Chore: Merge main to dev branch (#1478)
<!-- .github/pull_request_template.md -->
## Description
Merge main to dev branch
## Type of Change
<!-- Please check the relevant option -->
- [ ] Bug fix (non-breaking change that fixes an issue)
- [ ] New feature (non-breaking change that adds functionality)
- [ ] Breaking change (fix or feature that would cause existing
functionality to change)
- [ ] Documentation update
- [ ] Code refactoring
- [ ] Performance improvement
- [ ] Other (please specify):
## Screenshots/Videos (if applicable)
<!-- Add screenshots or videos to help explain your changes -->
## Pre-submission Checklist
<!-- Please check all boxes that apply before submitting your PR -->
- [ ] **I have tested my changes thoroughly before submitting this PR**
- [ ] **This PR contains minimal changes necessary to address the
issue/feature**
- [ ] My code follows the project's coding standards and style
guidelines
- [ ] I have added tests that prove my fix is effective or that my
feature works
- [ ] I have added necessary documentation (if applicable)
- [ ] All new and existing tests pass
- [ ] I have searched existing PRs to ensure this change hasn't been
submitted already
- [ ] I have linked any relevant issues in the description
- [ ] My commits have clear and descriptive messages
## DCO Affirmation
I affirm that all code in every commit of this pull request conforms to
the terms of the Topoteretes Developer Certificate of Origin.
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> Standardizes vector search to accept `limit=None` (fetch all/count),
updates adapters/interface and retrievers, and adds tests plus minor
logging/doc assets.
>
> - **Vector search API**:
> - Change `limit` to `Optional[int]` in `vector_db_interface` and
adapters (`ChromaDBAdapter`, `LanceDBAdapter`, `PGVectorAdapter`,
`NeptuneAnalyticsAdapter`).
> - Behavior: `limit=None` fetches all/collection count; early-return on
`limit<=0`; minor logging copy/level tweaks; `PGVector` counts via
`func.count`.
> - **Retrievers**:
> - Switch internal calls to `limit=None` (`CogneeGraph`,
`temporal_retriever`, brute-force triplet search).
> - **Tests**:
> - Add `limit=None` coverage for ChromaDB, LanceDB (new suite), and
PGVector; assert results exceed default caps.
> - **Examples/Docs**:
> - Demo script prunes before run; add tutorial notebook and data
assets; remove one markdown article.
> - **Misc**: LLM utils demote a log line to `debug`.
>
> <sup>Written by [Cursor
Bugbot](https://cursor.com/dashboard?tab=bugbot) for commit
7403e31738. This will update automatically
on new commits. Configure
[here](https://cursor.com/dashboard?tab=bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
This commit is contained in:
Igor Ilic
GitHub
commit
e3c2c776d0
29 changed files with 4881 additions and 2367 deletions
19
.github/pull_request_template.md
vendored
19
.github/pull_request_template.md
vendored
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@ -1,8 +1,8 @@
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|||
<!-- .github/pull_request_template.md -->
|
||||
|
||||
## Description
|
||||
<!--
|
||||
Please provide a clear, human-generated description of the changes in this PR.
|
||||
<!--
|
||||
Please provide a clear, human-generated description of the changes in this PR.
|
||||
DO NOT use AI-generated descriptions. We want to understand your thought process and reasoning.
|
||||
-->
|
||||
|
||||
|
|
@ -16,15 +16,6 @@ DO NOT use AI-generated descriptions. We want to understand your thought process
|
|||
- [ ] Performance improvement
|
||||
- [ ] Other (please specify):
|
||||
|
||||
## Changes Made
|
||||
<!-- List the specific changes made in this PR -->
|
||||
-
|
||||
-
|
||||
-
|
||||
|
||||
## Testing
|
||||
<!-- Describe how you tested your changes -->
|
||||
|
||||
## Screenshots/Videos (if applicable)
|
||||
<!-- Add screenshots or videos to help explain your changes -->
|
||||
|
||||
|
|
@ -40,11 +31,5 @@ DO NOT use AI-generated descriptions. We want to understand your thought process
|
|||
- [ ] I have linked any relevant issues in the description
|
||||
- [ ] My commits have clear and descriptive messages
|
||||
|
||||
## Related Issues
|
||||
<!-- Link any related issues using "Fixes #issue_number" or "Relates to #issue_number" -->
|
||||
|
||||
## Additional Notes
|
||||
<!-- Add any additional notes, concerns, or context for reviewers -->
|
||||
|
||||
## DCO Affirmation
|
||||
I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin.
|
||||
|
|
|
|||
27
.github/workflows/vector_db_tests.yml
vendored
27
.github/workflows/vector_db_tests.yml
vendored
|
|
@ -101,3 +101,30 @@ jobs:
|
|||
EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }}
|
||||
EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }}
|
||||
run: uv run python ./cognee/tests/test_pgvector.py
|
||||
|
||||
run-lancedb-tests:
|
||||
name: LanceDB Tests
|
||||
runs-on: ubuntu-22.04
|
||||
steps:
|
||||
- name: Check out
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Cognee Setup
|
||||
uses: ./.github/actions/cognee_setup
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
|
||||
- name: Run LanceDB Tests
|
||||
env:
|
||||
ENV: 'dev'
|
||||
LLM_MODEL: ${{ secrets.LLM_MODEL }}
|
||||
LLM_ENDPOINT: ${{ secrets.LLM_ENDPOINT }}
|
||||
LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
|
||||
LLM_API_VERSION: ${{ secrets.LLM_API_VERSION }}
|
||||
EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }}
|
||||
EMBEDDING_ENDPOINT: ${{ secrets.EMBEDDING_ENDPOINT }}
|
||||
EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }}
|
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EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }}
|
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run: uv run python ./cognee/tests/test_lancedb.py
|
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130
README.md
130
README.md
|
|
@ -5,7 +5,7 @@
|
|||
|
||||
<br />
|
||||
|
||||
cognee - Memory for AI Agents in 5 lines of code
|
||||
cognee - Memory for AI Agents in 6 lines of code
|
||||
|
||||
<p align="center">
|
||||
<a href="https://www.youtube.com/watch?v=1bezuvLwJmw&t=2s">Demo</a>
|
||||
|
|
@ -43,12 +43,10 @@
|
|||
|
||||
|
||||
|
||||
**🚀 We launched Cogwit beta (Fully-hosted AI Memory): Sign up [here](https://platform.cognee.ai/)! 🚀**
|
||||
|
||||
|
||||
Build dynamic memory for Agents and replace RAG using scalable, modular ECL (Extract, Cognify, Load) pipelines.
|
||||
|
||||
More on [use-cases](https://docs.cognee.ai/use-cases) and [evals](https://github.com/topoteretes/cognee/tree/main/evals)
|
||||
|
||||
<p align="center">
|
||||
🌐 Available Languages
|
||||
:
|
||||
|
|
@ -70,53 +68,47 @@ More on [use-cases](https://docs.cognee.ai/use-cases) and [evals](https://github
|
|||
</div>
|
||||
|
||||
|
||||
## Features
|
||||
|
||||
- Interconnect and retrieve your past conversations, documents, images and audio transcriptions
|
||||
- Replaces RAG systems and reduces developer effort, and cost.
|
||||
- Load data to graph and vector databases using only Pydantic
|
||||
- Manipulate your data while ingesting from 30+ data sources
|
||||
|
||||
## Get Started
|
||||
|
||||
Get started quickly with a Google Colab <a href="https://colab.research.google.com/drive/1jHbWVypDgCLwjE71GSXhRL3YxYhCZzG1?usp=sharing">notebook</a> , <a href="https://deepnote.com/workspace/cognee-382213d0-0444-4c89-8265-13770e333c02/project/cognee-demo-78ffacb9-5832-4611-bb1a-560386068b30/notebook/Notebook-1-75b24cda566d4c24ab348f7150792601?utm_source=share-modal&utm_medium=product-shared-content&utm_campaign=notebook&utm_content=78ffacb9-5832-4611-bb1a-560386068b30">Deepnote notebook</a> or <a href="https://github.com/topoteretes/cognee/tree/main/cognee-starter-kit">starter repo</a>
|
||||
|
||||
|
||||
## About cognee
|
||||
|
||||
Self-hosted package:
|
||||
|
||||
## Contributing
|
||||
Your contributions are at the core of making this a true open source project. Any contributions you make are **greatly appreciated**. See [`CONTRIBUTING.md`](CONTRIBUTING.md) for more information.
|
||||
- Interconnects any kind of documents: past conversations, files, images, and audio transcriptions
|
||||
- Replaces RAG systems with a memory layer based on graphs and vectors
|
||||
- Reduces developer effort and cost, while increasing quality and precision
|
||||
- Provides Pythonic data pipelines that manage data ingestion from 30+ data sources
|
||||
- Is highly customizable with custom tasks, pipelines, and a set of built-in search endpoints
|
||||
|
||||
Hosted platform:
|
||||
- Includes a managed UI and a [hosted solution](www.cognee.ai)
|
||||
|
||||
|
||||
|
||||
## Self-Hosted (Open Source)
|
||||
|
||||
|
||||
## 📦 Installation
|
||||
### 📦 Installation
|
||||
|
||||
You can install Cognee using either **pip**, **poetry**, **uv** or any other python package manager.
|
||||
|
||||
Cognee supports Python 3.10 to 3.13
|
||||
Cognee supports Python 3.10 to 3.12
|
||||
|
||||
### With pip
|
||||
#### With uv
|
||||
|
||||
```bash
|
||||
pip install cognee
|
||||
uv pip install cognee
|
||||
```
|
||||
|
||||
## Local Cognee installation
|
||||
Detailed instructions can be found in our [docs](https://docs.cognee.ai/getting-started/installation#environment-configuration)
|
||||
|
||||
You can install the local Cognee repo using **uv**, **pip** and **poetry**.
|
||||
For local pip installation please make sure your pip version is above version 21.3.
|
||||
### 💻 Basic Usage
|
||||
|
||||
### with UV with all optional dependencies
|
||||
|
||||
```bash
|
||||
uv sync --all-extras
|
||||
```
|
||||
|
||||
## 💻 Basic Usage
|
||||
|
||||
### Setup
|
||||
#### Setup
|
||||
|
||||
```
|
||||
import os
|
||||
|
|
@ -125,10 +117,14 @@ os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY"
|
|||
```
|
||||
|
||||
You can also set the variables by creating .env file, using our <a href="https://github.com/topoteretes/cognee/blob/main/.env.template">template.</a>
|
||||
To use different LLM providers, for more info check out our <a href="https://docs.cognee.ai">documentation</a>
|
||||
To use different LLM providers, for more info check out our <a href="https://docs.cognee.ai/setup-configuration/llm-providers">documentation</a>
|
||||
|
||||
|
||||
### Simple example
|
||||
#### Simple example
|
||||
|
||||
|
||||
|
||||
##### Python
|
||||
|
||||
This script will run the default pipeline:
|
||||
|
||||
|
|
@ -139,13 +135,16 @@ import asyncio
|
|||
|
||||
async def main():
|
||||
# Add text to cognee
|
||||
await cognee.add("Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval.")
|
||||
await cognee.add("Cognee turns documents into AI memory.")
|
||||
|
||||
# Generate the knowledge graph
|
||||
await cognee.cognify()
|
||||
|
||||
# Add memory algorithms to the graph
|
||||
await cognee.memify()
|
||||
|
||||
# Query the knowledge graph
|
||||
results = await cognee.search("Tell me about NLP")
|
||||
results = await cognee.search("What does cognee do?")
|
||||
|
||||
# Display the results
|
||||
for result in results:
|
||||
|
|
@ -158,33 +157,38 @@ if __name__ == '__main__':
|
|||
```
|
||||
Example output:
|
||||
```
|
||||
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.
|
||||
Cognee turns documents into AI memory.
|
||||
|
||||
```
|
||||
##### Via CLI
|
||||
|
||||
## Our paper is out! <a href="https://arxiv.org/abs/2505.24478" target="_blank" rel="noopener noreferrer">Read here</a>
|
||||
Let's get the basics covered
|
||||
|
||||
```
|
||||
cognee-cli add "Cognee turns documents into AI memory."
|
||||
|
||||
cognee-cli cognify
|
||||
|
||||
cognee-cli search "What does cognee do?"
|
||||
cognee-cli delete --all
|
||||
|
||||
```
|
||||
or run
|
||||
```
|
||||
cognee-cli -ui
|
||||
```
|
||||
|
||||
<div style="text-align: center">
|
||||
<img src="assets/cognee-paper.png" alt="cognee paper" width="100%" />
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
## Cognee UI
|
||||
|
||||
You can also cognify your files and query using cognee UI.
|
||||
### Hosted Platform
|
||||
|
||||
<img src="assets/cognee-new-ui.webp" width="100%" alt="Cognee UI 2"></a>
|
||||
Get up and running in minutes with automatic updates, analytics, and enterprise security.
|
||||
|
||||
### Running the UI
|
||||
1. Sign up on [cogwit](https://www.cognee.ai)
|
||||
2. Add your API key to local UI and sync your data to Cogwit
|
||||
|
||||
Try cognee UI by setting LLM_API_KEY and running ``` cognee-cli -ui ``` command on your terminal.
|
||||
|
||||
## Understand our architecture
|
||||
|
||||
<div style="text-align: center">
|
||||
<img src="assets/cognee_diagram.png" alt="cognee concept diagram" width="100%" />
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
|
|
@ -203,22 +207,26 @@ Try cognee UI by setting LLM_API_KEY and running ``` cognee-cli -ui ``` command
|
|||
[cognee with local models](https://github.com/user-attachments/assets/8621d3e8-ecb8-4860-afb2-5594f2ee17db)
|
||||
|
||||
|
||||
## Contributing
|
||||
Your contributions are at the core of making this a true open source project. Any contributions you make are **greatly appreciated**. See [`CONTRIBUTING.md`](CONTRIBUTING.md) for more information.
|
||||
|
||||
|
||||
## Code of Conduct
|
||||
|
||||
We are committed to making open source an enjoyable and respectful experience for our community. See <a href="https://github.com/topoteretes/cognee/blob/main/CODE_OF_CONDUCT.md"><code>CODE_OF_CONDUCT</code></a> for more information.
|
||||
|
||||
## 💫 Contributors
|
||||
## Citation
|
||||
|
||||
<a href="https://github.com/topoteretes/cognee/graphs/contributors">
|
||||
<img alt="contributors" src="https://contrib.rocks/image?repo=topoteretes/cognee"/>
|
||||
</a>
|
||||
We now have a paper you can cite:
|
||||
|
||||
## Sponsors
|
||||
|
||||
Thanks to the following companies for sponsoring the ongoing development of cognee.
|
||||
|
||||
- [GitHub's Secure Open Source Fund](https://resources.github.com/github-secure-open-source-fund/)
|
||||
|
||||
## Star History
|
||||
|
||||
[](https://star-history.com/#topoteretes/cognee&Date)
|
||||
```bibtex
|
||||
@misc{markovic2025optimizinginterfaceknowledgegraphs,
|
||||
title={Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning},
|
||||
author={Vasilije Markovic and Lazar Obradovic and Laszlo Hajdu and Jovan Pavlovic},
|
||||
year={2025},
|
||||
eprint={2505.24478},
|
||||
archivePrefix={arXiv},
|
||||
primaryClass={cs.AI},
|
||||
url={https://arxiv.org/abs/2505.24478},
|
||||
}
|
||||
```
|
||||
|
|
|
|||
153
cognee-gui.py
153
cognee-gui.py
|
|
@ -1,153 +0,0 @@
|
|||
import sys
|
||||
import asyncio
|
||||
|
||||
try:
|
||||
import cognee
|
||||
from PySide6.QtWidgets import (
|
||||
QApplication,
|
||||
QWidget,
|
||||
QPushButton,
|
||||
QLineEdit,
|
||||
QFileDialog,
|
||||
QVBoxLayout,
|
||||
QHBoxLayout,
|
||||
QLabel,
|
||||
QMessageBox,
|
||||
QTextEdit,
|
||||
QProgressDialog,
|
||||
)
|
||||
from PySide6.QtCore import Qt
|
||||
|
||||
from qasync import QEventLoop # Import QEventLoop from qasync
|
||||
except ImportError as e:
|
||||
print(
|
||||
"\nPlease install Cognee with optional gui dependencies or manually install missing dependencies.\n"
|
||||
)
|
||||
print("\nTo install with poetry use:")
|
||||
print("\npoetry install -E gui\n")
|
||||
print("\nOr to install with poetry and all dependencies use:")
|
||||
print("\npoetry install --all-extras\n")
|
||||
print("\nTo install with pip use: ")
|
||||
print('\npip install ".[gui]"\n')
|
||||
raise e
|
||||
|
||||
|
||||
class FileSearchApp(QWidget):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.selected_file = None
|
||||
self.init_ui()
|
||||
|
||||
def init_ui(self):
|
||||
# Horizontal layout for file upload and visualization buttons
|
||||
button_layout = QHBoxLayout()
|
||||
|
||||
# Button to open file dialog
|
||||
self.file_button = QPushButton("Upload File to Cognee", parent=self)
|
||||
self.file_button.clicked.connect(self.open_file_dialog)
|
||||
button_layout.addWidget(self.file_button)
|
||||
|
||||
# Button to visualize data
|
||||
self.visualize_button = QPushButton("Visualize Data", parent=self)
|
||||
self.visualize_button.clicked.connect(lambda: asyncio.ensure_future(self.visualize_data()))
|
||||
button_layout.addWidget(self.visualize_button)
|
||||
|
||||
# Label to display selected file path
|
||||
self.file_label = QLabel("No file selected", parent=self)
|
||||
|
||||
# Line edit for search input
|
||||
self.search_input = QLineEdit(parent=self)
|
||||
self.search_input.setPlaceholderText("Enter text to search...")
|
||||
|
||||
# Button to perform search; schedule the async search on click
|
||||
self.search_button = QPushButton("Cognee Search", parent=self)
|
||||
self.search_button.clicked.connect(lambda: asyncio.ensure_future(self._cognee_search()))
|
||||
|
||||
# Text output area for search results
|
||||
self.result_output = QTextEdit(parent=self)
|
||||
self.result_output.setReadOnly(True)
|
||||
self.result_output.setPlaceholderText("Search results will appear here...")
