Merge branch 'dev' into cog-1069-update-notebooks-evals

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Igor Ilic 2025-01-24 19:31:44 +01:00 committed by GitHub
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10 changed files with 247 additions and 33 deletions

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@ -68,32 +68,32 @@ jobs:
echo "HEAD_SHA=${{ github.event.pull_request.head.sha }}" >> $GITHUB_ENV
# Run profiler on the base branch
- name: Run profiler on base branch
env:
BASE_SHA: ${{ env.BASE_SHA }}
run: |
echo "Profiling the base branch for code_graph_pipeline.py"
echo "Checking out base SHA: $BASE_SHA"
git checkout $BASE_SHA
echo "This is the working directory: $PWD"
# Ensure the script is executable
chmod +x cognee/api/v1/cognify/code_graph_pipeline.py
# Run Scalene
poetry run pyinstrument --renderer json -o base_results.json cognee/api/v1/cognify/code_graph_pipeline.py
# Run profiler on head branch
# - name: Run profiler on head branch
# - name: Run profiler on base branch
# env:
# HEAD_SHA: ${{ env.HEAD_SHA }}
# BASE_SHA: ${{ env.BASE_SHA }}
# run: |
# echo "Profiling the head branch for code_graph_pipeline.py"
# echo "Checking out head SHA: $HEAD_SHA"
# git checkout $HEAD_SHA
# echo "Profiling the base branch for code_graph_pipeline.py"
# echo "Checking out base SHA: $BASE_SHA"
# git checkout $BASE_SHA
# echo "This is the working directory: $PWD"
# # Ensure the script is executable
# chmod +x cognee/api/v1/cognify/code_graph_pipeline.py
# # Run Scalene
# poetry run pyinstrument --renderer json -o head_results.json cognee/api/v1/cognify/code_graph_pipeline.py
# poetry run pyinstrument --renderer json -o base_results.json cognee/api/v1/cognify/code_graph_pipeline.py
# Run profiler on head branch
- name: Run profiler on head branch
env:
HEAD_SHA: ${{ env.HEAD_SHA }}
run: |
echo "Profiling the head branch for code_graph_pipeline.py"
echo "Checking out head SHA: $HEAD_SHA"
git checkout $HEAD_SHA
echo "This is the working directory: $PWD"
# Ensure the script is executable
chmod +x cognee/api/v1/cognify/code_graph_pipeline.py
# Run Scalene
poetry run pyinstrument --renderer json -o head_results.json cognee/api/v1/cognify/code_graph_pipeline.py
# # Compare profiling results
# - name: Compare profiling results

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@ -7,6 +7,10 @@ on:
description: "Location of example script to run"
required: true
type: string
arguments:
description: "Arguments for example script"
required: false
type: string
secrets:
GRAPHISTRY_USERNAME:
required: true
@ -53,4 +57,4 @@ jobs:
LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }}
GRAPHISTRY_USERNAME: ${{ secrets.GRAPHISTRY_USERNAME }}
GRAPHISTRY_PASSWORD: ${{ secrets.GRAPHISTRY_PASSWORD }}
run: poetry run python ${{ inputs.example-location }}
run: poetry run python ${{ inputs.example-location }} ${{ inputs.arguments }}

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@ -0,0 +1,22 @@
name: test | code graph example
on:
workflow_dispatch:
pull_request:
types: [labeled, synchronize]
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
jobs:
run_simple_example_test:
uses: ./.github/workflows/reusable_python_example.yml
with:
example-location: ./examples/python/code_graph_example.py
arguments: "--repo_path ./evals"
secrets:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
GRAPHISTRY_USERNAME: ${{ secrets.GRAPHISTRY_USERNAME }}
GRAPHISTRY_PASSWORD: ${{ secrets.GRAPHISTRY_PASSWORD }}

32
Dockerfile_modal Normal file
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@ -0,0 +1,32 @@
FROM python:3.11-slim
# Set environment variables
ENV PIP_NO_CACHE_DIR=true
ENV PATH="${PATH}:/root/.poetry/bin"
ENV PYTHONPATH=/app
ENV RUN_MODE=modal
ENV SKIP_MIGRATIONS=true
# System dependencies
RUN apt-get update && apt-get install -y \
gcc \
libpq-dev \
git \
curl \
build-essential \
&& rm -rf /var/lib/apt/lists/*
WORKDIR /app
ENV PYTHONPATH=/app
WORKDIR /app
COPY pyproject.toml poetry.lock /app/
RUN pip install poetry
RUN poetry install --all-extras --no-root --without dev
COPY cognee/ /app/cognee
COPY README.md /app/README.md

