LangChain Retriever Skill
SkillAI & modelsLangChain retriever implementation with various retrieval strategies for RAG applications
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/ai-agents-conversational/skills/langchain-retriever/SKILL.md and read by Ahel’s review.
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
- VectorStoreRetriever: Basic similarity search
- MultiQueryRetriever: Generates query variations
- ContextualCompressionRetriever: Filters and compresses results
- EnsembleRetriever: Combines multiple retrievers
- SelfQueryRetriever: Structured metadata filtering
- 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
Signals
- GitHub stars
- 2k
- Forks
- 113
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
langchain-retriever- Source
- github.com/a5c-ai/babysitter
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