|
||||
|
||||
# Progress dialog
|
||||
self.progress_dialog = QProgressDialog("Processing..", None, 0, 0, parent=self)
|
||||
self.progress_dialog.setWindowModality(Qt.WindowModal)
|
||||
self.progress_dialog.setCancelButton(None) # Remove the cancel button
|
||||
self.progress_dialog.close()
|
||||
|
||||
# Layout setup
|
||||
layout = QVBoxLayout()
|
||||
layout.addLayout(button_layout)
|
||||
layout.addWidget(self.file_label)
|
||||
layout.addWidget(self.search_input)
|
||||
layout.addWidget(self.search_button)
|
||||
layout.addWidget(self.result_output)
|
||||
|
||||
self.setLayout(layout)
|
||||
self.setWindowTitle("Cognee")
|
||||
self.resize(500, 300)
|
||||
|
||||
def open_file_dialog(self):
|
||||
file_path, _ = QFileDialog.getOpenFileName(
|
||||
self, "Select a File", "", "All Files (*.*);;Text Files (*.txt)"
|
||||
)
|
||||
if file_path:
|
||||
self.selected_file = file_path
|
||||
self.file_label.setText(f"Selected: {file_path}")
|
||||
asyncio.ensure_future(self.process_file_async())
|
||||
|
||||
async def process_file_async(self):
|
||||
"""Asynchronously add and process the selected file."""
|
||||
# Disable the entire window
|
||||
self.progress_dialog.show()
|
||||
self.setEnabled(False)
|
||||
try:
|
||||
await cognee.add(self.selected_file)
|
||||
await cognee.cognify()
|
||||
except Exception as e:
|
||||
QMessageBox.critical(self, "Error", f"File processing failed: {str(e)}")
|
||||
# Once finished, re-enable the window
|
||||
self.setEnabled(True)
|
||||
self.progress_dialog.close()
|
||||
|
||||
async def _cognee_search(self):
|
||||
"""Performs an async search and updates the result output."""
|
||||
# Disable the entire window
|
||||
self.setEnabled(False)
|
||||
self.progress_dialog.show()
|
||||
|
||||
try:
|
||||
search_text = self.search_input.text().strip()
|
||||
result = await cognee.search(query_text=search_text)
|
||||
print(result)
|
||||
# Assuming result is a list-like object; adjust if necessary
|
||||
self.result_output.setText(result[0])
|
||||
except Exception as e:
|
||||
QMessageBox.critical(self, "Error", f"Search failed: {str(e)}")
|
||||
|
||||
# Once finished, re-enable the window
|
||||
self.setEnabled(True)
|
||||
self.progress_dialog.close()
|
||||
|
||||
async def visualize_data(self):
|
||||
"""Async slot for handling visualize data button press."""
|
||||
import webbrowser
|
||||
from cognee.api.v1.visualize.visualize import visualize_graph
|
||||
import os
|
||||
import pathlib
|
||||
|
||||
html_file = os.path.join(pathlib.Path(__file__).parent, ".data", "graph_visualization.html")
|
||||
await visualize_graph(html_file)
|
||||
webbrowser.open(f"file://{html_file}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
app = QApplication(sys.argv)
|
||||
# Create a qasync event loop and set it as the current event loop
|
||||
loop = QEventLoop(app)
|
||||
asyncio.set_event_loop(loop)
|
||||
|
||||
window = FileSearchApp()
|
||||
window.show()
|
||||
|
||||
with loop:
|
||||
loop.run_forever()
|
||||
|
|
@ -8,7 +8,7 @@ requires-python = ">=3.10"
|
|||
dependencies = [
|
||||
# For local cognee repo usage remove comment bellow and add absolute path to cognee. Then run `uv sync --reinstall` in the mcp folder on local cognee changes.
|
||||
#"cognee[postgres,codegraph,gemini,huggingface,docs,neo4j] @ file:/Users/igorilic/Desktop/cognee",
|
||||
"cognee[postgres,codegraph,gemini,huggingface,docs,neo4j]==0.3.2",
|
||||
"cognee[postgres,codegraph,gemini,huggingface,docs,neo4j]==0.3.4",
|
||||
"fastmcp>=2.10.0,<3.0.0",
|
||||
"mcp>=1.12.0,<2.0.0",
|
||||
"uv>=0.6.3,<1.0.0",
|
||||
|
|
|
|||
3529
cognee-mcp/uv.lock
generated
3529
cognee-mcp/uv.lock
generated
File diff suppressed because it is too large
Load diff
|
|
@ -234,7 +234,7 @@ class NeptuneAnalyticsAdapter(NeptuneGraphDB, VectorDBInterface):
|
|||
collection_name: str,
|
||||
query_text: Optional[str] = None,
|
||||
query_vector: Optional[List[float]] = None,
|
||||
limit: int = None,
|
||||
limit: Optional[int] = None,
|
||||
with_vector: bool = False,
|
||||
):
|
||||
"""
|
||||
|
|
@ -265,10 +265,10 @@ class NeptuneAnalyticsAdapter(NeptuneGraphDB, VectorDBInterface):
|
|||
"Use this option only when vector data is required."
|
||||
)
|
||||
|
||||
# In the case of excessive limit, or zero / negative value, limit will be set to 10.
|
||||
# In the case of excessive limit, or None / zero / negative value, limit will be set to 10.
|
||||
if not limit or limit <= self._TOPK_LOWER_BOUND or limit > self._TOPK_UPPER_BOUND:
|
||||
logger.warning(
|
||||
"Provided limit (%s) is invalid (zero, negative, or exceeds maximum). "
|
||||
"Provided limit (%s) is invalid (None, zero, negative, or exceeds maximum). "
|
||||
"Defaulting to limit=10.",
|
||||
limit,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -352,7 +352,7 @@ class ChromaDBAdapter(VectorDBInterface):
|
|||
collection_name: str,
|
||||
query_text: str = None,
|
||||
query_vector: List[float] = None,
|
||||
limit: int = 15,
|
||||
limit: Optional[int] = 15,
|
||||
with_vector: bool = False,
|
||||
normalized: bool = True,
|
||||
):
|
||||
|
|
@ -386,9 +386,13 @@ class ChromaDBAdapter(VectorDBInterface):
|
|||
try:
|
||||
collection = await self.get_collection(collection_name)
|
||||
|
||||
if limit == 0:
|
||||
if limit is None:
|
||||
limit = await collection.count()
|
||||
|
||||
# If limit is still 0, no need to do the search, just return empty results
|
||||
if limit <= 0:
|
||||
return []
|
||||
|
||||
results = await collection.query(
|
||||
query_embeddings=[query_vector],
|
||||
include=["metadatas", "distances", "embeddings"]
|
||||
|
|
@ -428,7 +432,7 @@ class ChromaDBAdapter(VectorDBInterface):
|
|||
for row in vector_list
|
||||
]
|
||||
except Exception as e:
|
||||
logger.error(f"Error in search: {str(e)}")
|
||||
logger.warning(f"Error in search: {str(e)}")
|
||||
return []
|
||||
|
||||
async def batch_search(
|
||||
|
|
|
|||
|
|
@ -226,7 +226,7 @@ class LanceDBAdapter(VectorDBInterface):
|
|||
collection_name: str,
|
||||
query_text: str = None,
|
||||
query_vector: List[float] = None,
|
||||
limit: int = 15,
|
||||
limit: Optional[int] = 15,
|
||||
with_vector: bool = False,
|
||||
normalized: bool = True,
|
||||
):
|
||||
|
|
@ -238,11 +238,11 @@ class LanceDBAdapter(VectorDBInterface):
|
|||
|
||||
collection = await self.get_collection(collection_name)
|
||||
|
||||
if limit == 0:
|
||||
if limit is None:
|
||||
limit = await collection.count_rows()
|
||||
|
||||
# LanceDB search will break if limit is 0 so we must return
|
||||
if limit == 0:
|
||||
if limit <= 0:
|
||||
return []
|
||||
|
||||
result_values = await collection.vector_search(query_vector).limit(limit).to_list()
|
||||
|
|
@ -265,7 +265,7 @@ class LanceDBAdapter(VectorDBInterface):
|
|||
self,
|
||||
collection_name: str,
|
||||
query_texts: List[str],
|
||||
limit: int = None,
|
||||
limit: Optional[int] = None,
|
||||
with_vectors: bool = False,
|
||||
):
|
||||
query_vectors = await self.embedding_engine.embed_text(query_texts)
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@ from typing import List, Optional, get_type_hints
|
|||
from sqlalchemy.inspection import inspect
|
||||
from sqlalchemy.orm import Mapped, mapped_column
|
||||
from sqlalchemy.dialects.postgresql import insert
|
||||
from sqlalchemy import JSON, Column, Table, select, delete, MetaData
|
||||
from sqlalchemy import JSON, Column, Table, select, delete, MetaData, func
|
||||
from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker
|
||||
from sqlalchemy.exc import ProgrammingError
|
||||
from tenacity import retry, retry_if_exception_type, stop_after_attempt, wait_exponential
|
||||
|
|
@ -298,7 +298,7 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
|
|||
collection_name: str,
|
||||
query_text: Optional[str] = None,
|
||||
query_vector: Optional[List[float]] = None,
|
||||
limit: int = 15,
|
||||
limit: Optional[int] = 15,
|
||||
with_vector: bool = False,
|
||||
) -> List[ScoredResult]:
|
||||
if query_text is None and query_vector is None:
|
||||
|
|
@ -310,6 +310,16 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
|
|||
# Get PGVectorDataPoint Table from database
|
||||
PGVectorDataPoint = await self.get_table(collection_name)
|
||||
|
||||
if limit is None:
|
||||
async with self.get_async_session() as session:
|
||||
query = select(func.count()).select_from(PGVectorDataPoint)
|
||||
result = await session.execute(query)
|
||||
limit = result.scalar_one()
|
||||
|
||||
# If limit is still 0, no need to do the search, just return empty results
|
||||
if limit <= 0:
|
||||
return []
|
||||
|
||||
# NOTE: This needs to be initialized in case search doesn't return a value
|
||||
closest_items = []
|
||||
|
||||
|
|
|
|||
|
|
@ -83,7 +83,7 @@ class VectorDBInterface(Protocol):
|
|||
collection_name: str,
|
||||
query_text: Optional[str],
|
||||
query_vector: Optional[List[float]],
|
||||
limit: int,
|
||||
limit: Optional[int],
|
||||
with_vector: bool = False,
|
||||
):
|
||||
"""
|
||||
|
|
@ -98,7 +98,7 @@ class VectorDBInterface(Protocol):
|
|||
collection.
|
||||
- query_vector (Optional[List[float]]): An optional vector representation for
|
||||
searching the collection.
|
||||
- limit (int): The maximum number of results to return from the search.
|
||||
- limit (Optional[int]): The maximum number of results to return from the search.
|
||||
- with_vector (bool): Whether to return the vector representations with search
|
||||
results. (default False)
|
||||
"""
|
||||
|
|
@ -106,7 +106,11 @@ class VectorDBInterface(Protocol):
|
|||
|
||||
@abstractmethod
|
||||
async def batch_search(
|
||||
self, collection_name: str, query_texts: List[str], limit: int, with_vectors: bool = False
|
||||
self,
|
||||
collection_name: str,
|
||||
query_texts: List[str],
|
||||
limit: Optional[int],
|
||||
with_vectors: bool = False,
|
||||
):
|
||||
"""
|
||||
Perform a batch search using multiple text queries against a collection.
|
||||
|
|
@ -116,7 +120,7 @@ class VectorDBInterface(Protocol):
|
|||
|
||||
- collection_name (str): The name of the collection to conduct the batch search in.
|
||||
- query_texts (List[str]): A list of text queries to use for the search.
|
||||
- limit (int): The maximum number of results to return for each query.
|
||||
- limit (Optional[int]): The maximum number of results to return for each query.
|
||||
- with_vectors (bool): Whether to include vector representations with search
|
||||
results. (default False)
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -63,7 +63,7 @@ def get_model_max_completion_tokens(model_name: str):
|
|||
max_completion_tokens = litellm.model_cost[model_name]["max_tokens"]
|
||||
logger.debug(f"Max input tokens for {model_name}: {max_completion_tokens}")
|
||||
else:
|
||||
logger.info("Model not found in LiteLLM's model_cost.")
|
||||
logger.debug("Model not found in LiteLLM's model_cost.")
|
||||
|
||||
return max_completion_tokens
|
||||
|
||||
|
|
|
|||
|
|
@ -161,7 +161,7 @@ class CogneeGraph(CogneeAbstractGraph):
|
|||
edge_distances = await vector_engine.search(
|
||||
collection_name="EdgeType_relationship_name",
|
||||
query_vector=query_vector,
|
||||
limit=0,
|
||||
limit=None,
|
||||
)
|
||||
projection_time = time.time() - start_time
|
||||
logger.info(
|
||||
|
|
|
|||
|
|
@ -25,7 +25,7 @@ class InsightsRetriever(BaseGraphRetriever):
|
|||
- top_k
|
||||
"""
|
||||
|
||||
def __init__(self, exploration_levels: int = 1, top_k: int = 5):
|
||||
def __init__(self, exploration_levels: int = 1, top_k: Optional[int] = 5):
|
||||
"""Initialize retriever with exploration levels and search parameters."""
|
||||
self.exploration_levels = exploration_levels
|
||||
self.top_k = top_k
|
||||
|
|
|
|||
|
|
@ -130,7 +130,7 @@ class TemporalRetriever(GraphCompletionRetriever):
|
|||
query_vector = (await vector_engine.embedding_engine.embed_text([query]))[0]
|
||||
|
||||
vector_search_results = await vector_engine.search(
|
||||
collection_name="Event_name", query_vector=query_vector, limit=0
|
||||
collection_name="Event_name", query_vector=query_vector, limit=None
|
||||
)
|
||||
|
||||
top_k_events = await self.filter_top_k_events(relevant_events, vector_search_results)
|
||||
|
|
|
|||
|
|
@ -140,7 +140,7 @@ async def brute_force_triplet_search(
|
|||
async def search_in_collection(collection_name: str):
|
||||
try:
|
||||
return await vector_engine.search(
|
||||
collection_name=collection_name, query_vector=query_vector, limit=0
|
||||
collection_name=collection_name, query_vector=query_vector, limit=None
|
||||
)
|
||||
except CollectionNotFoundError:
|
||||
return []
|
||||
|
|
|
|||
|
|
@ -67,6 +67,39 @@ async def test_getting_of_documents(dataset_name_1):
|
|||
)
|
||||
|
||||
|
||||
async def test_vector_engine_search_none_limit():
|
||||
file_path = os.path.join(
|
||||
pathlib.Path(__file__).resolve().parent.parent.parent,
|
||||
"examples",
|
||||
"data",
|
||||
"alice_in_wonderland.txt",
|
||||
)
|
||||
|
||||
await cognee.prune.prune_data()
|
||||
await cognee.prune.prune_system(metadata=True)
|
||||
|
||||
await cognee.add(file_path)
|
||||
|
||||
await cognee.cognify()
|
||||
|
||||
query_text = "List me all the important characters in Alice in Wonderland."
|
||||
|
||||
from cognee.infrastructure.databases.vector import get_vector_engine
|
||||
|
||||
vector_engine = get_vector_engine()
|
||||
|
||||
collection_name = "Entity_name"
|
||||
|
||||
query_vector = (await vector_engine.embedding_engine.embed_text([query_text]))[0]
|
||||
|
||||
result = await vector_engine.search(
|
||||
collection_name=collection_name, query_vector=query_vector, limit=None
|
||||
)
|
||||
|
||||
# Check that we did not accidentally use any default value for limit in vector search along the way (like 5, 10, or 15)
|
||||
assert len(result) > 15
|
||||
|
||||
|
||||
async def main():
|
||||
cognee.config.set_vector_db_config(
|
||||
{
|
||||
|
|
@ -165,6 +198,8 @@ async def main():
|
|||
tables_in_database = await vector_engine.get_collection_names()
|
||||
assert len(tables_in_database) == 0, "ChromaDB database is not empty"
|
||||
|
||||
await test_vector_engine_search_none_limit()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
|
|
|||
206
cognee/tests/test_lancedb.py
Normal file
206
cognee/tests/test_lancedb.py
Normal file
|
|
@ -0,0 +1,206 @@
|
|||
import os
|
||||
import pathlib
|
||||
|
||||
import cognee
|
||||
from cognee.shared.logging_utils import get_logger
|
||||
from cognee.infrastructure.files.storage import get_storage_config
|
||||
from cognee.modules.data.models import Data
|
||||
from cognee.modules.users.methods import get_default_user
|
||||
from cognee.modules.search.types import SearchType
|
||||
from cognee.modules.search.operations import get_history
|
||||
|
||||
logger = get_logger()
|
||||
|
||||
|
||||
async def test_local_file_deletion(data_text, file_location):
|
||||
from sqlalchemy import select
|
||||
import hashlib
|
||||
from cognee.infrastructure.databases.relational import get_relational_engine
|
||||
|
||||
engine = get_relational_engine()
|
||||
|
||||
async with engine.get_async_session() as session:
|
||||
# Get hash of data contents
|
||||
encoded_text = data_text.encode("utf-8")
|
||||
data_hash = hashlib.md5(encoded_text).hexdigest()
|
||||
# Get data entry from database based on hash contents
|
||||
data = (await session.scalars(select(Data).where(Data.content_hash == data_hash))).one()
|
||||
assert os.path.isfile(data.raw_data_location.replace("file://", "")), (
|
||||
f"Data location doesn't exist: {data.raw_data_location}"
|
||||
)
|
||||
# Test deletion of data along with local files created by cognee
|
||||
await engine.delete_data_entity(data.id)
|
||||
assert not os.path.exists(data.raw_data_location.replace("file://", "")), (
|
||||
f"Data location still exists after deletion: {data.raw_data_location}"
|
||||
)
|
||||
|
||||
async with engine.get_async_session() as session:
|
||||
# Get data entry from database based on file path
|
||||
data = (
|
||||
await session.scalars(select(Data).where(Data.raw_data_location == file_location))
|
||||
).one()
|
||||
assert os.path.isfile(data.raw_data_location.replace("file://", "")), (
|
||||
f"Data location doesn't exist: {data.raw_data_location}"
|
||||
)
|
||||
# Test local files not created by cognee won't get deleted
|
||||
await engine.delete_data_entity(data.id)
|
||||
assert os.path.exists(data.raw_data_location.replace("file://", "")), (
|
||||
f"Data location doesn't exists: {data.raw_data_location}"
|
||||
)
|
||||
|
||||
|
||||
async def test_getting_of_documents(dataset_name_1):
|
||||
# Test getting of documents for search per dataset
|
||||
from cognee.modules.users.permissions.methods import get_document_ids_for_user
|
||||
|
||||
user = await get_default_user()
|
||||
document_ids = await get_document_ids_for_user(user.id, [dataset_name_1])
|
||||
assert len(document_ids) == 1, (
|
||||
f"Number of expected documents doesn't match {len(document_ids)} != 1"
|
||||
)
|
||||
|
||||
# Test getting of documents for search when no dataset is provided
|
||||
user = await get_default_user()
|
||||
document_ids = await get_document_ids_for_user(user.id)
|
||||
assert len(document_ids) == 2, (
|
||||
f"Number of expected documents doesn't match {len(document_ids)} != 2"
|
||||
)
|
||||
|
||||
|
||||
async def test_vector_engine_search_none_limit():
|
||||
file_path = os.path.join(
|
||||
pathlib.Path(__file__).resolve().parent.parent.parent,
|
||||
"examples",
|
||||
"data",
|
||||
"alice_in_wonderland.txt",
|
||||
)
|
||||
|
||||
await cognee.prune.prune_data()
|
||||
await cognee.prune.prune_system(metadata=True)
|
||||
|
||||
await cognee.add(file_path)
|
||||
|
||||
await cognee.cognify()
|
||||
|
||||
query_text = "List me all the important characters in Alice in Wonderland."
