Merge branch 'dev' into cog-1069-update-notebooks-evals
This commit is contained in:
commit
39df73b811
10 changed files with 247 additions and 33 deletions
40
.github/workflows/profiling.yaml
vendored
40
.github/workflows/profiling.yaml
vendored
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@ -68,32 +68,32 @@ jobs:
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echo "HEAD_SHA=${{ github.event.pull_request.head.sha }}" >> $GITHUB_ENV
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# Run profiler on the base branch
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- name: Run profiler on base branch
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env:
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BASE_SHA: ${{ env.BASE_SHA }}
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run: |
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echo "Profiling the base branch for code_graph_pipeline.py"
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echo "Checking out base SHA: $BASE_SHA"
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git checkout $BASE_SHA
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echo "This is the working directory: $PWD"
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# Ensure the script is executable
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chmod +x cognee/api/v1/cognify/code_graph_pipeline.py
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# Run Scalene
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poetry run pyinstrument --renderer json -o base_results.json cognee/api/v1/cognify/code_graph_pipeline.py
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# Run profiler on head branch
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# - name: Run profiler on head branch
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# - name: Run profiler on base branch
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# env:
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# HEAD_SHA: ${{ env.HEAD_SHA }}
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# BASE_SHA: ${{ env.BASE_SHA }}
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# run: |
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# echo "Profiling the head branch for code_graph_pipeline.py"
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# echo "Checking out head SHA: $HEAD_SHA"
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# git checkout $HEAD_SHA
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# echo "Profiling the base branch for code_graph_pipeline.py"
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# echo "Checking out base SHA: $BASE_SHA"
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# git checkout $BASE_SHA
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# echo "This is the working directory: $PWD"
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# # Ensure the script is executable
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# chmod +x cognee/api/v1/cognify/code_graph_pipeline.py
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# # Run Scalene
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# poetry run pyinstrument --renderer json -o head_results.json cognee/api/v1/cognify/code_graph_pipeline.py
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# poetry run pyinstrument --renderer json -o base_results.json cognee/api/v1/cognify/code_graph_pipeline.py
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# Run profiler on head branch
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- name: Run profiler on head branch
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env:
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HEAD_SHA: ${{ env.HEAD_SHA }}
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run: |
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echo "Profiling the head branch for code_graph_pipeline.py"
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echo "Checking out head SHA: $HEAD_SHA"
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git checkout $HEAD_SHA
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echo "This is the working directory: $PWD"
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# Ensure the script is executable
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chmod +x cognee/api/v1/cognify/code_graph_pipeline.py
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# Run Scalene
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poetry run pyinstrument --renderer json -o head_results.json cognee/api/v1/cognify/code_graph_pipeline.py
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# # Compare profiling results
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# - name: Compare profiling results
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|
|
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@ -7,6 +7,10 @@ on:
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description: "Location of example script to run"
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required: true
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type: string
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arguments:
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description: "Arguments for example script"
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required: false
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type: string
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secrets:
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GRAPHISTRY_USERNAME:
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required: true
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@ -53,4 +57,4 @@ jobs:
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LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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GRAPHISTRY_USERNAME: ${{ secrets.GRAPHISTRY_USERNAME }}
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GRAPHISTRY_PASSWORD: ${{ secrets.GRAPHISTRY_PASSWORD }}
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run: poetry run python ${{ inputs.example-location }}
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run: poetry run python ${{ inputs.example-location }} ${{ inputs.arguments }}
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22
.github/workflows/test_code_graph_example.yml
vendored
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22
.github/workflows/test_code_graph_example.yml
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@ -0,0 +1,22 @@
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name: test | code graph example
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on:
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workflow_dispatch:
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pull_request:
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types: [labeled, synchronize]
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concurrency:
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group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
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cancel-in-progress: true
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jobs:
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run_simple_example_test:
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uses: ./.github/workflows/reusable_python_example.yml
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with:
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example-location: ./examples/python/code_graph_example.py
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arguments: "--repo_path ./evals"
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secrets:
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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GRAPHISTRY_USERNAME: ${{ secrets.GRAPHISTRY_USERNAME }}
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GRAPHISTRY_PASSWORD: ${{ secrets.GRAPHISTRY_PASSWORD }}
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32
Dockerfile_modal
Normal file
32
Dockerfile_modal
Normal file
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@ -0,0 +1,32 @@
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FROM python:3.11-slim
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# Set environment variables
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ENV PIP_NO_CACHE_DIR=true
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ENV PATH="${PATH}:/root/.poetry/bin"
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ENV PYTHONPATH=/app
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ENV RUN_MODE=modal
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ENV SKIP_MIGRATIONS=true
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# System dependencies
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RUN apt-get update && apt-get install -y \
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gcc \
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libpq-dev \
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git \
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curl \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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ENV PYTHONPATH=/app
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WORKDIR /app
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COPY pyproject.toml poetry.lock /app/
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RUN pip install poetry
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RUN poetry install --all-extras --no-root --without dev
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COPY cognee/ /app/cognee
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COPY README.md /app/README.md
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22
README.md
22
README.md
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@ -241,6 +241,28 @@ Please see the cognee [Development Guide](https://docs.cognee.ai/quickstart/) fo
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```bash
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pip install cognee
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```
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### Deployment at Scale (Modal)
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Scale cognee in 4(+1) simple steps to handle enterprise workloads using [Modal](https://modal.com)'s GPU-powered infrastructure
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**1. Install the modal python client**
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```bash
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pip install modal
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```
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**2. Create a free account on [Modal](https://modal.com)**
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**3. Set Up Modal API Key**
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```bash
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modal token set --token-id TOKEN_ID --token-secret TOKEN_SECRET --profile=PROFILE
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modal profile activate PROFILE
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```
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**4. Run cognee example**
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This simple example will deploy separate cognee instances building their own memory stores and answering a list of questions at scale.
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```bash
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modal run -d modal_deployment.py
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```
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**5. Change the modal_deploy script and develop your own AI memory at scale 🚀**
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## 💫 Contributors
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|
|
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@ -77,14 +77,51 @@ class SQLAlchemyAdapter:
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text(f"DROP TABLE IF EXISTS {schema_name}.{table_name} CASCADE;")
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)
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async def insert_data(self, schema_name: str, table_name: str, data: list[dict]):
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columns = ", ".join(data[0].keys())
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values = ", ".join([f"({', '.join([f':{key}' for key in row.keys()])})" for row in data])
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insert_query = text(f"INSERT INTO {schema_name}.{table_name} ({columns}) VALUES {values};")
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async def insert_data(
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self,
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table_name: str,
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data: list[dict],
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schema_name: Optional[str] = "public",
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) -> int:
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"""
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Insert data into specified table using SQLAlchemy Core with batch optimization
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Returns number of inserted rows
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async with self.engine.begin() as connection:
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await connection.execute(insert_query, data)
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await connection.close()
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Usage Example:
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from cognee.infrastructure.databases.relational.get_relational_engine import get_relational_engine
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from uuid import UUID
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db = get_relational_engine()
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table_name = "groups"
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data = {
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"id": UUID("c70a3cec-3309-44df-8ee6-eced820cf438"),
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"name": "test"
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}
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await db.insert_data(table_name, data)
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"""
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if not data:
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logger.info("No data provided for insertion")
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return 0
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try:
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# Use SQLAlchemy Core insert with execution options
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async with self.engine.begin() as conn:
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# Dialect-agnostic table reference
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if self.engine.dialect.name == "sqlite":
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# Foreign key constraints are disabled by default in SQLite (for backwards compatibility),
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# so must be enabled for each database connection/session separately.
