
||||
|
|
@ -113,8 +113,9 @@ Choose one of the `Docker Compose` files that meets your preferred model and gra
|
|||
### AWS Bedrock API
|
||||
|
||||
```
|
||||
export AWS_ID_KEY=<ID-KEY-HERE>
|
||||
export AWS_SECRET_KEY=<TOKEN-GOES-HERE>
|
||||
export AWS_ACCESS_KEY_ID=<ID-KEY-HERE>
|
||||
export AWS_SECRET_ACCESS_KEY=<TOKEN-GOES-HERE>
|
||||
export AWS_DEFAULT_REGION=<REGION-HERE>
|
||||
docker compose -f tg-launch-bedrock-cassandra.yaml up -d # Using Cassandra as the graph store
|
||||
docker compose -f tg-launch-bedrock-neo4j.yaml up -d # Using Neo4j as the graph store
|
||||
```
|
||||
|
|
|
|||
|
|
@ -577,7 +577,7 @@
|
|||
"disableTextWrap": false,
|
||||
"editorMode": "builder",
|
||||
"exemplar": false,
|
||||
"expr": "increase(processing_count_total{status!=\"success\"}[$__rate_interval])",
|
||||
"expr": "sum by(job) (increase(rate_limit_count_total[$__rate_interval]))",
|
||||
"format": "time_series",
|
||||
"fullMetaSearch": false,
|
||||
"includeNullMetadata": true,
|
||||
|
|
@ -588,7 +588,7 @@
|
|||
"useBackend": false
|
||||
}
|
||||
],
|
||||
"title": "Errors",
|
||||
"title": "Rate limit events",
|
||||
"type": "timeseries"
|
||||
},
|
||||
{
|
||||
|
|
|
|||
|
|
@ -20,6 +20,18 @@ scrape_configs:
|
|||
- targets:
|
||||
- 'pulsar:8080'
|
||||
|
||||
- job_name: 'bookie'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
- targets:
|
||||
- 'bookie:8000'
|
||||
|
||||
- job_name: 'zookeeper'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
- targets:
|
||||
- 'zookeeper:8000'
|
||||
|
||||
- job_name: 'pdf-decoder'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
|
|
@ -32,11 +44,17 @@ scrape_configs:
|
|||
- targets:
|
||||
- 'chunker:8000'
|
||||
|
||||
- job_name: 'vectorize'
|
||||
- job_name: 'document-embeddings'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
- targets:
|
||||
- 'vectorize:8000'
|
||||
- 'document-embeddings:8000'
|
||||
|
||||
- job_name: 'graph-embeddings'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
- targets:
|
||||
- 'graph-embeddings:8000'
|
||||
|
||||
- job_name: 'embeddings'
|
||||
scrape_interval: 5s
|
||||
|
|
@ -74,6 +92,12 @@ scrape_configs:
|
|||
- targets:
|
||||
- 'metering-rag:8000'
|
||||
|
||||
- job_name: 'store-doc-embeddings'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
- targets:
|
||||
- 'store-doc-embeddings:8000'
|
||||
|
||||
- job_name: 'store-graph-embeddings'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
|
|
@ -104,6 +128,12 @@ scrape_configs:
|
|||
- targets:
|
||||
- 'graph-rag:8000'
|
||||
|
||||
- job_name: 'document-rag'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
- targets:
|
||||
- 'document-rag:8000'
|
||||
|
||||
- job_name: 'prompt'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
|
|
@ -122,6 +152,12 @@ scrape_configs:
|
|||
- targets:
|
||||
- 'query-graph-embeddings:8000'
|
||||
|
||||
- job_name: 'query-doc-embeddings'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
- targets:
|
||||
- 'query-doc-embeddings:8000'
|
||||
|
||||
- job_name: 'query-triples'
|
||||
scrape_interval: 5s
|
||||
static_configs:
|
||||
|
|
@ -145,3 +181,7 @@ scrape_configs:
|
|||
static_configs:
|
||||
- targets:
|
||||
- 'workbench-ui:8000'
|
||||
|
||||
# Cassandra
|
||||
# qdrant
|
||||
|
||||
|
|
|
|||
|
|
@ -13,6 +13,7 @@
|
|||
import "patterns/llm-claude.jsonnet",
|
||||
import "patterns/llm-cohere.jsonnet",
|
||||
import "patterns/llm-llamafile.jsonnet",
|
||||
import "patterns/llm-mistral.jsonnet",
|
||||
import "patterns/llm-ollama.jsonnet",
|
||||
import "patterns/llm-openai.jsonnet",
|
||||
import "patterns/llm-vertexai.jsonnet",
|
||||
|
|
|
|||
|
|
@ -1,47 +1,80 @@
|
|||
{
|
||||
|
||||
// Essentials
|
||||
"trustgraph-base": import "components/trustgraph.jsonnet",
|
||||
"pulsar": import "components/pulsar.jsonnet",
|
||||
|
||||
// LLMs
|
||||
"azure": import "components/azure.jsonnet",
|
||||
"azure-openai": import "components/azure-openai.jsonnet",
|
||||
"bedrock": import "components/bedrock.jsonnet",
|
||||
"claude": import "components/claude.jsonnet",
|
||||
"cohere": import "components/cohere.jsonnet",
|
||||
"document-rag": import "components/document-rag.jsonnet",
|
||||
"embeddings-hf": import "components/embeddings-hf.jsonnet",
|
||||
"embeddings-ollama": import "components/embeddings-ollama.jsonnet",
|
||||
"googleaistudio": import "components/googleaistudio.jsonnet",
|
||||
"grafana": import "components/grafana.jsonnet",
|
||||
"mistral": import "components/mistral.jsonnet",
|
||||
"ollama": import "components/ollama.jsonnet",
|
||||
"openai": import "components/openai.jsonnet",
|
||||
"vertexai": import "components/vertexai.jsonnet",
|
||||
|
||||
// LLMs for RAG
|
||||
"azure-rag": import "components/azure-rag.jsonnet",
|
||||
"azure-openai-rag": import "components/azure-openai-rag.jsonnet",
|
||||
"bedrock-rag": import "components/bedrock-rag.jsonnet",
|
||||
"claude-rag": import "components/claude-rag.jsonnet",
|
||||
"cohere-rag": import "components/cohere-rag.jsonnet",
|
||||
"googleaistudio-rag": import "components/googleaistudio-rag.jsonnet",
|
||||
"mistral-rag": import "components/mistral-rag.jsonnet",
|
||||
"ollama-rag": import "components/ollama-rag.jsonnet",
|
||||
"openai-rag": import "components/openai-rag.jsonnet",
|
||||
"vertexai-rag": import "components/vertexai-rag.jsonnet",
|
||||
|
||||
// Embeddings
|
||||
"embeddings-ollama": import "components/embeddings-ollama.jsonnet",
|
||||
"embeddings-hf": import "components/embeddings-hf.jsonnet",
|
||||
"embeddings-fastembed": import "components/embeddings-fastembed.jsonnet",
|
||||
|
||||
// Processing pipelines
|
||||
"graph-rag": import "components/graph-rag.jsonnet",
|
||||
"document-rag": import "components/document-rag.jsonnet",
|
||||
|
||||
// OCR options
|
||||
"ocr": import "components/ocr.jsonnet",
|
||||
"mistral-ocr": import "components/mistral-ocr.jsonnet",
|
||||
|
||||
// Librarian - document management
|
||||
"librarian": import "components/librarian.jsonnet",
|
||||
|
||||
// Vector stores
|
||||
"vector-store-milvus": import "components/milvus.jsonnet",
|
||||
"vector-store-qdrant": import "components/qdrant.jsonnet",
|
||||
"vector-store-pinecone": import "components/pinecone.jsonnet",
|
||||
|
||||
// Triples stores
|
||||
"triple-store-cassandra": import "components/cassandra.jsonnet",
|
||||
"triple-store-neo4j": import "components/neo4j.jsonnet",
|
||||
"triple-store-falkordb": import "components/falkordb.jsonnet",
|
||||
"triple-store-memgraph": import "components/memgraph.jsonnet",
|
||||
|
||||
// Observability support
|
||||
"grafana": import "components/grafana.jsonnet",
|
||||
|
||||
// Pulsar manager is a UI for Pulsar. Uses a LOT of memory
|
||||
"pulsar-manager": import "components/pulsar-manager.jsonnet",
|
||||
|
||||
"llamafile": import "components/llamafile.jsonnet",
|
||||
"ollama": import "components/ollama.jsonnet",
|
||||
"openai": import "components/openai.jsonnet",
|
||||
"override-recursive-chunker": import "components/chunker-recursive.jsonnet",
|
||||
|
||||
// The prompt manager
|
||||
"prompt-template": import "components/prompt-template.jsonnet",
|
||||
"prompt-overrides": import "components/prompt-overrides.jsonnet",
|
||||
|
||||
"pulsar": import "components/pulsar.jsonnet",
|
||||
"pulsar-manager": import "components/pulsar-manager.jsonnet",
|
||||
"trustgraph-base": import "components/trustgraph.jsonnet",
|
||||
"vector-store-milvus": import "components/milvus.jsonnet",
|
||||
"vector-store-qdrant": import "components/qdrant.jsonnet",
|
||||
"vector-store-pinecone": import "components/pinecone.jsonnet",
|
||||
"vertexai": import "components/vertexai.jsonnet",
|
||||
"workbench-ui": import "components/workbench-ui.jsonnet",
|
||||
"null": {},
|
||||
|
||||
// ReAct agent
|
||||
"agent-manager-react": import "components/agent-manager-react.jsonnet",
|
||||
|
||||
// FIXME: Dupes
|
||||
"cassandra": import "components/cassandra.jsonnet",
|
||||
"neo4j": import "components/neo4j.jsonnet",
|
||||
"memgraph": import "components/memgraph.jsonnet",
|
||||
"qdrant": import "components/qdrant.jsonnet",
|
||||
"pinecone": import "components/pinecone.jsonnet",
|
||||
"milvus": import "components/milvus.jsonnet",
|
||||
"falkordb": import "components/falkordb.jsonnet",
|
||||
"trustgraph": import "components/trustgraph.jsonnet",
|
||||
// Optional UI
|
||||
"workbench-ui": import "components/workbench-ui.jsonnet",
|
||||
|
||||
// Does nothing. But, can be a hack to overwrite parameters
|
||||
"null": {},
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -14,11 +14,15 @@ local default_prompts = import "prompts/default-prompts.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("agent-manager")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"agent-manager-react",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"--prompt-request-queue",
|
||||
"non-persistent://tg/request/prompt-rag",
|
||||
"--prompt-response-queue",
|
||||
"non-persistent://tg/response/prompt-rag",
|
||||
"--tool-type",
|
||||
] + [
|
||||
tool.id + "=" + tool.type
|
||||
|
|
|
|||
61
templates/components/azure-openai-rag.jsonnet
Normal file
61
templates/components/azure-openai-rag.jsonnet
Normal file
|
|
@ -0,0 +1,61 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["ollama-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"azure-openai-rag-model":: "GPT-3.5-Turbo",
|
||||
"azure-openai-rag-max-output-tokens":: 4192,
|
||||
"azure-openai-rag-temperature":: 0.0,
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("azure-openai-credentials")
|
||||
.with_env_var("AZURE_TOKEN", "azure-token");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-azure",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["azure-openai-rag-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["azure-openai-rag-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["azure-openai-" + key]:: value,
|
||||
},
|
||||
|
||||
"azure-openai-model":: "GPT-3.5-Turbo",
|
||||
"azure-openai-max-output-tokens":: 4192,
|
||||
"azure-openai-temperature":: 0.0,
|
||||
|
|
@ -18,7 +23,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-azure-openai",
|
||||
"-p",
|
||||
|
|
@ -34,48 +39,18 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-azure",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["azure-openai-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["azure-openai-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
60
templates/components/azure-rag.jsonnet
Normal file
60
templates/components/azure-rag.jsonnet
Normal file
|
|
@ -0,0 +1,60 @@
|
|||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["azure-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"azure-rag-max-output-tokens":: 4096,
|
||||
"azure-rag-temperature":: 0.0,
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("azure-credentials")
|
||||
.with_env_var("AZURE_TOKEN", "azure-token")
|
||||
.with_env_var("AZURE_ENDPOINT", "azure-endpoint");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-azure",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["azure-rag-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["azure-rag-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
}
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -1,10 +1,14 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["azure-" + key]:: value,
|
||||
},
|
||||
|
||||
"azure-max-output-tokens":: 4096,
|
||||
"azure-temperature":: 0.0,
|
||||
|
||||
|
|
@ -18,7 +22,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-azure",
|
||||
"-p",
|
||||
|
|
@ -32,48 +36,18 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-azure",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["azure-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["azure-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
}
|
||||
|
|
|
|||
66
templates/components/bedrock-rag.jsonnet
Normal file
66
templates/components/bedrock-rag.jsonnet
Normal file
|
|
@ -0,0 +1,66 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
local chunker = import "chunker-recursive.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["bedrock-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"bedrock-rag-max-output-tokens":: 4096,
|
||||
"bedrock-rag-temperature":: 0.0,
|
||||
"bedrock-rag-model":: "mistral.mixtral-8x7b-instruct-v0:1",
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("bedrock-credentials")
|
||||
.with_env_var("AWS_ACCESS_KEY_ID", "aws-id-key")
|
||||
.with_env_var("AWS_SECRET_ACCESS_KEY", "aws-secret")
|
||||
.with_env_var("AWS_DEFAULT_REGION", "aws-region");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_bedrock)
|
||||
.with_command([
|
||||
"text-completion-bedrock",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["bedrock-rag-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["bedrock-rag-temperature"],
|
||||
"-m",
|
||||
$["bedrock-rag-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts + chunker
|
||||
|
||||
|
|
@ -6,6 +6,11 @@ local chunker = import "chunker-recursive.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["bedrock-" + key]:: value,
|
||||
},
|
||||
|
||||
"bedrock-max-output-tokens":: 4096,
|
||||
"bedrock-temperature":: 0.0,
|
||||
"bedrock-model":: "mistral.mixtral-8x7b-instruct-v0:1",
|
||||
|
|
@ -15,13 +20,13 @@ local chunker = import "chunker-recursive.jsonnet";
|
|||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("bedrock-credentials")
|
||||
.with_env_var("AWS_ID_KEY", "aws-id-key")
|
||||
.with_env_var("AWS_SECRET", "aws-secret")
|
||||
.with_env_var("AWS_REGION", "aws-region");
|
||||
.with_env_var("AWS_ACCESS_KEY_ID", "aws-id-key")
|
||||
.with_env_var("AWS_SECRET_ACCESS_KEY", "aws-secret")
|
||||
.with_env_var("AWS_DEFAULT_REGION", "aws-region");
|
||||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_bedrock)
|
||||
.with_command([
|
||||
"text-completion-bedrock",
|
||||
"-p",
|
||||
|
|
@ -37,50 +42,18 @@ local chunker = import "chunker-recursive.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-bedrock",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["bedrock-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["bedrock-temperature"],
|
||||
"-m",
|
||||
$["bedrock-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ cassandra + {
|
|||
|
||||
local container =
|
||||
engine.container("store-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-write-cassandra",
|
||||
"-p",
|
||||
|
|
@ -44,7 +44,7 @@ cassandra + {
|
|||
|
||||
local container =
|
||||
engine.container("query-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-query-cassandra",
|
||||
"-p",
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("chunker")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"chunker-recursive",
|
||||
"-p",
|
||||
|
|
|
|||
63
templates/components/claude-rag.jsonnet
Normal file
63
templates/components/claude-rag.jsonnet
Normal file
|
|
@ -0,0 +1,63 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["claude-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"claude-rag-model":: "claude-3-sonnet-20240229",
|
||||
"claude-rag-max-output-tokens":: 4096,
|
||||
"claude-rag-temperature":: 0.0,
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("claude-credentials")
|
||||
.with_env_var("CLAUDE_KEY", "claude-key");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-claude",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["claude-rag-max-output-tokens"]),
|
||||
"-m",
|
||||
$["claude-rag-model"],
|
||||
"-t",
|
||||
"%0.3f" % $["claude-rag-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,6 +5,12 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["claude-" + key]:: value,
|
||||
},
|
||||
|
||||
"claude-model":: "claude-3-sonnet-20240229",
|
||||
"claude-max-output-tokens":: 4096,
|
||||
"claude-temperature":: 0.0,
|
||||
|
||||
|
|
@ -13,17 +19,19 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("claude-credentials")
|
||||
.with_env_var("CLAUDE_KEY_TOKEN", "claude-key");
|
||||
.with_env_var("CLAUDE_KEY", "claude-key");
|
||||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-claude",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["claude-max-output-tokens"]),
|
||||
"-m",
|
||||
$["claude-model"],
|
||||
"-t",
|
||||
"%0.3f" % $["claude-temperature"],
|
||||
])
|
||||
|
|
@ -31,48 +39,18 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-claude",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["claude-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["claude-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
56
templates/components/cohere-rag.jsonnet
Normal file
56
templates/components/cohere-rag.jsonnet
Normal file
|
|
@ -0,0 +1,56 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["cohere-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"cohere-rag-temperature":: 0.0,
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("cohere-credentials")
|
||||
.with_env_var("COHERE_KEY", "cohere-key");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-cohere",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-t",
|
||||
"%0.3f" % $["cohere-rag-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,9 +5,10 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
// Override chunking
|
||||
"chunk-size":: 150,
|
||||
"chunk-overlap":: 10,
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["cohere-" + key]:: value,
|
||||
},
|
||||
|
||||
"cohere-temperature":: 0.0,
|
||||
|
||||
|
|
@ -20,7 +21,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-cohere",
|
||||
"-p",
|
||||
|
|
@ -31,45 +32,18 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-cohere",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-t",
|
||||
"%0.3f" % $["cohere-temperature"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
|
|
@ -5,17 +5,21 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
