langchain-embeddings
CommunityMaster text embeddings with LangChain.
Authorevanfang0054
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides a comprehensive guide and practical examples for integrating various text embedding models within the LangChain framework, enabling semantic understanding and retrieval of textual data.
Core Features & Use Cases
- Model Integration: Connect with popular embedding providers like OpenAI, Azure OpenAI, Cohere, HuggingFace, and Ollama.
- Semantic Search Foundation: Learn how to generate embeddings crucial for building RAG systems and vector databases.
- Use Case: Embed a collection of customer support documents to enable a semantic search feature, allowing users to find relevant information based on the meaning of their queries rather than just keywords.
Quick Start
Use the langchain-embeddings skill to generate an embedding for the text "What is the capital of France?".
Dependency Matrix
Required Modules
@langchain/openai@langchain/cohere@langchain/ollama@langchain/community
Components
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: langchain-embeddings Download link: https://github.com/evanfang0054/x-codegen-agent/archive/main.zip#langchain-embeddings Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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