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await conn.execute(text("PRAGMA foreign_keys=ON"))
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table = await self.get_table(table_name) # SQLite ignores schemas
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else:
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table = await self.get_table(table_name, schema_name)
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result = await conn.execute(table.insert().values(data))
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# Return rowcount for validation
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return result.rowcount
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except Exception as e:
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logger.error(f"Insert failed: {str(e)}")
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raise e # Re-raise for error handling upstream
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async def get_schema_list(self) -> List[str]:
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"""
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|
|
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|||
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|
@ -8,7 +8,6 @@ from cognee.modules.data.methods import get_datasets
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from cognee.modules.data.methods.get_dataset_data import get_dataset_data
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from cognee.modules.data.methods.get_datasets_by_name import get_datasets_by_name
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from cognee.modules.data.models import Data
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from cognee.modules.data.operations.write_metadata import write_metadata
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from cognee.modules.ingestion.data_types import BinaryData
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from cognee.modules.users.methods import get_default_user
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from cognee.shared.CodeGraphEntities import Repository
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|
|
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|||
94
modal_deployment.py
Normal file
94
modal_deployment.py
Normal file
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|
@ -0,0 +1,94 @@
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import modal
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import os
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import logging
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import asyncio
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import cognee
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import signal
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|
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from cognee.api.v1.search import SearchType
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from cognee.shared.utils import setup_logging
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|
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app = modal.App("cognee-runner")
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||||
|
||||
image = (
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modal.Image.from_dockerfile(path="Dockerfile_modal", force_build=False)
|
||||
.copy_local_file("pyproject.toml", "pyproject.toml")
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||||
.copy_local_file("poetry.lock", "poetry.lock")
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.env({"ENV": os.getenv("ENV"), "LLM_API_KEY": os.getenv("LLM_API_KEY")})
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.poetry_install_from_file(poetry_pyproject_toml="pyproject.toml")
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.pip_install("protobuf", "h2")
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)
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||||
@app.function(image=image, concurrency_limit=10)
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async def entry(text: str, query: str):
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setup_logging(logging.ERROR)
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await cognee.prune.prune_data()
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await cognee.prune.prune_system(metadata=True)
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await cognee.add(text)
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await cognee.cognify()
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search_results = await cognee.search(SearchType.GRAPH_COMPLETION, query_text=query)
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return {
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"text": text,
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"query": query,
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"answer": search_results[0] if search_results else None,
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}
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||||
|
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|
||||
@app.local_entrypoint()
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||||
async def main():
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text_queries = [
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{