"document-rag-doc-limit":: 20,
|
||||
|
||||
"document-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("document-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"document-rag",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"--doc-limit",
|
||||
std.toString($["document-rag-doc-limit"]),
|
||||
"--prompt-request-queue",
|
||||
"non-persistent://tg/request/prompt-rag",
|
||||
"--prompt-response-queue",
|
||||
|
|
@ -39,5 +43,35 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
},
|
||||
|
||||
"document-embeddings" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("document-embeddings")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"document-embeddings",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
])
|
||||
.with_limits("1.0", "512M")
|
||||
.with_reservations("0.5", "512M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"document-embeddings", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
}
|
||||
|
||||
|
|
|
|||
43
templates/components/embeddings-fastembed.jsonnet
Normal file
43
templates/components/embeddings-fastembed.jsonnet
Normal file
|
|
@ -0,0 +1,43 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
"embeddings-model":: "sentence-transformers/all-MiniLM-L6-v2",
|
||||
|
||||
embeddings +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("embeddings")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"embeddings-fastembed",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-m",
|
||||
$["embeddings-model"],
|
||||
])
|
||||
.with_limits("1.0", "400M")
|
||||
.with_reservations("0.5", "400M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"embeddings", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
}
|
||||
|
||||
|
|
@ -13,7 +13,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_hf)
|
||||
.with_command([
|
||||
"embeddings-hf",
|
||||
"-p",
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@ local url = import "values/url.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"embeddings-ollama",
|
||||
"-p",
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@ falkordb + {
|
|||
|
||||
local container =
|
||||
engine.container("store-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-write-falkordb",
|
||||
"-p",
|
||||
|
|
@ -45,7 +45,7 @@ falkordb + {
|
|||
|
||||
local container =
|
||||
engine.container("query-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-query-falkordb",
|
||||
"-p",
|
||||
|
|
|
|||
65
templates/components/googleaistudio-rag.jsonnet
Normal file
65
templates/components/googleaistudio-rag.jsonnet
Normal file
|
|
@ -0,0 +1,65 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["googleaistudio-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"googleaistudio-rag-max-output-tokens":: 4096,
|
||||
"googleaistudio-rag-temperature":: 0.0,
|
||||
"googleaistudio-rag-model":: "gemini-1.5-flash-002",
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("googleaistudio-credentials")
|
||||
.with_env_var("GOOGLE_AI_STUDIO_KEY", "googleaistudio-key");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-googleaistudio",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString(
|
||||
$["googleaistudio-rag-max-output-tokens"]
|
||||
),
|
||||
"-t",
|
||||
"%0.3f" % $["googleaistudio-rag-temperature"],
|
||||
"-m",
|
||||
$["googleaistudio-rag-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["googleaistudio-" + key]:: value,
|
||||
},
|
||||
|
||||
"googleaistudio-max-output-tokens":: 4096,
|
||||
"googleaistudio-temperature":: 0.0,
|
||||
"googleaistudio-model":: "gemini-1.5-flash-002",
|
||||
|
|
@ -13,12 +18,12 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("googleaistudio-key")
|
||||
local envSecrets = engine.envSecrets("googleaistudio-credentials")
|
||||
.with_env_var("GOOGLE_AI_STUDIO_KEY", "googleaistudio-key");
|
||||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-googleaistudio",
|
||||
"-p",
|
||||
|
|
@ -34,50 +39,18 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-googleaistudio",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["googleaistudio-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["googleaistudio-temperature"],
|
||||
"-m",
|
||||
$["googleaistudio-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
|
|
@ -6,7 +6,8 @@ local url = import "values/url.jsonnet";
|
|||
|
||||
"graph-rag-entity-limit":: 50,
|
||||
"graph-rag-triple-limit":: 30,
|
||||
"graph-rag-max-subgraph-size":: 3000,
|
||||
"graph-rag-max-subgraph-size":: 400,
|
||||
"graph-rag-max-path-length":: 2,
|
||||
|
||||
"kg-extract-definitions" +: {
|
||||
|
||||
|
|
@ -14,7 +15,7 @@ local url = import "values/url.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("kg-extract-definitions")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"kg-extract-definitions",
|
||||
"-p",
|
||||
|
|
@ -44,7 +45,7 @@ local url = import "values/url.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("kg-extract-relationships")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"kg-extract-relationships",
|
||||
"-p",
|
||||
|
|
@ -74,7 +75,7 @@ local url = import "values/url.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("kg-extract-topics")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"kg-extract-topics",
|
||||
"-p",
|
||||
|
|
@ -104,7 +105,7 @@ local url = import "values/url.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("graph-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"graph-rag",
|
||||
"-p",
|
||||
|
|
@ -119,6 +120,8 @@ local url = import "values/url.jsonnet";
|
|||
std.toString($["graph-rag-triple-limit"]),
|
||||
"--max-subgraph-size",
|
||||
std.toString($["graph-rag-max-subgraph-size"]),
|
||||
"--max-path-length",
|
||||
std.toString($["graph-rag-max-path-length"]),
|
||||
])
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
|
@ -138,5 +141,35 @@ local url = import "values/url.jsonnet";
|
|||
|
||||
},
|
||||
|
||||
"graph-embeddings" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("graph-embeddings")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"graph-embeddings",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
])
|
||||
.with_limits("1.0", "512M")
|
||||
.with_reservations("0.5", "512M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"graph-embeddings", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
}
|
||||
|
||||
|
|
|
|||
43
templates/components/librarian.jsonnet
Normal file
43
templates/components/librarian.jsonnet
Normal file
|
|
@ -0,0 +1,43 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local minio = import "stores/minio.jsonnet";
|
||||
local cassandra = import "stores/cassandra.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
"librarian" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("librarian")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"librarian",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
])
|
||||
.with_limits("0.5", "256M")
|
||||
.with_reservations("0.1", "256M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"librarian", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
}
|
||||
|
||||
// Minio and Cassandra are used by the Librarian
|
||||
+ minio + cassandra
|
||||
|
||||
57
templates/components/llamafile-rag.jsonnet
Normal file
57
templates/components/llamafile-rag.jsonnet
Normal file
|
|
@ -0,0 +1,57 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/slm.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["llamafile-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"llamafile-rag-model":: "LLaMA_CPP",
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("llamafile-credentials")
|
||||
.with_env_var("LLAMAFILE_URL", "llamafile-url");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-llamafile",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-m",
|
||||
$["llamafile-rag-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,6 +5,11 @@ local prompts = import "prompts/slm.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["llamafile-" + key]:: value,
|
||||
},
|
||||
|
||||
"llamafile-model":: "LLaMA_CPP",
|
||||
|
||||
"text-completion" +: {
|
||||
|
|
@ -16,7 +21,7 @@ local prompts = import "prompts/slm.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-llamafile",
|
||||
"-p",
|
||||
|
|
@ -28,46 +33,18 @@ local prompts = import "prompts/slm.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-llamafile",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-m",
|
||||
$["llamafile-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ memgraph + {
|
|||
|
||||
local container =
|
||||
engine.container("store-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-write-memgraph",
|
||||
"-p",
|
||||
|
|
@ -48,7 +48,7 @@ memgraph + {
|
|||
|
||||
local container =
|
||||
engine.container("query-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-query-memgraph",
|
||||
"-p",
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ milvus + {
|
|||
|
||||
local container =
|
||||
engine.container("store-graph-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"ge-write-milvus",
|
||||
"-p",
|
||||
|
|
@ -44,7 +44,7 @@ milvus + {
|
|||
|
||||
local container =
|
||||
engine.container("query-graph-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"ge-query-milvus",
|
||||
"-p",
|
||||
|
|
@ -76,7 +76,7 @@ milvus + {
|
|||
|
||||
local container =
|
||||
engine.container("store-doc-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"de-write-milvus",
|
||||
"-p",
|
||||
|
|
@ -108,7 +108,7 @@ milvus + {
|
|||
|
||||
local container =
|
||||
engine.container("query-doc-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"de-query-milvus",
|
||||
"-p",
|
||||
|
|
|
|||
47
templates/components/mistral-ocr.jsonnet
Normal file
47
templates/components/mistral-ocr.jsonnet
Normal file
|
|
@ -0,0 +1,47 @@
|
|||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["mistral-" + key]:: value,
|
||||
},
|
||||
|
||||
"pdf-decoder" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("mistral-credentials")
|
||||
.with_env_var("MISTRAL_TOKEN", "mistral-token");
|
||||
|
||||
local container =
|
||||
engine.container("mistral-ocr")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"pdf-ocr-mistral",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"mistral-ocr", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
63
templates/components/mistral-rag.jsonnet
Normal file
63
templates/components/mistral-rag.jsonnet
Normal file
|
|
@ -0,0 +1,63 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["mistral-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"mistral-rag-max-output-tokens":: 4096,
|
||||
"mistral-rag-temperature":: 0.0,
|
||||
"mistral-rag-model":: "ministral-8b-latest",
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("mistral-credentials")
|
||||
.with_env_var("MISTRAL_TOKEN", "mistral-token");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-mistral",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["mistral-rag-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["mistral-rag-temperature"],
|
||||
"-m",
|
||||
$["mistral-rag-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
59
templates/components/mistral.jsonnet
Normal file
59
templates/components/mistral.jsonnet
Normal file
|
|
@ -0,0 +1,59 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["mistral-" + key]:: value,
|
||||
},
|
||||
|
||||
"mistral-max-output-tokens":: 4096,
|
||||
"mistral-temperature":: 0.0,
|
||||
"mistral-model":: "ministral-8b-latest",
|
||||
|
||||
"text-completion" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("mistral-credentials")
|
||||
.with_env_var("MISTRAL_TOKEN", "mistral-token");
|
||||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-mistral",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["mistral-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["mistral-temperature"],
|
||||
"-m",
|
||||
$["mistral-model"],
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -13,7 +13,7 @@ neo4j + {
|
|||
|
||||
local container =
|
||||
engine.container("store-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-write-neo4j",
|
||||
"-p",
|
||||
|
|
@ -45,7 +45,7 @@ neo4j + {
|
|||
|
||||
local container =
|
||||
engine.container("query-triples")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"triples-query-neo4j",
|
||||
"-p",
|
||||
|
|
|
|||
38
templates/components/ocr.jsonnet
Normal file
38
templates/components/ocr.jsonnet
Normal file
|
|
@ -0,0 +1,38 @@
|
|||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
"pdf-decoder" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("pdf-ocr")
|
||||
.with_image(images.trustgraph_ocr)
|
||||
.with_command([
|
||||
"pdf-ocr",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
])
|
||||
.with_limits("1.0", "512M")
|
||||
.with_reservations("0.1", "512M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"pdf-ocr", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
57
templates/components/ollama-rag.jsonnet
Normal file
57
templates/components/ollama-rag.jsonnet
Normal file
|
|
@ -0,0 +1,57 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["ollama-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"ollama-rag-model":: "gemma2:9b",
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("ollama-credentials")
|
||||
.with_env_var("OLLAMA_HOST", "ollama-host");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-ollama",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-m",
|
||||
$["ollama-rag-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["ollama-" + key]:: value,
|
||||
},
|
||||
|
||||
"ollama-model":: "gemma2:9b",
|
||||
|
||||
"text-completion" +: {
|
||||
|
|
@ -16,7 +21,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-ollama",
|
||||
"-p",
|
||||
|
|
@ -28,46 +33,18 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-ollama",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-m",
|
||||
$["ollama-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
63
templates/components/openai-rag.jsonnet
Normal file
63
templates/components/openai-rag.jsonnet
Normal file
|
|
@ -0,0 +1,63 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["openai-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"openai-rag-max-output-tokens":: 4096,
|
||||
"openai-rag-temperature":: 0.0,
|
||||
"openai-rag-model":: "GPT-3.5-Turbo",
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local envSecrets = engine.envSecrets("openai-credentials")
|
||||
.with_env_var("OPENAI_TOKEN", "openai-token");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-openai",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["openai-rag-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["openai-rag-temperature"],
|
||||
"-m",
|
||||
$["openai-rag-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSetRag,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["openai-" + key]:: value,
|
||||
},
|
||||
|
||||
"openai-max-output-tokens":: 4096,
|
||||
"openai-temperature":: 0.0,
|
||||
"openai-model":: "GPT-3.5-Turbo",
|
||||
|
|
@ -18,7 +23,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"text-completion-openai",
|
||||
"-p",
|
||||
|
|
@ -34,50 +39,18 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerRag =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-openai",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-x",
|
||||
std.toString($["openai-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["openai-temperature"],
|
||||
"-m",
|
||||
$["openai-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_env_var_secrets(envSecrets)
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion", [ container ]
|
||||
);
|
||||
|
||||
local containerSetRag = engine.containers(
|
||||
"text-completion-rag", [ containerRag ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
local serviceRag =
|
||||
engine.internalService(containerSetRag)
|
||||
.with_port(8080, 8080, "metrics");
|
||||
|
||||
engine.resources([
|
||||
envSecrets,
|
||||
containerSet,
|
||||
containerSetRag,
|
||||
service,
|
||||
serviceRag,
|
||||
])
|
||||
|
||||
},
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ local cassandra_hosts = "cassandra";
|
|||
|
||||
local container =
|
||||
engine.container("store-graph-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"ge-write-pinecone",
|
||||
"-p",
|
||||
|
|
@ -52,7 +52,7 @@ local cassandra_hosts = "cassandra";
|
|||
|
||||
local container =
|
||||
engine.container("query-graph-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"ge-query-pinecone",
|
||||
"-p",
|
||||
|
|
@ -87,7 +87,7 @@ local cassandra_hosts = "cassandra";
|
|||
|
||||
local container =
|
||||
engine.container("store-doc-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"de-write-pinecone",
|
||||
"-p",
|
||||
|
|
@ -122,7 +122,7 @@ local cassandra_hosts = "cassandra";
|
|||
|
||||
local container =
|
||||
engine.container("query-doc-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"de-query-pinecone",
|
||||
"-p",
|
||||
|
|
|
|||
|
|
@ -1,7 +1,3 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
local default_prompts = import "prompts/default-prompts.jsonnet";
|
||||
|
||||
{
|
||||
|
|
|
|||
|
|
@ -44,7 +44,7 @@ local default_prompts = import "prompts/default-prompts.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("prompt")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"prompt-template",
|
||||
"-p",
|
||||
|
|
@ -84,7 +84,7 @@ local default_prompts = import "prompts/default-prompts.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("prompt-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"prompt-template",
|
||||
"-p",
|
||||
|
|
|
|||
|
|
@ -2,32 +2,114 @@ local base = import "base/base.jsonnet";
|
|||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
|
||||
// This is a Pulsar configuration. Non-standalone mode so we deploy
|
||||
// individual components: bookkeeper, broker and zookeeper.
