/langchain-retriever

name: langchain-retriever
description: LangChain retriever implementation with various retrieval strategies for RAG applications
allowed-tools:
  - Read
  - Write
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  - Bash
  - Glob
  - Grep
graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:retrieval-augmented-generation, skill-area:search-indexing]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:ml-model-lifecycle, workflow:feature-development]

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