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@ -241,6 +241,28 @@ Please see the cognee [Development Guide](https://docs.cognee.ai/quickstart/) fo
```bash
pip install cognee
```
### Deployment at Scale (Modal)
Scale cognee in 4(+1) simple steps to handle enterprise workloads using [Modal](https://modal.com)'s GPU-powered infrastructure
**1. Install the modal python client**
```bash
pip install modal
```
**2. Create a free account on [Modal](https://modal.com)**
**3. Set Up Modal API Key**
```bash
modal token set --token-id TOKEN_ID --token-secret TOKEN_SECRET --profile=PROFILE
modal profile activate PROFILE
```
**4. Run cognee example**
This simple example will deploy separate cognee instances building their own memory stores and answering a list of questions at scale.
```bash
modal run -d modal_deployment.py
```
**5. Change the modal_deploy script and develop your own AI memory at scale 🚀**
## 💫 Contributors

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@ -77,14 +77,51 @@ class SQLAlchemyAdapter:
text(f"DROP TABLE IF EXISTS {schema_name}.{table_name} CASCADE;")
)
async def insert_data(self, schema_name: str, table_name: str, data: list[dict]):
columns = ", ".join(data[0].keys())
values = ", ".join([f"({', '.join([f':{key}' for key in row.keys()])})" for row in data])
insert_query = text(f"INSERT INTO {schema_name}.{table_name} ({columns}) VALUES {values};")
async def insert_data(
self,
table_name: str,
data: list[dict],
schema_name: Optional[str] = "public",
) -> int:
"""
Insert data into specified table using SQLAlchemy Core with batch optimization
Returns number of inserted rows
async with self.engine.begin() as connection:
await connection.execute(insert_query, data)
await connection.close()
Usage Example:
from cognee.infrastructure.databases.relational.get_relational_engine import get_relational_engine
from uuid import UUID
db = get_relational_engine()
table_name = "groups"
data = {
"id": UUID("c70a3cec-3309-44df-8ee6-eced820cf438"),
"name": "test"
}
await db.insert_data(table_name, data)
"""
if not data:
logger.info("No data provided for insertion")
return 0
try:
# Use SQLAlchemy Core insert with execution options
async with self.engine.begin() as conn:
# Dialect-agnostic table reference
if self.engine.dialect.name == "sqlite":
# Foreign key constraints are disabled by default in SQLite (for backwards compatibility),
# so must be enabled for each database connection/session separately.
await conn.execute(text("PRAGMA foreign_keys=ON"))
table = await self.get_table(table_name) # SQLite ignores schemas
else:
table = await self.get_table(table_name, schema_name)
result = await conn.execute(table.insert().values(data))
# Return rowcount for validation
return result.rowcount
except Exception as e:
logger.error(f"Insert failed: {str(e)}")
raise e # Re-raise for error handling upstream
async def get_schema_list(self) -> List[str]:
"""

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@ -8,7 +8,6 @@ from cognee.modules.data.methods import get_datasets
from cognee.modules.data.methods.get_dataset_data import get_dataset_data
from cognee.modules.data.methods.get_datasets_by_name import get_datasets_by_name
from cognee.modules.data.models import Data
from cognee.modules.data.operations.write_metadata import write_metadata
from cognee.modules.ingestion.data_types import BinaryData
from cognee.modules.users.methods import get_default_user
from cognee.shared.CodeGraphEntities import Repository

94
modal_deployment.py Normal file
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@ -0,0 +1,94 @@
import modal
import os
import logging
import asyncio
import cognee
import signal
from cognee.api.v1.search import SearchType
from cognee.shared.utils import setup_logging
app = modal.App("cognee-runner")
image = (
modal.Image.from_dockerfile(path="Dockerfile_modal", force_build=False)
.copy_local_file("pyproject.toml", "pyproject.toml")
.copy_local_file("poetry.lock", "poetry.lock")
.env({"ENV": os.getenv("ENV"), "LLM_API_KEY": os.getenv("LLM_API_KEY")})
.poetry_install_from_file(poetry_pyproject_toml="pyproject.toml")
.pip_install("protobuf", "h2")
)
@app.function(image=image, concurrency_limit=10)
async def entry(text: str, query: str):
setup_logging(logging.ERROR)
await cognee.prune.prune_data()
await cognee.prune.prune_system(metadata=True)
await cognee.add(text)
await cognee.cognify()
search_results = await cognee.search(SearchType.GRAPH_COMPLETION, query_text=query)
return {
"text": text,
"query": query,
"answer": search_results[0] if search_results else None,
}
@app.local_entrypoint()
async def main():
text_queries = [
{
"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
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@ -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"

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@ -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"