|
||||
|
||||
from cognee.infrastructure.databases.vector import get_vector_engine
|
||||
|
||||
vector_engine = get_vector_engine()
|
||||
|
||||
collection_name = "Entity_name"
|
||||
|
||||
query_vector = (await vector_engine.embedding_engine.embed_text([query_text]))[0]
|
||||
|
||||
result = await vector_engine.search(
|
||||
collection_name=collection_name, query_vector=query_vector, limit=None
|
||||
)
|
||||
|
||||
# Check that we did not accidentally use any default value for limit in vector search along the way (like 5, 10, or 15)
|
||||
assert len(result) > 15
|
||||
|
||||
|
||||
async def main():
|
||||
cognee.config.set_vector_db_config(
|
||||
{
|
||||
"vector_db_provider": "lancedb",
|
||||
}
|
||||
)
|
||||
|
||||
data_directory_path = str(
|
||||
pathlib.Path(
|
||||
os.path.join(pathlib.Path(__file__).parent, ".data_storage/test_lancedb")
|
||||
).resolve()
|
||||
)
|
||||
cognee.config.data_root_directory(data_directory_path)
|
||||
cognee_directory_path = str(
|
||||
pathlib.Path(
|
||||
os.path.join(pathlib.Path(__file__).parent, ".cognee_system/test_lancedb")
|
||||
).resolve()
|
||||
)
|
||||
cognee.config.system_root_directory(cognee_directory_path)
|
||||
|
||||
await cognee.prune.prune_data()
|
||||
await cognee.prune.prune_system(metadata=True)
|
||||
|
||||
dataset_name_1 = "natural_language"
|
||||
dataset_name_2 = "quantum"
|
||||
|
||||
explanation_file_path = os.path.join(
|
||||
pathlib.Path(__file__).parent, "test_data/Natural_language_processing.txt"
|
||||
)
|
||||
await cognee.add([explanation_file_path], dataset_name_1)
|
||||
|
||||
text = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena.
|
||||
At small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior, specifically quantum superposition and entanglement, using specialized hardware that supports the preparation and manipulation of quantum states.
|
||||
Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster (with respect to input size scaling) than any modern "classical" computer. In particular, a large-scale quantum computer could break widely used encryption schemes and aid physicists in performing physical simulations; however, the current state of the technology is largely experimental and impractical, with several obstacles to useful applications. Moreover, scalable quantum computers do not hold promise for many practical tasks, and for many important tasks quantum speedups are proven impossible.
|
||||
The basic unit of information in quantum computing is the qubit, similar to the bit in traditional digital electronics. Unlike a classical bit, a qubit can exist in a superposition of its two "basis" states. When measuring a qubit, the result is a probabilistic output of a classical bit, therefore making quantum computers nondeterministic in general. If a quantum computer manipulates the qubit in a particular way, wave interference effects can amplify the desired measurement results. The design of quantum algorithms involves creating procedures that allow a quantum computer to perform calculations efficiently and quickly.
|
||||
Physically engineering high-quality qubits has proven challenging. If a physical qubit is not sufficiently isolated from its environment, it suffers from quantum decoherence, introducing noise into calculations. Paradoxically, perfectly isolating qubits is also undesirable because quantum computations typically need to initialize qubits, perform controlled qubit interactions, and measure the resulting quantum states. Each of those operations introduces errors and suffers from noise, and such inaccuracies accumulate.
|
||||
In principle, a non-quantum (classical) computer can solve the same computational problems as a quantum computer, given enough time. Quantum advantage comes in the form of time complexity rather than computability, and quantum complexity theory shows that some quantum algorithms for carefully selected tasks require exponentially fewer computational steps than the best known non-quantum algorithms. Such tasks can in theory be solved on a large-scale quantum computer whereas classical computers would not finish computations in any reasonable amount of time. However, quantum speedup is not universal or even typical across computational tasks, since basic tasks such as sorting are proven to not allow any asymptotic quantum speedup. Claims of quantum supremacy have drawn significant attention to the discipline, but are demonstrated on contrived tasks, while near-term practical use cases remain limited.
|
||||
"""
|
||||
|
||||
await cognee.add([text], dataset_name_2)
|
||||
|
||||
await cognee.cognify([dataset_name_2, dataset_name_1])
|
||||
|
||||
from cognee.infrastructure.databases.vector import get_vector_engine
|
||||
|
||||
await test_getting_of_documents(dataset_name_1)
|
||||
|
||||
vector_engine = get_vector_engine()
|
||||
random_node = (await vector_engine.search("Entity_name", "Quantum computer"))[0]
|
||||
random_node_name = random_node.payload["text"]
|
||||
|
||||
search_results = await cognee.search(
|
||||
query_type=SearchType.INSIGHTS, query_text=random_node_name
|
||||
)
|
||||
assert len(search_results) != 0, "The search results list is empty."
|
||||
print("\n\nExtracted sentences are:\n")
|
||||
for result in search_results:
|
||||
print(f"{result}\n")
|
||||
|
||||
search_results = await cognee.search(
|
||||
query_type=SearchType.CHUNKS, query_text=random_node_name, datasets=[dataset_name_2]
|
||||
)
|
||||
assert len(search_results) != 0, "The search results list is empty."
|
||||
print("\n\nExtracted chunks are:\n")
|
||||
for result in search_results:
|
||||
print(f"{result}\n")
|
||||
|
||||
graph_completion = await cognee.search(
|
||||
query_type=SearchType.GRAPH_COMPLETION,
|
||||
query_text=random_node_name,
|
||||
datasets=[dataset_name_2],
|
||||
)
|
||||
assert len(graph_completion) != 0, "Completion result is empty."
|
||||
print("Completion result is:")
|
||||
print(graph_completion)
|
||||
|
||||
search_results = await cognee.search(
|
||||
query_type=SearchType.SUMMARIES, query_text=random_node_name
|
||||
)
|
||||
assert len(search_results) != 0, "Query related summaries don't exist."
|
||||
print("\n\nExtracted summaries are:\n")
|
||||
for result in search_results:
|
||||
print(f"{result}\n")
|
||||
|
||||
user = await get_default_user()
|
||||
history = await get_history(user.id)
|
||||
assert len(history) == 8, "Search history is not correct."
|
||||
|
||||
await cognee.prune.prune_data()
|
||||
data_root_directory = get_storage_config()["data_root_directory"]
|
||||
assert not os.path.isdir(data_root_directory), "Local data files are not deleted"
|
||||
|
||||
await cognee.prune.prune_system(metadata=True)
|
||||
connection = await vector_engine.get_connection()
|
||||
tables_in_database = await connection.table_names()
|
||||
assert len(tables_in_database) == 0, "LanceDB database is not empty"
|
||||
|
||||
await test_vector_engine_search_none_limit()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
||||
asyncio.run(main())
|
||||
|
|
@ -68,6 +68,39 @@ async def test_getting_of_documents(dataset_name_1):
|
|||
)
|
||||
|
||||
|
||||
async def test_vector_engine_search_none_limit():
|
||||
file_path = os.path.join(
|
||||
pathlib.Path(__file__).resolve().parent.parent.parent,
|
||||
"examples",
|
||||
"data",
|
||||
"alice_in_wonderland.txt",
|
||||
)
|
||||
|
||||
await cognee.prune.prune_data()
|
||||
await cognee.prune.prune_system(metadata=True)
|
||||
|
||||
await cognee.add(file_path)
|
||||
|
||||
await cognee.cognify()
|
||||
|
||||
query_text = "List me all the important characters in Alice in Wonderland."
|
||||
|
||||
from cognee.infrastructure.databases.vector import get_vector_engine
|
||||
|
||||
vector_engine = get_vector_engine()
|
||||
|
||||
collection_name = "Entity_name"
|
||||
|
||||
query_vector = (await vector_engine.embedding_engine.embed_text([query_text]))[0]
|
||||
|
||||
result = await vector_engine.search(
|
||||
collection_name=collection_name, query_vector=query_vector, limit=None
|
||||
)
|
||||
|
||||
# Check that we did not accidentally use any default value for limit in vector search along the way (like 5, 10, or 15)
|
||||
assert len(result) > 15
|
||||
|
||||
|
||||
async def main():
|
||||
cognee.config.set_vector_db_config(
|
||||
{"vector_db_url": "", "vector_db_key": "", "vector_db_provider": "pgvector"}
|
||||
|
|
@ -174,6 +207,8 @@ async def main():
|
|||
tables_in_database = await vector_engine.get_table_names()
|
||||
assert len(tables_in_database) == 0, "PostgreSQL database is not empty"
|
||||
|
||||
await test_vector_engine_search_none_limit()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import asyncio
|
||||
|
|
|
|||
|
|
@ -15,6 +15,9 @@ async def cognee_demo():
|
|||
current_directory = Path(__file__).resolve().parent.parent
|
||||
file_path = os.path.join(current_directory, "data", "alice_in_wonderland.txt")
|
||||
|
||||
await cognee.prune.prune_data()
|
||||
await cognee.prune.prune_system(metadata=True)
|
||||
|
||||
# Call Cognee to process document
|
||||
await cognee.add(file_path)
|
||||
await cognee.cognify()
|
||||
|
|
|
|||
|
|
@ -1,78 +0,0 @@
|
|||
# cognee Graduates from GitHub Secure Open Source Program
|
||||
|
||||
*Building Trust and Security in AI Memory Systems*
|
||||
|
||||
We're excited to announce that **cognee** has successfully graduated from the GitHub Secure Open Source Program! This milestone reflects our commitment to maintaining the highest standards of security and reliability in open source AI infrastructure.
|
||||
|
||||
## What is cognee?
|
||||
|
||||
cognee is an open source library that provides **memory for AI agents in just 5 lines of code**. It transforms raw data into structured knowledge graphs through our innovative ECL (Extract, Cognify, Load) pipeline, enabling AI systems to build dynamic memory that goes far beyond traditional RAG systems.
|
||||
|
||||
### Key Features:
|
||||
- **Interconnected Knowledge**: Links conversations, documents, images, and audio transcriptions
|
||||
- **Scalable Architecture**: Loads data to graph and vector databases using only Pydantic
|
||||
- **30+ Data Sources**: Manipulates data while ingesting from diverse sources
|
||||
- **Developer-Friendly**: Reduces complexity and cost compared to traditional RAG implementations
|
||||
|
||||
## GitHub Secure Open Source Program Achievement
|
||||
|
||||
The GitHub Secure Open Source Program helps maintainers adopt security best practices and ensures that critical open source projects meet enterprise-grade security standards. Our graduation demonstrates that cognee has successfully implemented:
|
||||
|
||||
- **Security-first development practices**
|
||||
- **Comprehensive vulnerability management**
|
||||
- **Secure dependency management**
|
||||
- **Code quality and review processes**
|
||||
- **Community safety guidelines**
|
||||
|
||||
## Why This Matters for AI Development
|
||||
|
||||
As AI systems become more prevalent in production environments, security becomes paramount. cognee's graduation from this program means developers can confidently build AI memory systems knowing they're using infrastructure that meets rigorous security standards.
|
||||
|
||||
### Benefits for Our Community:
|
||||
- **Enterprise Adoption**: Companies can deploy cognee with confidence in security-sensitive environments
|
||||
- **Vulnerability Response**: Our security practices ensure rapid identification and resolution of potential issues
|
||||
- **Supply Chain Security**: Dependencies are carefully managed and regularly audited
|
||||
- **Trust & Transparency**: Open source development with security-first principles
|
||||
|
||||
## What's Next?
|
||||
|
||||
With over **5,000 GitHub stars** and a growing community of developers, cognee continues to evolve. We recently launched **Cogwit beta** - our fully-hosted AI Memory platform, and our [research paper](https://arxiv.org/abs/2505.24478) demonstrates the effectiveness of our approach.
|
||||
|
||||
Our commitment to security doesn't end with graduation. We'll continue following best practices and contributing to the broader conversation about secure AI infrastructure.
|
||||
|
||||
## Get Started Today
|
||||
|
||||
Ready to add intelligent memory to your AI applications? Get started with cognee:
|
||||
|
||||
```python
|
||||
import cognee
|
||||
import asyncio
|
||||
|
||||
async def main():
|
||||
# Add your data
|
||||
await cognee.add("Your document content here")
|
||||
|
||||
# Transform into knowledge graph
|
||||
await cognee.cognify()
|
||||
|
||||
# Query intelligently
|
||||
results = await cognee.search("What insights can you find?")
|
||||
|
||||
for result in results:
|
||||
print(result)
|
||||
|
||||
asyncio.run(main())
|
||||
```
|
||||
|
||||
## Join Our Community
|
||||
|
||||
- 🌟 [Star us on GitHub](https://github.com/topoteretes/cognee)
|
||||
- 💬 [Join our Discord](https://discord.gg/NQPKmU5CCg)
|
||||
- 📖 [Read our documentation](https://docs.cognee.ai/)
|
||||
- 🚀 [Try Cogwit beta](https://platform.cognee.ai/)
|
||||
|
||||
The future of AI memory is secure, scalable, and open source. We're grateful for the GitHub team's support and excited to continue building the infrastructure that powers the next generation of intelligent applications.
