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Merge remote-tracking branch 'origin/dev'

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This commit is contained in:
Boris Arzentar 2025-04-02 12:50:53 +02:00
commit de50b36322
13 changed files with 1941 additions and 100 deletions
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2
.github/workflows/test_code_graph_example.yml vendored
View file

@ -15,7 +15,7 @@ jobs:
uses: ./.github/workflows/reusable_python_example.yml
with:
example-location: ./examples/python/code_graph_example.py
arguments: "--repo_path ./evals"
arguments: "--repo_path ./cognee/tasks/graph"
secrets:
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }}

4
Dockerfile
View file

@ -5,11 +5,11 @@ ARG POETRY_EXTRAS="\
# API \
api \
# Storage & Databases \
filesystem postgres weaviate qdrant neo4j falkordb milvus kuzu \
filesystem postgres weaviate qdrant neo4j falkordb milvus kuzu chromadb \
# Notebooks & Interactive Environments \
notebook \
# LLM & AI Frameworks \
langchain llama-index gemini huggingface ollama mistral groq \
langchain llama-index gemini huggingface ollama mistral groq anthropic \
# Evaluation & Monitoring \
deepeval evals posthog \
# Graph Processing & Code Analysis \

13
README.md
View file

@ -113,7 +113,8 @@ if __name__ == '__main__':
```
Example output:
```
# ({'id': UUID('bc338a39-64d6-549a-acec-da60846dd90d'), 'updated_at': datetime.datetime(2024, 11, 21, 12, 23, 1, 211808, tzinfo=datetime.timezone.utc), 'name': 'natural language processing', 'description': 'An interdisciplinary subfield of computer science and information retrieval.'}, {'relationship_name': 'is_a_subfield_of', 'source_node_id': UUID('bc338a39-64d6-549a-acec-da60846dd90d'), 'target_node_id': UUID('6218dbab-eb6a-5759-a864-b3419755ffe0'), 'updated_at': datetime.datetime(2024, 11, 21, 12, 23, 15, 473137, tzinfo=datetime.timezone.utc)}, {'id': UUID('6218dbab-eb6a-5759-a864-b3419755ffe0'), 'updated_at': datetime.datetime(2024, 11, 21, 12, 23, 1, 211808, tzinfo=datetime.timezone.utc), 'name': 'computer science', 'description': 'The study of computation and information processing.'})
Natural Language Processing (NLP) is a cross-disciplinary and interdisciplinary field that involves computer science and information retrieval. It focuses on the interaction between computers and human language, enabling machines to understand and process natural language.
```
Graph visualization:
<a href="https://rawcdn.githack.com/topoteretes/cognee/refs/heads/add-visualization-readme/assets/graph_visualization.html"><img src="assets/graph_visualization.png" width="100%" alt="Graph Visualization"></a>
@ -132,10 +133,18 @@ For more advanced usage, have a look at our <a href="https://docs.cognee.ai"> do
## Demos
What is AI memory:
1. What is AI memory:
[Learn about cognee](https://github.com/user-attachments/assets/8b2a0050-5ec4-424c-b417-8269971503f0)
2. Simple GraphRAG demo
[Simple GraphRAG demo](https://github.com/user-attachments/assets/d80b0776-4eb9-4b8e-aa22-3691e2d44b8f)
3. cognee with Ollama
[cognee with local models](https://github.com/user-attachments/assets/8621d3e8-ecb8-4860-afb2-5594f2ee17db)
## Code of Conduct

158
cognee-mcp/src/server.py
View file

@ -1,10 +1,11 @@
import asyncio
import json
import os
import sys
import cognee
from cognee.shared.logging_utils import get_logger, get_log_file_location
import importlib.util
from contextlib import redirect_stderr, redirect_stdout
from contextlib import redirect_stdout
# from PIL import Image as PILImage
import mcp.types as types
@ -90,56 +91,55 @@ async def list_tools() -> list[types.Tool]:
@mcp.call_tool()
async def call_tools(name: str, arguments: dict) -> list[types.TextContent]:
try:
with open(os.devnull, "w") as fnull:
with redirect_stdout(fnull), redirect_stderr(fnull):
log_file = get_log_file_location()