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"text": "NASA's Artemis program aims to return humans to the Moon by 2026, focusing on sustainable exploration and preparing for future Mars missions.",
|
||||
"query": "When does NASA plan to return humans to the Moon under the Artemis program?",
|
||||
},
|
||||
{
|
||||
"text": "According to a 2022 UN report, global food waste amounts to approximately 931 million tons annually, with households contributing 61% of the total.",
|
||||
"query": "How much food waste do households contribute annually according to the 2022 UN report?",
|
||||
},
|
||||
{
|
||||
"text": "The 2021 census data revealed that Tokyo's population reached 14 million, reflecting a 2.1% increase compared to the previous census conducted in 2015.",
|
||||
"query": "What was Tokyo's population according to the 2021 census data?",
|
||||
},
|
||||
{
|
||||
"text": "A recent study published in the Journal of Nutrition found that consuming 30 grams of almonds daily can lower LDL cholesterol levels by 7% over a 12-week period.",
|
||||
"query": "How much can daily almond consumption lower LDL cholesterol according to the study?",
|
||||
},
|
||||
{
|
||||
"text": "Amazon's Prime membership grew to 200 million subscribers in 2023, marking a 10% increase from the previous year, driven by exclusive content and faster delivery options.",
|
||||
"query": "How many Prime members did Amazon have in 2023?",
|
||||
},
|
||||
{
|
||||
"text": "A new report by the International Energy Agency states that global renewable energy capacity increased by 295 gigawatts in 2022, primarily driven by solar and wind power expansion.",
|
||||
"query": "By how much did global renewable energy capacity increase in 2022 according to the report?",
|
||||
},
|
||||
{
|
||||
"text": "The World Health Organization reported in 2023 that the global life expectancy has risen to 73.4 years, an increase of 5.5 years since the year 2000.",
|
||||
"query": "What is the current global life expectancy according to the WHO's 2023 report?",
|
||||
},
|
||||
{
|
||||
"text": "The FIFA World Cup 2022 held in Qatar attracted a record-breaking audience of 5 billion people across various digital and traditional broadcasting platforms.",
|
||||
"query": "How many people watched the FIFA World Cup 2022?",
|
||||
},
|
||||
{
|
||||
"text": "The European Space Agency's JUICE mission, launched in 2023, aims to explore Jupiter's icy moons, including Ganymede, Europa, and Callisto, over the next decade.",
|
||||
"query": "Which moons is the JUICE mission set to explore?",
|
||||
},
|
||||
{
|
||||
"text": "According to a report by the International Labour Organization, the global unemployment rate in 2023 was estimated at 5.4%, reflecting a slight decrease compared to the previous year.",
|
||||
"query": "What was the global unemployment rate in 2023 according to the ILO?",
|
||||
},
|
||||
]
|
||||
|
||||
tasks = [entry.remote.aio(item["text"], item["query"]) for item in text_queries]
|
||||
|
||||
results = await asyncio.gather(*tasks)
|
||||
|
||||
print("\nFinal Results:")
|
||||
|
||||
for result in results:
|
||||
print(result)
|
||||
print("----")
|
||||
|
||||
os.kill(os.getpid(), signal.SIGTERM)
|
||||
9
poetry.lock
generated
9
poetry.lock
generated
|
|
@ -1,4 +1,4 @@
|
|||
# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
|
||||
# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "aiofiles"
|
||||
|
|
@ -4998,8 +4998,8 @@ files = [
|
|||
[package.dependencies]
|
||||
numpy = [
|
||||
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
|
||||
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
|
||||
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
|
||||
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
|
||||
]
|
||||
python-dateutil = ">=2.8.2"
|
||||
pytz = ">=2020.1"
|
||||
|
|
@ -5927,8 +5927,8 @@ astroid = ">=3.3.8,<=3.4.0-dev0"
|
|||
colorama = {version = ">=0.4.5", markers = "sys_platform == \"win32\""}
|
||||
dill = [
|
||||
{version = ">=0.2", markers = "python_version < \"3.11\""},
|
||||
{version = ">=0.3.6", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
|
||||
{version = ">=0.3.7", markers = "python_version >= \"3.12\""},
|
||||
{version = ">=0.3.6", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
|
||||
]
|
||||
isort = ">=4.2.5,<5.13.0 || >5.13.0,<6"
|
||||
mccabe = ">=0.6,<0.8"
|
||||
|
|
@ -8796,6 +8796,7 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
|
|||
type = ["pytest-mypy"]
|
||||
|
||||
[extras]
|
||||
codegraph = ["jedi", "parso"]
|
||||
deepeval = ["deepeval"]
|
||||
docs = ["unstructured"]
|
||||
falkordb = ["falkordb"]
|
||||
|
|
@ -8814,4 +8815,4 @@ weaviate = ["weaviate-client"]
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10.0,<3.13"
|
||||
content-hash = "d40b127fc83e2f623276d7f001e726490a4ccad195350e8ff0b10c7e3b53775a"
|
||||
content-hash = "9b5d0162e4fdaaded920a2c8b448e07ec794c55914c1d6e18c6ab9b48c42df2d"
|
||||
|
|
|
|||
|
|
@ -77,6 +77,8 @@ pre-commit = "^4.0.1"
|
|||
httpx = "0.27.0"
|
||||
bokeh="^3.6.2"
|
||||
nltk = "3.9.1"
|
||||
parso = {version = "^0.8.4", optional = true}
|
||||
jedi = {version = "^0.19.2", optional = true}
|
||||
|
||||
|
||||
[tool.poetry.extras]
|
||||
|
|
@ -94,6 +96,7 @@ falkordb = ["falkordb"]
|
|||
groq = ["groq"]
|
||||
milvus = ["pymilvus"]
|
||||
docs = ["unstructured"]
|
||||
codegraph = ["parso", "jedi"]
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.4.0"
|
||||
|
|
|
|||
Loading…
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