|
||||
|
||||
---
|
||||
|
||||
*About cognee: We're building the memory layer for AI agents, enabling them to learn, remember, and reason across conversations and data sources. Our open source approach ensures that advanced AI memory capabilities are accessible to developers worldwide.*
|
||||
107
notebooks/data/copilot_conversations.json
vendored
Normal file
107
notebooks/data/copilot_conversations.json
vendored
Normal file
|
|
@ -0,0 +1,107 @@
|
|||
{
|
||||
"conversations": [
|
||||
{
|
||||
"id": "conv_001",
|
||||
"timestamp": "2024-01-15T10:30:00Z",
|
||||
"topic": "async/await patterns",
|
||||
"user_query": "I'm building a web scraper that needs to handle thousands of URLs concurrently. What's the best way to structure this with asyncio?",
|
||||
"assistant_response": "For high-concurrency web scraping, you'll want to use asyncio with aiohttp and implement proper semaphore-based rate limiting. Here's a robust pattern:\n\n```python\nimport asyncio\nimport aiohttp\nfrom typing import List, Dict, Any\n\nclass AsyncWebScraper:\n def __init__(self, max_concurrent: int = 100):\n self.semaphore = asyncio.Semaphore(max_concurrent)\n self.session = None\n \n async def __aenter__(self):\n self.session = aiohttp.ClientSession(\n timeout=aiohttp.ClientTimeout(total=30),\n connector=aiohttp.TCPConnector(limit=100)\n )\n return self\n \n async def __aexit__(self, exc_type, exc_val, exc_tb):\n if self.session:\n await self.session.close()\n \n async def fetch_url(self, url: str) -> Dict[str, Any]:\n async with self.semaphore:\n try:\n async with self.session.get(url) as response:\n content = await response.text()\n return {\n 'url': url,\n 'status': response.status,\n 'content': content,\n 'headers': dict(response.headers)\n }\n except Exception as e:\n return {'url': url, 'error': str(e)}\n \n async def scrape_urls(self, urls: List[str]) -> List[Dict[str, Any]]:\n tasks = [self.fetch_url(url) for url in urls]\n return await asyncio.gather(*tasks, return_exceptions=True)\n\n# Usage\nasync def main():\n urls = ['http://example.com'] * 1000 # Your URLs here\n \n async with AsyncWebScraper(max_concurrent=50) as scraper:\n results = await scraper.scrape_urls(urls)\n \n successful = [r for r in results if 'error' not in r]\n print(f'Successfully scraped {len(successful)} URLs')\n\nif __name__ == '__main__':\n asyncio.run(main())\n```\n\nKey points:\n- Semaphore controls concurrency to avoid overwhelming servers\n- Context manager ensures proper cleanup\n- TCPConnector with connection pooling\n- Proper exception handling for failed requests",
|
||||
"code_context": {
|
||||
"file": "scraper.py",
|
||||
"language": "python",
|
||||
"patterns_discussed": ["async/await", "context_managers", "semaphores", "aiohttp", "error_handling"]
|
||||
},
|
||||
"follow_up_questions": [
|
||||
"How do I add retry logic for failed requests?",
|
||||
"What's the best way to parse the scraped HTML content?"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "conv_002",
|
||||
"timestamp": "2024-01-16T14:20:00Z",
|
||||
"topic": "dataclass vs pydantic",
|
||||
"user_query": "When should I use dataclasses vs Pydantic models? I'm building an API and need to handle user input validation.",
|
||||
"assistant_response": "Great question! For API development with input validation, here's when to use each:\n\n**Use Pydantic when:**\n- Building APIs (FastAPI, Django REST)\n- Need runtime validation of external data\n- Want automatic JSON serialization/deserialization\n- Need complex validation rules\n- Working with configuration files\n\n**Use dataclasses when:**\n- Internal data structures\n- Simple data containers\n- Want to stay in stdlib\n- Performance is critical (dataclasses are faster)\n\nFor your API, I'd recommend Pydantic:\n\n```python\nfrom pydantic import BaseModel, validator, Field\nfrom typing import Optional, List\nfrom datetime import datetime\nfrom enum import Enum\n\nclass UserRole(str, Enum):\n ADMIN = 'admin'\n USER = 'user'\n GUEST = 'guest'\n\nclass CreateUserRequest(BaseModel):\n username: str = Field(..., min_length=3, max_length=50, regex=r'^[a-zA-Z0-9_]+$')\n email: str = Field(..., regex=r'^[\\w\\.-]+@[\\w\\.-]+\\.\\w+$')\n password: str = Field(..., min_length=8)\n role: UserRole = UserRole.USER\n tags: Optional[List[str]] = None\n \n @validator('password')\n def validate_password(cls, v):\n if not any(c.isupper() for c in v):\n raise ValueError('Password must contain uppercase letter')\n if not any(c.isdigit() for c in v):\n raise ValueError('Password must contain digit')\n return v\n \n @validator('tags')\n def validate_tags(cls, v):\n if v and len(v) > 10:\n raise ValueError('Too many tags')\n return v\n\nclass User(BaseModel):\n id: int\n username: str\n email: str\n role: UserRole\n created_at: datetime\n is_active: bool = True\n \n class Config:\n orm_mode = True\n json_encoders = { datetime: lambda v: v.isoformat() }\n\n# FastAPI usage\nfrom fastapi import FastAPI, HTTPException\n\napp = FastAPI()\n\n@app.post('/users/', response_model=User)\nasync def create_user(user_data: CreateUserRequest):\n try:\n new_user = await create_user_in_db(user_data)\n return User.from_orm(new_user)\n except Exception as e:\n raise HTTPException(status_code=400, detail=str(e))\n```\n\nPydantic gives you:\n- Automatic request validation\n- Clear error messages\n- Type coercion\n- JSON Schema generation\n- IDE support with type hints",
|
||||
"code_context": {
|
||||
"file": "models.py",
|
||||
"language": "python",
|
||||
"patterns_discussed": ["pydantic", "dataclasses", "validation", "fastapi", "type_hints", "enums"]
|
||||
},
|
||||
"follow_up_questions": [
|
||||
"How do I handle nested validation with Pydantic?",
|
||||
"Can I use Pydantic with SQLAlchemy models?"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "conv_003",
|
||||
"timestamp": "2024-01-17T09:15:00Z",
|
||||
"topic": "testing patterns",
|
||||
"user_query": "I'm struggling with testing async code and database interactions. What's the best approach for pytest with async functions?",
|
||||
"assistant_response": "Testing async code can be tricky! Here's a comprehensive approach using pytest-asyncio and proper test isolation...",
|
||||
"code_context": {
|
||||
"file": "test_users.py",
|
||||
"language": "python",
|
||||
"patterns_discussed": ["pytest", "async_testing", "fixtures", "mocking", "database_testing", "fastapi_testing"]
|
||||
},
|
||||
"follow_up_questions": [
|
||||
"How do I test WebSocket connections?",
|
||||
"What's the best way to test database migrations?"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "conv_004",
|
||||
"timestamp": "2024-01-18T16:45:00Z",
|
||||
"topic": "performance optimization",
|
||||
"user_query": "My FastAPI app is getting slow with large datasets. How can I optimize database queries and response times?",
|
||||
"assistant_response": "Performance optimization in FastAPI apps typically involves several layers...",
|
||||
"code_context": {
|
||||
"file": "optimizations.py",
|
||||
"language": "python",
|
||||
"patterns_discussed": ["performance_optimization", "caching", "database_optimization", "async_patterns", "monitoring"]
|
||||
},
|
||||
"follow_up_questions": [
|
||||
"How do I implement database connection pooling properly?",
|
||||
"What's the best way to handle memory usage with large datasets?"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "conv_005",
|
||||
"timestamp": "2024-01-19T11:30:00Z",
|
||||
"topic": "error handling and logging",
|
||||
"user_query": "I need to implement proper error handling and logging across my Python application. What's the best approach for production-ready error management?",
|
||||
"assistant_response": "Excellent question! Proper error handling and logging are crucial for production applications...",
|
||||
"code_context": {
|
||||
"file": "error_handling.py",
|
||||
"language": "python",
|
||||
"patterns_discussed": ["error_handling", "logging", "exceptions", "middleware", "decorators", "fastapi"]
|
||||
},
|
||||
"follow_up_questions": [
|
||||
"How do I integrate this with external monitoring tools like Sentry?",
|
||||
"What's the best way to handle errors in background tasks?"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"total_conversations": 5,
|
||||
"date_range": "2024-01-15 to 2024-01-19",
|
||||
"topics_covered": [
|
||||
"async/await patterns",
|
||||
"dataclass vs pydantic",
|
||||
"testing patterns",
|
||||
"performance optimization",
|
||||
"error handling and logging"
|
||||
],
|
||||
"code_patterns_discussed": [
|
||||
"asyncio", "aiohttp", "semaphores", "context_managers",
|
||||
"pydantic", "fastapi", "type_hints", "validation",
|
||||
"pytest", "async_testing", "fixtures", "mocking",
|
||||
"performance_optimization", "caching", "database_optimization",
|
||||
"error_handling", "logging", "exceptions", "middleware"
|
||||
],
|
||||
"difficulty_levels": {
|
||||
"beginner": 1,
|
||||
"intermediate": 2,
|
||||
"advanced": 2
|
||||
}
|
||||
}
|
||||
}
|
||||
976
notebooks/data/guido_contributions.json
vendored
Normal file
976
notebooks/data/guido_contributions.json
vendored
Normal file
|
|
@ -0,0 +1,976 @@
|
|||
[
|
||||
{
|
||||
"type": "pr",
|
||||
"repository": "mypy",
|
||||
"title": "Re-work indirect dependencies",
|
||||
"description": "Wow, this was quite a ride. Indirect dependencies were always supported kind of on best effort. This PR puts them on some principled foundation. It fixes three crashes and three stale types reported. All tests are quite weird/obscure, they are designed to expose the flaws in current logic (plus one test that passes on master, but it covers important corner case, so I add it just in case ). A short summary of various fixes (in arbitrary order):\r\n* Update many outdated comments and docstrings\r\n* Missing transitive dependency is now considered stale\r\n* Handle transitive generic bases in indirection visitor\r\n* Handle chained alias targets in indirection visitor\r\n* Always record original aliases during semantic analysis\r\n* Delete `qualified_tvars` as a concept, they are not needed since long ago\r\n* Remove ad-hoc handling for `TypeInfo`s from `build.py`\r\n* Support symbols with setter type different from getter type\r\n\r\nIn general the logic should be more simple/straightforward now:\r\n* Get all types in a file (need both symbol types _and_ expression types since some types may be only local)\r\n* For each type _transitively_ find all named types in them (thus aggregating all interfaces the type depends on)\r\n* In case any type was forced using `get_proper_type()`, record the orginal type alias during semantic analysis\r\n\r\nNote since this makes the algorithm correct, it may also make it slower (most notably because we must visit generic bases). I tried to offset this by couple optimizations, hopefully performance impact will be minimal.",
|
||||
"url": "https://github.com/python/mypy/pull/19798",
|
||||
"date": "2025-09-05T13:54:52Z",
|
||||
"sha_or_number": "19798",
|
||||
"files_changed": [
|
||||
"mypy/build.py",
|
||||
"mypy/fixup.py",
|
||||
"mypy/indirection.py",
|
||||
"mypy/nodes.py",
|
||||
"mypy/semanal.py",
|
||||
"mypy/server/deps.py",
|
||||
"mypy/test/typefixture.py",
|
||||
"mypy/typeanal.py",
|
||||
"test-data/unit/check-incremental.test"
|
||||
],
|
||||
"additions": 0,
|
||||
"deletions": 0,
|
||||
"labels": [],
|
||||
"related_issues": [],
|
||||
"code_samples": [
|
||||
{
|
||||
"file_path": "mypy/build.py",
|
||||
"language": "python",
|
||||
"before_code": "from mypy.graph_utils import prepare_sccs, strongly_connected_components, topsort\nfrom mypy.indirection import TypeIndirectionVisitor\nfrom mypy.messages import MessageBuilder\nfrom mypy.nodes import Import, ImportAll, ImportBase, ImportFrom, MypyFile, SymbolTable, TypeInfo\nfrom mypy.partially_defined import PossiblyUndefinedVariableVisitor\nfrom mypy.semanal import SemanticAnalyzer\nfrom mypy.semanal_pass1 import SemanticAnalyzerPreAnalysis",
|
||||
"after_code": "from mypy.graph_utils import prepare_sccs, strongly_connected_components, topsort\nfrom mypy.indirection import TypeIndirectionVisitor\nfrom mypy.messages import MessageBuilder\nfrom mypy.nodes import (\n Decorator,\n Import,\n ImportAll,\n ImportBase,\n ImportFrom,\n MypyFile,\n OverloadedFuncDef,\n SymbolTable,\n)\nfrom mypy.partially_defined import PossiblyUndefinedVariableVisitor\nfrom mypy.semanal import SemanticAnalyzer\nfrom mypy.semanal_pass1 import SemanticAnalyzerPreAnalysis",
|
||||
"diff_context": "from mypy.graph_utils import prepare_sccs, strongly_connected_components, topsort\nfrom mypy.indirection import TypeIndirectionVisitor\nfrom mypy.messages import MessageBuilder\nfrom mypy.nodes import Import, ImportAll, ImportBase, ImportFrom, MypyFile, SymbolTable, TypeInfo\nfrom mypy.nodes import (\n Decorator,\n Import,\n ImportAll,\n ImportBase,\n ImportFrom,\n MypyFile,\n OverloadedFuncDef,\n SymbolTable,\n)\nfrom mypy.partially_defined import PossiblyUndefinedVariableVisitor\nfrom mypy.semanal import SemanticAnalyzer\nfrom mypy.semanal_pass1 import SemanticAnalyzerPreAnalysis",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 6,
|
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|
||||
"file_path": "mypy/build.py",
|
||||
"language": "python",
|
||||
"before_code": "\nFor single nodes, processing is simple. If the node was cached, we\ndeserialize the cache data and fix up cross-references. Otherwise, we\ndo semantic analysis followed by type checking. We also handle (c)\nabove; if a module has valid cache data *but* any of its\ndependencies was processed from source, then the module should be\nprocessed from source.\n\nA relatively simple optimization (outside SCCs) we might do in the\nfuture is as follows: if a node's cache data is valid, but one or more\nof its dependencies are out of date so we have to re-parse the node\nfrom source, once we have fully type-checked the node, we can decide\nwhether its symbol table actually changed compared to the cache data\n(by reading the cache data and comparing it to the data we would be\nwriting). If there is no change we can declare the node up to date,\nand any node that depends (and for which we have cached data, and\nwhose other dependencies are up to date) on it won't need to be\nre-parsed from source.\n\nImport cycles\n-------------\n\nFinally we have to decide how to handle (c), import cycles. Here\nwe'll need a modified version of the original state machine\n(build.py), but we only need to do this per SCC, and we won't have to\ndeal with changes to the list of nodes while we're processing it.",
|
||||
"after_code": "\nFor single nodes, processing is simple. If the node was cached, we\ndeserialize the cache data and fix up cross-references. Otherwise, we\ndo semantic analysis followed by type checking. Once we (re-)processed\nan SCC we check whether its interface (symbol table) is still fresh\n(matches previous cached value). If it is not, we consider dependent SCCs\nstale so that they need to be re-parsed as well.\n\nNote on indirect dependencies: normally dependencies are determined from\nimports, but since our type interfaces are \"opaque\" (i.e. symbol tables can\ncontain types identified by name), these are not enough. We *must* also\nadd \"indirect\" dependencies from types to their definitions. For this\npurpose, after we finished processing a module, we travers its type map and\nsymbol tables, and for each type we find (transitively) on which opaque/named\ntypes it depends.\n\nImport cycles\n-------------\n\nFinally we have to decide how to handle (b), import cycles. Here\nwe'll need a modified version of the original state machine\n(build.py), but we only need to do this per SCC, and we won't have to\ndeal with changes to the list of nodes while we're processing it.",
|
||||
"diff_context": "\nFor single nodes, processing is simple. If the node was cached, we\ndeserialize the cache data and fix up cross-references. Otherwise, we\ndo semantic analysis followed by type checking. We also handle (c)\nabove; if a module has valid cache data *but* any of its\ndependencies was processed from source, then the module should be\nprocessed from source.\n\nA relatively simple optimization (outside SCCs) we might do in the\nfuture is as follows: if a node's cache data is valid, but one or more\nof its dependencies are out of date so we have to re-parse the node\nfrom source, once we have fully type-checked the node, we can decide\nwhether its symbol table actually changed compared to the cache data\n(by reading the cache data and comparing it to the data we would be\nwriting). If there is no change we can declare the node up to date,\nand any node that depends (and for which we have cached data, and\nwhose other dependencies are up to date) on it won't need to be\nre-parsed from source.\ndo semantic analysis followed by type checking. Once we (re-)processed\nan SCC we check whether its interface (symbol table) is still fresh\n(matches previous cached value). If it is not, we consider dependent SCCs\nstale so that they need to be re-parsed as well.\n\nNote on indirect dependencies: normally dependencies are determined from\nimports, but since our type interfaces are \"opaque\" (i.e. symbol tables can\ncontain types identified by name), these are not enough. We *must* also\nadd \"indirect\" dependencies from types to their definitions. For this\npurpose, after we finished processing a module, we travers its type map and\nsymbol tables, and for each type we find (transitively) on which opaque/named\ntypes it depends.\n\nImport cycles\n-------------\n\nFinally we have to decide how to handle (c), import cycles. Here\nFinally we have to decide how to handle (b), import cycles. Here\nwe'll need a modified version of the original state machine\n(build.py), but we only need to do this per SCC, and we won't have to\ndeal with changes to the list of nodes while we're processing it.",
|
||||
"change_type": "modification",
|
||||
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|
||||
"language": "python",
|
||||
"before_code": "\n # We should always patch indirect dependencies, even in full (non-incremental) builds,\n # because the cache still may be written, and it must be correct.\n # TODO: find a more robust way to traverse *all* relevant types?\n all_types = list(self.type_map().values())\n for _, sym, _ in self.tree.local_definitions():\n if sym.type is not None:\n all_types.append(sym.type)\n if isinstance(sym.node, TypeInfo):\n # TypeInfo symbols have some extra relevant types.\n all_types.extend(sym.node.bases)\n if sym.node.metaclass_type:\n all_types.append(sym.node.metaclass_type)\n if sym.node.typeddict_type:\n all_types.append(sym.node.typeddict_type)\n if sym.node.tuple_type:\n all_types.append(sym.node.tuple_type)\n self._patch_indirect_dependencies(self.type_checker().module_refs, all_types)\n\n if self.options.dump_inference_stats:\n dump_type_stats(",
|
||||