|
||||
//
|
||||
// This also deploys the TrustGraph 'admin' container which initialises
|
||||
// TrustGraph-specific namespaces etc.
|
||||
|
||||
{
|
||||
|
||||
"pulsar" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
// local confVolume = engine.volume("pulsar-conf").with_size("2G");
|
||||
local dataVolume = engine.volume("pulsar-data").with_size("20G");
|
||||
// Zookeeper volume
|
||||
local zkVolume = engine.volume("zookeeper").with_size("1G");
|
||||
|
||||
local container =
|
||||
// Zookeeper container
|
||||
local zkContainer =
|
||||
engine.container("zookeeper")
|
||||
.with_image(images.pulsar)
|
||||
.with_command([
|
||||
"bash",
|
||||
"-c",
|
||||
"bin/apply-config-from-env.py conf/zookeeper.conf && bin/generate-zookeeper-config.sh conf/zookeeper.conf && exec bin/pulsar zookeeper"
|
||||
])
|
||||
.with_limits("1", "400M")
|
||||
.with_reservations("0.05", "400M")
|
||||
.with_user("0:1000")
|
||||
.with_volume_mount(zkVolume, "/pulsar/data/zookeeper")
|
||||
.with_environment({
|
||||
"metadataStoreUrl": "zk:zookeeper:2181",
|
||||
"PULSAR_MEM": "-Xms256m -Xmx256m -XX:MaxDirectMemorySize=256m",
|
||||
})
|
||||
.with_port(2181, 2181, "zookeeper")
|
||||
.with_port(2888, 2888, "zookeeper2")
|
||||
.with_port(3888, 3888, "zookeeper3");
|
||||
|
||||
// Pulsar cluster init container
|
||||
local initContainer =
|
||||
engine.container("pulsar-init")
|
||||
.with_image(images.pulsar)
|
||||
.with_command([
|
||||
"bash",
|
||||
"-c",
|
||||
"sleep 10 && bin/pulsar initialize-cluster-metadata --cluster cluster-a --zookeeper zookeeper:2181 --configuration-store zookeeper:2181 --web-service-url http://pulsar:8080 --broker-service-url pulsar://pulsar:6650",
|
||||
])
|
||||
.with_limits("1", "512M")
|
||||
.with_reservations("0.05", "512M")
|
||||
.with_environment({
|
||||
"PULSAR_MEM": "-Xms256m -Xmx256m -XX:MaxDirectMemorySize=256m",
|
||||
});
|
||||
|
||||
|
||||
// Bookkeeper volume
|
||||
local bookieVolume = engine.volume("bookie").with_size("20G");
|
||||
|
||||
// Bookkeeper container
|
||||
local bookieContainer =
|
||||
engine.container("bookie")
|
||||
.with_image(images.pulsar)
|
||||
.with_command([
|
||||
"bash",
|
||||
"-c",
|
||||
"bin/apply-config-from-env.py conf/bookkeeper.conf && exec bin/pulsar bookie"
|
||||
// false ^ causes this to be a 'failure' exit.
|
||||
])
|
||||
.with_limits("1", "800M")
|
||||
.with_reservations("0.1", "800M")
|
||||
.with_user("0:1000")
|
||||
.with_volume_mount(bookieVolume, "/pulsar/data/bookkeeper")
|
||||
.with_environment({
|
||||
"clusterName": "cluster-a",
|
||||
"zkServers": "zookeeper:2181",
|
||||
"bookieId": "bookie",
|
||||
"metadataStoreUri": "metadata-store:zk:zookeeper:2181",
|
||||
"advertisedAddress": "bookie",
|
||||
"BOOKIE_MEM": "-Xms512m -Xmx512m -XX:MaxDirectMemorySize=256m",
|
||||
})
|
||||
.with_port(3181, 3181, "bookie");
|
||||
|
||||
// Pulsar broker, stateless (uses ZK and Bookkeeper for state)
|
||||
local brokerContainer =
|
||||
engine.container("pulsar")
|
||||
.with_image(images.pulsar)
|
||||
.with_command(["bin/pulsar", "standalone"])
|
||||
.with_command([
|
||||
"bash",
|
||||
"-c",
|
||||
"bin/apply-config-from-env.py conf/broker.conf && exec bin/pulsar broker"
|
||||
])
|
||||
.with_limits("1", "800M")
|
||||
.with_reservations("0.1", "800M")
|
||||
.with_environment({
|
||||
"PULSAR_MEM": "-Xms600M -Xmx600M"
|
||||
"metadataStoreUrl": "zk:zookeeper:2181",
|
||||
"zookeeperServers": "zookeeper:2181",
|
||||
"clusterName": "cluster-a",
|
||||
"managedLedgerDefaultEnsembleSize": "1",
|
||||
"managedLedgerDefaultWriteQuorum": "1",
|
||||
"managedLedgerDefaultAckQuorum": "1",
|
||||
"advertisedAddress": "pulsar",
|
||||
"advertisedListeners": "external:pulsar://pulsar:6650,localhost:pulsar://localhost:6650",
|
||||
"PULSAR_MEM": "-Xms512m -Xmx512m -XX:MaxDirectMemorySize=256m",
|
||||
})
|
||||
.with_limits("2.0", "1500M")
|
||||
.with_reservations("1.0", "1500M")
|
||||
// .with_volume_mount(confVolume, "/pulsar/conf")
|
||||
.with_volume_mount(dataVolume, "/pulsar/data")
|
||||
.with_port(6650, 6650, "bookie")
|
||||
.with_port(8080, 8080, "http");
|
||||
.with_port(6650, 6650, "pulsar")
|
||||
.with_port(8080, 8080, "admin");
|
||||
|
||||
// Trustgraph Pulsar initialisation
|
||||
local adminContainer =
|
||||
engine.container("init-pulsar")
|
||||
.with_image(images.trustgraph)
|
||||
engine.container("init-trustgraph")
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"tg-init-pulsar",
|
||||
"-p",
|
||||
|
|
@ -36,10 +118,32 @@ local url = import "values/url.jsonnet";
|
|||
.with_limits("1", "128M")
|
||||
.with_reservations("0.1", "128M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
// Container sets
|
||||
local zkContainerSet = engine.containers(
|
||||
"zookeeper",
|
||||
[
|
||||
zkContainer,
|
||||
]
|
||||
);
|
||||
|
||||
local initContainerSet = engine.containers(
|
||||
"init-pulsar",
|
||||
[
|
||||
initContainer,
|
||||
]
|
||||
);
|
||||
|
||||
local bookieContainerSet = engine.containers(
|
||||
"bookie",
|
||||
[
|
||||
bookieContainer,
|
||||
]
|
||||
);
|
||||
|
||||
local brokerContainerSet = engine.containers(
|
||||
"pulsar",
|
||||
[
|
||||
container
|
||||
brokerContainer,
|
||||
]
|
||||
);
|
||||
|
||||
|
|
@ -50,17 +154,35 @@ local url = import "values/url.jsonnet";
|
|||
]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.service(containerSet)
|
||||
.with_port(6650, 6650, "bookie")
|
||||
.with_port(8080, 8080, "http");
|
||||
// Zookeeper service
|
||||
local zkService =
|
||||
engine.service(zkContainerSet)
|
||||
.with_port(2181, 2181, "zookeeper")
|
||||
.with_port(2888, 2888, "zookeeper2")
|
||||
.with_port(3888, 3888, "zookeeper3");
|
||||
|
||||
// Bookkeeper service
|
||||
local bookieService =
|
||||
engine.service(bookieContainerSet)
|
||||
.with_port(3181, 3181, "bookie");
|
||||
|
||||
// Pulsar broker service
|
||||
local brokerService =
|
||||
engine.service(brokerContainerSet)
|
||||
.with_port(6650, 6650, "pulsar")
|
||||
.with_port(8080, 8080, "admin");
|
||||
|
||||
engine.resources([
|
||||
// confVolume,
|
||||
dataVolume,
|
||||
containerSet,
|
||||
zkVolume,
|
||||
bookieVolume,
|
||||
zkContainerSet,
|
||||
initContainerSet,
|
||||
bookieContainerSet,
|
||||
brokerContainerSet,
|
||||
adminContainerSet,
|
||||
service,
|
||||
zkService,
|
||||
bookieService,
|
||||
brokerService,
|
||||
])
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ qdrant + {
|
|||
|
||||
local container =
|
||||
engine.container("store-graph-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"ge-write-qdrant",
|
||||
"-p",
|
||||
|
|
@ -44,7 +44,7 @@ qdrant + {
|
|||
|
||||
local container =
|
||||
engine.container("query-graph-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"ge-query-qdrant",
|
||||
"-p",
|
||||
|
|
@ -76,7 +76,7 @@ qdrant + {
|
|||
|
||||
local container =
|
||||
engine.container("store-doc-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"de-write-qdrant",
|
||||
"-p",
|
||||
|
|
@ -108,7 +108,7 @@ qdrant + {
|
|||
|
||||
local container =
|
||||
engine.container("query-doc-embeddings")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"de-query-qdrant",
|
||||
"-p",
|
||||
|
|
|
|||
|
|
@ -1,7 +1,6 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompt = import "prompt-template.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
|
|
@ -22,7 +21,7 @@ local prompt = import "prompt-template.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("api-gateway")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"api-gateway",
|
||||
"-p",
|
||||
|
|
@ -61,7 +60,7 @@ local prompt = import "prompt-template.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("chunker")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"chunker-token",
|
||||
"-p",
|
||||
|
|
@ -95,7 +94,7 @@ local prompt = import "prompt-template.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("pdf-decoder")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"pdf-decoder",
|
||||
"-p",
|
||||
|
|
@ -119,43 +118,13 @@ local prompt = import "prompt-template.jsonnet";
|
|||
|
||||
},
|
||||
|
||||
"vectorize" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("vectorize")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"embeddings-vectorize",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
])
|
||||
.with_limits("1.0", "512M")
|
||||
.with_reservations("0.5", "512M");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"vectorize", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
"metering" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local container =
|
||||
engine.container("metering")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"metering",
|
||||
"-p",
|
||||
|
|
@ -185,7 +154,7 @@ local prompt = import "prompt-template.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("metering-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_flow)
|
||||
.with_command([
|
||||
"metering",
|
||||
"-p",
|
||||
|
|
@ -211,5 +180,5 @@ local prompt = import "prompt-template.jsonnet";
|
|||
|
||||
},
|
||||
|
||||
} + prompt
|
||||
}
|
||||
|
||||
|
|
|
|||
74
templates/components/vertexai-rag.jsonnet
Normal file
74
templates/components/vertexai-rag.jsonnet
Normal file
|
|
@ -0,0 +1,74 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local url = import "values/url.jsonnet";
|
||||
local prompts = import "prompts/mixtral.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["vertexai-rag-" + key]:: value,
|
||||
},
|
||||
|
||||
"vertexai-rag-model":: "gemini-1.0-pro-001",
|
||||
"vertexai-rag-private-key":: "/vertexai/private.json",
|
||||
"vertexai-rag-region":: "us-central1",
|
||||
"vertexai-rag-max-output-tokens":: 4096,
|
||||
"vertexai-rag-temperature":: 0.0,
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local cfgVol = engine.secretVolume(
|
||||
"vertexai-creds",
|
||||
"./vertexai",
|
||||
{
|
||||
"private.json": importstr "vertexai/private.json",
|
||||
}
|
||||
);
|
||||
|
||||
local container =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph_vertexai)
|
||||
.with_command([
|
||||
"text-completion-vertexai",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-k",
|
||||
$["vertexai-rag-private-key"],
|
||||
"-r",
|
||||
$["vertexai-rag-region"],
|
||||
"-x",
|
||||
std.toString($["vertexai-rag-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["vertexai-rag-temperature"],
|
||||
"-m",
|
||||
$["vertexai-rag-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_limits("0.5", "256M")
|
||||
.with_reservations("0.1", "256M")
|
||||
.with_volume_mount(cfgVol, "/vertexai");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion-rag", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
cfgVol,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
}
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
{
|
||||
|
||||
with:: function(key, value)
|
||||
self + {
|
||||
["vertexai-" + key]:: value,
|
||||
},
|
||||
|
||||
"vertexai-model":: "gemini-1.0-pro-001",
|
||||
"vertexai-private-key":: "/vertexai/private.json",
|
||||
"vertexai-region":: "us-central1",
|
||||
|
|
@ -25,7 +30,7 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
local container =
|
||||
engine.container("text-completion")
|
||||
.with_image(images.trustgraph)
|
||||
.with_image(images.trustgraph_vertexai)
|
||||
.with_command([
|
||||
"text-completion-vertexai",
|
||||
"-p",
|
||||
|
|
@ -61,59 +66,5 @@ local prompts = import "prompts/mixtral.jsonnet";
