diff --git a/.env.template b/.env.template
index f3168e6e2..b91f89540 100644
--- a/.env.template
+++ b/.env.template
@@ -203,6 +203,16 @@ LITELLM_LOG="ERROR"
# DEFAULT_USER_EMAIL=""
# DEFAULT_USER_PASSWORD=""
+################################################################################
+# 📂 AWS Settings
+################################################################################
+
+#AWS_REGION=""
+#AWS_ENDPOINT_URL=""
+#AWS_ACCESS_KEY_ID=""
+#AWS_SECRET_ACCESS_KEY=""
+#AWS_SESSION_TOKEN=""
+
------------------------------- END OF POSSIBLE SETTINGS -------------------------------
diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
index 76ff5965c..0e6f74188 100644
--- a/.github/pull_request_template.md
+++ b/.github/pull_request_template.md
@@ -1,8 +1,8 @@
## Description
-
@@ -16,15 +16,6 @@ DO NOT use AI-generated descriptions. We want to understand your thought process
- [ ] Performance improvement
- [ ] Other (please specify):
-## Changes Made
-
--
--
--
-
-## Testing
-
-
## Screenshots/Videos (if applicable)
@@ -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
-
-
-## Additional Notes
-
-
## 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.
diff --git a/.github/workflows/vector_db_tests.yml b/.github/workflows/vector_db_tests.yml
index a82194db3..06b58c962 100644
--- a/.github/workflows/vector_db_tests.yml
+++ b/.github/workflows/vector_db_tests.yml
@@ -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 }}
+ EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }}
+ run: uv run python ./cognee/tests/test_lancedb.py
\ No newline at end of file
diff --git a/README.md b/README.md
index 30f829c93..25eb2d519 100644
--- a/README.md
+++ b/README.md
@@ -5,7 +5,7 @@
- cognee - Memory for AI Agents in 5 lines of code
+ cognee - Memory for AI Agents in 6 lines of code
Demo
@@ -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)
-
🌐 Available Languages
:
@@ -70,53 +68,47 @@ More on [use-cases](https://docs.cognee.ai/use-cases) and [evals](https://github
-## 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 notebook , Deepnote notebook or starter repo
+## 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](https://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 template.
-To use different LLM providers, for more info check out our documentation
+To use different LLM providers, for more info check out our documentation
-### 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! Read here
+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
+```
-
-
-
+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
-
-
-
-
CODE_OF_CONDUCT for more information.
-## 💫 Contributors
+## Citation
-
- 
-
+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},
+}
+```
diff --git a/cognee-frontend/src/ui/Layout/Header.tsx b/cognee-frontend/src/ui/Layout/Header.tsx
index 7a1d2e906..1bc57f699 100644
--- a/cognee-frontend/src/ui/Layout/Header.tsx
+++ b/cognee-frontend/src/ui/Layout/Header.tsx
@@ -2,10 +2,11 @@
import Link from "next/link";
import Image from "next/image";
-import { useBoolean } from "@/utils";
+import { useEffect } from "react";
+import { useBoolean, fetch } from "@/utils";
import { CloseIcon, CloudIcon, CogneeIcon } from "../Icons";
-import { CTAButton, GhostButton, IconButton, Modal } from "../elements";
+import { CTAButton, GhostButton, IconButton, Modal, StatusDot } from "../elements";
import syncData from "@/modules/cloud/syncData";
interface HeaderProps {
@@ -23,6 +24,12 @@ export default function Header({ user }: HeaderProps) {
setFalse: closeSyncModal,
} = useBoolean(false);
+ const {
+ value: isMCPConnected,
+ setTrue: setMCPConnected,
+ setFalse: setMCPDisconnected,
+ } = useBoolean(false);
+
const handleDataSyncConfirm = () => {
syncData()
.finally(() => {
@@ -30,6 +37,19 @@ export default function Header({ user }: HeaderProps) {
});
};
+ useEffect(() => {
+ const checkMCPConnection = () => {
+ fetch.checkMCPHealth()
+ .then(() => setMCPConnected())
+ .catch(() => setMCPDisconnected());
+ };
+
+ checkMCPConnection();
+ const interval = setInterval(checkMCPConnection, 30000);
+
+ return () => clearInterval(interval);
+ }, [setMCPConnected, setMCPDisconnected]);
+
return (
<>