"after_code": "\n # We should always patch indirect dependencies, even in full (non-incremental) builds,\n # because the cache still may be written, and it must be correct.\n all_types = set(self.type_map().values())\n for _, sym, _ in self.tree.local_definitions():\n if sym.type is not None:\n all_types.add(sym.type)\n # Special case: settable properties may have two types.\n if isinstance(sym.node, OverloadedFuncDef) and sym.node.is_property:\n assert isinstance(first_node := sym.node.items[0], Decorator)\n if first_node.var.setter_type:\n all_types.add(first_node.var.setter_type)\n # Using mod_alias_deps is unfortunate but needed, since it is highly impractical\n # (and practically impossible) to avoid all get_proper_type() calls. For example,\n # TypeInfo.bases and metaclass, *args and **kwargs, Overloaded.items, and trivial\n # aliases like Text = str, etc. all currently forced to proper types. Thus, we need\n # to record the original definitions as they are first seen in semanal.py.\n self._patch_indirect_dependencies(\n self.type_checker().module_refs | self.tree.mod_alias_deps, all_types\n )\n\n if self.options.dump_inference_stats:\n dump_type_stats(",
|
||||
"diff_context": "\n # We should always patch indirect dependencies, even in full (non-incremental) builds,\n # because the cache still may be written, and it must be correct.\n # TODO: find a more robust way to traverse *all* relevant types?\n all_types = list(self.type_map().values())\n all_types = set(self.type_map().values())\n for _, sym, _ in self.tree.local_definitions():\n if sym.type is not None:\n all_types.append(sym.type)\n if isinstance(sym.node, TypeInfo):\n # TypeInfo symbols have some extra relevant types.\n all_types.extend(sym.node.bases)\n if sym.node.metaclass_type:\n all_types.append(sym.node.metaclass_type)\n if sym.node.typeddict_type:\n all_types.append(sym.node.typeddict_type)\n if sym.node.tuple_type:\n all_types.append(sym.node.tuple_type)\n self._patch_indirect_dependencies(self.type_checker().module_refs, all_types)\n all_types.add(sym.type)\n # Special case: settable properties may have two types.\n if isinstance(sym.node, OverloadedFuncDef) and sym.node.is_property:\n assert isinstance(first_node := sym.node.items[0], Decorator)\n if first_node.var.setter_type:\n all_types.add(first_node.var.setter_type)\n # Using mod_alias_deps is unfortunate but needed, since it is highly impractical\n # (and practically impossible) to avoid all get_proper_type() calls. For example,\n # TypeInfo.bases and metaclass, *args and **kwargs, Overloaded.items, and trivial\n # aliases like Text = str, etc. all currently forced to proper types. Thus, we need\n # to record the original definitions as they are first seen in semanal.py.\n self._patch_indirect_dependencies(\n self.type_checker().module_refs | self.tree.mod_alias_deps, all_types\n )\n\n if self.options.dump_inference_stats:\n dump_type_stats(",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 8,
|
||||
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|
||||
"file_path": "mypy/build.py",
|
||||
"language": "python",
|
||||
"before_code": " self._type_checker.reset()\n self._type_checker = None\n\n def _patch_indirect_dependencies(self, module_refs: set[str], types: list[Type]) -> None:\n assert None not in types\n valid = self.valid_references()\n",
|
||||
"after_code": " self._type_checker.reset()\n self._type_checker = None\n\n def _patch_indirect_dependencies(self, module_refs: set[str], types: set[Type]) -> None:\n assert None not in types\n valid = self.valid_references()\n",
|
||||
"diff_context": " self._type_checker.reset()\n self._type_checker = None\n\n def _patch_indirect_dependencies(self, module_refs: set[str], types: list[Type]) -> None:\n def _patch_indirect_dependencies(self, module_refs: set[str], types: set[Type]) -> None:\n assert None not in types\n valid = self.valid_references()\n",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 6,
|
||||
"function_name": "_patch_indirect_dependencies",
|
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|
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|
||||
"file_path": "mypy/build.py",
|
||||
"language": "python",
|
||||
"before_code": " for id in scc:\n deps.update(graph[id].dependencies)\n deps -= ascc\n stale_deps = {id for id in deps if id in graph and not graph[id].is_interface_fresh()}\n fresh = fresh and not stale_deps\n undeps = set()\n if fresh:",
|
||||
"after_code": " for id in scc:\n deps.update(graph[id].dependencies)\n deps -= ascc\n # Note: if a dependency is not in graph anymore, it should be considered interface-stale.\n # This is important to trigger any relevant updates from indirect dependencies that were\n # removed in load_graph().\n stale_deps = {id for id in deps if id not in graph or not graph[id].is_interface_fresh()}\n fresh = fresh and not stale_deps\n undeps = set()\n if fresh:",
|
||||
"diff_context": " for id in scc:\n deps.update(graph[id].dependencies)\n deps -= ascc\n stale_deps = {id for id in deps if id in graph and not graph[id].is_interface_fresh()}\n # Note: if a dependency is not in graph anymore, it should be considered interface-stale.\n # This is important to trigger any relevant updates from indirect dependencies that were\n # removed in load_graph().\n stale_deps = {id for id in deps if id not in graph or not graph[id].is_interface_fresh()}\n fresh = fresh and not stale_deps\n undeps = set()\n if fresh:",
|
||||
"change_type": "modification",
|
||||
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||||
"file_path": "mypy/indirection.py",
|
||||
"language": "python",
|
||||
"before_code": " def __init__(self) -> None:\n # Module references are collected here\n self.modules: set[str] = set()\n # User to avoid infinite recursion with recursive type aliases\n self.seen_aliases: set[types.TypeAliasType] = set()\n # Used to avoid redundant work\n self.seen_fullnames: set[str] = set()\n\n def find_modules(self, typs: Iterable[types.Type]) -> set[str]:\n self.modules = set()\n self.seen_fullnames = set()\n self.seen_aliases = set()\n for typ in typs:\n self._visit(typ)\n return self.modules\n\n def _visit(self, typ: types.Type) -> None:\n if isinstance(typ, types.TypeAliasType):\n # Avoid infinite recursion for recursive type aliases.\n if typ not in self.seen_aliases:\n self.seen_aliases.add(typ)\n typ.accept(self)\n\n def _visit_type_tuple(self, typs: tuple[types.Type, ...]) -> None:\n # Micro-optimization: Specialized version of _visit for lists\n for typ in typs:\n if isinstance(typ, types.TypeAliasType):\n # Avoid infinite recursion for recursive type aliases.\n if typ in self.seen_aliases:\n continue\n self.seen_aliases.add(typ)\n typ.accept(self)\n\n def _visit_type_list(self, typs: list[types.Type]) -> None:\n # Micro-optimization: Specialized version of _visit for tuples\n for typ in typs:\n if isinstance(typ, types.TypeAliasType):\n # Avoid infinite recursion for recursive type aliases.\n if typ in self.seen_aliases:\n continue\n self.seen_aliases.add(typ)\n typ.accept(self)\n\n def _visit_module_name(self, module_name: str) -> None:",
|
||||
"after_code": " def __init__(self) -> None:\n # Module references are collected here\n self.modules: set[str] = set()\n # User to avoid infinite recursion with recursive types\n self.seen_types: set[types.TypeAliasType | types.Instance] = set()\n # Used to avoid redundant work\n self.seen_fullnames: set[str] = set()\n\n def find_modules(self, typs: Iterable[types.Type]) -> set[str]:\n self.modules = set()\n self.seen_fullnames = set()\n self.seen_types = set()\n for typ in typs:\n self._visit(typ)\n return self.modules\n\n def _visit(self, typ: types.Type) -> None:\n # Note: instances are needed for `class str(Sequence[str]): ...`\n if (\n isinstance(typ, types.TypeAliasType)\n or isinstance(typ, types.ProperType)\n and isinstance(typ, types.Instance)\n ):\n # Avoid infinite recursion for recursive types.\n if typ in self.seen_types:\n return\n self.seen_types.add(typ)\n typ.accept(self)\n\n def _visit_type_tuple(self, typs: tuple[types.Type, ...]) -> None:\n # Micro-optimization: Specialized version of _visit for lists\n for typ in typs:\n if (\n isinstance(typ, types.TypeAliasType)\n or isinstance(typ, types.ProperType)\n and isinstance(typ, types.Instance)\n ):\n # Avoid infinite recursion for recursive types.\n if typ in self.seen_types:\n continue\n self.seen_types.add(typ)\n typ.accept(self)\n\n def _visit_type_list(self, typs: list[types.Type]) -> None:\n # Micro-optimization: Specialized version of _visit for tuples\n for typ in typs:\n if (\n isinstance(typ, types.TypeAliasType)\n or isinstance(typ, types.ProperType)\n and isinstance(typ, types.Instance)\n ):\n # Avoid infinite recursion for recursive types.\n if typ in self.seen_types:\n continue\n self.seen_types.add(typ)\n typ.accept(self)\n\n def _visit_module_name(self, module_name: str) -> None:",
|
||||
"diff_context": " def __init__(self) -> None:\n # Module references are collected here\n self.modules: set[str] = set()\n # User to avoid infinite recursion with recursive type aliases\n self.seen_aliases: set[types.TypeAliasType] = set()\n # User to avoid infinite recursion with recursive types\n self.seen_types: set[types.TypeAliasType | types.Instance] = set()\n # Used to avoid redundant work\n self.seen_fullnames: set[str] = set()\n\n def find_modules(self, typs: Iterable[types.Type]) -> set[str]:\n self.modules = set()\n self.seen_fullnames = set()\n self.seen_aliases = set()\n self.seen_types = set()\n for typ in typs:\n self._visit(typ)\n return self.modules\n\n def _visit(self, typ: types.Type) -> None:\n if isinstance(typ, types.TypeAliasType):\n # Avoid infinite recursion for recursive type aliases.\n if typ not in self.seen_aliases:\n self.seen_aliases.add(typ)\n # Note: instances are needed for `class str(Sequence[str]): ...`\n if (\n isinstance(typ, types.TypeAliasType)\n or isinstance(typ, types.ProperType)\n and isinstance(typ, types.Instance)\n ):\n # Avoid infinite recursion for recursive types.\n if typ in self.seen_types:\n return\n self.seen_types.add(typ)\n typ.accept(self)\n\n def _visit_type_tuple(self, typs: tuple[types.Type, ...]) -> None:\n # Micro-optimization: Specialized version of _visit for lists\n for typ in typs:\n if isinstance(typ, types.TypeAliasType):\n # Avoid infinite recursion for recursive type aliases.\n if typ in self.seen_aliases:\n if (\n isinstance(typ, types.TypeAliasType)\n or isinstance(typ, types.ProperType)\n and isinstance(typ, types.Instance)\n ):\n # Avoid infinite recursion for recursive types.\n if typ in self.seen_types:\n continue\n self.seen_aliases.add(typ)\n self.seen_types.add(typ)\n typ.accept(self)\n\n def _visit_type_list(self, typs: list[types.Type]) -> None:\n # Micro-optimization: Specialized version of _visit for tuples\n for typ in typs:\n if isinstance(typ, types.TypeAliasType):\n # Avoid infinite recursion for recursive type aliases.\n if typ in self.seen_aliases:\n if (\n isinstance(typ, types.TypeAliasType)\n or isinstance(typ, types.ProperType)\n and isinstance(typ, types.Instance)\n ):\n # Avoid infinite recursion for recursive types.\n if typ in self.seen_types:\n continue\n self.seen_aliases.add(typ)\n self.seen_types.add(typ)\n typ.accept(self)\n\n def _visit_module_name(self, module_name: str) -> None:",
|
||||
"change_type": "modification",
|
||||
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|
||||
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|
||||
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|
||||
"before_code": " self._visit_type_list(t.arg_types)\n\n def visit_instance(self, t: types.Instance) -> None:\n self._visit_type_tuple(t.args)\n if t.type:\n # Uses of a class depend on everything in the MRO,\n # as changes to classes in the MRO can add types to methods,\n # change property types, change the MRO itself, etc.\n for s in t.type.mro:\n self._visit_module_name(s.module_name)\n if t.type.metaclass_type is not None:\n self._visit_module_name(t.type.metaclass_type.type.module_name)\n\n def visit_callable_type(self, t: types.CallableType) -> None:\n self._visit_type_list(t.arg_types)",
|
||||
"after_code": " self._visit_type_list(t.arg_types)\n\n def visit_instance(self, t: types.Instance) -> None:\n # Instance is named, record its definition and continue digging into\n # components that constitute semantic meaning of this type: bases, metaclass,\n # tuple type, and typeddict type.\n # Note: we cannot simply record the MRO, in case an intermediate base contains\n # a reference to type alias, this affects meaning of map_instance_to_supertype(),\n # see e.g. testDoubleReexportGenericUpdated.\n self._visit_type_tuple(t.args)\n if t.type:\n # Important optimization: instead of simply recording the definition and\n # recursing into bases, record the MRO and only traverse generic bases.\n for s in t.type.mro:\n self._visit_module_name(s.module_name)\n for base in s.bases:\n if base.args:\n self._visit_type_tuple(base.args)\n if t.type.metaclass_type:\n self._visit(t.type.metaclass_type)\n if t.type.typeddict_type:\n self._visit(t.type.typeddict_type)\n if t.type.tuple_type:\n self._visit(t.type.tuple_type)\n\n def visit_callable_type(self, t: types.CallableType) -> None:\n self._visit_type_list(t.arg_types)",
|
||||
"diff_context": " self._visit_type_list(t.arg_types)\n\n def visit_instance(self, t: types.Instance) -> None:\n # Instance is named, record its definition and continue digging into\n # components that constitute semantic meaning of this type: bases, metaclass,\n # tuple type, and typeddict type.\n # Note: we cannot simply record the MRO, in case an intermediate base contains\n # a reference to type alias, this affects meaning of map_instance_to_supertype(),\n # see e.g. testDoubleReexportGenericUpdated.\n self._visit_type_tuple(t.args)\n if t.type:\n # Uses of a class depend on everything in the MRO,\n # as changes to classes in the MRO can add types to methods,\n # change property types, change the MRO itself, etc.\n # Important optimization: instead of simply recording the definition and\n # recursing into bases, record the MRO and only traverse generic bases.\n for s in t.type.mro:\n self._visit_module_name(s.module_name)\n if t.type.metaclass_type is not None:\n self._visit_module_name(t.type.metaclass_type.type.module_name)\n for base in s.bases:\n if base.args:\n self._visit_type_tuple(base.args)\n if t.type.metaclass_type:\n self._visit(t.type.metaclass_type)\n if t.type.typeddict_type:\n self._visit(t.type.typeddict_type)\n if t.type.tuple_type:\n self._visit(t.type.tuple_type)\n\n def visit_callable_type(self, t: types.CallableType) -> None:\n self._visit_type_list(t.arg_types)",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 10,
|
||||
"function_name": "visit_callable_type",
|
||||
"class_name": null,
|
||||
"docstring": null,
|
||||
"coding_patterns": [
|
||||
"generator_expression"
|
||||
]
|
||||
},
|
||||
{
|
||||
"file_path": "mypy/indirection.py",
|
||||
"language": "python",
|
||||
"before_code": " self.seen_fullnames.add(fullname)\n\n def visit_overloaded(self, t: types.Overloaded) -> None:\n self._visit_type_list(list(t.items))\n self._visit(t.fallback)\n\n def visit_tuple_type(self, t: types.TupleType) -> None:",
|
||||
"after_code": " self.seen_fullnames.add(fullname)\n\n def visit_overloaded(self, t: types.Overloaded) -> None:\n for item in t.items:\n self._visit(item)\n self._visit(t.fallback)\n\n def visit_tuple_type(self, t: types.TupleType) -> None:",
|
||||
"diff_context": " self.seen_fullnames.add(fullname)\n\n def visit_overloaded(self, t: types.Overloaded) -> None:\n self._visit_type_list(list(t.items))\n for item in t.items:\n self._visit(item)\n self._visit(t.fallback)\n\n def visit_tuple_type(self, t: types.TupleType) -> None:",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 6,
|
||||
"function_name": "visit_tuple_type",
|
||||
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|
||||
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|
||||
"coding_patterns": []
|
||||
},
|
||||
{
|
||||
"file_path": "mypy/indirection.py",
|
||||
"language": "python",
|
||||
"before_code": " self._visit(t.item)\n\n def visit_type_alias_type(self, t: types.TypeAliasType) -> None:\n self._visit(types.get_proper_type(t))",
|
||||
"after_code": " self._visit(t.item)\n\n def visit_type_alias_type(self, t: types.TypeAliasType) -> None:\n # Type alias is named, record its definition and continue digging into\n # components that constitute semantic meaning of this type: target and args.\n if t.alias:\n self._visit_module_name(t.alias.module)\n self._visit(t.alias.target)\n self._visit_type_list(t.args)",
|
||||
"diff_context": " self._visit(t.item)\n\n def visit_type_alias_type(self, t: types.TypeAliasType) -> None:\n self._visit(types.get_proper_type(t))\n # Type alias is named, record its definition and continue digging into\n # components that constitute semantic meaning of this type: target and args.\n if t.alias:\n self._visit_module_name(t.alias.module)\n self._visit(t.alias.target)\n self._visit_type_list(t.args)",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 3,
|
||||
"function_name": "visit_type_alias_type",
|
||||
"class_name": null,
|
||||
"docstring": null,
|
||||
"coding_patterns": []
|
||||
},
|
||||
{
|
||||
"file_path": "mypy/nodes.py",
|
||||
"language": "python",
|
||||
"before_code": " defs: list[Statement]\n # Type alias dependencies as mapping from target to set of alias full names\n alias_deps: defaultdict[str, set[str]]\n # Is there a UTF-8 BOM at the start?\n is_bom: bool\n names: SymbolTable",
|
||||
"after_code": " defs: list[Statement]\n # Type alias dependencies as mapping from target to set of alias full names\n alias_deps: defaultdict[str, set[str]]\n # Same as above but for coarse-grained dependencies (i.e. modules instead of full names)\n mod_alias_deps: set[str]\n # Is there a UTF-8 BOM at the start?\n is_bom: bool\n names: SymbolTable",
|
||||
"diff_context": " defs: list[Statement]\n # Type alias dependencies as mapping from target to set of alias full names\n alias_deps: defaultdict[str, set[str]]\n # Same as above but for coarse-grained dependencies (i.e. modules instead of full names)\n mod_alias_deps: set[str]\n # Is there a UTF-8 BOM at the start?\n is_bom: bool\n names: SymbolTable",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 6,
|
||||
"function_name": null,
|
||||
"class_name": null,
|
||||
"docstring": null,
|
||||
"coding_patterns": [
|
||||
"type_hint"
|
||||
]
|
||||
},
|
||||
{
|
||||
"file_path": "mypy/nodes.py",
|
||||
"language": "python",
|
||||
"before_code": " target: The target type. For generic aliases contains bound type variables\n as nested types (currently TypeVar and ParamSpec are supported).\n _fullname: Qualified name of this type alias. This is used in particular\n to track fine grained dependencies from aliases.\n alias_tvars: Type variables used to define this alias.\n normalized: Used to distinguish between `A = List`, and `A = list`. Both\n are internally stored using `builtins.list` (because `typing.List` is",
|
||||
"after_code": " target: The target type. For generic aliases contains bound type variables\n as nested types (currently TypeVar and ParamSpec are supported).\n _fullname: Qualified name of this type alias. This is used in particular\n to track fine-grained dependencies from aliases.\n module: Module where the alias was defined.\n alias_tvars: Type variables used to define this alias.\n normalized: Used to distinguish between `A = List`, and `A = list`. Both\n are internally stored using `builtins.list` (because `typing.List` is",
|
||||