|
|||
|
||||
},
|
||||
|
||||
"text-completion-rag" +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local cfgVol = engine.secretVolume(
|
||||
"vertexai-creds",
|
||||
"./vertexai",
|
||||
{
|
||||
"private.json": importstr "vertexai/private.json",
|
||||
}
|
||||
);
|
||||
|
||||
local container =
|
||||
engine.container("text-completion-rag")
|
||||
.with_image(images.trustgraph)
|
||||
.with_command([
|
||||
"text-completion-vertexai",
|
||||
"-p",
|
||||
url.pulsar,
|
||||
"-k",
|
||||
$["vertexai-private-key"],
|
||||
"-r",
|
||||
$["vertexai-region"],
|
||||
"-x",
|
||||
std.toString($["vertexai-max-output-tokens"]),
|
||||
"-t",
|
||||
"%0.3f" % $["vertexai-temperature"],
|
||||
"-m",
|
||||
$["vertexai-model"],
|
||||
"-i",
|
||||
"non-persistent://tg/request/text-completion-rag",
|
||||
"-o",
|
||||
"non-persistent://tg/response/text-completion-rag",
|
||||
])
|
||||
.with_limits("0.5", "256M")
|
||||
.with_reservations("0.1", "256M")
|
||||
.with_volume_mount(cfgVol, "/vertexai");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"text-completion-rag", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.internalService(containerSet)
|
||||
.with_port(8000, 8000, "metrics");
|
||||
|
||||
engine.resources([
|
||||
cfgVol,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
}
|
||||
|
||||
} + prompts
|
||||
|
||||
|
|
|
|||
16
templates/config-to-aks-k8s.jsonnet
Normal file
16
templates/config-to-aks-k8s.jsonnet
Normal file
|
|
@ -0,0 +1,16 @@
|
|||
|
||||
local engine = import "engine/aks-k8s.jsonnet";
|
||||
local decode = import "util/decode-config.jsonnet";
|
||||
local components = import "components.jsonnet";
|
||||
|
||||
// Import config
|
||||
local config = import "config.json";
|
||||
|
||||
// Produce patterns from config
|
||||
local patterns = decode(config);
|
||||
|
||||
// Extract resources usnig the engine
|
||||
local resourceList = engine.package(patterns);
|
||||
|
||||
resourceList
|
||||
|
||||
45
templates/engine/aks-k8s.jsonnet
Normal file
45
templates/engine/aks-k8s.jsonnet
Normal file
|
|
@ -0,0 +1,45 @@
|
|||
|
||||
local k8s = import "k8s.jsonnet";
|
||||
|
||||
local ns = {
|
||||
apiVersion: "v1",
|
||||
kind: "Namespace",
|
||||
metadata: {
|
||||
name: "trustgraph",
|
||||
},
|
||||
"spec": {
|
||||
},
|
||||
};
|
||||
|
||||
local sc = {
|
||||
apiVersion: "storage.k8s.io/v1",
|
||||
kind: "StorageClass",
|
||||
metadata: {
|
||||
name: "tg",
|
||||
},
|
||||
provisioner: "disk.csi.azure.com",
|
||||
parameters: {
|
||||
// Standard disks (spinning magnetic), Locally Redundant Storage
|
||||
// Cheapest, basically
|
||||
skuName: "Standard_LRS",
|
||||
},
|
||||
reclaimPolicy: "Delete",
|
||||
volumeBindingMode: "WaitForFirstConsumer",
|
||||
};
|
||||
|
||||
k8s + {
|
||||
|
||||
// Extract resources usnig the engine
|
||||
package:: function(patterns)
|
||||
local resources = [sc, ns] + std.flattenArrays([
|
||||
p.create(self) for p in std.objectValues(patterns)
|
||||
]);
|
||||
local resourceList = {
|
||||
apiVersion: "v1",
|
||||
kind: "List",
|
||||
items: [ns, sc] + resources,
|
||||
};
|
||||
resourceList
|
||||
|
||||
}
|
||||
|
||||
|
|
@ -22,6 +22,8 @@
|
|||
|
||||
with_image:: function(x) self + { image: x },
|
||||
|
||||
with_user:: function(x) self + { user: x },
|
||||
|
||||
with_command:: function(x) self + { command: x },
|
||||
|
||||
with_environment:: function(x) self + {
|
||||
|
|
@ -75,6 +77,10 @@
|
|||
{ command: container.command }
|
||||
else {}) +
|
||||
|
||||
(if std.objectHas(container, "user") then
|
||||
{ user: container.user }
|
||||
else {}) +
|
||||
|
||||
(if ! std.isEmpty(container.environment) then
|
||||
{ environment: container.environment }
|
||||
else {}) +
|
||||
|
|
|
|||
|
|
@ -14,6 +14,8 @@
|
|||
|
||||
with_image:: function(x) self + { image: x },
|
||||
|
||||
with_user:: function(x) self + { user: x },
|
||||
|
||||
with_command:: function(x) self + { command: x },
|
||||
|
||||
with_environment:: function(x) self + {
|
||||
|
|
|
|||
|
|
@ -7,6 +7,8 @@ import logging
|
|||
import os
|
||||
import sys
|
||||
import zipfile
|
||||
import pathlib
|
||||
from io import BytesIO
|
||||
|
||||
logger = logging.getLogger("generate")
|
||||
logging.basicConfig(level=logging.INFO, format='%(message)s')
|
||||
|
|
@ -15,9 +17,13 @@ private_json = "Put your GCP private.json here"
|
|||
|
||||
class Generator:
|
||||
|
||||
def __init__(self, config, base="./templates/", version="0.0.0"):
|
||||
def __init__(
|
||||
self, config, templates="./templates/", resources="./resources",
|
||||
version="0.0.0",
|
||||
):
|
||||
|
||||
self.jsonnet_base = base
|
||||
self.templates = pathlib.Path(templates)
|
||||
self.resources = pathlib.Path(resources)
|
||||
self.config = config
|
||||
self.version = f"\"{version}\"".encode("utf-8")
|
||||
|
||||
|
|
@ -34,25 +40,30 @@ class Generator:
|
|||
path = os.path.join(".", dir, filename)
|
||||
return str(path), self.config
|
||||
|
||||
if filename == "version.jsonnet" and dir == "./templates/values/":
|
||||
if filename == "version.jsonnet" and dir == "templates/values/":
|
||||
path = os.path.join(".", dir, filename)
|
||||
return str(path), self.version
|
||||
|
||||
if dir:
|
||||
candidates = [
|
||||
os.path.join(".", dir, filename),
|
||||
os.path.join(".", filename)
|
||||
self.templates.joinpath(dir, filename),
|
||||
self.templates.joinpath(filename),
|
||||
self.resources.joinpath(dir, filename),
|
||||
self.resources.joinpath(filename),
|
||||
pathlib.Path(dir).joinpath(filename),
|
||||
]
|
||||
else:
|
||||
candidates = [
|
||||
os.path.join(".", filename)
|
||||
self.templates.joinpath(filename),
|
||||
pathlib.Path(dir).joinpath(filename),
|
||||
pathlib.Path(filename),
|
||||
]
|
||||
|
||||
try:
|
||||
|
||||
if filename == "vertexai/private.json":
|
||||
|
||||
return candidates[0], private_json.encode("utf-8")
|
||||
return str(candidates[0]), private_json.encode("utf-8")
|
||||
|
||||
for c in candidates:
|
||||
logger.debug("Try: %s", c)
|
||||
|
|
@ -68,73 +79,157 @@ class Generator:
|
|||
|
||||
except:
|
||||
|
||||
path = os.path.join(self.jsonnet_base, filename)
|
||||
path = os.path.join(self.templates, filename)
|
||||
logger.debug("Try: %s", path)
|
||||
with open(path, "rb") as f:
|
||||
logger.debug("Loaded: %s", path)
|
||||
return str(path), f.read()
|
||||
|
||||
def main():
|
||||
class Packager:
|
||||
|
||||
if len(sys.argv) != 3:
|
||||
print()
|
||||
print("Usage:")
|
||||
print(" generate <outfile> <version> < input.json")
|
||||
print()
|
||||
sys.exit(1)
|
||||
def __init__(self):
|
||||
self.templates = pathlib.Path("./templates")
|
||||
self.resources = pathlib.Path("./")
|
||||
|
||||
outfile = sys.argv[1]
|
||||
version = sys.argv[2]
|
||||
def process(
|
||||
self, config, version="0.0.0", platform="docker-compose",
|
||||
):
|
||||
|
||||
cfg = sys.stdin.read()
|
||||
cfg = json.loads(cfg)
|
||||
config = config.encode("utf-8")
|
||||
|
||||
logger.info(f"Outputting to {outfile}...")
|
||||
gen = Generator(
|
||||
config, templates=self.templates, resources=self.resources,
|
||||
version=version
|
||||
)
|
||||
|
||||
with zipfile.ZipFile(outfile, mode='w') as out:
|
||||
path = self.templates.joinpath(
|
||||
f"config-to-{platform}.jsonnet"
|
||||
)
|
||||
wrapper = path.read_text()
|
||||
|
||||
processed = gen.process(wrapper)
|
||||
|
||||
return processed
|
||||
|
||||
def generate(self, config, version, platform):
|
||||
|
||||
logger.info(f"Generating for platform={platform} version={version}")
|
||||
|
||||
try:
|
||||
|
||||
if platform in set(["docker-compose", "podman-compose"]):
|
||||
return self.generate_docker_compose(
|
||||
"docker-compose", version, config
|
||||
)
|
||||
elif platform in set(["minikube-k8s", "gcp-k8s", "aks-k8s"]):
|
||||
return self.generate_k8s(
|
||||
platform, version, config
|
||||
)
|
||||
else:
|
||||
raise RuntimeError("Bad configuration")
|
||||
|
||||
except Exception as e:
|
||||
logging.error(f"Exception: {e}")
|
||||
raise e
|
||||
|
||||
def generate_docker_compose(self, platform, version, config):
|
||||
|
||||
processed = self.process(
|
||||
config, platform=platform, version=version
|
||||
)
|
||||
|
||||
y = yaml.dump(processed)
|
||||
|
||||
mem = BytesIO()
|
||||
|
||||
with zipfile.ZipFile(mem, mode='w') as out:
|
||||
|
||||
def output(name, content):
|
||||
logger.info(f"Adding {name}...")
|
||||
out.writestr(name, content)
|
||||
|
||||
fname = "tg-launch.yaml"
|
||||
|
||||
platform = "docker-compose"
|
||||
|
||||
with open(f"./templates/config-to-{platform}.jsonnet", "r") as f:
|
||||
wrapper = f.read()
|
||||
|
||||
gen = Generator(json.dumps(cfg).encode("utf-8"), version=version)
|
||||
|
||||
processed = gen.process(wrapper)
|
||||
|
||||
y = yaml.dump(processed)
|
||||
fname = "docker-compose.yaml"
|
||||
|
||||
output(fname, y)
|
||||
|
||||
# Placeholder for the private.json file. Won't put actual credentials
|
||||
# here.
|
||||
output("docker-compose/vertexai/private.json", private_json)
|
||||
|
||||
# Grafana config
|
||||
with open("grafana/dashboards/dashboard.json") as f:
|
||||
output(
|
||||
"docker-compose/grafana/dashboards/dashboard.json", f.read()
|
||||
path = self.resources.joinpath(
|
||||
"grafana/dashboards/dashboard.json"
|
||||
)
|
||||
res = path.read_text()
|
||||
output("grafana/dashboards/dashboard.json", res)
|
||||
|
||||
with open("grafana/provisioning/dashboard.yml") as f:
|
||||
output(
|
||||
"docker-compose/grafana/provisioning/dashboard.yml", f.read()
|
||||
path = self.resources.joinpath(
|
||||
"grafana/provisioning/dashboard.yml"
|
||||
)
|
||||
res = path.read_text()
|
||||
output("grafana/provisioning/dashboard.yml", res)
|
||||
|
||||
with open("grafana/provisioning/datasource.yml") as f:
|
||||
output(
|
||||
"docker-compose/grafana/provisioning/datasource.yml", f.read()
|
||||
path = self.resources.joinpath(
|
||||
"grafana/provisioning/datasource.yml"
|
||||
)
|
||||
res = path.read_text()
|
||||
output("grafana/provisioning/datasource.yml", res)
|
||||
|
||||
# Prometheus config
|
||||
with open("prometheus/prometheus.yml") as f:
|
||||
output("docker-compose/prometheus/prometheus.yml", f.read())
|
||||
path = self.resources.joinpath(
|
||||
"prometheus/prometheus.yml"
|
||||
)
|
||||
res = path.read_text()
|
||||
output("prometheus/prometheus.yml", res)
|
||||
|
||||
logger.info("Generation complete.")
|
||||
|
||||
return mem.getvalue()
|
||||
|
||||
def generate_k8s(self, platform, version, config):
|
||||
|
||||
processed = self.process(
|
||||
config, platform=platform, version=version
|
||||
)
|
||||
|
||||
y = yaml.dump(processed)
|
||||
|
||||
mem = BytesIO()
|
||||
|
||||
with zipfile.ZipFile(mem, mode='w') as out:
|
||||
|
||||
def output(name, content):
|
||||
logger.info(f"Adding {name}...")
|
||||
out.writestr(name, content)
|
||||
|
||||
fname = "resources.yaml"
|
||||
|
||||
output(fname, y)
|
||||
|
||||
logger.info("Generation complete.")
|
||||
|
||||
return mem.getvalue()
|
||||
|
||||
def main():
|
||||
|
||||
if len(sys.argv) != 4:
|
||||
print()
|
||||
print("Usage:")
|
||||
print(" generate <outfile> <version> <platform> < input.json")
|
||||
print()
|
||||
sys.exit(1)
|
||||
|
||||
outfile = sys.argv[1]
|
||||
version = sys.argv[2]
|
||||
platform = sys.argv[3]
|
||||
|
||||
cfg = sys.stdin.read()
|
||||
|
||||
logger.info(f"Outputting to {outfile}...")