# NOTE: MCP uses stdout to communicate, we must redirect all output
# going to stdout ( like the print function ) to stderr.
with redirect_stdout(sys.stderr):
log_file = get_log_file_location()
if name == "cognify":
asyncio.create_task(
cognify(
text=arguments["text"],
graph_model_file=arguments.get("graph_model_file"),
graph_model_name=arguments.get("graph_model_name"),
)
if name == "cognify":
asyncio.create_task(
cognify(
text=arguments["text"],
graph_model_file=arguments.get("graph_model_file"),
graph_model_name=arguments.get("graph_model_name"),
)
)
text = (
f"Background process launched due to MCP timeout limitations.\n"
f"Average completion time is around 4 minutes.\n"
f"For current cognify status you can check the log file at: {log_file}"
text = (
f"Background process launched due to MCP timeout limitations.\n"
f"Average completion time is around 4 minutes.\n"
f"For current cognify status you can check the log file at: {log_file}"
)
return [
types.TextContent(
type="text",
text=text,
)
]
if name == "codify":
asyncio.create_task(codify(arguments.get("repo_path")))
return [
types.TextContent(
type="text",
text=text,
)
]
if name == "codify":
asyncio.create_task(codify(arguments.get("repo_path")))
text = (
f"Background process launched due to MCP timeout limitations.\n"
f"Average completion time is around 4 minutes.\n"
f"For current codify status you can check the log file at: {log_file}"
)
text = (
f"Background process launched due to MCP timeout limitations.\n"
f"Average completion time is around 4 minutes.\n"
f"For current codify status you can check the log file at: {log_file}"
return [
types.TextContent(
type="text",
text=text,
)
]
elif name == "search":
search_results = await search(arguments["search_query"], arguments["search_type"])
return [
types.TextContent(
type="text",
text=text,
)
]
elif name == "search":
search_results = await search(
arguments["search_query"], arguments["search_type"]
)
return [types.TextContent(type="text", text=search_results)]
elif name == "prune":
await prune()
return [types.TextContent(type="text", text=search_results)]
elif name == "prune":
await prune()
return [types.TextContent(type="text", text="Pruned")]
return [types.TextContent(type="text", text="Pruned")]
except Exception as e:
logger.error(f"Error calling tool '{name}': {str(e)}")
return [types.TextContent(type="text", text=f"Error calling tool '{name}': {str(e)}")]
@ -147,45 +147,56 @@ async def call_tools(name: str, arguments: dict) -> list[types.TextContent]:
async def cognify(text: str, graph_model_file: str = None, graph_model_name: str = None) -> str:
"""Build knowledge graph from the input text"""
logger.info("Cognify process starting.")
if graph_model_file and graph_model_name:
graph_model = load_class(graph_model_file, graph_model_name)
else:
graph_model = KnowledgeGraph
# NOTE: MCP uses stdout to communicate, we must redirect all output
# going to stdout ( like the print function ) to stderr.
# As cognify is an async background job the output had to be redirected again.
with redirect_stdout(sys.stderr):
logger.info("Cognify process starting.")
if graph_model_file and graph_model_name:
graph_model = load_class(graph_model_file, graph_model_name)
else:
graph_model = KnowledgeGraph
await cognee.add(text)
await cognee.add(text)
try:
await cognee.cognify(graph_model=graph_model)
logger.info("Cognify process finished.")
except Exception as e:
logger.error("Cognify process failed.")
raise ValueError(f"Failed to cognify: {str(e)}")
try:
await cognee.cognify(graph_model=graph_model)
logger.info("Cognify process finished.")
except Exception as e:
logger.error("Cognify process failed.")
raise ValueError(f"Failed to cognify: {str(e)}")
async def codify(repo_path: str):
logger.info("Codify process starting.")
results = []
async for result in run_code_graph_pipeline(repo_path, False):
results.append(result)
logger.info(result)
if all(results):
logger.info("Codify process finished succesfully.")
else:
logger.info("Codify process failed.")
# NOTE: MCP uses stdout to communicate, we must redirect all output
# going to stdout ( like the print function ) to stderr.
# As codify is an async background job the output had to be redirected again.
with redirect_stdout(sys.stderr):
logger.info("Codify process starting.")
results = []
async for result in run_code_graph_pipeline(repo_path, False):
results.append(result)
logger.info(result)
if all(results):
logger.info("Codify process finished succesfully.")
else:
logger.info("Codify process failed.")