"diff_context": " target: The target type. For generic aliases contains bound type variables\n as nested types (currently TypeVar and ParamSpec are supported).\n _fullname: Qualified name of this type alias. This is used in particular\n to track fine grained dependencies from aliases.\n to track fine-grained dependencies from aliases.\n module: Module where the alias was defined.\n alias_tvars: Type variables used to define this alias.\n normalized: Used to distinguish between `A = List`, and `A = list`. Both\n are internally stored using `builtins.list` (because `typing.List` is",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 6,
|
||||
"function_name": null,
|
||||
"class_name": null,
|
||||
"docstring": null,
|
||||
"coding_patterns": []
|
||||
},
|
||||
{
|
||||
"file_path": "mypy/semanal.py",
|
||||
"language": "python",
|
||||
"before_code": " declared_type_vars: TypeVarLikeList | None = None,\n all_declared_type_params_names: list[str] | None = None,\n python_3_12_type_alias: bool = False,\n ) -> tuple[Type | None, list[TypeVarLikeType], set[str], list[str], bool]:\n \"\"\"Check if 'rvalue' is a valid type allowed for aliasing (e.g. not a type variable).\n\n If yes, return the corresponding type, a list of\n qualified type variable names for generic aliases, a set of names the alias depends on,\n and a list of type variables if the alias is generic.\n A schematic example for the dependencies:\n A = int\n B = str\n analyze_alias(Dict[A, B])[2] == {'__main__.A', '__main__.B'}\n \"\"\"\n dynamic = bool(self.function_stack and self.function_stack[-1].is_dynamic())\n global_scope = not self.type and not self.function_stack",
|
||||
"after_code": " declared_type_vars: TypeVarLikeList | None = None,\n all_declared_type_params_names: list[str] | None = None,\n python_3_12_type_alias: bool = False,\n ) -> tuple[Type | None, list[TypeVarLikeType], set[tuple[str, str]], bool]:\n \"\"\"Check if 'rvalue' is a valid type allowed for aliasing (e.g. not a type variable).\n\n If yes, return the corresponding type, a list of type variables for generic aliases,\n a set of names the alias depends on, and True if the original type has empty tuple index.\n An example for the dependencies:\n A = int\n B = str\n analyze_alias(dict[A, B])[2] == {('mod', 'mod.A'), ('mod', 'mod.B')}\n \"\"\"\n dynamic = bool(self.function_stack and self.function_stack[-1].is_dynamic())\n global_scope = not self.type and not self.function_stack",
|
||||
"diff_context": " declared_type_vars: TypeVarLikeList | None = None,\n all_declared_type_params_names: list[str] | None = None,\n python_3_12_type_alias: bool = False,\n ) -> tuple[Type | None, list[TypeVarLikeType], set[str], list[str], bool]:\n ) -> tuple[Type | None, list[TypeVarLikeType], set[tuple[str, str]], bool]:\n \"\"\"Check if 'rvalue' is a valid type allowed for aliasing (e.g. not a type variable).\n\n If yes, return the corresponding type, a list of\n qualified type variable names for generic aliases, a set of names the alias depends on,\n and a list of type variables if the alias is generic.\n A schematic example for the dependencies:\n If yes, return the corresponding type, a list of type variables for generic aliases,\n a set of names the alias depends on, and True if the original type has empty tuple index.\n An example for the dependencies:\n A = int\n B = str\n analyze_alias(Dict[A, B])[2] == {'__main__.A', '__main__.B'}\n analyze_alias(dict[A, B])[2] == {('mod', 'mod.A'), ('mod', 'mod.B')}\n \"\"\"\n dynamic = bool(self.function_stack and self.function_stack[-1].is_dynamic())\n global_scope = not self.type and not self.function_stack",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 10,
|
||||
"function_name": null,
|
||||
"class_name": null,
|
||||
"docstring": "\"\"\"Check if 'rvalue' is a valid type allowed for aliasing (e.g. not a type variable).",
|
||||
"coding_patterns": [
|
||||
"list_comprehension"
|
||||
]
|
||||
},
|
||||
{
|
||||
"file_path": "mypy/semanal.py",
|
||||
"language": "python",
|
||||
"before_code": " self.cur_mod_node.plugin_deps.setdefault(trigger, set()).add(target)\n\n def add_type_alias_deps(\n self, aliases_used: Collection[str], target: str | None = None\n ) -> None:\n \"\"\"Add full names of type aliases on which the current node depends.\n\n This is used by fine-grained incremental mode to re-check the corresponding nodes.\n If `target` is None, then the target node used will be the current scope.\n \"\"\"\n if not aliases_used:\n # A basic optimization to avoid adding targets with no dependencies to\n # the `alias_deps` dict.\n return\n if target is None:\n target = self.scope.current_target()\n self.cur_mod_node.alias_deps[target].update(aliases_used)\n\n def is_mangled_global(self, name: str) -> bool:\n # A global is mangled if there exists at least one renamed variant.",
|
||||
"after_code": " self.cur_mod_node.plugin_deps.setdefault(trigger, set()).add(target)\n\n def add_type_alias_deps(\n self, aliases_used: Collection[tuple[str, str]], target: str | None = None\n ) -> None:\n \"\"\"Add full names of type aliases on which the current node depends.\n\n This is used by fine-grained incremental mode to re-check the corresponding nodes.\n If `target` is None, then the target node used will be the current scope. For\n coarse-grained mode, add just the module names where aliases are defined.\n \"\"\"\n if not aliases_used:\n return\n if target is None:\n target = self.scope.current_target()\n for mod, fn in aliases_used:\n self.cur_mod_node.alias_deps[target].add(fn)\n self.cur_mod_node.mod_alias_deps.add(mod)\n\n def is_mangled_global(self, name: str) -> bool:\n # A global is mangled if there exists at least one renamed variant.",
|
||||
"diff_context": " self.cur_mod_node.plugin_deps.setdefault(trigger, set()).add(target)\n\n def add_type_alias_deps(\n self, aliases_used: Collection[str], target: str | None = None\n self, aliases_used: Collection[tuple[str, str]], target: str | None = None\n ) -> None:\n \"\"\"Add full names of type aliases on which the current node depends.\n\n This is used by fine-grained incremental mode to re-check the corresponding nodes.\n If `target` is None, then the target node used will be the current scope.\n If `target` is None, then the target node used will be the current scope. For\n coarse-grained mode, add just the module names where aliases are defined.\n \"\"\"\n if not aliases_used:\n # A basic optimization to avoid adding targets with no dependencies to\n # the `alias_deps` dict.\n return\n if target is None:\n target = self.scope.current_target()\n self.cur_mod_node.alias_deps[target].update(aliases_used)\n for mod, fn in aliases_used:\n self.cur_mod_node.alias_deps[target].add(fn)\n self.cur_mod_node.mod_alias_deps.add(mod)\n\n def is_mangled_global(self, name: str) -> bool:\n # A global is mangled if there exists at least one renamed variant.",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 15,
|
||||
"function_name": "is_mangled_global",
|
||||
"class_name": null,
|
||||
"docstring": "\"\"\"Add full names of type aliases on which the current node depends.",
|
||||
"coding_patterns": [
|
||||
"list_comprehension"
|
||||
]
|
||||
}
|
||||
],
|
||||
"commit_message_style": "concise_subject",
|
||||
"python_version": null,
|
||||
"pep_status": null
|
||||
},
|
||||
{
|
||||
"type": "pr",
|
||||
"repository": "mypy",
|
||||
"title": "chore: add cline_docs/ to .gitignore",
|
||||
"description": "Cline is a commonly used LLM tool which, under certain conditions, creates a cline_docs/ folder with task status and todo items etc\r\n\r\nThis folder is only helpful locally (unless we decide we want to add actual guidelines for Cline here, but thats outside the scope of this PR) so this PR adds it to .gitignore\r\n\r\n<!-- If this pull request fixes an issue, add \"Fixes #NNN\" with the issue number. -->\r\n\r\n<!--\r\nChecklist:\r\n- Read the [Contributing Guidelines](https://github.com/python/mypy/blob/master/CONTRIBUTING.md)\r\n- Add tests for all changed behaviour.\r\n- If you can't add a test, please explain why and how you verified your changes work.\r\n- Make sure CI passes.\r\n- Please do not force push to the PR once it has been reviewed.\r\n-->\r\n",
|
||||
"url": "https://github.com/python/mypy/pull/19797",
|
||||
"date": "2025-09-05T02:35:14Z",
|
||||
"sha_or_number": "19797",
|
||||
"files_changed": [
|
||||
".gitignore"
|
||||
],
|
||||
"additions": 0,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
"type": "pr",
|
||||
"repository": "mypy",
|
||||
"title": "[mypyc] Add type annotations to tests",
|
||||
"description": "Missing type annotations can compromise test coverage. My eventual goal is to require annotations by default in all run tests.\r\n",
|
||||
"url": "https://github.com/python/mypy/pull/19794",
|
||||
"date": "2025-09-04T15:56:30Z",
|
||||
"sha_or_number": "19794",
|
||||
"files_changed": [
|
||||
"mypyc/test-data/fixtures/ir.py",
|
||||
"mypyc/test-data/fixtures/typing-full.pyi",
|
||||
"mypyc/test-data/run-dunders.test",
|
||||
"mypyc/test-data/run-singledispatch.test"
|
||||
],
|
||||
"additions": 0,
|
||||
"deletions": 0,
|
||||
"labels": [],
|
||||
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|
||||
"code_samples": [
|
||||
{
|
||||
"file_path": "mypyc/test-data/fixtures/ir.py",
|
||||
"language": "python",
|
||||
"before_code": " def __iadd__(self, value: Iterable[_T], /) -> List[_T]: ... # type: ignore[misc]\n def append(self, x: _T) -> None: pass\n def pop(self, i: int = -1) -> _T: pass\n def count(self, _T) -> int: pass\n def extend(self, l: Iterable[_T]) -> None: pass\n def insert(self, i: int, x: _T) -> None: pass\n def sort(self) -> None: pass",
|
||||
"after_code": " def __iadd__(self, value: Iterable[_T], /) -> List[_T]: ... # type: ignore[misc]\n def append(self, x: _T) -> None: pass\n def pop(self, i: int = -1) -> _T: pass\n def count(self, x: _T) -> int: pass\n def extend(self, l: Iterable[_T]) -> None: pass\n def insert(self, i: int, x: _T) -> None: pass\n def sort(self) -> None: pass",
|
||||
"diff_context": " def __iadd__(self, value: Iterable[_T], /) -> List[_T]: ... # type: ignore[misc]\n def append(self, x: _T) -> None: pass\n def pop(self, i: int = -1) -> _T: pass\n def count(self, _T) -> int: pass\n def count(self, x: _T) -> int: pass\n def extend(self, l: Iterable[_T]) -> None: pass\n def insert(self, i: int, x: _T) -> None: pass\n def sort(self) -> None: pass",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 6,
|
||||
"function_name": "sort",
|
||||
"class_name": null,
|
||||
"docstring": null,
|
||||
"coding_patterns": [
|
||||
"function_definition",
|
||||
"type_hint"
|
||||
]
|
||||
},
|
||||
{
|
||||
"file_path": "mypyc/test-data/fixtures/ir.py",
|
||||
"language": "python",
|
||||
"before_code": "def id(o: object) -> int: pass\n# This type is obviously wrong but the test stubs don't have Sized anymore\ndef len(o: object) -> int: pass\ndef print(*object) -> None: pass\ndef isinstance(x: object, t: object) -> bool: pass\ndef iter(i: Iterable[_T]) -> Iterator[_T]: pass\n@overload",
|
||||
"after_code": "def id(o: object) -> int: pass\n# This type is obviously wrong but the test stubs don't have Sized anymore\ndef len(o: object) -> int: pass\ndef print(*args: object) -> None: pass\ndef isinstance(x: object, t: object) -> bool: pass\ndef iter(i: Iterable[_T]) -> Iterator[_T]: pass\n@overload",
|
||||
"diff_context": "def id(o: object) -> int: pass\n# This type is obviously wrong but the test stubs don't have Sized anymore\ndef len(o: object) -> int: pass\ndef print(*object) -> None: pass\ndef print(*args: object) -> None: pass\ndef isinstance(x: object, t: object) -> bool: pass\ndef iter(i: Iterable[_T]) -> Iterator[_T]: pass\n@overload",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 6,
|
||||
"function_name": "iter",
|
||||
"class_name": null,
|
||||
"docstring": null,
|
||||
"coding_patterns": [
|
||||
"function_definition",
|
||||
"type_hint"
|
||||
]
|
||||
},
|
||||
{
|
||||
"file_path": "mypyc/test-data/fixtures/typing-full.pyi",
|
||||
"language": "python",
|
||||
"before_code": "class GenericMeta(type): pass\n\nclass _SpecialForm:\n def __getitem__(self, index): ...\nclass TypeVar:\n def __init__(self, name, *args, bound=None): ...\n def __or__(self, other): ...\n\ncast = 0\noverload = 0",
|
||||
"after_code": "class GenericMeta(type): pass\n\nclass _SpecialForm:\n def __getitem__(self, index: Any) -> Any: ...\nclass TypeVar:\n def __init__(self, name: str, *args: Any, bound: Any = None): ...\n def __or__(self, other: Any) -> Any: ...\n\ncast = 0\noverload = 0",
|
||||
"diff_context": "class GenericMeta(type): pass\n\nclass _SpecialForm:\n def __getitem__(self, index): ...\n def __getitem__(self, index: Any) -> Any: ...\nclass TypeVar:\n def __init__(self, name, *args, bound=None): ...\n def __or__(self, other): ...\n def __init__(self, name: str, *args: Any, bound: Any = None): ...\n def __or__(self, other: Any) -> Any: ...\n\ncast = 0\noverload = 0",
|
||||
"change_type": "modification",
|
||||
"lines_of_context": 7,
|
||||
"function_name": "__or__",
|
||||
"class_name": "TypeVar",
|
||||
"docstring": null,
|
||||
"coding_patterns": [
|
||||
"function_definition",
|
||||
"type_hint"
|
||||
]
|
||||
}
|
||||
],
|
||||
"commit_message_style": "concise_subject",
|
||||
"python_version": null,
|
||||
"pep_status": null
|
||||
},
|
||||
{
|
||||
"type": "pr",
|
||||
"repository": "mypy",
|
||||
"title": "Check functions without annotations in mypyc tests",
|
||||
"description": "c.f. https://github.com/python/mypy/pull/19217#discussion_r2314303410\r\n\r\nDisallowing functions without annotations (where not relevant to the tests) is probably a good idea, but this creates a large number of failures which would take some time to go through (many due to common issues, like untyped functions in the fixtures).\r\n\r\nAs a smaller step in the right direction, this sets `check_untyped_defs = True` for the `run-*` tests so that we at least check functions without annotations. ",
|
||||
"url": "https://github.com/python/mypy/pull/19792",
|
||||
"date": "2025-09-04T14:42:17Z",
|
||||
"sha_or_number": "19792",
|
||||
"files_changed": [
|
||||
"mypyc/test-data/fixtures/ir.py",
|
||||
"mypyc/test-data/run-classes.test",
|
||||
"mypyc/test/test_run.py"
|
||||
],
|
||||
"additions": 0,
|
||||
"deletions": 0,
|
||||
"labels": [],
|
||||
"related_issues": [],
|
||||
"code_samples": [
|
||||
{
|
||||
"file_path": "mypyc/test-data/fixtures/ir.py",
|
||||
"language": "python",
|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"diff_context": " Performance improvements are modest -- we expect to be improving this\n over the next few releases.\n\n* :pep:`667`: :attr:`FrameType.f_locals <frame.f_locals>` when used in\n a function now returns a write-through proxy to the frame's locals,\n rather than a ``dict``. See the PEP for corresponding C API changes\n and deprecations.\n\nNew typing features:\n\n* :pep:`696`: Type parameters (:data:`typing.TypeVar`, :data:`typing.ParamSpec`,",
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|
||||
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|
||||
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|
||||
"title": "gh-118335: Rename --experimental-interpreter on Windows to --experimental-jit-interpreter (#118497)",
|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"title": "Support TypeGuard (PEP 647) (#9865)",
|
||||
"description": "Support TypeGuard (PEP 647) (#9865)\n\nPEP 647 is still in draft mode, but it is likely to be accepted, and this helps solve some real issues.",
|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
"diff_context": " if literal(expr) == LITERAL_TYPE:\n vartype = type_map[expr]\n return self.conditional_callable_type_map(expr, vartype)\n elif isinstance(node.callee, RefExpr):\n if node.callee.type_guard is not None:\n # TODO: Follow keyword args or *args, **kwargs\n if node.arg_kinds[0] != nodes.ARG_POS:\n self.fail(\"Type guard requires positional argument\", node)\n return {}, {}\n if literal(expr) == LITERAL_TYPE:\n return {expr: TypeGuardType(node.callee.type_guard)}, {}\n elif isinstance(node, ComparisonExpr):\n # Step 1: Obtain the types of each operand and whether or not we can\n # narrow their types. (For example, we shouldn't try narrowing the",
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||||
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||||
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||||
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||||
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|
||||
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|
||||
"after_code": " ret_type=self.object_type(),\n fallback=self.named_type('builtins.function'))\n callee_type = get_proper_type(self.accept(e.callee, type_context, always_allow_any=True))\n if (isinstance(e.callee, RefExpr)\n and isinstance(callee_type, CallableType)\n and callee_type.type_guard is not None):\n # Cache it for find_isinstance_check()\n e.callee.type_guard = callee_type.type_guard\n if (self.chk.options.disallow_untyped_calls and\n self.chk.in_checked_function() and\n isinstance(callee_type, CallableType)",
|
||||
"diff_context": " ret_type=self.object_type(),\n fallback=self.named_type('builtins.function'))\n callee_type = get_proper_type(self.accept(e.callee, type_context, always_allow_any=True))\n if (isinstance(e.callee, RefExpr)\n and isinstance(callee_type, CallableType)\n and callee_type.type_guard is not None):\n # Cache it for find_isinstance_check()\n e.callee.type_guard = callee_type.type_guard\n if (self.chk.options.disallow_untyped_calls and\n self.chk.in_checked_function() and\n isinstance(callee_type, CallableType)",
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
"diff_context": " \"\"\"\n if literal(expr) >= LITERAL_TYPE:\n restriction = self.chk.binder.get(expr)\n # Ignore the error about using get_proper_type().\n if isinstance(restriction, TypeGuardType): # type: ignore[misc]\n # A type guard forces the new type even if it doesn't overlap the old.\n return restriction.type_guard\n # If the current node is deferred, some variables may get Any types that they\n # otherwise wouldn't have. We don't want to narrow down these since it may\n # produce invalid inferred Optional[Any] types, at least.",
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
"after_code": " for t, a in zip(template.arg_types, cactual.arg_types):\n # Negate direction due to function argument type contravariance.\n res.extend(infer_constraints(t, a, neg_op(self.direction)))\n template_ret_type, cactual_ret_type = template.ret_type, cactual.ret_type\n if template.type_guard is not None:\n template_ret_type = template.type_guard\n if cactual.type_guard is not None:\n cactual_ret_type = cactual.type_guard\n res.extend(infer_constraints(template_ret_type, cactual_ret_type,\n self.direction))\n return res\n elif isinstance(self.actual, AnyType):",
|
||||
"diff_context": " for t, a in zip(template.arg_types, cactual.arg_types):\n # Negate direction due to function argument type contravariance.\n res.extend(infer_constraints(t, a, neg_op(self.direction)))\n res.extend(infer_constraints(template.ret_type, cactual.ret_type,\n template_ret_type, cactual_ret_type = template.ret_type, cactual.ret_type\n if template.type_guard is not None:\n template_ret_type = template.type_guard\n if cactual.type_guard is not None:\n cactual_ret_type = cactual.type_guard\n res.extend(infer_constraints(template_ret_type, cactual_ret_type,\n self.direction))\n return res\n elif isinstance(self.actual, AnyType):",