|
||||
|
||||
p = Packager()
|
||||
resp = p.generate(cfg, version, platform)
|
||||
|
||||
with open(outfile, "wb") as f:
|
||||
f.write(resp)
|
||||
|
||||
return
|
||||
|
||||
main()
|
||||
|
||||
|
|
|
|||
|
|
@ -87,8 +87,18 @@ def full_config_object(
|
|||
):
|
||||
|
||||
return config_object([
|
||||
graph_store, "pulsar", vector_store, embeddings,
|
||||
"graph-rag", "grafana", "trustgraph", llm, "workbench-ui",
|
||||
"triple-store-" + graph_store,
|
||||
"pulsar",
|
||||
"vector-store-" + vector_store,
|
||||
embeddings,
|
||||
"graph-rag",
|
||||
"grafana",
|
||||
"trustgraph-base",
|
||||
llm,
|
||||
llm + "-rag",
|
||||
"workbench-ui",
|
||||
"prompt-template",
|
||||
"agent-manager-react",
|
||||
])
|
||||
|
||||
def generate_config(
|
||||
|
|
@ -124,7 +134,7 @@ def generate_all(output, version):
|
|||
]:
|
||||
for model in [
|
||||
# "azure", "azure-openai", "bedrock", "claude", "cohere",
|
||||
# "googleaistudio", "llamafile",
|
||||
# "googleaistudio", "llamafile", "mistral",
|
||||
"ollama",
|
||||
# "openai", "vertexai",
|
||||
]:
|
||||
|
|
|
|||
32
templates/patterns/llm-mistral.jsonnet
Normal file
32
templates/patterns/llm-mistral.jsonnet
Normal file
|
|
@ -0,0 +1,32 @@
|
|||
{
|
||||
pattern: {
|
||||
name: "mistral",
|
||||
icon: "🤖💬",
|
||||
title: "Add Mistral LLM endpoint for text completion",
|
||||
description: "This pattern integrates a Mistral LLM service for text completion operations. You need a Mistral subscription and have an API key to be able to use this service.",
|
||||
requires: ["pulsar", "trustgraph"],
|
||||
features: ["llm"],
|
||||
args: [
|
||||
{
|
||||
name: "mistral-max-output-tokens",
|
||||
label: "Maximum output tokens",
|
||||
type: "integer",
|
||||
description: "Limit on number tokens to generate",
|
||||
default: 4096,
|
||||
required: true,
|
||||
},
|
||||
{
|
||||
name: "mistral-temperature",
|
||||
label: "Temperature",
|
||||
type: "slider",
|
||||
description: "Controlling predictability / creativity balance",
|
||||
min: 0,
|
||||
max: 1,
|
||||
step: 0.05,
|
||||
default: 0.5,
|
||||
},
|
||||
],
|
||||
category: [ "llm" ],
|
||||
},
|
||||
module: "components/mistral.jsonnet",
|
||||
}
|
||||
|
|
@ -13,7 +13,7 @@ local images = import "values/images.jsonnet";
|
|||
engine.container("cassandra")
|
||||
.with_image(images.cassandra)
|
||||
.with_environment({
|
||||
JVM_OPTS: "-Xms300M -Xmx300M",
|
||||
JVM_OPTS: "-Xms300M -Xmx300M -Dcassandra.skip_wait_for_gossip_to_settle=0",
|
||||
})
|
||||
.with_limits("1.0", "1000M")
|
||||
.with_reservations("0.5", "1000M")
|
||||
|
|
|
|||
|
|
@ -7,6 +7,8 @@ local images = import "values/images.jsonnet";
|
|||
|
||||
create:: function(engine)
|
||||
|
||||
local vol = engine.volume("memgraph").with_size("20G");
|
||||
|
||||
local container =
|
||||
engine.container("memgraph")
|
||||
.with_image(images.memgraph_mage)
|
||||
|
|
@ -16,7 +18,8 @@ local images = import "values/images.jsonnet";
|
|||
.with_limits("1.0", "1000M")
|
||||
.with_reservations("0.5", "1000M")
|
||||
.with_port(7474, 7474, "api")
|
||||
.with_port(7687, 7687, "api2");
|
||||
.with_port(7687, 7687, "api2")
|
||||
.with_volume_mount(vol, "/var/lib/memgraph");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"memgraph", [ container ]
|
||||
|
|
@ -28,6 +31,7 @@ local images = import "values/images.jsonnet";
|
|||
.with_port(7687, 7687, "api2");
|
||||
|
||||
engine.resources([
|
||||
vol,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
|
@ -65,4 +69,3 @@ local images = import "values/images.jsonnet";
|
|||
},
|
||||
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -1,7 +1,8 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
local minio = import "stores/minio.jsonnet";
|
||||
|
||||
{
|
||||
minio {
|
||||
|
||||
etcd +: {
|
||||
|
||||
|
|
@ -47,47 +48,6 @@ local images = import "values/images.jsonnet";
|
|||
|
||||
},
|
||||
|
||||
mino +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local vol = engine.volume("minio-data").with_size("20G");
|
||||
|
||||
local container =
|
||||
engine.container("minio")
|
||||
.with_image(images.minio)
|
||||
.with_command([
|
||||
"minio",
|
||||
"server",
|
||||
"/minio_data",
|
||||
"--console-address",
|
||||
":9001",
|
||||
])
|
||||
.with_environment({
|
||||
MINIO_ROOT_USER: "minioadmin",
|
||||
MINIO_ROOT_PASSWORD: "minioadmin",
|
||||
})
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.25", "128M")
|
||||
.with_port(9001, 9001, "api")
|
||||
.with_volume_mount(vol, "/minio_data");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"etcd", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.service(containerSet)
|
||||
.with_port(9001, 9001, "api");
|
||||
|
||||
engine.resources([
|
||||
vol,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
milvus +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
|
|
|||
49
templates/stores/minio.jsonnet
Normal file
49
templates/stores/minio.jsonnet
Normal file
|
|
@ -0,0 +1,49 @@
|
|||
local base = import "base/base.jsonnet";
|
||||
local images = import "values/images.jsonnet";
|
||||
|
||||
{
|
||||
|
||||
minio +: {
|
||||
|
||||
create:: function(engine)
|
||||
|
||||
local vol = engine.volume("minio-data").with_size("20G");
|
||||
|
||||
local container =
|
||||
engine.container("minio")
|
||||
.with_image(images.minio)
|
||||
.with_command([
|
||||
"minio",
|
||||
"server",
|
||||
"/minio_data",
|
||||
"--console-address",
|
||||
":9001",
|
||||
])
|
||||
.with_environment({
|
||||
MINIO_ROOT_USER: "minioadmin",
|
||||
MINIO_ROOT_PASSWORD: "minioadmin",
|
||||
})
|
||||
.with_limits("0.5", "128M")
|
||||
.with_reservations("0.25", "128M")
|
||||
.with_port(9000, 9000, "api")
|
||||
.with_port(9001, 9001, "console")
|
||||
.with_volume_mount(vol, "/minio_data");
|
||||
|
||||
local containerSet = engine.containers(
|
||||
"etcd", [ container ]
|
||||
);
|
||||
|
||||
local service =
|
||||
engine.service(containerSet)
|
||||
.with_port(9000, 9000, "api")
|
||||
.with_port(9001, 9001, "console");
|
||||
|
||||
engine.resources([
|
||||
vol,
|
||||
containerSet,
|
||||
service,
|
||||
])
|
||||
|
||||
},
|
||||
|
||||
}
|
||||
|
|
@ -14,12 +14,14 @@ local images = import "values/images.jsonnet";
|
|||
.with_image(images.neo4j)
|
||||
.with_environment({
|
||||
NEO4J_AUTH: "neo4j/password",
|
||||
NEO4J_server_memory_pagecache_size: "512m",
|
||||
NEO4J_server_memory_heap_max__size: "512m",
|
||||
// NEO4J_server_bolt_listen__address: "0.0.0.0:7687",
|
||||
// NEO4J_server_default__listen__address: "0.0.0.0",
|
||||
// NEO4J_server_http_listen__address: "0.0.0.0:7474",
|
||||
})
|
||||
.with_limits("1.0", "768M")
|
||||
.with_reservations("0.5", "768M")
|
||||
.with_limits("1.0", "1536M")
|
||||
.with_reservations("0.5", "1536M")
|
||||
.with_port(7474, 7474, "api")
|
||||
.with_port(7687, 7687, "api2")
|
||||
.with_volume_mount(vol, "/data");
|
||||
|
|
|
|||
|
|
@ -1,18 +1,23 @@
|
|||
local version = import "version.jsonnet";
|
||||
{
|
||||
cassandra: "docker.io/cassandra:4.1.6",
|
||||
neo4j: "docker.io/neo4j:5.22.0-community-bullseye",
|
||||
neo4j: "docker.io/neo4j:5.26.0-community-bullseye",
|
||||
pulsar: "docker.io/apachepulsar/pulsar:3.3.1",
|
||||
pulsar_manager: "docker.io/apachepulsar/pulsar-manager:v0.4.0",
|
||||
etcd: "quay.io/coreos/etcd:v3.5.15",
|
||||
minio: "docker.io/minio/minio:RELEASE.2024-08-17T01-24-54Z",
|
||||
minio: "docker.io/minio/minio:RELEASE.2025-02-03T21-03-04Z",
|
||||
milvus: "docker.io/milvusdb/milvus:v2.4.9",
|
||||
prometheus: "docker.io/prom/prometheus:v2.53.2",
|
||||
grafana: "docker.io/grafana/grafana:11.1.4",
|
||||
trustgraph: "docker.io/trustgraph/trustgraph-flow:" + version,
|
||||
qdrant: "docker.io/qdrant/qdrant:v1.11.1",
|
||||
trustgraph_base: "docker.io/trustgraph/trustgraph-base:" + version,
|
||||
trustgraph_flow: "docker.io/trustgraph/trustgraph-flow:" + version,
|
||||
trustgraph_ocr: "docker.io/trustgraph/trustgraph-ocr:" + version,
|
||||
trustgraph_bedrock: "docker.io/trustgraph/trustgraph-bedrock:" + version,
|
||||
trustgraph_vertexai: "docker.io/trustgraph/trustgraph-vertexai:" + version,
|
||||
trustgraph_hf: "docker.io/trustgraph/trustgraph-hf:" + version,
|
||||
qdrant: "docker.io/qdrant/qdrant:v1.13.3",
|
||||
memgraph_mage: "docker.io/memgraph/memgraph-mage:1.22-memgraph-2.22",
|
||||
memgraph_lab: "docker.io/memgraph/lab:2.19.1",
|
||||
falkordb: "docker.io/falkordb/falkordb:latest",
|
||||
"workbench-ui": "docker.io/trustgraph/workbench-ui:0.1.6",
|
||||
"workbench-ui": "docker.io/trustgraph/workbench-ui:0.2.4",
|
||||
}
|
||||
|
|
|
|||
|
|
@ -102,11 +102,21 @@ class Api:
|
|||
except:
|
||||
raise ProtocolException(f"Response not formatted correctly")
|
||||
|
||||
def graph_rag(self, question):
|
||||
def graph_rag(
|
||||
self, question, user="trustgraph", collection="default",
|
||||
entity_limit=50, triple_limit=30, max_subgraph_size=150,
|
||||
max_path_length=2,
|
||||
):
|
||||
|
||||
# The input consists of a question
|
||||
input = {
|
||||
"query": question
|
||||
"query": question,
|
||||
"user": user,
|
||||
"collection": collection,
|
||||
"entity-limit": entity_limit,
|
||||
"triple-limit": triple_limit,
|
||||
"max-subgraph-size": max_subgraph_size,
|
||||
"max-path-length": max_path_length,
|
||||
}
|
||||
|
||||
url = f"{self.url}graph-rag"
|
||||
|
|
@ -131,6 +141,41 @@ class Api:
|
|||
except:
|
||||
raise ProtocolException(f"Response not formatted correctly")
|
||||
|
||||
def document_rag(
|
||||
self, question, user="trustgraph", collection="default",
|
||||
doc_limit=10,
|
||||
):
|
||||
|
||||
# The input consists of a question
|
||||
input = {
|
||||
"query": question,
|
||||
"user": user,
|
||||
"collection": collection,
|
||||
"doc-limit": doc_limit,
|
||||
}
|
||||
|
||||
url = f"{self.url}document-rag"
|
||||
|
||||
# Invoke the API, input is passed as JSON
|
||||
resp = requests.post(url, json=input)
|
||||
|
||||
# Should be a 200 status code
|
||||
if resp.status_code != 200:
|
||||
raise ProtocolException(f"Status code {resp.status_code}")
|
||||
|
||||
try:
|
||||
# Parse the response as JSON
|
||||
object = resp.json()
|
||||
except:
|
||||
raise ProtocolException(f"Expected JSON response")
|
||||
|
||||
self.check_error(resp)
|
||||
|
||||
try:
|
||||
return object["response"]
|
||||
except:
|
||||
raise ProtocolException(f"Response not formatted correctly")
|
||||
|
||||
def embeddings(self, text):
|
||||
|
||||
# The input consists of a text block
|
||||
|
|
|
|||
|
|
@ -3,4 +3,6 @@ from . base_processor import BaseProcessor
|
|||
from . consumer import Consumer
|
||||
from . producer import Producer
|
||||
from . consumer_producer import ConsumerProducer
|
||||
from . publisher import Publisher
|
||||
from . subscriber import Subscriber
|
||||
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
|
||||
import asyncio
|
||||
import os
|
||||
import argparse
|
||||
import pulsar
|
||||
|
|
@ -11,6 +12,7 @@ from .. log_level import LogLevel
|
|||
class BaseProcessor:
|
||||
|
||||
default_pulsar_host = os.getenv("PULSAR_HOST", 'pulsar://pulsar:6650')
|
||||
default_pulsar_api_key = os.getenv("PULSAR_API_KEY", None)
|
||||
|
||||
def __init__(self, **params):
|
||||
|
||||
|
|
@ -28,14 +30,28 @@ class BaseProcessor:
|
|||
})
|
||||
|
||||
pulsar_host = params.get("pulsar_host", self.default_pulsar_host)
|
||||
pulsar_listener = params.get("pulsar_listener", None)
|
||||
pulsar_api_key = params.get("pulsar_api_key", None)
|
||||
log_level = params.get("log_level", LogLevel.INFO)
|
||||
|
||||
self.pulsar_host = pulsar_host
|
||||
self.pulsar_api_key = pulsar_api_key
|
||||
|
||||
if pulsar_api_key:
|
||||
auth = pulsar.AuthenticationToken(pulsar_api_key)
|
||||
self.client = pulsar.Client(
|
||||
pulsar_host,
|
||||
authentication=auth,
|
||||
logger=pulsar.ConsoleLogger(log_level.to_pulsar())
|
||||
)
|
||||
else:
|
||||
self.client = pulsar.Client(
|
||||
pulsar_host,
|
||||
listener_name=pulsar_listener,
|
||||
logger=pulsar.ConsoleLogger(log_level.to_pulsar())
|
||||
)
|
||||
|
||||
self.pulsar_listener = pulsar_listener
|
||||
|
||||
def __del__(self):
|
||||
|
||||
|
|
@ -52,6 +68,17 @@ class BaseProcessor:
|
|||
help=f'Pulsar host (default: {__class__.default_pulsar_host})',
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--pulsar-api-key',
|
||||
default=__class__.default_pulsar_api_key,
|
||||
help=f'Pulsar API key',
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--pulsar-listener',
|
||||
help=f'Pulsar listener (default: none)',
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-l', '--log-level',
|
||||
type=LogLevel,
|
||||
|
|
@ -74,11 +101,20 @@ class BaseProcessor:
|
|||
help=f'Pulsar host (default: 8000)',
|
||||
)
|
||||
|
||||
def run(self):
|
||||
async def start(self):
|
||||
pass
|
||||
|
||||
async def run(self):
|
||||
raise RuntimeError("Something should have implemented the run method")
|
||||
|
||||
@classmethod
|
||||
def start(cls, prog, doc):
|
||||
async def launch_async(cls, args):
|
||||
p = cls(**args)
|
||||
await p.start()
|
||||
await p.run()
|
||||
|
||||
@classmethod
|
||||
def launch(cls, prog, doc):
|
||||
|
||||
parser = argparse.ArgumentParser(
|
||||
prog=prog,
|
||||
|
|
@ -99,8 +135,7 @@ class BaseProcessor:
|
|||
|
||||
try:
|
||||
|
||||
p = cls(**args)
|
||||
p.run()
|
||||
asyncio.run(cls.launch_async(args))
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("Keyboard interrupt.")