async def search(search_query: str, search_type: str) -> str:
"""Search the knowledge graph"""
search_results = await cognee.search(
query_type=SearchType[search_type.upper()], query_text=search_query
)
# NOTE: MCP uses stdout to communicate, we must redirect all output
# going to stdout ( like the print function ) to stderr.
with redirect_stdout(sys.stderr):
search_results = await cognee.search(
query_type=SearchType[search_type.upper()], query_text=search_query
)
if search_type.upper() == "CODE":
return json.dumps(search_results, cls=JSONEncoder)
else:
results = retrieved_edges_to_string(search_results)
return results
if search_type.upper() == "CODE":
return json.dumps(search_results, cls=JSONEncoder)
else:
results = retrieved_edges_to_string(search_results)
return results
async def prune():
@ -198,7 +209,7 @@ async def main():
try:
from mcp.server.stdio import stdio_server
logger.info("Starting Cognee MCP server...")
logger.info("Cognee MCP server started...")
async with stdio_server() as (read_stream, write_stream):
await mcp.run(
@ -215,7 +226,8 @@ async def main():
raise_exceptions=True,
)
logger.info("Cognee MCP server started.")
logger.info("Cognee MCP server closed.")
except Exception as e:
logger.error(f"Server failed to start: {str(e)}", exc_info=True)
raise

2
cognee/infrastructure/files/utils/get_file_metadata.py
View file

@ -21,7 +21,7 @@ def get_file_metadata(file: BinaryIO) -> FileMetadata:
file_type = guess_file_type(file)
file_path = file.name
file_name = file_path.split("/")[-1].split(".")[0] if file_path else None
file_name = str(file_path).split("/")[-1].split(".")[0] if file_path else None
return FileMetadata(
name=file_name,

2
cognee/modules/ingestion/classify.py
View file

@ -11,7 +11,7 @@ def classify(data: Union[str, BinaryIO], filename: str = None):
return TextData(data)
if isinstance(data, BufferedReader) or isinstance(data, SpooledTemporaryFile):
return BinaryData(data, data.name.split("/")[-1] if data.name else filename)
return BinaryData(data, str(data.name).split("/")[-1] if data.name else filename)
raise IngestionError(
message=f"Type of data sent to classify(data: Union[str, BinaryIO) not supported: {type(data)}"

37
cognee/shared/logging_utils.py
View file

@ -69,7 +69,7 @@ class PlainFileHandler(logging.FileHandler):
logger_name = record.msg.get("logger", record.name)
# Format timestamp
timestamp = datetime.now().strftime("%Y-%m-%dT%H:%M:%S.%fZ")
timestamp = datetime.now().strftime(get_timestamp_format())
# Create the log entry
log_entry = f"{timestamp} [{record.levelname.ljust(8)}] {message}{context_str} [{logger_name}]\n"
@ -226,7 +226,7 @@ def setup_logging(log_level=None, name=None):
structlog.stdlib.add_logger_name,
structlog.stdlib.add_log_level,
structlog.stdlib.PositionalArgumentsFormatter(),
structlog.processors.TimeStamper(fmt="iso"),
structlog.processors.TimeStamper(fmt=get_timestamp_format(), utc=True),
structlog.processors.StackInfoRenderer(),
exception_handler, # Add our custom exception handler
structlog.processors.UnicodeDecoder(),
@ -288,9 +288,18 @@ def setup_logging(log_level=None, name=None):
stream_handler.setFormatter(console_formatter)
stream_handler.setLevel(log_level)
# Check if we already have a log file path from the environment
# NOTE: environment variable must be used here as it allows us to
# log to a single file with a name based on a timestamp in a multiprocess setting.
# Without it, we would have a separate log file for every process.
log_file_path = os.environ.get("LOG_FILE_NAME")
if not log_file_path:
# Create a new log file name with the cognee start time
start_time = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
log_file_path = os.path.join(LOGS_DIR, f"{start_time}.log")
os.environ["LOG_FILE_NAME"] = log_file_path
# Create a file handler that uses our custom PlainFileHandler
current_time = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
log_file_path = os.path.join(LOGS_DIR, f"{current_time}.log")
file_handler = PlainFileHandler(log_file_path, encoding="utf-8")
file_handler.setLevel(DEBUG)
@ -328,3 +337,23 @@ def get_log_file_location():
for handler in root_logger.handlers:
if isinstance(handler, logging.FileHandler):
return handler.baseFilename
def get_timestamp_format():
# NOTE: Some users have complained that Cognee crashes when trying to get microsecond value
# Added handler to not use microseconds if users can't access it
logger = structlog.get_logger()
try:
# We call datetime.now() here to test if microseconds are supported.
# If they are not supported a ValueError will be raised
datetime.now().strftime("%Y-%m-%dT%H:%M:%S.%f")
return "%Y-%m-%dT%H:%M:%S.%f"
except Exception as e:
logger.debug(f"Exception caught: {e}")
logger.debug(
"Could not use microseconds for the logging timestamp, defaulting to use hours minutes and seconds only"
)
# We call datetime.now() here to test if won't break.
datetime.now().strftime("%Y-%m-%dT%H:%M:%S")
# We return the timestamp format without microseconds as they are not supported
return "%Y-%m-%dT%H:%M:%S"

30
docker-compose.yml
View file

@ -22,19 +22,23 @@ services:
cpus: "2.0"
memory: 8GB
frontend:
container_name: frontend
build:
context: ./cognee-frontend
dockerfile: Dockerfile
volumes:
- ./cognee-frontend/src:/app/src
- ./cognee-frontend/public:/app/public
ports:
- 3000:3000
# - 9229:9229 # Debugging
networks:
- cognee-network
# NOTE: Frontend is a work in progress and is not intended to be used by users yet.
# If you want to use Cognee with a UI environment you can run the cognee-gui.py script or
# integrate the Cognee MCP Server to Cursor / Claude Desktop / Visual Studio Code ( through Cline/Roo )
# frontend:
# container_name: frontend
# build:
# context: ./cognee-frontend
# dockerfile: Dockerfile
# volumes:
# - ./cognee-frontend/src:/app/src
# - ./cognee-frontend/public:/app/public
# ports:
# - 3000:3000
# # - 9229:9229 # Debugging
# networks:
# - cognee-network
neo4j:
image: neo4j:latest

9
examples/python/code_graph_example.py
View file

@ -1,5 +1,7 @@
import argparse
import asyncio
import cognee
from cognee import SearchType
from cognee.shared.logging_utils import get_logger, ERROR
from cognee.api.v1.cognify.code_graph_pipeline import run_code_graph_pipeline
@ -10,6 +12,13 @@ async def main(repo_path, include_docs):
async for run_status in run_code_graph_pipeline(repo_path, include_docs=include_docs):
run_status = run_status
# Test CODE search
search_results = await cognee.search(query_type=SearchType.CODE, query_text="test")
assert len(search_results) != 0, "The search results list is empty."
print("\n\nSearch results are:\n")
for result in search_results:
print(f"{result}\n")
return run_status

128
notebooks/github_graph_visualization.html Normal file
View file

@ -0,0 +1,128 @@
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<script src="https://d3js.org/d3.v5.min.js"></script>
<style>
body, html { margin: 0; padding: 0; width: 100%; height: 100%; overflow: hidden; background: linear-gradient(90deg, #101010, #1a1a2e); color: white; font-family: 'Inter', sans-serif; }
svg { width: 100vw; height: 100vh; display: block; }
.links line { stroke: rgba(255, 255, 255, 0.4); stroke-width: 2px; }
.nodes circle { stroke: white; stroke-width: 0.5px; filter: drop-shadow(0 0 5px rgba(255,255,255,0.3)); }
.node-label { font-size: 5px; font-weight: bold; fill: white; text-anchor: middle; dominant-baseline: middle; font-family: 'Inter', sans-serif; pointer-events: none; }
.edge-label { font-size: 3px; fill: rgba(255, 255, 255, 0.7); text-anchor: middle; dominant-baseline: middle; font-family: 'Inter', sans-serif; pointer-events: none; }
</style>
</head>
<body>
<svg></svg>
<script>
var nodes = [];
var links = [];
var svg = d3.select("svg"),
width = window.innerWidth,
height = window.innerHeight;
var container = svg.append("g");
var simulation = d3.forceSimulation(nodes)
.force("link", d3.forceLink(links).id(d => d.id).strength(0.1))
.force("charge", d3.forceManyBody().strength(-275))
.force("center", d3.forceCenter(width / 2, height / 2))
.force("x", d3.forceX().strength(0.1).x(width / 2))
.force("y", d3.forceY().strength(0.1).y(height / 2));
var link = container.append("g")
.attr("class", "links")
.selectAll("line")
.data(links)
.enter().append("line")
.attr("stroke-width", 2);
var edgeLabels = container.append("g")
.attr("class", "edge-labels")
.selectAll("text")
.data(links)
.enter().append("text")
.attr("class", "edge-label")
.text(d => d.relation);
var nodeGroup = container.append("g")
.attr("class", "nodes")
.selectAll("g")
.data(nodes)
.enter().append("g");
var node = nodeGroup.append("circle")
.attr("r", 13)
.attr("fill", d => d.color)
