Add dedicated CLAUDE.md files for every component

CLAUDE.md

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+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Project Overview
+
+This is the Store component of the Symfony AI ecosystem, providing a low-level abstraction for storing and retrieving documents in vector stores. The component enables Retrieval Augmented Generation (RAG) applications by offering unified interfaces for various vector database implementations.
+
+## Development Commands
+
+### Testing
+Run the full test suite:
+```bash
+vendor/bin/phpunit
+```
+
+Run tests for a specific bridge (e.g., InMemory):
+```bash
+vendor/bin/phpunit tests/Bridge/Local/InMemoryStoreTest.php
+```
+
+Run a single test method:
+```bash
+vendor/bin/phpunit --filter testMethodName
+```
+
+### Code Quality
+Run PHPStan static analysis:
+```bash
+vendor/bin/phpstan analyse
+```
+
+### Installation
+Install dependencies:
+```bash
+composer install
+```
+
+## Architecture
+
+### Core Interfaces
+- **StoreInterface**: Main interface defining `add()` and `query()` methods for vector document storage and retrieval
+- **ManagedStoreInterface**: Extension interface providing `setup()` and `drop()` methods for store lifecycle management
+- **Indexer**: High-level service that converts TextDocuments to VectorDocuments and stores them in batches
+
+### Bridge Pattern Architecture
+The component follows a bridge pattern with implementations for multiple vector stores:
+
+**Database Bridges**: Postgres, MariaDB, ClickHouse, MongoDB, Neo4j, SurrealDB
+**Cloud Service Bridges**: Azure AI Search, Pinecone
+**Search Engine Bridges**: Meilisearch, Typesense, Weaviate, Qdrant, Milvus
+**Local Bridges**: InMemoryStore, CacheStore (PSR-6)
+**External Service Bridges**: ChromaDb (requires codewithkyrian/chromadb-php)
+
+### Document System
+- **TextDocument**: Input documents containing text and metadata
+- **VectorDocument**: Documents with embedded vectors for storage
+- **Vectorizer**: Converts TextDocuments to VectorDocuments using AI Platform
+- **Transformers**: ChainTransformer, TextSplitTransformer, ChunkDelayTransformer for document preprocessing
+
+### Key Dependencies
+- **symfony/ai-platform**: For AI model integration and vectorization
+- **psr/log**: For logging throughout the indexing process
+- **symfony/http-client**: For HTTP-based vector store communication
+
+### Test Architecture
+Tests follow the same bridge structure as source code, with each store implementation having corresponding test classes. Tests use PHPUnit 11+ with strict configuration for coverage and error handling.