|
||||
|
|
@ -118,3 +153,4 @@ class BaseProcessor:
|
|||
print("Will retry...", flush=True)
|
||||
|
||||
time.sleep(4)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,11 +1,16 @@
|
|||
|
||||
import asyncio
|
||||
from pulsar.schema import JsonSchema
|
||||
import pulsar
|
||||
from prometheus_client import Histogram, Info, Counter, Enum
|
||||
import time
|
||||
|
||||
from . base_processor import BaseProcessor
|
||||
from .. exceptions import TooManyRequests
|
||||
|
||||
default_rate_limit_retry = 10
|
||||
default_rate_limit_timeout = 7200
|
||||
|
||||
class Consumer(BaseProcessor):
|
||||
|
||||
def __init__(self, **params):
|
||||
|
|
@ -21,11 +26,18 @@ class Consumer(BaseProcessor):
|
|||
|
||||
super(Consumer, self).__init__(**params)
|
||||
|
||||
input_queue = params.get("input_queue")
|
||||
subscriber = params.get("subscriber")
|
||||
input_schema = params.get("input_schema")
|
||||
self.input_queue = params.get("input_queue")
|
||||
self.subscriber = params.get("subscriber")
|
||||
self.input_schema = params.get("input_schema")
|
||||
|
||||
if input_schema == None:
|
||||
self.rate_limit_retry = params.get(
|
||||
"rate_limit_retry", default_rate_limit_retry
|
||||
)
|
||||
self.rate_limit_timeout = params.get(
|
||||
"rate_limit_timeout", default_rate_limit_timeout
|
||||
)
|
||||
|
||||
if self.input_schema == None:
|
||||
raise RuntimeError("input_schema must be specified")
|
||||
|
||||
if not hasattr(__class__, "request_metric"):
|
||||
|
|
@ -43,18 +55,28 @@ class Consumer(BaseProcessor):
|
|||
'processing_count', 'Processing count', ["status"]
|
||||
)
|
||||
|
||||
if not hasattr(__class__, "rate_limit_metric"):
|
||||
__class__.rate_limit_metric = Counter(
|
||||
'rate_limit_count', 'Rate limit event count',
|
||||
)
|
||||
|
||||
__class__.pubsub_metric.info({
|
||||
"input_queue": input_queue,
|
||||
"subscriber": subscriber,
|
||||
"input_schema": input_schema.__name__,
|
||||
"input_queue": self.input_queue,
|
||||
"subscriber": self.subscriber,
|
||||
"input_schema": self.input_schema.__name__,
|
||||
"rate_limit_retry": str(self.rate_limit_retry),
|
||||
"rate_limit_timeout": str(self.rate_limit_timeout),
|
||||
})
|
||||
|
||||
self.consumer = self.client.subscribe(
|
||||
input_queue, subscriber,
|
||||
schema=JsonSchema(input_schema),
|
||||
self.input_queue, self.subscriber,
|
||||
consumer_type=pulsar.ConsumerType.Shared,
|
||||
schema=JsonSchema(self.input_schema),
|
||||
)
|
||||
|
||||
def run(self):
|
||||
print("Initialised consumer.", flush=True)
|
||||
|
||||
async def run(self):
|
||||
|
||||
__class__.state_metric.state('running')
|
||||
|
||||
|
|
@ -62,32 +84,62 @@ class Consumer(BaseProcessor):
|
|||
|
||||
msg = self.consumer.receive()
|
||||
|
||||
expiry = time.time() + self.rate_limit_timeout
|
||||
|
||||
# This loop is for retry on rate-limit / resource limits
|
||||
while True:
|
||||
|
||||
if time.time() > expiry:
|
||||
|
||||
print("Gave up waiting for rate-limit retry", flush=True)
|
||||
|
||||
# Message failed to be processed, this causes it to
|
||||
# be retried
|
||||
self.consumer.negative_acknowledge(msg)
|
||||
|
||||
__class__.processing_metric.labels(status="error").inc()
|
||||
|
||||
# Break out of retry loop, processes next message
|
||||
break
|
||||
|
||||
try:
|
||||
|
||||
with __class__.request_metric.time():
|
||||
self.handle(msg)
|
||||
await self.handle(msg)
|
||||
|
||||
# Acknowledge successful processing of the message
|
||||
self.consumer.acknowledge(msg)
|
||||
|
||||
__class__.processing_metric.labels(status="success").inc()
|
||||
|
||||
# Break out of retry loop
|
||||
break
|
||||
|
||||
except TooManyRequests:
|
||||
self.consumer.negative_acknowledge(msg)
|
||||
print("TooManyRequests: will retry")
|
||||
__class__.processing_metric.labels(status="rate-limit").inc()
|
||||
time.sleep(5)
|
||||
|
||||
print("TooManyRequests: will retry...", flush=True)
|
||||
|
||||
__class__.rate_limit_metric.inc()
|
||||
|
||||
# Sleep
|
||||
time.sleep(self.rate_limit_retry)
|
||||
|
||||
# Contine from retry loop, just causes a reprocessing
|
||||
continue
|
||||
|
||||
except Exception as e:
|
||||
|
||||
print("Exception:", e, flush=True)
|
||||
|
||||
# Message failed to be processed
|
||||
# Message failed to be processed, this causes it to
|
||||
# be retried
|
||||
self.consumer.negative_acknowledge(msg)
|
||||
|
||||
__class__.processing_metric.labels(status="error").inc()
|
||||
|
||||
# Break out of retry loop, processes next message
|
||||
break
|
||||
|
||||
@staticmethod
|
||||
def add_args(parser, default_input_queue, default_subscriber):
|
||||
|
||||
|
|
@ -105,3 +157,17 @@ class Consumer(BaseProcessor):
|
|||
help=f'Queue subscriber name (default: {default_subscriber})'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--rate-limit-retry',
|
||||
type=int,
|
||||
default=default_rate_limit_retry,
|
||||
help=f'Rate limit retry (default: {default_rate_limit_retry})'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--rate-limit-timeout',
|
||||
type=int,
|
||||
default=default_rate_limit_timeout,
|
||||
help=f'Rate limit timeout (default: {default_rate_limit_timeout})'
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,113 +1,48 @@
|
|||
|
||||
from pulsar.schema import JsonSchema
|
||||
import pulsar
|
||||
from prometheus_client import Histogram, Info, Counter, Enum
|
||||
import time
|
||||
|
||||
from . base_processor import BaseProcessor
|
||||
from . consumer import Consumer
|
||||
from .. exceptions import TooManyRequests
|
||||
|
||||
# FIXME: Derive from consumer? And producer?
|
||||
|
||||
class ConsumerProducer(BaseProcessor):
|
||||
class ConsumerProducer(Consumer):
|
||||
|
||||
def __init__(self, **params):
|
||||
|
||||
if not hasattr(__class__, "state_metric"):
|
||||
__class__.state_metric = Enum(
|
||||
'processor_state', 'Processor state',
|
||||
states=['starting', 'running', 'stopped']
|
||||
)
|
||||
__class__.state_metric.state('starting')
|
||||
super(ConsumerProducer, self).__init__(**params)
|
||||
|
||||
__class__.state_metric.state('starting')
|
||||
|
||||
input_queue = params.get("input_queue")
|
||||
output_queue = params.get("output_queue")
|
||||
subscriber = params.get("subscriber")
|
||||
input_schema = params.get("input_schema")
|
||||
output_schema = params.get("output_schema")
|
||||
|
||||
if not hasattr(__class__, "request_metric"):
|
||||
__class__.request_metric = Histogram(
|
||||
'request_latency', 'Request latency (seconds)'
|
||||
)
|
||||
self.output_queue = params.get("output_queue")
|
||||
self.output_schema = params.get("output_schema")
|
||||
|
||||
if not hasattr(__class__, "output_metric"):
|
||||
__class__.output_metric = Counter(
|
||||
'output_count', 'Output items created'
|
||||
)
|
||||
|
||||
if not hasattr(__class__, "pubsub_metric"):
|
||||
__class__.pubsub_metric = Info(
|
||||
'pubsub', 'Pub/sub configuration'
|
||||
)
|
||||
|
||||
if not hasattr(__class__, "processing_metric"):
|
||||
__class__.processing_metric = Counter(
|
||||
'processing_count', 'Processing count', ["status"]
|
||||
)
|
||||
|
||||
__class__.pubsub_metric.info({
|
||||
"input_queue": input_queue,
|
||||
"output_queue": output_queue,
|
||||
"subscriber": subscriber,
|
||||
"input_schema": input_schema.__name__,
|
||||
"output_schema": output_schema.__name__,
|
||||
"input_queue": self.input_queue,
|
||||
"output_queue": self.output_queue,
|
||||
"subscriber": self.subscriber,
|
||||
"input_schema": self.input_schema.__name__,
|
||||
"output_schema": self.output_schema.__name__,
|
||||
"rate_limit_retry": str(self.rate_limit_retry),
|
||||
"rate_limit_timeout": str(self.rate_limit_timeout),
|
||||
})
|
||||
|
||||
super(ConsumerProducer, self).__init__(**params)
|
||||
|
||||
if input_schema == None:
|
||||
raise RuntimeError("input_schema must be specified")
|
||||
|
||||
if output_schema == None:
|
||||
if self.output_schema == None:
|
||||
raise RuntimeError("output_schema must be specified")
|
||||
|
||||
self.producer = self.client.create_producer(
|
||||
topic=output_queue,
|
||||
schema=JsonSchema(output_schema),
|
||||
topic=self.output_queue,
|
||||
schema=JsonSchema(self.output_schema),
|
||||
chunking_enabled=True,
|
||||
)
|
||||
|
||||
self.consumer = self.client.subscribe(
|
||||
input_queue, subscriber,
|
||||
schema=JsonSchema(input_schema),
|
||||
)
|
||||
print("Initialised consumer/producer.")
|
||||
|
||||
def run(self):
|
||||
|
||||
__class__.state_metric.state('running')
|
||||
|
||||
while True:
|
||||
|
||||
msg = self.consumer.receive()
|
||||
|
||||
try:
|
||||
|
||||
with __class__.request_metric.time():
|
||||
resp = self.handle(msg)
|
||||
|
||||
# Acknowledge successful processing of the message
|
||||
self.consumer.acknowledge(msg)
|
||||
|
||||
__class__.processing_metric.labels(status="success").inc()
|
||||
|
||||
except TooManyRequests:
|
||||
self.consumer.negative_acknowledge(msg)
|
||||
print("TooManyRequests: will retry")
|
||||
__class__.processing_metric.labels(status="rate-limit").inc()
|
||||
time.sleep(5)
|
||||
continue
|
||||
|
||||
except Exception as e:
|
||||
|
||||
print("Exception:", e, flush=True)
|
||||
|
||||
# Message failed to be processed
|
||||
self.consumer.negative_acknowledge(msg)
|
||||
|
||||
__class__.processing_metric.labels(status="error").inc()
|
||||
|
||||
def send(self, msg, properties={}):
|
||||
async def send(self, msg, properties={}):
|
||||
self.producer.send(msg, properties)
|
||||
__class__.output_metric.inc()
|
||||
|
||||
|
|
@ -117,19 +52,7 @@ class ConsumerProducer(BaseProcessor):
|
|||
default_output_queue,
|
||||
):
|
||||
|
||||
BaseProcessor.add_args(parser)
|
||||
|
||||
parser.add_argument(
|
||||
'-i', '--input-queue',
|
||||
default=default_input_queue,
|
||||
help=f'Input queue (default: {default_input_queue})'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-s', '--subscriber',
|
||||
default=default_subscriber,
|
||||
help=f'Queue subscriber name (default: {default_subscriber})'
|
||||
)
|
||||
Consumer.add_args(parser, default_input_queue, default_subscriber)
|
||||
|
||||
parser.add_argument(
|
||||
'-o', '--output-queue',
|
||||
|
|
|
|||
|
|
@ -34,9 +34,10 @@ class Producer(BaseProcessor):
|
|||
self.producer = self.client.create_producer(
|
||||
topic=output_queue,
|
||||
schema=JsonSchema(output_schema),
|
||||
chunking_enabled=True,
|
||||
)
|
||||
|
||||
def send(self, msg, properties={}):
|
||||
async def send(self, msg, properties={}):
|
||||
self.producer.send(msg, properties)
|
||||
__class__.output_metric.inc()
|
||||
|
||||
|
|
|
|||
|
|
@ -6,37 +6,43 @@ import threading
|
|||
|
||||
class Publisher:
|
||||
|
||||
def __init__(self, pulsar_host, topic, schema=None, max_size=10,
|
||||
chunking_enabled=False):
|
||||
self.pulsar_host = pulsar_host
|
||||
def __init__(self, pulsar_client, topic, schema=None, max_size=10,
|
||||
chunking_enabled=True):
|
||||
self.client = pulsar_client
|
||||
self.topic = topic
|
||||
self.schema = schema
|
||||
self.q = queue.Queue(maxsize=max_size)
|
||||
self.chunking_enabled = chunking_enabled
|
||||
self.running = True
|
||||
|
||||
def start(self):
|
||||
self.task = threading.Thread(target=self.run)
|
||||
self.task.start()
|
||||
|
||||
def stop(self):
|
||||
self.running = False
|
||||
|
||||
def join(self):
|
||||
self.stop()
|
||||
self.task.join()
|
||||
|
||||
def run(self):
|
||||
|
||||
while True:
|
||||
while self.running:
|
||||
|
||||
try:
|
||||
|
||||
client = pulsar.Client(
|
||||
self.pulsar_host,
|
||||
)
|
||||
|
||||
producer = client.create_producer(
|
||||
producer = self.client.create_producer(
|
||||
topic=self.topic,
|
||||
schema=self.schema,
|
||||
chunking_enabled=self.chunking_enabled,
|
||||
)
|
||||
|
||||
while True:
|
||||
while self.running:
|
||||
|
||||
id, item = self.q.get()
|
||||
try:
|
||||
id, item = self.q.get(timeout=0.5)
|
||||
except queue.Empty:
|
||||
continue
|
||||
|
||||
if id:
|
||||
producer.send(item, { "id": id })
|
||||
|
|
@ -51,3 +57,5 @@ class Publisher:
|
|||
|
||||
def send(self, id, msg):
|
||||
self.q.put((id, msg))
|
||||
|
||||
|
||||
|
|
@ -6,9 +6,9 @@ import time
|
|||
|
||||
class Subscriber:
|
||||
|
||||
def __init__(self, pulsar_host, topic, subscription, consumer_name,
|
||||
def __init__(self, pulsar_client, topic, subscription, consumer_name,
|
||||
schema=None, max_size=100):
|
||||
self.pulsar_host = pulsar_host
|
||||
self.client = pulsar_client
|
||||
self.topic = topic
|
||||
self.subscription = subscription
|
||||
self.consumer_name = consumer_name
|
||||
|
|
@ -17,29 +17,32 @@ class Subscriber:
|
|||
self.full = {}
|
||||
self.max_size = max_size
|
||||
self.lock = threading.Lock()
|
||||
self.running = True
|
||||
|
||||
def start(self):
|
||||
self.task = threading.Thread(target=self.run)
|
||||
self.task.start()
|
||||
|
||||
def stop(self):
|
||||
self.running = False
|
||||
|
||||
def join(self):
|
||||
self.task.join()
|
||||
|
||||
def run(self):
|
||||
|
||||
while True:
|
||||
while self.running:
|
||||
|
||||
try:
|
||||
|
||||
client = pulsar.Client(
|
||||
self.pulsar_host,
|
||||
)
|
||||
|
||||
consumer = client.subscribe(
|
||||
consumer = self.client.subscribe(
|
||||
topic=self.topic,
|
||||
subscription_name=self.subscription,
|
||||
consumer_name=self.consumer_name,
|
||||
schema=self.schema,
|
||||
)
|
||||
|
||||
while True:
|
||||
while self.running:
|
||||
|
||||
msg = consumer.receive()
|
||||
|
||||
|
|
@ -57,12 +60,14 @@ class Subscriber:
|
|||
|
||||
if id in self.q:
|
||||
try:
|
||||
# FIXME: Timeout means data goes missing
|
||||
self.q[id].put(value, timeout=0.5)
|
||||
except:
|
||||
pass
|
||||
|
||||
for q in self.full.values():
|
||||
try:
|
||||
# FIXME: Timeout means data goes missing
|
||||
q.put(value, timeout=0.5)
|
||||
except:
|
||||
pass
|
||||
|
|
@ -20,6 +20,7 @@ class AgentClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue is None: input_queue = agent_request_queue
|
||||
|
|
@ -33,6 +34,7 @@ class AgentClient(BaseClient):
|
|||
pulsar_host=pulsar_host,
|
||||
input_schema=AgentRequest,
|
||||
output_schema=AgentResponse,
|
||||
pulsar_api_key=pulsar_api_key
|
||||
)
|
||||
|
||||
def request(
|
||||
|
|
|
|||
|
|
@ -27,6 +27,7 @@ class BaseClient:
|
|||
input_schema=None,
|
||||
output_schema=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None: raise RuntimeError("Need input_queue")
|
||||
|
|
@ -37,9 +38,17 @@ class BaseClient:
|
|||
if subscriber == None:
|
||||
subscriber = str(uuid.uuid4())
|
||||
|
||||
if pulsar_api_key:
|
||||
auth = pulsar.AuthenticationToken(pulsar_api_key)
|
||||
self.client = pulsar.Client(
|
||||
pulsar_host,
|
||||