|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
"file_path": "mypy/expandtype.py",
|
||||
"language": "python",
|
||||
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|
||||
"after_code": "\n def visit_callable_type(self, t: CallableType) -> Type:\n return t.copy_modified(arg_types=self.expand_types(t.arg_types),\n ret_type=t.ret_type.accept(self),\n type_guard=(t.type_guard.accept(self)\n if t.type_guard is not None else None))\n\n def visit_overloaded(self, t: Overloaded) -> Type:\n items = [] # type: List[CallableType]",
|
||||
"diff_context": "\n def visit_callable_type(self, t: CallableType) -> Type:\n return t.copy_modified(arg_types=self.expand_types(t.arg_types),\n ret_type=t.ret_type.accept(self))\n ret_type=t.ret_type.accept(self),\n type_guard=(t.type_guard.accept(self)\n if t.type_guard is not None else None))\n\n def visit_overloaded(self, t: Overloaded) -> Type:\n items = [] # type: List[CallableType]",
|
||||
"change_type": "modification",
|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
{
|
||||
"file_path": "mypy/fixup.py",
|
||||
"language": "python",
|
||||
"before_code": " for arg in ct.bound_args:\n if arg:\n arg.accept(self)\n\n def visit_overloaded(self, t: Overloaded) -> None:\n for ct in t.items():",
|
||||
"after_code": " for arg in ct.bound_args:\n if arg:\n arg.accept(self)\n if ct.type_guard is not None:\n ct.type_guard.accept(self)\n\n def visit_overloaded(self, t: Overloaded) -> None:\n for ct in t.items():",
|
||||
"diff_context": " for arg in ct.bound_args:\n if arg:\n arg.accept(self)\n if ct.type_guard is not None:\n ct.type_guard.accept(self)\n\n def visit_overloaded(self, t: Overloaded) -> None:\n for ct in t.items():",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
"python_version": null,
|
||||
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|
||||
},
|
||||
{
|
||||
"type": "commit",
|
||||
"repository": "mypy",
|
||||
"title": "Add a separate issue form to report crashes (#9549)",
|
||||
"description": "Add a separate issue form to report crashes (#9549)",
|
||||
"url": "https://github.com/python/mypy/commit/cca6e2fdc874b7538bd1d2ef70daab687b2a0363",
|
||||
"date": "2020-10-08T22:30:06Z",
|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"diff_context": "---\nname: Crash Report\nabout: Crash (traceback or \"INTERNAL ERROR\")\nlabels: \"crash\"\n---\n\n<!--\n Use this form only if mypy reports an \"INTERNAL ERROR\" and/or gives a traceback.\n Please include the traceback and all other messages below (use `mypy --show-traceback`).\n-->\n\n**Crash Report**\n\n(Tell us what happened.)\n\n**Traceback**\n\n```\n(Insert traceback and other messages from mypy here -- use `--show-traceback`.)\n```\n\n**To Reproduce**\n\n(Write what you did to reproduce the crash. Full source code is\nappreciated. We also very much appreciate it if you try to narrow the\nsource down to a small stand-alone example.)\n\n**Your Environment**\n\n<!-- Include as many relevant details about the environment you experienced the bug in -->\n\n- Mypy version used:\n- Mypy command-line flags:\n- Mypy configuration options from `mypy.ini` (and other config files):\n- Python version used:\n- Operating system and version:\n\n<!--\nYou can freely edit this text, please remove all the lines\nyou believe are unnecessary.\n-->",
|
||||
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|
||||
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|
||||
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|
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
{
|
||||
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|
||||
"repository": "mypy",
|
||||
"title": "Make the new bug templates less markup-heavy (#9438)",
|
||||
"description": "Make the new bug templates less markup-heavy (#9438)\n\n- Remove emoji\r\n- Instead of `## H2 headings` just use `**bold**`\r\n- Add link to docs\r\n- Add suggestion for new users not to file a bug",
|
||||
"url": "https://github.com/python/mypy/commit/6f07cb6a2e02446b909846f99817f674675e826e",
|
||||
"date": "2020-09-11T18:35:59Z",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"additions": 24,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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||||
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|
||||
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|
||||
{
|
||||
"type": "commit",
|
||||
"repository": "mypy",
|
||||
"title": "Add MYPY_CONFIG_FILE_DIR to environment when config file is read (2nd try) (#9414)",
|
||||
"description": "Add MYPY_CONFIG_FILE_DIR to environment when config file is read (2nd try) (#9414)\n\n(This fixes the mistake I introduced in the previous version.)\r\n\r\nResubmit of #9403.\r\n\r\nFixes #7968.\r\n\r\nCo-authored-by: aghast <aghast@aghast.dev>",
|
||||
"url": "https://github.com/python/mypy/commit/9d038469d80e36057c77e0a8a18831f829778f9d",
|
||||
"date": "2020-09-04T20:55:14Z",
|
||||
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|
||||
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|
||||
"mypy/config_parser.py",
|
||||
"mypy/test/testcmdline.py",
|
||||
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|
||||
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|
||||
"additions": 15,
|
||||
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|
||||
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|
||||
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|
||||
"9403",
|
||||
"7968",
|
||||
"9414"
|
||||
],
|
||||
"code_samples": [],
|
||||
"commit_message_style": "imperative_mood; references_issue; has_body",
|
||||
"python_version": null,
|
||||
"pep_status": null
|
||||
},
|
||||
{
|
||||
"type": "commit",
|
||||
"repository": "mypy",
|
||||
"title": "Revert \"Add MYPY_CONFIG_FILE_DIR to environment when config file is read (#9403)\"",
|
||||
"description": "Revert \"Add MYPY_CONFIG_FILE_DIR to environment when config file is read (#9403)\"\n\nReason: This broke CI.\n\nThis reverts commit 652aca96609c876c47ca7eaa68d67ac1e36f4215.",
|
||||
"url": "https://github.com/python/mypy/commit/57d3473ae906fe945953b874d3dcb66efb2710ca",
|
||||
"date": "2020-09-04T02:45:27Z",
|
||||
"sha_or_number": "57d3473ae906fe945953b874d3dcb66efb2710ca",
|
||||
"files_changed": [
|
||||
"mypy/config_parser.py",
|
||||
"mypy/test/testcmdline.py",
|
||||
"test-data/unit/envvars.test"
|
||||
],
|
||||
"additions": 0,
|
||||
"deletions": 15,
|
||||
"labels": [],
|
||||
"related_issues": [
|
||||
"9403"
|
||||
],
|
||||
"code_samples": [],
|
||||
"commit_message_style": "references_issue; has_body",
|
||||
"python_version": null,
|
||||
"pep_status": null
|
||||
},
|
||||
{
|
||||
"type": "commit",
|
||||
"repository": "mypy",
|
||||
"title": "Revert issue template (#9345) -- it doesn't work",
|
||||
"description": "Revert issue template (#9345) -- it doesn't work\n\nThis reverts commit 18c84e0f6906cfb315c367aa35550a4727cb57f8.",
|
||||
"url": "https://github.com/python/mypy/commit/42a522089c6b418727e143c181128e902acf0908",
|
||||
"date": "2020-08-27T22:21:28Z",
|
||||
"sha_or_number": "42a522089c6b418727e143c181128e902acf0908",
|
||||
"files_changed": [
|
||||
".github/ISSUE_TEMPLATE/bug.md",
|
||||
".github/ISSUE_TEMPLATE/documentation.md",
|
||||
".github/ISSUE_TEMPLATE/feature.md",
|
||||
".github/ISSUE_TEMPLATE/question.md",
|
||||
".github/PULL_REQUEST_TEMPLATE.md",
|
||||
"ISSUE_TEMPLATE.md"
|
||||
],
|
||||
"additions": 20,
|
||||
"deletions": 110,
|
||||
"labels": [],
|
||||
"related_issues": [
|
||||
"9345"
|
||||
],
|
||||
"code_samples": [
|
||||
{
|
||||
"file_path": ".github/ISSUE_TEMPLATE/bug.md",
|
||||
"language": "markdown",
|
||||
"before_code": "---\nname: 🐛 Bug Report\nlabels: \"bug\"\n---\n\n<!--\nNote: If the problem you are reporting is about a specific library function, then the typeshed tracker is better suited\nfor this report: https://github.com/python/typeshed/issues\n-->\n\n## 🐛 Bug Report\n\n(A clear and concise description of what the bug is.)\n\n## To Reproduce\n\n(Write your steps here:)\n\n1. Step 1...\n1. Step 2...\n1. Step 3...\n\n## Expected Behavior\n\n<!--\n How did you expect your project to behave?\n It’s fine if you’re not sure your understanding is correct.\n Write down what you thought would happen. If you just expected no errors, you can delete this section.\n-->\n\n(Write what you thought would happen.)\n\n## Actual Behavior\n\n<!--\n Did something go wrong?\n Is something broken, or not behaving as you expected?\n-->\n\n(Write what happened.)\n\n## Your Environment\n\n<!-- Include as many relevant details about the environment you experienced the bug in -->\n\n- Mypy version used:\n- Mypy command-line flags:\n- Mypy configuration options from `mypy.ini` (and other config files):\n- Python version used:\n- Operating system and version:\n\n<!--\nYou can freely edit this text, please remove all the lines\nyou believe are unnecessary.\n-->",
|
||||
"after_code": "",
|
||||
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||||
"change_type": "deletion",
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||||
"language": "markdown",
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|
||||
"after_code": "",
|
||||
"diff_context": "---\nname: 🚀 Feature\nlabels: \"feature\"\n---\n\n## 🚀 Feature\n\n(A clear and concise description of your feature proposal.)\n\n## Pitch\n\n(Please explain why this feature should be implemented and how it would be used. Add examples, if applicable.)",
|
||||
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|
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|
||||
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|
||||
"diff_context": "### Have you read the [Contributing Guidelines](https://github.com/python/mypy/blob/master/CONTRIBUTING.md)?\n\n(Once you have, delete this section. If you leave it in, your PR may be closed without action.)\n\n### Description\n\n<!--\nIf this pull request closes or fixes an issue, write Closes #NNN\" or \"Fixes #NNN\" in that exact\nformat.\n-->\n\n(Explain how this PR changes mypy.)\n\n## Test Plan\n\n<!--\nIf this is a documentation change, rebuild the docs (link to instructions) and review the changed pages for markup errors.\nIf this is a code change, include new tests (link to the testing docs). Be sure to run the tests locally and fix any errors before submitting the PR (more instructions).\nIf this change cannot be tested by the CI, please explain how to verify it manually.\n-->\n\n(Write your test plan here. If you changed any code, please provide us with clear instructions on how you verified your changes work.)",
|
||||
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]
|
||||
79
notebooks/data/my_developer_rules.md
vendored
Normal file
79
notebooks/data/my_developer_rules.md
vendored
Normal file
|
|
@ -0,0 +1,79 @@
|
|||
Assistant Guidelines
|
||||
These rules are absolutely imperative to adhere to. Comply with them precisely as they are outlined.
|
||||
|
||||
The agent must use sequential thinking MCP tool to work out problems.
|
||||
|
||||
Core Behavior Guidelines
|
||||
|
||||
Respond only to explicit requests. Do not add files, code, tests, or comments unless asked.
|
||||
|
||||
Follow instructions precisely. No assumptions or speculative additions.
|
||||
|
||||
Use provided context accurately.
|
||||
|
||||
Avoid extra output. No debugging logs or test harnesses unless requested.
|
||||
|
||||
Produce clean, optimized code when code is requested. Respect existing style.
|
||||
|
||||
Deliver complete, standalone solutions. No placeholders.
|
||||
|
||||
Limit file creation. Only create new files when necessary.
|
||||
|
||||
If you modify the model in a user's code, you must confirm with the user and never be sneaky. Always tell the user exactly what you are doing.
|
||||
|
||||
Communication & Delivery
|
||||
|
||||
9. Don't explain unless asked. Do not expose reasoning in outputs.
|
||||
10. If unsure, say "I don't know." Avoid hallucinated content.
|
||||
11. Maintain consistency across sessions. Refer to project memory and documentation.
|
||||
12. Respect privacy and permissions. Never leak or infer secure data.
|
||||
13. Prioritize targeted edits over full rewrites.
|
||||
14. Optimize incrementally. Avoid unnecessary overhauls.
|
||||
|
||||
Spec.md Requirement
|
||||
|
||||
You must maintain a file named Spec.md. This file acts as the single source of truth for the project.
|
||||
|
||||
Rules:
|
||||
|
||||
Before starting any implementation, check if Spec.md already exists.
|
||||
|
||||
If it does not exist, create one using the template provided below.
|
||||
|
||||
Always update Spec.md before and after any major change.
|
||||
|
||||
Use the contents of Spec.md to guide logic, structure, and implementation decisions.
|
||||
|
||||
When updating a section, condense previous content to keep the document concise.
|
||||
|
||||
Spec.md Starter Template (Plain Text Format)
|
||||
|
||||
Title: Spec.md – Project Specification
|
||||
|
||||
Section: Purpose
|
||||
Describe the main goal of this feature, tool, or system.
|
||||
|
||||
Section: Core Functionality
|
||||
List the key features, expected behaviors, and common use cases.
|
||||
|
||||
Section: Architecture Overview
|
||||
Summarize the technical setup, frameworks used, and main modules or services.
|
||||
|
||||
Section: Input and Output Contracts
|
||||
List all inputs and outputs in a table-like format:
|
||||
|
||||
Input: describe the input data, its format, and where it comes from.
|
||||
|
||||
Output: describe the output data, its format, and its destination.
|
||||
|
||||
Section: Edge Cases and Constraints
|
||||
List known limitations, special scenarios, and fallback behaviors.
|
||||
|
||||
Section: File and Module Map
|
||||
List all important files or modules and describe what each one is responsible for.
|
||||
|
||||
Section: Open Questions or TODOs
|
||||
Create a checklist of unresolved decisions, logic that needs clarification, or tasks that are still pending.
|
||||
|
||||
Section: Last Updated
|
||||
Include the most recent update date and who made the update.
|
||||
74
notebooks/data/pep_style_guide.md
vendored
Normal file
74
notebooks/data/pep_style_guide.md
vendored
Normal file
|
|
@ -0,0 +1,74 @@
|
|||
# PEP 8 Style Guide: Essentials
|
||||
|
||||
## Code Layout
|
||||
- Indentation: 4 spaces per level
|
||||
- Line length: 79 for code (88/100 acceptable by team), 72 for comments/docstrings
|
||||
- Blank lines: 2 around top-level defs/classes, 1 between methods
|
||||
|
||||
```python
|
||||
# Hanging indent for long calls
|
||||
foo = long_function_name(
|
||||
var_one, var_two,
|
||||
var_three, var_four,
|
||||
)
|
||||
```
|
||||
|
||||
## Imports
|
||||
- One import per line
|
||||
- Group: stdlib, third-party, local
|
||||
- Prefer absolute imports; avoid wildcard imports
|
||||
|
||||
```python
|
||||
import os
|
||||
import sys
|
||||
from subprocess import Popen, PIPE
|
||||
|
||||
import requests
|
||||
|
||||
from myproject.models import User
|
||||
```
|
||||
|
||||
## Whitespace
|
||||
- No space inside brackets or before commas/semicolons
|
||||
- Spaces around binary operators
|
||||
|
||||
```python
|
||||
x = 1
|
||||
hypot2 = x * x + y * y
|
||||
```
|
||||
|
||||
## Naming
|
||||
- snake_case: functions, variables
|
||||
- PascalCase: classes
|
||||
- SCREAMING_SNAKE_CASE: constants
|
||||
|
||||
## Comments & Docstrings
|
||||
- Use complete sentences; keep up to date
|
||||
- Triple-double quotes for public modules, classes, functions
|
||||
```python
|
||||
def f(x: int) -> int:
|
||||
"""Return x doubled."""
|
||||
return x * 2
|
||||
```
|
||||
|
||||
## Type Hints
|
||||
- Space after colon; arrow for returns
|
||||
```python
|
||||
def munge(s: str) -> str: ...
|
||||
```
|
||||
|
||||
## Tooling
|
||||
- Black, isort, Flake8 (or Ruff) to automate style
|
||||
- Example pyproject.toml excerpt:
|
||||
```toml
|
||||
[tool.black]
|
||||
line-length = 88
|
||||
|
||||
[tool.isort]
|
||||
profile = "black"
|
||||
```
|
||||
|
||||
## Common Violations
|
||||
- E501: line too long -> break with parentheses
|
||||
- E225: missing whitespace around operator
|
||||
- E402: module import not at top of file
|
||||
74
notebooks/data/zen_principles.md
vendored
Normal file
74
notebooks/data/zen_principles.md
vendored
Normal file
|
|
@ -0,0 +1,74 @@
|
|||
# The Zen of Python: Practical Guide
|
||||
|
||||
## Overview
|
||||
The Zen of Python (Tim Peters, import this) captures Python's philosophy. Use these principles as a checklist during design, coding, and reviews.
|
||||
|
||||
## Key Principles With Guidance
|
||||
|
||||
### 1. Beautiful is better than ugly
|
||||
Prefer descriptive names, clear structure, and consistent formatting.
|
||||
|
||||
### 2. Explicit is better than implicit
|
||||
Be clear about behavior, imports, and types.
|
||||
```python
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
def get_future_date(days_ahead: int) -> datetime:
|
||||
return datetime.now() + timedelta(days=days_ahead)
|
||||
```
|
||||
|
||||
### 3. Simple is better than complex
|
||||
Choose straightforward solutions first.
|
||||
|
||||
### 4. Complex is better than complicated
|
||||
When complexity is needed, organize it with clear abstractions.
|
||||
|
||||
### 5. Flat is better than nested
|
||||
Use early returns to reduce indentation.
|
||||
|
||||
### 6. Sparse is better than dense
|
||||
Give code room to breathe with whitespace.
|
||||
|
||||
### 7. Readability counts
|
||||
Optimize for human readers; add docstrings for nontrivial code.
|
||||
|
||||
### 8. Special cases aren't special enough to break the rules
|
||||
Stay consistent; exceptions should be rare and justified.
|
||||
|
||||
### 9. Although practicality beats purity
|
||||
Prefer practical solutions that teams can maintain.
|
||||
|
||||
### 10. Errors should never pass silently
|
||||
Handle exceptions explicitly; log with context.
|
||||
|
||||
### 11. Unless explicitly silenced
|
||||
Silence only specific, acceptable errors and document why.
|
||||
|
||||
### 12. In the face of ambiguity, refuse the temptation to guess
|
||||
Require explicit inputs and behavior.
|
||||
|
||||
### 13. There should be one obvious way to do it
|
||||
Prefer standard library patterns and idioms.
|
||||
|
||||
### 14. Although that way may not be obvious at first
|
||||
Learn Python idioms; embrace clarity over novelty.
|
||||
|
||||
### 15. Now is better than never; 16. Never is often better than right now
|
||||
Iterate, but don't rush broken code.
|
||||
|
||||
### 17/18. Hard to explain is bad; easy to explain is good
|
||||
Prefer designs you can explain simply.
|
||||
|
||||
### 19. Namespaces are one honking great idea
|
||||
Use modules/packages to separate concerns; avoid wildcard imports.
|
||||
|
||||
## Modern Python Tie-ins
|
||||
- Type hints reinforce explicitness
|
||||
- Context managers enforce safe resource handling
|
||||
- Dataclasses improve readability for data containers
|
||||
|
||||
## Quick Review Checklist
|
||||
- Is it readable and explicit?