.call(d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended));
nodeGroup.append("text")
.attr("class", "node-label")
.attr("dy", 4)
.attr("text-anchor", "middle")
.text(d => d.name);
node.append("title").text(d => JSON.stringify(d));
simulation.on("tick", function() {
link.attr("x1", d => d.source.x)
.attr("y1", d => d.source.y)
.attr("x2", d => d.target.x)
.attr("y2", d => d.target.y);
edgeLabels
.attr("x", d => (d.source.x + d.target.x) / 2)
.attr("y", d => (d.source.y + d.target.y) / 2 - 5);
node.attr("cx", d => d.x)
.attr("cy", d => d.y);
nodeGroup.select("text")
.attr("x", d => d.x)
.attr("y", d => d.y)
.attr("dy", 4)
.attr("text-anchor", "middle");
});
svg.call(d3.zoom().on("zoom", function() {
container.attr("transform", d3.event.transform);
}));
function dragstarted(d) {
if (!d3.event.active) simulation.alphaTarget(0.3).restart();
d.fx = d.x;
d.fy = d.y;
}
function dragged(d) {
d.fx = d3.event.x;
d.fy = d3.event.y;
}
function dragended(d) {
if (!d3.event.active) simulation.alphaTarget(0);
d.fx = null;
d.fy = null;
}
window.addEventListener("resize", function() {
width = window.innerWidth;
height = window.innerHeight;
svg.attr("width", width).attr("height", height);
simulation.force("center", d3.forceCenter(width / 2, height / 2));
simulation.alpha(1).restart();
});
</script>
<svg style="position: fixed; bottom: 10px; right: 10px; width: 150px; height: auto; z-index: 9999;" viewBox="0 0 158 44" fill="none" xmlns="http://www.w3.org/2000/svg">
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1577
notebooks/ontology_demo.ipynb Normal file
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76
poetry.lock generated
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@ -7849,6 +7849,63 @@ files = [
[package.extras]
dev = ["build", "flake8", "mypy", "pytest", "twine"]
[[package]]
name = "pyside6"
version = "6.8.3"
description = "Python bindings for the Qt cross-platform application and UI framework"
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python-versions = "<3.14,>=3.9"
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PySide6-Essentials = "6.8.3"
shiboken6 = "6.8.3"
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shiboken6 = "6.8.3"
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version = "6.8.3"
description = "Python bindings for the Qt cross-platform application and UI framework (Essentials)"
optional = true
python-versions = "<3.14,>=3.9"
groups = ["main"]
markers = "extra == \"gui\""
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[package.dependencies]
shiboken6 = "6.8.3"
[[package]]
name = "pysocks"
version = "1.7.1"
@ -9379,6 +9436,21 @@ files = [
{file = "shellingham-1.5.4.tar.gz", hash = "sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"},
]
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version = "6.8.3"
description = "Python/C++ bindings helper module"
optional = true
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groups = ["main"]
markers = "extra == \"gui\""
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[[package]]
name = "simplejson"
version = "3.20.1"
@ -11251,7 +11323,7 @@ filesystem = ["botocore"]
gemini = []
graphiti = ["graphiti-core"]
groq = ["groq"]
gui = ["qasync"]
gui = ["pyside6", "qasync"]
huggingface = ["transformers"]
kuzu = ["kuzu"]
langchain = ["langchain_text_splitters", "langsmith"]
@ -11269,4 +11341,4 @@ weaviate = ["weaviate-client"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<=3.13"
content-hash = "4bda223028508503b326912854c60fa4a5f60349370d26f22dd997d0dec11e01"
content-hash = "25b759ffc908ce0b4df33344424d2043dd3126d944c6d2e9b24031bd24e1152b"

3
pyproject.toml
View file

@ -1,6 +1,6 @@
[tool.poetry]
name = "cognee"
version = "0.1.35"
version = "0.1.36"
description = "Cognee - is a library for enriching LLM context with a semantic layer for better understanding and reasoning."
authors = ["Vasilije Markovic", "Boris Arzentar"]
readme = "README.md"
@ -82,6 +82,7 @@ gdown = {version = "^5.2.0", optional = true}
qasync = {version = "^0.27.1", optional = true}
graphiti-core = {version = "^0.7.0", optional = true}
structlog = "^25.2.0"
pyside6 = {version = "^6.8.3", optional = true}
[tool.poetry.extras]