logger=pulsar.ConsoleLogger(log_level),
|
||||
authentication=auth,
|
||||
)
|
||||
else:
|
||||
self.client = pulsar.Client(
|
||||
pulsar_host,
|
||||
logger=pulsar.ConsoleLogger(log_level)
|
||||
)
|
||||
|
||||
self.producer = self.client.create_producer(
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ class DocumentEmbeddingsClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None:
|
||||
|
|
@ -34,12 +35,17 @@ class DocumentEmbeddingsClient(BaseClient):
|
|||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_host=pulsar_host,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
input_schema=DocumentEmbeddingsRequest,
|
||||
output_schema=DocumentEmbeddingsResponse,
|
||||
)
|
||||
|
||||
def request(self, vectors, limit=10, timeout=300):
|
||||
def request(
|
||||
self, vectors, user="trustgraph", collection="default",
|
||||
limit=10, timeout=300
|
||||
):
|
||||
return self.call(
|
||||
user=user, collection=collection,
|
||||
vectors=vectors, limit=limit, timeout=timeout
|
||||
).documents
|
||||
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ class DocumentRagClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None:
|
||||
|
|
@ -34,6 +35,7 @@ class DocumentRagClient(BaseClient):
|
|||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_host=pulsar_host,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
input_schema=DocumentRagQuery,
|
||||
output_schema=DocumentRagResponse,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ class EmbeddingsClient(BaseClient):
|
|||
output_queue=None,
|
||||
subscriber=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None:
|
||||
|
|
@ -34,6 +35,7 @@ class EmbeddingsClient(BaseClient):
|
|||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_host=pulsar_host,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
input_schema=EmbeddingsRequest,
|
||||
output_schema=EmbeddingsResponse,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ class GraphEmbeddingsClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None:
|
||||
|
|
@ -34,6 +35,7 @@ class GraphEmbeddingsClient(BaseClient):
|
|||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_host=pulsar_host,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
input_schema=GraphEmbeddingsRequest,
|
||||
output_schema=GraphEmbeddingsResponse,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ class GraphRagClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None:
|
||||
|
|
@ -34,6 +35,7 @@ class GraphRagClient(BaseClient):
|
|||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_host=pulsar_host,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
input_schema=GraphRagQuery,
|
||||
output_schema=GraphRagResponse,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ class LlmClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue is None: input_queue = text_completion_request_queue
|
||||
|
|
@ -31,6 +32,7 @@ class LlmClient(BaseClient):
|
|||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_host=pulsar_host,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
input_schema=TextCompletionRequest,
|
||||
output_schema=TextCompletionResponse,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -39,6 +39,7 @@ class PromptClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None:
|
||||
|
|
@ -53,6 +54,7 @@ class PromptClient(BaseClient):
|
|||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_host=pulsar_host,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
input_schema=PromptRequest,
|
||||
output_schema=PromptResponse,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -21,6 +21,7 @@ class TriplesQueryClient(BaseClient):
|
|||
input_queue=None,
|
||||
output_queue=None,
|
||||
pulsar_host="pulsar://pulsar:6650",
|
||||
pulsar_api_key=None,
|
||||
):
|
||||
|
||||
if input_queue == None:
|
||||
|
|
@ -34,6 +35,7 @@ class TriplesQueryClient(BaseClient):
|
|||
subscriber=subscriber,
|
||||
input_queue=input_queue,
|
||||
output_queue=output_queue,
|
||||
pulsar_api_key=pulsar_api_key,
|
||||
pulsar_host=pulsar_host,
|
||||
input_schema=TriplesQueryRequest,
|
||||
output_schema=TriplesQueryResponse,
|
||||
|
|
|
|||
|
|
@ -8,7 +8,6 @@ class LlmError(Exception):
|
|||
class ParseError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
|
||||
|
||||
class RequestError(Exception):
|
||||
pass
|
||||
|
||||
|
|
|
|||
|
|
@ -10,5 +10,6 @@ from . retrieval import *
|
|||
from . metadata import *
|
||||
from . agent import *
|
||||
from . lookup import *
|
||||
from . library import *
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -35,14 +35,18 @@ chunk_ingest_queue = topic('chunk-load')
|
|||
|
||||
############################################################################
|
||||
|
||||
# Chunk embeddings are an embeddings associated with a text chunk
|
||||
# Document embeddings are embeddings associated with a chunk
|
||||
|
||||
class ChunkEmbeddings(Record):
|
||||
metadata = Metadata()
|
||||
vectors = Array(Array(Double()))
|
||||
chunk = Bytes()
|
||||
vectors = Array(Array(Double()))
|
||||
|
||||
chunk_embeddings_ingest_queue = topic('chunk-embeddings-load')
|
||||
# This is a 'batching' mechanism for the above data
|
||||
class DocumentEmbeddings(Record):
|
||||
metadata = Metadata()
|
||||
chunks = Array(ChunkEmbeddings())
|
||||
|
||||
document_embeddings_store_queue = topic('document-embeddings-store')
|
||||
|
||||
############################################################################
|
||||
|
||||
|
|
@ -51,6 +55,8 @@ chunk_embeddings_ingest_queue = topic('chunk-embeddings-load')
|
|||
class DocumentEmbeddingsRequest(Record):
|
||||
vectors = Array(Array(Double()))
|
||||
limit = Integer()
|
||||
user = String()
|
||||
collection = String()
|
||||
|
||||
class DocumentEmbeddingsResponse(Record):
|
||||
error = Error()
|
||||
|
|
@ -62,3 +68,4 @@ document_embeddings_request_queue = topic(
|
|||
document_embeddings_response_queue = topic(
|
||||
'doc-embeddings', kind='non-persistent', namespace='response',
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -7,12 +7,31 @@ from . metadata import Metadata
|
|||
|
||||
############################################################################
|
||||
|
||||
# Entity context are an entity associated with textual context
|
||||
|
||||
class EntityContext(Record):
|
||||
entity = Value()
|
||||
context = String()
|
||||
|
||||
# This is a 'batching' mechanism for the above data
|
||||
class EntityContexts(Record):
|
||||
metadata = Metadata()
|
||||
entities = Array(EntityContext())
|
||||
|
||||
entity_contexts_ingest_queue = topic('entity-contexts-load')
|
||||
|
||||
############################################################################
|
||||
|
||||
# Graph embeddings are embeddings associated with a graph entity
|
||||
|
||||
class EntityEmbeddings(Record):
|
||||
entity = Value()
|
||||
vectors = Array(Array(Double()))
|
||||
|
||||
# This is a 'batching' mechanism for the above data
|
||||
class GraphEmbeddings(Record):
|
||||
metadata = Metadata()
|
||||
vectors = Array(Array(Double()))
|
||||
entity = Value()
|
||||
entities = Array(EntityEmbeddings())
|
||||
|
||||
graph_embeddings_store_queue = topic('graph-embeddings-store')
|
||||
|
||||
|
|
|
|||
74
trustgraph-base/trustgraph/schema/library.py
Normal file
74
trustgraph-base/trustgraph/schema/library.py
Normal file
|
|
@ -0,0 +1,74 @@
|
|||
|
||||
from pulsar.schema import Record, Bytes, String, Array, Long
|
||||
from . types import Triple
|
||||
from . topic import topic
|
||||
from . types import Error
|
||||
from . metadata import Metadata
|
||||
from . documents import Document, TextDocument
|
||||
|
||||
# add
|
||||
# -> (id, document)
|
||||
# <- ()
|
||||
# <- (error)
|
||||
|
||||
# list
|
||||
# -> (user, collection?)
|
||||
# <- (info)
|
||||
# <- (error)
|
||||
|
||||
# add(Metadata, Bytes) : error?
|
||||
# copy(id, user, collection)
|
||||
# move(id, user, collection)
|
||||
# delete(id)
|
||||
# get(id) : Bytes
|
||||
# reindex(id)
|
||||
# list(user, collection) : id[]
|
||||
# info(id[]) : DocumentInfo[]
|
||||
# search(<key,op,value>[]) : id[]
|
||||
|
||||
class DocumentPackage(Record):
|
||||
id = String()
|
||||
document = Bytes()
|
||||
kind = String()
|
||||
user = String()
|
||||
collection = String()
|
||||
title = String()
|
||||
comments = String()
|
||||
time = Long()
|
||||
metadata = Array(Triple())
|
||||
|
||||
class DocumentInfo(Record):
|
||||
id = String()
|
||||
kind = String()
|
||||
user = String()
|
||||
collection = String()
|
||||
title = String()
|
||||
comments = String()
|
||||
time = Long()
|
||||
metadata = Array(Triple())
|
||||
|
||||
class Criteria(Record):
|
||||
key = String()
|
||||
value = String()
|
||||
operator = String()
|
||||
|
||||
class LibrarianRequest(Record):
|
||||
operation = String()
|
||||
id = String()
|
||||
document = DocumentPackage()
|
||||
user = String()
|
||||
collection = String()
|
||||
criteria = Array(Criteria())
|
||||
|
||||
class LibrarianResponse(Record):
|
||||
error = Error()
|
||||
document = DocumentPackage()
|
||||
info = Array(DocumentInfo())
|
||||
|
||||
librarian_request_queue = topic(
|
||||
'librarian', kind='non-persistent', namespace='request'
|
||||
)
|
||||
librarian_response_queue = topic(
|
||||
'librarian', kind='non-persistent', namespace='response',
|
||||
)
|
||||
|
||||
|
|
@ -11,6 +11,10 @@ class GraphRagQuery(Record):
|
|||
query = String()
|
||||
user = String()
|
||||
collection = String()
|
||||
entity_limit = Integer()
|
||||
triple_limit = Integer()
|
||||
max_subgraph_size = Integer()
|
||||
max_path_length = Integer()
|
||||
|
||||
class GraphRagResponse(Record):
|
||||
error = Error()
|
||||
|
|
@ -31,6 +35,7 @@ class DocumentRagQuery(Record):
|
|||
query = String()
|
||||
user = String()
|
||||
collection = String()
|
||||
doc_limit = Integer()
|
||||
|
||||
class DocumentRagResponse(Record):
|
||||
error = Error()
|
||||
|
|
|
|||
|
|
@ -34,7 +34,7 @@ setuptools.setup(
|
|||
python_requires='>=3.8',
|
||||
download_url = "https://github.com/trustgraph-ai/trustgraph/archive/refs/tags/v" + version + ".tar.gz",
|
||||
install_requires=[
|
||||
"trustgraph-base>=0.18,<0.19",
|
||||
"trustgraph-base>=0.21,<0.22",
|
||||
"pulsar-client",
|
||||
"prometheus-client",
|
||||
"boto3",
|
||||
|
|
|
|||
|
|
@ -8,6 +8,7 @@ import boto3
|
|||
import json
|
||||
from prometheus_client import Histogram
|
||||
import os
|
||||
import enum
|
||||
|
||||
from .... schema import TextCompletionRequest, TextCompletionResponse, Error
|
||||
from .... schema import text_completion_request_queue
|
||||
|
|
@ -24,32 +25,163 @@ default_subscriber = module
|
|||
default_model = 'mistral.mistral-large-2407-v1:0'
|
||||
default_temperature = 0.0
|
||||
default_max_output = 2048
|
||||
default_aws_id_key = os.getenv("AWS_ID_KEY", None)
|
||||
default_aws_secret = os.getenv("AWS_SECRET", None)
|
||||
default_aws_region = os.getenv("AWS_REGION", 'us-west-2')
|
||||
default_top_p = 0.99
|
||||
default_top_k = 40
|
||||
|
||||
# Actually, these could all just be None, no need to get environment
|
||||
# variables, as Boto3 would pick all these up if not passed in as args
|
||||
default_access_key_id = os.getenv("AWS_ACCESS_KEY_ID", None)
|
||||
default_secret_access_key = os.getenv("AWS_SECRET_ACCESS_KEY", None)
|
||||
default_session_token = os.getenv("AWS_SESSION_TOKEN", None)
|
||||
default_profile = os.getenv("AWS_PROFILE", None)
|
||||
default_region = os.getenv("AWS_DEFAULT_REGION", None)
|
||||
|
||||
# Variant API handling depends on the model type
|
||||
|
||||
class ModelHandler:
|
||||
def __init__(self):
|
||||
self.temperature = default_temperature
|
||||
self.max_output = default_max_output
|
||||
self.top_p = default_top_p
|
||||
self.top_k = default_top_k
|
||||
def set_temperature(self, temperature):
|
||||
self.temperature = temperature
|
||||
def set_max_output(self, max_output):
|
||||
self.max_output = max_output
|
||||
def set_top_p(self, top_p):
|
||||
self.top_p = top_p
|
||||
def set_top_k(self, top_k):
|
||||
self.top_k = top_k
|
||||
def encode_request(self, system, prompt):
|
||||
raise RuntimeError("format_request not implemented")
|
||||
def decode_response(self, response):
|
||||
raise RuntimeError("format_request not implemented")
|
||||
|
||||
class Mistral(ModelHandler):
|
||||
def __init__(self):
|
||||
self.top_p = 0.99
|
||||
self.top_k = 40
|
||||
def encode_request(self, system, prompt):
|
||||
return json.dumps({
|
||||
"prompt": f"{system}\n\n{prompt}",
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": self.top_p,
|
||||
"top_k": self.top_k,
|
||||
})
|
||||
def decode_response(self, response):
|
||||
response_body = json.loads(response.get("body").read())
|
||||
return response_body['outputs'][0]['text']
|
||||
|
||||
# Llama 3
|
||||
class Meta(ModelHandler):
|
||||
def __init__(self):
|
||||
self.top_p = 0.95
|
||||
def encode_request(self, system, prompt):
|
||||
return json.dumps({
|
||||
"prompt": f"{system}\n\n{prompt}",
|
||||
"max_gen_len": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": self.top_p,
|
||||
})
|
||||
def decode_response(self, response):
|
||||
model_response = json.loads(response["body"].read())
|
||||
return model_response["generation"]
|
||||
|
||||
class Anthropic(ModelHandler):
|
||||
def __init__(self):
|
||||
self.top_p = 0.999
|
||||
def encode_request(self, system, prompt):
|
||||
return json.dumps({
|
||||
"anthropic_version": "bedrock-2023-05-31",
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": self.top_p,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": f"{system}\n\n{prompt}",
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
})
|
||||
def decode_response(self, response):
|
||||
model_response = json.loads(response["body"].read())
|
||||
return model_response['content'][0]['text']
|
||||
|
||||
class Ai21(ModelHandler):
|
||||
def __init__(self):
|
||||
self.top_p = 0.9
|
||||
def encode_request(self, system, prompt):
|
||||
return json.dumps({
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": self.top_p,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": f"{system}\n\n{prompt}"
|
||||
}
|
||||
]
|
||||
})
|
||||
def decode_response(self, response):
|
||||
content = response['body'].read()
|
||||
content_str = content.decode('utf-8')
|
||||
content_json = json.loads(content_str)
|
||||
return content_json['choices'][0]['message']['content']
|
||||
|
||||
class Cohere(ModelHandler):
|
||||
def encode_request(self, system, prompt):
|
||||
return json.dumps({
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"message": f"{system}\n\n{prompt}",
|
||||
})
|
||||
def decode_response(self, response):
|
||||