|
||||
- Is this the simplest working solution?
|
||||
- Are errors explicit and logged?
|
||||
- Are modules/namespaces used appropriately?
|
||||
584
notebooks/tutorial.ipynb
vendored
Normal file
584
notebooks/tutorial.ipynb
vendored
Normal file
|
|
@ -0,0 +1,584 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6f22c8fe6d92cfcc",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Using Cognee with Python Development Data\n",
|
||||
"\n",
|
||||
"Unite authoritative Python practice (Guido van Rossum's own contributions!), normative guidance (Zen/PEP 8), and your lived context (rules + conversations) into one *AI memory* that produces answers that are relevant, explainable, and consistent."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "fe69acbf9ab1a22b",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## What You'll Learn\n",
|
||||
"\n",
|
||||
"In this comprehensive tutorial, you'll discover how to transform scattered development data into an intelligent knowledge system that enhances your coding workflow. By the end, you'll have:\n",
|
||||
"\n",
|
||||
"- **Connected disparate data sources** (Guido's CPython contributions, mypy development, PEP discussions, your Python projects) into a unified AI memory graph\n",
|
||||
"- **Built an memory layer** that understands Python design philosophy, best practice coding patterns, and your preferences and experience\n",
|
||||
"- **Learn how to use intelligent search capabilities** that combine the diverse context\n",
|
||||
"\n",
|
||||
"This tutorial demonstrates the power of **knowledge graphs** and **retrieval-augmented generation (RAG)** for software development, showing you how to build systems that learn from Python's creator and improve your own Python development."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b03b59c064213dd4",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Cognee and its core operations\n",
|
||||
"\n",
|
||||
"Before we dive in, let's understand the core Cognee operations we'll be working with:\n",
|
||||
"\n",
|
||||
"- **`cognee.add()`** - Ingests raw data (files, text, APIs) into the system\n",
|
||||
"- **`cognee.cognify()`** - Processes and structures data into a knowledge graph using AI\n",
|
||||
"- **`cognee.search()`** - Queries the knowledge graph with natural language or Cypher\n",
|
||||
"- **`cognee.memify()`** - Cognee's \"secret sauce\" that infers implicit connections and rules from your data"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6a7669fbb6a3e6c7",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Data used in this tutorial\n",
|
||||
"\n",
|
||||
"Cognee can ingest many types of sources. In this tutorial, we use a small, concrete set of files that cover different perspectives:\n",
|
||||
"\n",
|
||||
"- **`guido_contributions.json` — Authoritative exemplars.** Real PRs and commits from Guido van Rossum (mypy, CPython). These show how Python’s creator solved problems and provide concrete anchors for patterns.\n",
|
||||
"- **`pep_style_guide.md` — Norms.** Encodes community style and typing conventions (PEP 8 and related). Ensures that search results and inferred rules align with widely accepted standards.\n",
|
||||
"- **`zen_principles.md` — Philosophy.** The Zen of Python. Grounds design trade‑offs (simplicity, explicitness, readability) beyond syntax or mechanics.\n",
|
||||
"- **`my_developer_rules.md` — Local constraints.** Your house rules, conventions, and project‑specific requirements (scope, privacy, Spec.md). Keeps recommendations relevant to your actual workflow.\n",
|
||||
"- **`copilot_conversations.json` — Personal history.** Transcripts of real assistant conversations, including your questions, code snippets, and discussion topics. Captures “how you code” and connects it to “how Guido codes.”"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2a5dac2c6fdc7ca7",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Preliminaries\n",
|
||||
"\n",
|
||||
"Cognee relies heavily on async functions.\n",
|
||||
"We need `nest_asyncio` so `await` works in this notebook."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "20cb02b49e3c53e2",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:35:00.836706Z",
|
||||
"start_time": "2025-09-07T14:35:00.832646Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import nest_asyncio\n",
|
||||
"nest_asyncio.apply()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "30e66c894fb4cfd5",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"To strike the balanace between speed, cost, anc quality, we recommend using OpenAI's `4o-mini` model; make sure your `.env` file contains this line:\n",
|
||||
"\n",
|
||||
"```LLM_MODEL=\"gpt-4o-mini\"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "45e1caaec20c9518",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"We will do a quick import check."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "9386ecb596860399",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:35:03.910260Z",
|
||||
"start_time": "2025-09-07T14:35:00.938966Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import cognee\n",
|
||||
"import os\n",
|
||||
"from pathlib import Path\n",
|
||||
"\n",
|
||||
"print('🔍 Quick Cognee Import Check')\n",
|
||||
"print('=' * 30)\n",
|
||||
"print(f'📍 Cognee location: {cognee.__file__}')\n",
|
||||
"print(f'📁 Package directory: {os.path.dirname(cognee.__file__)}')\n",
|
||||
"\n",
|
||||
"# Check if it's local or installed\n",
|
||||
"current_dir = Path.cwd()\n",
|
||||
"cognee_path = Path(cognee.__file__)\n",
|
||||
"if current_dir in cognee_path.parents:\n",
|
||||
" print('🏠 Status: LOCAL DEVELOPMENT VERSION')\n",
|
||||
"else:\n",
|
||||
" print('📦 Status: INSTALLED PACKAGE')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "76895c6570d1a4dc",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"And just to be safe, we will make sure that the path contains the root directory, so Python can find everything it needs to run the notebook."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "19e74e6b691020db",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:35:03.921217Z",
|
||||
"start_time": "2025-09-07T14:35:03.918659Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import sys\n",
|
||||
"from pathlib import Path\n",
|
||||
"notebook_dir = Path.cwd()\n",
|
||||
"if notebook_dir.name == 'notebooks':\n",
|
||||
" project_root = notebook_dir.parent\n",
|
||||
"else:\n",
|
||||
" project_root = Path.cwd()\n",
|
||||
"\n",
|
||||
"# Add project root to the beginning of sys.path\n",
|
||||
"project_root_str = str(project_root.absolute())\n",
|
||||
"if project_root_str not in sys.path:\n",
|
||||
" sys.path.insert(0, project_root_str)\n",
|
||||
"\n",
|
||||
"print(f\"📁 Project root: {project_root_str}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "af584b935cbdc8d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Finally, we will begin with a clean slate, by removing any previous Cognee data:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "dd47383aa9519465",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:35:06.194073Z",
|
||||
"start_time": "2025-09-07T14:35:03.929446Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"await cognee.prune.prune_data()\n",
|
||||
"await cognee.prune.prune_system(metadata=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "93c9783037715026",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### First data ingestion: Exploring Guido's Python Contributions\n",
|
||||
"\n",
|
||||
"We'll begin with a document that contains detailed PRs and commits from Guido van Rossum's work on mypy and CPython, showing real-world examples of Python's creator solving type system and language design challenges.\n",
|
||||
"\n",
|
||||
"We'll use Cognee's `add()` and `cognify()` functions to ingest this data and build a knowledge graph that connects Guido's development patterns with Python best practices."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b8743ed520b4de37",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:39:53.511862Z",
|
||||
"start_time": "2025-09-07T14:35:06.228778Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import cognee\n",
|
||||
"\n",
|
||||
"result = await cognee.add(\n",
|
||||
" os.path.abspath(\"data/guido_contributions.json\"),\n",
|
||||
" node_set=[\"guido_data\"]\n",
|
||||
")\n",
|
||||
"await cognee.cognify(temporal_cognify=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f08b362cbf12b398",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:39:53.561679Z",
|
||||
"start_time": "2025-09-07T14:39:53.559528Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"results = await cognee.search(\"Show me commits\")\n",
|
||||
"print(results[0])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "10d582d02ead905e",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### What's just happened?\n",
|
||||
"The `search()` function uses natural language to query a knowledge graph containing Guido's development history.\n",
|
||||
"Unlike traditional databases, Cognee understands the relationships between commits, language features, design decisions, and evolution over time.\n",
|
||||
"\n",
|
||||
"Cognee also allows you to visualize the graphs created:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "1fb068f422bda6cf",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:39:53.688017Z",
|
||||
"start_time": "2025-09-07T14:39:53.598467Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from cognee import visualize_graph\n",
|
||||
"await visualize_graph('./guido_contributions.html')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f24341c97d6eaccb",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:39:53.733197Z",
|
||||
"start_time": "2025-09-07T14:39:53.729922Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from IPython.display import IFrame, HTML, display\n",
|
||||
"display(IFrame(\"./guido_contributions.html\", width=\"100%\", height=\"500\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "3418aa17bf35e3bb",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Why visualization matters:** Knowledge graphs reveal hidden patterns in data. In this case, patterins in Guido's contributions to Python's development. The interactive visualization shows how different projects (CPython, mypy, PEPs), features, and time periods connect - insights that show Python's thoughtful evolution.\n",
|
||||
"\n",
|
||||
"Take a moment to explore the graph. Notice how:\n",
|
||||
"\n",
|
||||
"- CPython core development clusters around 2020\n",
|
||||
"- Mypy contributions focus on fixtures and run classes\n",
|
||||
"- PEP discussions mention Thomas Grainiger and Adam Turner\n",
|
||||
"- Time-based connections show how ideas evolved into features\n",
|
||||
"\n",
|
||||
"*Note: You can open the visualization on your browser using the html file from path provided above.*"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "5e8d9094a09ae05d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Ingesting more data\n",
|
||||
"\n",
|
||||
"Now we'll add the remaining data and see how they connections emerge between Guido's contributions, Python best practices, and user conversations."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "5315318324968f0f",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:40:48.589875Z",
|
||||
"start_time": "2025-09-07T14:39:53.785054Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"\n",
|
||||
"await cognee.add(os.path.abspath(\"data/copilot_conversations.json\"), node_set=[\"developer_data\"])\n",
|
||||
"await cognee.add(os.path.abspath(\"data/my_developer_rules.md\"), node_set=[\"developer_data\"])\n",
|
||||
"await cognee.add(os.path.abspath(\"data/zen_principles.md\"), node_set=[\"principles_data\"])\n",
|
||||
"await cognee.add(os.path.abspath(\"data/pep_style_guide.md\"), node_set=[\"principles_data\"])\n",
|
||||
"\n",
|
||||
"await cognee.cognify(temporal_cognify=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "98b69c45db2fca3",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:40:51.305617Z",
|
||||
"start_time": "2025-09-07T14:40:48.605622Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"results = await cognee.search(\n",
|
||||
" \"What Python type hinting challenges did I face, and how does Guido approach similar problems in mypy?\",\n",
|
||||
" query_type=cognee.SearchType.GRAPH_COMPLETION\n",
|
||||
")\n",
|
||||
"print(results)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6c49c4c252036fa1",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"You'll see that cognee has connected your Python development challenges with Guido's approaches, revealing patterns like:\n",
|
||||
"\n",
|
||||
"- \"Type hint implementation failed due to circular imports - similar to issue Guido solved in mypy PR #1234\"\n",
|
||||
"- \"Performance bottleneck in list comprehension matches pattern Guido optimized in CPython commit abc123\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "a1f4606bfed8fc45",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Memify\n",
|
||||
"\n",
|
||||
"Let's now introduce the memory functions. These algorithms run on top of your semantic layer, connecting the dots and improving the search.\n",
|
||||
"\n",
|
||||
"Memify is customizable and can use any transformation you'd like to write."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "20234960f7566b15",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:43:42.390990Z",
|
||||
"start_time": "2025-09-07T14:40:51.321301Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"await cognee.memify()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "58d3ccec16f67c24",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**What `memify()` does for Python:** This advanced function uses AI to:\n",
|
||||
"\n",
|
||||
"- **Infer rule patterns** from your code (e.g., \"When implementing iterators, always follow the protocol Guido established\")\n",
|
||||
"- **Connect design philosophy to practice** (e.g., linking \"explicit is better than implicit\" to your type hinting decisions)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "a304033f9f0f5dcf",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Now let's see how the system has connected your Python development patterns with established best practices:\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "518fa9b17a604657",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:43:44.837614Z",
|
||||
"start_time": "2025-09-07T14:43:42.465351Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Search for connections between your async patterns and Python philosophy\n",
|
||||
"results = await cognee.search(\n",
|
||||
" query_text= \"How does my AsyncWebScraper implementation align with Python's design principles?\",\n",
|
||||
" query_type=cognee.SearchType.GRAPH_COMPLETION\n",
|
||||
")\n",
|
||||
"print(\"Python Pattern Analysis:\", results)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2c77c1582ab9fc32",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Nodeset filtering\n",
|
||||
"\n",
|
||||
"You may have noticed that we added different documents to different datasets. This allows us to narrow our retrieval at search time.\n",
|
||||
"\n",
|
||||
"By constraining searches to particular node sets, you can ensure that responses draw from appropriate sources. Questions about style guidelines can be directed specifically to PEP documents and design principles, while implementation questions can focus on actual code examples and developer experiences."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "c64036c03abe41e7",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:43:49.542281Z",
|
||||
"start_time": "2025-09-07T14:43:44.852455Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from cognee.modules.engine.models.node_set import NodeSet\n",
|
||||
"results = await cognee.search(\n",
|
||||
" query_text= \"How should variables be named?\",\n",
|
||||
" query_type=cognee.SearchType.GRAPH_COMPLETION,\n",
|
||||
" node_type=NodeSet,\n",
|
||||
" node_name=['principles_data']\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"print(results)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c641b8b7e50dd2ae",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Temporal graphs\n",
|
||||
"\n",
|
||||
"The `temporal_cognify` option enabled during graph construction provides powerful capabilities for understanding how Python development has evolved over time. This temporal awareness allows queries that explore trends, identify periods of intense development activity, or understand how specific features emerged and matured.\n",
|
||||
"\n",
|
||||
"Temporal queries can reveal insights about development velocity, the relationship between different features introduced in similar timeframes, or how implementation approaches have changed as the language has evolved. This historical perspective provides valuable context for understanding current best practices and anticipating future directions.\n",
|
||||
"\n",
|
||||
"For example:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "28e7d5a75e076b8f",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:43:55.278031Z",
|
||||
"start_time": "2025-09-07T14:43:49.555704Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"result = await cognee.search(\n",
|
||||
" query_text = \"What can we learn from Guido's contributions in 2025?\",\n",
|
||||
" query_type=cognee.SearchType.TEMPORAL\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"print(result)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ec6cf074a6c272ab",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Feedback loops\n",
|
||||
"\n",
|
||||
"cognee supports continuous improvement through a feedback mechanism that captures the utility and relevance of search results based on actualy user messages. This creates a learning system that adapts to your specific needs and preferences over time.\n",
|
||||
"\n",
|
||||
"When search interactions are saved, you can store the results use SearchType.FEEDBACK to provide feedback about the last_k answer from the system. This feedback becomes part of the graph itself, helping the system provide increasingly relevant results."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "67dec85a658aad76",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:43:58.472950Z",
|
||||
"start_time": "2025-09-07T14:43:55.288993Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"answer = await cognee.search(\n",
|
||||
" query_type=cognee.SearchType.GRAPH_COMPLETION,\n",
|
||||
" query_text=\"What is the most zen thing about Python?\",\n",
|
||||
" save_interaction=True, # This enables feedback later\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"print(answer)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2f64d90e6dadaefb",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"This enables giving feedback, that itself can also be stored in the graph and will be included in future searches:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "870149ea58fd109c",
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2025-09-07T14:44:00.503091Z",
|
||||
"start_time": "2025-09-07T14:43:58.480893Z"
|
||||
}
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"feedback = await cognee.search(\n",
|
||||
" query_type=cognee.SearchType.FEEDBACK,\n",
|
||||
" query_text=\"Last result was useful, I like code that complies with best practices.\",\n",
|
||||
" last_k=1,\n",
|
||||
")"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": ".venv",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.11"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
711
poetry.lock
generated
711
poetry.lock
generated
File diff suppressed because it is too large
Load diff
366
uv.lock
generated
366
uv.lock
generated
|
|
@ -203,7 +203,7 @@ wheels = [
|
|||
|
||||
[[package]]
|
||||
name = "anthropic"
|
||||
version = "0.68.0"
|
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version = "0.68.1"
|
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source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "anyio" },
|
||||
|
|
@ -215,9 +215,9 @@ dependencies = [
|
|||
{ name = "sniffio" },
|
||||
{ name = "typing-extensions" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/64/46/da44bf087ddaf3f7dbe4808c00c7cde466fe68c4fc9fbebdfc231f4ea205/anthropic-0.68.0.tar.gz", hash = "sha256:507e9b5f627d1b249128ff15b21855e718fa4ed8dabc787d0e68860a4b32a7a8", size = 471584, upload-time = "2025-09-17T15:20:19.509Z" }
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sdist = { url = "https://files.pythonhosted.org/packages/43/b9/5e736a924dabe0473b212597ae83a124e09818fac672998bb5960a64e9b1/anthropic-0.68.1.tar.gz", hash = "sha256:5fc01019dfffbc39e87a24f4d7cfe34e83dda4fff7b5371f33639f982f0c8dba", size = 471965, upload-time = "2025-09-26T16:27:30.547Z" }
|
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/60/32/2d7553184b05bdbec61dd600014a55b9028408aee6128b25cb6f20e3002c/anthropic-0.68.0-py3-none-any.whl", hash = "sha256:ac579ea5eca22a7165b1042e6af57c4bf556e51afae3ca80e24768d4756b78c0", size = 325199, upload-time = "2025-09-17T15:20:17.452Z" },
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{ url = "https://files.pythonhosted.org/packages/c9/5c/e871e40ba11338502569a3f5cb176650f99f7b4ecf915f4d38fe2b8cff37/anthropic-0.68.1-py3-none-any.whl", hash = "sha256:40fc545c4781ebc45d8e7849240c4001f40d61d18a17e5363c0acb10afefc33b", size = 325214, upload-time = "2025-09-26T16:27:29.049Z" },
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]
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|
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[[package]]
|
||||
|
|
@ -1811,26 +1811,54 @@ wheels = [
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|
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[[package]]
|
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name = "fastuuid"
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/40/91/32ce82a14650148b6979ccd1a0089fd63d92505a90fb7156d2acc3245cbd/fastuuid-0.12.0-cp311-cp311-win_amd64.whl", hash = "sha256:07afc8e674e67ac3d35a608c68f6809da5fab470fb4ef4469094fdb32ba36c51", size = 156643, upload-time = "2025-01-27T18:05:59.266Z" },
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[[package]]
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|
@ -7184,11 +7214,11 @@ asyncio = [
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[[package]]
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|||
Loading…
Add table
Reference in a new issue