# Langchain Retriever

> LangChain retriever implementation with various retrieval strategies for RAG applications

- Skill: `a5c-ai/langchain-retriever` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add a5c-ai/langchain-retriever`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/langchain-retriever/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/langchain-retriever

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# LangChain Retriever Skill

## Capabilities

- Implement various LangChain retriever types
- Configure vector store retrievers
- Set up multi-query retrievers for improved recall
- Implement contextual compression retrievers
- Design ensemble retrievers combining multiple strategies
- Configure self-query retrievers for structured filtering

## Target Processes

- rag-pipeline-implementation
- advanced-rag-patterns

## Implementation Details

### Retriever Types

1. **VectorStoreRetriever**: Basic similarity search
2. **MultiQueryRetriever**: Generates query variations
3. **ContextualCompressionRetriever**: Filters and compresses results
4. **EnsembleRetriever**: Combines multiple retrievers
5. **SelfQueryRetriever**: Structured metadata filtering
6. **ParentDocumentRetriever**: Returns parent chunks

### Configuration Options

- Search type (similarity, mmr, similarity_score_threshold)
- Number of documents to retrieve (k)
- Score thresholds
- Metadata filtering
- Compression settings

### Dependencies

- langchain
- langchain-community
- Vector store client