content = response['body'].read()
|
||||
content_str = content.decode('utf-8')
|
||||
content_json = json.loads(content_str)
|
||||
return content_json['text']
|
||||
|
||||
Default=Mistral
|
||||
|
||||
class Processor(ConsumerProducer):
|
||||
|
||||
def __init__(self, **params):
|
||||
|
||||
print(params)
|
||||
|
||||
input_queue = params.get("input_queue", default_input_queue)
|
||||
output_queue = params.get("output_queue", default_output_queue)
|
||||
subscriber = params.get("subscriber", default_subscriber)
|
||||
|
||||
model = params.get("model", default_model)
|
||||
aws_id_key = params.get("aws_id_key", default_aws_id_key)
|
||||
aws_secret = params.get("aws_secret", default_aws_secret)
|
||||
aws_region = params.get("aws_region", default_aws_region)
|
||||
temperature = params.get("temperature", default_temperature)
|
||||
max_output = params.get("max_output", default_max_output)
|
||||
|
||||
if aws_id_key is None:
|
||||
raise RuntimeError("AWS ID not specified")
|
||||
aws_access_key_id = params.get(
|
||||
"aws_access_key_id", default_access_key_id
|
||||
)
|
||||
|
||||
if aws_secret is None:
|
||||
raise RuntimeError("AWS secret not specified")
|
||||
aws_secret_access_key = params.get(
|
||||
"aws_secret_access_key", default_secret_access_key
|
||||
)
|
||||
|
||||
if aws_region is None:
|
||||
raise RuntimeError("AWS region not specified")
|
||||
aws_session_token = params.get(
|
||||
"aws_session_token", default_session_token
|
||||
)
|
||||
|
||||
aws_region = params.get(
|
||||
"aws_region", default_region
|
||||
)
|
||||
|
||||
aws_profile = params.get(
|
||||
"aws_profile", default_profile
|
||||
)
|
||||
|
||||
super(Processor, self).__init__(
|
||||
**params | {
|
||||
|
|
@ -81,17 +213,51 @@ class Processor(ConsumerProducer):
|
|||
self.temperature = temperature
|
||||
self.max_output = max_output
|
||||
|
||||
self.variant = self.determine_variant(self.model)()
|
||||
self.variant.set_temperature(temperature)
|
||||
self.variant.set_max_output(max_output)
|
||||
|
||||
self.session = boto3.Session(
|
||||
aws_access_key_id=aws_id_key,
|
||||
aws_secret_access_key=aws_secret,
|
||||
region_name=aws_region
|
||||
aws_access_key_id=aws_access_key_id,
|
||||
aws_secret_access_key=aws_secret_access_key,
|
||||
aws_session_token=aws_session_token,
|
||||
profile_name=aws_profile,
|
||||
region_name=aws_region,
|
||||
)
|
||||
|
||||
self.bedrock = self.session.client(service_name='bedrock-runtime')
|
||||
|
||||
print("Initialised", flush=True)
|
||||
|
||||
def handle(self, msg):
|
||||
def determine_variant(self, model):
|
||||
|
||||
# FIXME: Missing, Amazon models, Deepseek
|
||||
|
||||
# This set of conditions deals with normal bedrock on-demand usage
|
||||
if self.model.startswith("mistral"):
|
||||
return Mistral
|
||||
elif self.model.startswith("meta"):
|
||||
return Meta
|
||||
elif self.model.startswith("anthropic"):
|
||||
return Anthropic
|
||||
elif self.model.startswith("ai21"):
|
||||
return Ai21
|
||||
elif self.model.startswith("cohere"):
|
||||
return Cohere
|
||||
|
||||
# The inference profiles
|
||||
if self.model.startswith("us.meta"):
|
||||
return Meta
|
||||
elif self.model.startswith("us.anthropic"):
|
||||
return Anthropic
|
||||
elif self.model.startswith("eu.meta"):
|
||||
return Meta
|
||||
elif self.model.startswith("eu.anthropic"):
|
||||
return Anthropic
|
||||
|
||||
return Default
|
||||
|
||||
async def handle(self, msg):
|
||||
|
||||
v = msg.value()
|
||||
|
||||
|
|
@ -101,126 +267,23 @@ class Processor(ConsumerProducer):
|
|||
|
||||
print(f"Handling prompt {id}...", flush=True)
|
||||
|
||||
prompt = v.system + "\n\n" + v.prompt
|
||||
|
||||
try:
|
||||
|
||||
# Mistral Input Format
|
||||
if self.model.startswith("mistral"):
|
||||
promptbody = json.dumps({
|
||||
"prompt": prompt,
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": 0.99,
|
||||
"top_k": 40
|
||||
})
|
||||
|
||||
# Llama 3.1 Input Format
|
||||
elif self.model.startswith("meta"):
|
||||
promptbody = json.dumps({
|
||||
"prompt": prompt,
|
||||
"max_gen_len": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": 0.95,
|
||||
})
|
||||
|
||||
# Anthropic Input Format
|
||||
elif self.model.startswith("anthropic"):
|
||||
promptbody = json.dumps({
|
||||
"anthropic_version": "bedrock-2023-05-31",
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": 0.999,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": prompt
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
})
|
||||
|
||||
# Jamba Input Format
|
||||
elif self.model.startswith("ai21"):
|
||||
promptbody = json.dumps({
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": 0.9,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": prompt
|
||||
}
|
||||
]
|
||||
})
|
||||
|
||||
# Cohere Input Format
|
||||
elif self.model.startswith("cohere"):
|
||||
promptbody = json.dumps({
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"message": prompt
|
||||
})
|
||||
|
||||
# Use Mistral format as defualt
|
||||
else:
|
||||
promptbody = json.dumps({
|
||||
"prompt": prompt,
|
||||
"max_tokens": self.max_output,
|
||||
"temperature": self.temperature,
|
||||
"top_p": 0.99,
|
||||
"top_k": 40
|
||||
})
|
||||
promptbody = self.variant.encode_request(v.system, v.prompt)
|
||||
|
||||
accept = 'application/json'
|
||||
contentType = 'application/json'
|
||||
|
||||
# FIXME: Consider catching request limits and raise TooManyRequests
|
||||
# See https://boto3.amazonaws.com/v1/documentation/api/latest/guide/retries.html
|
||||
|
||||
with __class__.text_completion_metric.time():
|
||||
response = self.bedrock.invoke_model(
|
||||
body=promptbody, modelId=self.model, accept=accept,
|
||||
body=promptbody,
|
||||
modelId=self.model,
|
||||
accept=accept,
|
||||
contentType=contentType
|
||||
)
|
||||
|
||||
# Mistral Response Structure
|
||||
if self.model.startswith("mistral"):
|
||||
response_body = json.loads(response.get("body").read())
|
||||
outputtext = response_body['outputs'][0]['text']
|
||||
|
||||
# Claude Response Structure
|
||||
elif self.model.startswith("anthropic"):
|
||||
model_response = json.loads(response["body"].read())
|
||||
outputtext = model_response['content'][0]['text']
|
||||
|
||||
# Llama 3.1 Response Structure
|
||||
elif self.model.startswith("meta"):
|
||||
model_response = json.loads(response["body"].read())
|
||||
outputtext = model_response["generation"]
|
||||
|
||||
# Jamba Response Structure
|
||||
elif self.model.startswith("ai21"):
|
||||
content = response['body'].read()
|
||||
content_str = content.decode('utf-8')
|
||||
content_json = json.loads(content_str)
|
||||
outputtext = content_json['choices'][0]['message']['content']
|
||||
|
||||
# Cohere Input Format
|
||||
elif self.model.startswith("cohere"):
|
||||
content = response['body'].read()
|
||||
content_str = content.decode('utf-8')
|
||||
content_json = json.loads(content_str)
|
||||
outputtext = content_json['text']
|
||||
|
||||
# Use Mistral as default
|
||||
else:
|
||||
response_body = json.loads(response.get("body").read())
|
||||
outputtext = response_body['outputs'][0]['text']
|
||||
# Response structure decode
|
||||
outputtext = self.variant.decode_response(response)
|
||||
|
||||
metadata = response['ResponseMetadata']['HTTPHeaders']
|
||||
inputtokens = int(metadata['x-amzn-bedrock-input-token-count'])
|
||||
|
|
@ -243,30 +306,18 @@ class Processor(ConsumerProducer):
|
|||
|
||||
print("Done.", flush=True)
|
||||
|
||||
except self.bedrock.exceptions.ThrottlingException as e:
|
||||
|
||||
# FIXME: Wrong exception, don't know what Bedrock throws
|
||||
# for a rate limit
|
||||
except TooManyRequests:
|
||||
print("Hit rate limit:", e, flush=True)
|
||||
|
||||
print("Send rate limit response...", flush=True)
|
||||
|
||||
r = TextCompletionResponse(
|
||||
error=Error(
|
||||
type = "rate-limit",
|
||||
message = str(e),
|
||||
),
|
||||
response=None,
|
||||
in_token=None,
|
||||
out_token=None,
|
||||
model=None,
|
||||
)
|
||||
|
||||
self.producer.send(r, properties={"id": id})
|
||||
|
||||
self.consumer.acknowledge(msg)
|
||||
# Leave rate limit retries to the base handler
|
||||
raise TooManyRequests()
|
||||
|
||||
except Exception as e:
|
||||
|
||||
# Apart from rate limits, treat all exceptions as unrecoverable
|
||||
|
||||
print(type(e))
|
||||
print(f"Exception: {e}")
|
||||
|
||||
print("Send error response...", flush=True)
|
||||
|
|
@ -299,21 +350,27 @@ class Processor(ConsumerProducer):
|
|||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-z', '--aws-id-key',
|
||||
default=default_aws_id_key,
|
||||
help=f'AWS ID Key'
|
||||
'-z', '--aws-access-key-id',
|
||||
default=default_access_key_id,
|
||||
help=f'AWS access key ID'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-k', '--aws-secret',
|
||||
default=default_aws_secret,
|
||||
help=f'AWS Secret Key'
|
||||
'-k', '--aws-secret-access-key',
|
||||
default=default_secret_access_key,
|
||||
help=f'AWS secret access key'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-r', '--aws-region',
|
||||
default=default_aws_region,
|
||||
help=f'AWS Region'
|
||||
default=default_region,
|
||||
help=f'AWS region'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'--aws-profile', '--profile',
|
||||
default=default_profile,
|
||||
help=f'AWS profile name'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
|
|
@ -332,5 +389,5 @@ class Processor(ConsumerProducer):
|
|||
|
||||
def run():
|
||||
|
||||
Processor.start(module, __doc__)
|
||||
Processor.launch(module, __doc__)
|
||||
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ diagnostic utility.
|
|||
import msgpack
|
||||
import sys
|
||||
import argparse
|
||||
import json
|
||||
|
||||
def dump(input_file, action):
|
||||
|
||||
|
|
@ -17,7 +18,7 @@ def dump(input_file, action):
|
|||
unpacker = msgpack.Unpacker(f, raw=False)
|
||||
|
||||
for unpacked in unpacker:
|
||||
print(unpacked)
|
||||
print(json.dumps(unpacked))
|
||||
|
||||
def summary(input_file, action):
|
||||
|
||||
|
|
|
|||
|
|
@ -6,23 +6,23 @@ Connects to the graph query service and dumps all graph edges.
|
|||
|
||||
import argparse
|
||||
import os
|
||||
from trustgraph.clients.triples_query_client import TriplesQueryClient
|
||||
from trustgraph.api import Api
|
||||
|
||||
default_pulsar_host = os.getenv("PULSAR_HOST", 'pulsar://localhost:6650')
|
||||
default_url = os.getenv("TRUSTGRAPH_URL", 'http://localhost:8088/')
|
||||
default_user = 'trustgraph'
|
||||
default_collection = 'default'
|
||||
|
||||
def show_graph(pulsar, user, collection):
|
||||
def show_graph(url, user, collection):
|
||||
|
||||
tq = TriplesQueryClient(pulsar_host=pulsar)
|
||||
api = Api(url)
|
||||
|
||||
rows = tq.request(
|
||||
user=user, collection=collection,
|
||||
s=None, p=None, o=None, limit=10_000_000
|
||||
rows = api.triples_query(
|
||||
# user=user, collection=collection,
|
||||
s=None, p=None, o=None, limit=10_000,
|
||||
)
|
||||
|
||||
for row in rows:
|
||||
print(row.s.value, row.p.value, row.o.value)
|
||||
print(row.s, row.p, row.o)
|
||||
|
||||
def main():
|
||||
|
||||
|
|
@ -32,19 +32,19 @@ def main():
|
|||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-p', '--pulsar-host',
|
||||
default=default_pulsar_host,
|
||||
help=f'Pulsar host (default: {default_pulsar_host})',
|
||||
'-u', '--api-url',
|
||||
default=default_url,
|
||||
help=f'API URL (default: {default_url})',
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-u', '--user',
|
||||
'-U', '--user',
|
||||
default=default_user,
|
||||
help=f'User ID (default: {default_user})'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-c', '--collection',
|
||||
'-C', '--collection',
|
||||
default=default_collection,
|
||||
help=f'Collection ID (default: {default_collection})'
|
||||
)
|
||||
|
|
@ -54,7 +54,8 @@ def main():
|
|||
try:
|
||||
|
||||
show_graph(
|
||||
pulsar=args.pulsar_host, user=args.user,
|
||||
url=args.api_url,
|
||||
user=args.user,
|
||||
collection=args.collection,
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -5,37 +5,45 @@ Connects to the graph query service and dumps all graph edges in Turtle
|
|||
format.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import os
|
||||
from trustgraph.clients.triples_query_client import TriplesQueryClient
|
||||
import rdflib
|
||||
import io
|
||||
import sys
|
||||
import argparse
|
||||
import os
|
||||
|
||||
default_pulsar_host = os.getenv("PULSAR_HOST", 'pulsar://localhost:6650')
|
||||
from trustgraph.api import Api, Uri
|
||||
|
||||
def show_graph(pulsar):
|
||||
default_url = os.getenv("TRUSTGRAPH_URL", 'http://localhost:8088/')
|
||||
default_user = 'trustgraph'
|
||||
default_collection = 'default'
|
||||
|
||||
tq = TriplesQueryClient(pulsar_host=pulsar)
|
||||
def show_graph(url, user, collection):
|
||||
|
||||
rows = tq.request(None, None, None, limit=10_000_000)
|
||||
api = Api(url)
|
||||
|
||||
rows = api.triples_query(
|
||||
s=None, p=None, o=None,
|
||||
limit=10_000)
|
||||
# user=user, collection=collection,
|
||||
|
||||
g = rdflib.Graph()
|
||||
|
||||
for row in rows:
|
||||
|
||||
sv = rdflib.term.URIRef(row.s.value)
|
||||
pv = rdflib.term.URIRef(row.p.value)
|
||||
sv = rdflib.term.URIRef(row.s)
|
||||
pv = rdflib.term.URIRef(row.p)
|
||||
|
||||
if row.o.is_uri:
|
||||
if isinstance(row.o, Uri):
|
||||
|
||||
# Skip malformed URLs with spaces in
|
||||
if " " in row.o.value:
|
||||
if " " in row.o:
|
||||
continue
|
||||
|
||||
ov = rdflib.term.URIRef(row.o.value)
|
||||
ov = rdflib.term.URIRef(row.o)
|
||||
|
||||
else:
|
||||
ov = rdflib.term.Literal(row.o.value)
|
||||
|
||||
ov = rdflib.term.Literal(row.o)
|
||||
|
||||
g.add((sv, pv, ov))
|
||||
|
||||
|
|
@ -56,16 +64,32 @@ def main():
|
|||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-p', '--pulsar-host',
|
||||
default=default_pulsar_host,
|
||||
help=f'Pulsar host (default: {default_pulsar_host})',
|
||||
'-u', '--api-url',
|
||||
default=default_url,
|
||||
help=f'API URL (default: {default_url})',
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-U', '--user',
|
||||
default=default_user,
|
||||
help=f'User ID (default: {default_user})'
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
'-C', '--collection',
|
||||
default=default_collection,
|
||||
help=f'Collection ID (default: {default_collection})'
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
|
||||
show_graph(args.pulsar_host)
|
||||
show_graph(
|
||||
url=args.api_url,
|
||||
user=args.user,
|
||||
collection=args.collection
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
|
||||
|
|
|
|||
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Reference in a new issue