Address PR review feedback

Author: hande-k

integrations/cognee/.gitignore

@@ -1,125 +1,14 @@
 # cognee-haystack
 
-[![PyPI](https://img.shields.io/pypi/v/cognee-haystack.svg)](https://pypi.org/project/cognee-haystack/)
-[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)
+[![PyPI - Version](https://img.shields.io/pypi/v/cognee-haystack.svg)](https://pypi.org/project/cognee-haystack)
+[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/cognee-haystack.svg)](https://pypi.org/project/cognee-haystack)
 
-A [Haystack](https://haystack.deepset.ai/) integration for [Cognee](https://github.com/topoteretes/cognee) — open-source memory for AI agents.
+[Cognee](https://www.cognee.ai/) integration for [Haystack](https://haystack.deepset.ai/) — open-source memory for AI agents.
 
-[Cognee](https://www.cognee.ai/) gives agents persistent, traceable memory by transforming raw data (e.g., unstructured documents, relational databases, etc.) into a knowledge engine that is both searchable by meaning and connected by relationships. Cognee uses an ECL (Extract, Cognify, Load) pipeline: vector search, knowledge graphs, with support for ontology-based entity grounding (e.g. OWL) and Pydantic-defined graph schemas.
+- [Changelog](https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/cognee/CHANGELOG.md)
 
-Cognee serves developers and teams building agentic systems where agents need to retain context across sessions, learn from user feedback, and operate in multi-tenant, data-isolated environments. Cognee is available as an open-source Python library (Apache 2.0), a self-hosted/on-prem subscription tier, and a managed cloud service (Cognee Cloud at platform.cognee.ai).
+---
 
+## Contributing
 
-## Installation
-
-```bash
-pip install cognee-haystack
-```
-
-To use the `CogneeMemoryStore` with Haystack's experimental Agent:
-
-```bash
-pip install "cognee-haystack[memory]"
-```
-
-## Components
-
-### CogneeWriter
-
-Adds Haystack Documents to Cognee's knowledge engine via `cognee.add()`, with optional automatic `cognee.cognify()`.
-
-```python
-from haystack import Document, Pipeline
-from haystack_integrations.components.connectors.cognee import CogneeWriter
-
-pipeline = Pipeline()
-pipeline.add_component("writer", CogneeWriter(dataset_name="my_data", auto_cognify=True))
-
-docs = [Document(content="Cognee builds a structured memory from unstructured data.")]
-pipeline.run({"writer": {"documents": docs}})
-```
-
-### CogneeCognifier
-
-Standalone `cognee.cognify()` step — useful when you want to separate adding and processing.
-
-```python
-from haystack_integrations.components.connectors.cognee import CogneeCognifier
-
-cognifier = CogneeCognifier()
-cognifier.run()  # {"cognified": True}
-```
-
-### CogneeRetriever
-
-Searches Cognee's memory and returns Haystack `Document` objects.
-
-```python
-from haystack import Pipeline
-from haystack_integrations.components.connectors.cognee import CogneeRetriever
-
-pipeline = Pipeline()
-pipeline.add_component("retriever", CogneeRetriever(search_type="GRAPH_COMPLETION", top_k=5))
-
-result = pipeline.run({"retriever": {"query": "What is Cognee?"}})
-for doc in result["retriever"]["documents"]:
-    print(doc.content)
-```
-
-**Supported search types:** `GRAPH_COMPLETION`, `CHUNKS`, `SUMMARIES`, `INSIGHTS`, and others from Cognee's `SearchType` enum.
-
-### CogneeMemoryStore
-
-Memory backend for Haystack's experimental Agent, backed by Cognee.
-
-```python
-from haystack.dataclasses import ChatMessage
-from haystack_integrations.components.connectors.cognee import CogneeMemoryStore
-
-store = CogneeMemoryStore(search_type="GRAPH_COMPLETION", top_k=5)
-
-# Store memories
-store.add_memories(messages=[
-    ChatMessage.from_user("The project deadline is next Friday.")
-])
-
-# Recall memories
-results = store.search_memories(query="When is the deadline?")
-```
-
-## Configuration
-
-Cognee uses environment variables for its LLM and storage configuration:
-
-```bash
-export LLM_API_KEY="sk-..."
-```
-
-See the [Cognee documentation](https://docs.cognee.ai/) for additional configuration options.
-
-## Examples
-
-See the [`examples/`](examples/) directory for runnable demos:
-
-- **`demo_pipeline.py`** — Index documents and search with CogneeWriter + CogneeRetriever
-- **`demo_memory_agent.py`** — Use CogneeMemoryStore as a conversational memory backend
-
-## Development
-
-```bash
-cd integrations/cognee
-
-# Format and lint
-hatch run fmt
-hatch run fmt-check
-
-# Type checking
-hatch run test:types
-
-# Run tests
-hatch run test:unit
-```
-
-## License
-
-Apache 2.0 — see [LICENSE](LICENSE) for details.
+Refer to the general [Contribution Guidelines](https://github.com/deepset-ai/haystack-core-integrations/blob/main/CONTRIBUTING.md).