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name: LangChain description: Workflow patterns and gotchas for LangChain. Directs to RAG for implementation.

LangChain Workflow

When to Choose LangChain

• Need composable chains with many integrations
• Building RAG/retrieval applications
• Want broad LLM provider support
• Need document processing pipelines

Decision Framework

Component Selection

Query RAG: mcp__agentic-rag__query_sdk("component example", sdk="langchain", mode="build")

Critical Gotchas

These trip up everyone:

1. LCEL is the pattern - Use chain = prompt | llm | parser, not legacy chains
2. RunnablePassthrough for context - Pass data through the chain explicitly
3. Output parsers matter - Without one, you get raw text not structured data
4. Invoke vs stream vs batch - Different methods for different use cases
5. Async needs ainvoke - Sync methods block; use async for concurrency
6. Memory isn't automatic - You must explicitly add and manage it
7. API keys via env vars - Each provider has its own key format

Workflow: Building a LangChain Application

Step 1: Dependencies

RAG Query: mcp__agentic-rag__query_sdk("langchain installation packages", sdk="langchain", mode="explain")

Step 2: LLM Setup

RAG Query: mcp__agentic-rag__query_sdk("ChatOpenAI ChatAnthropic setup", sdk="langchain", mode="build")

Step 3: Prompt Design

RAG Query: mcp__agentic-rag__query_sdk("ChatPromptTemplate messages", sdk="langchain", mode="build")

Step 4: Chain Composition

RAG Query: mcp__agentic-rag__query_sdk("LCEL chain pipe operator", sdk="langchain", mode="build")

Step 5: Tool Integration (if needed)

RAG Query: mcp__agentic-rag__query_sdk("StructuredTool from_function", sdk="langchain", mode="build")

Step 6: Retrieval (if RAG)

RAG Query: mcp__agentic-rag__query_sdk("vector store retriever", sdk="langchain", mode="build")

Common Error Patterns

LangChain vs LangGraph

Advanced Features

Query RAG when you need:

• Streaming: "langchain streaming callback"
• Callbacks/tracing: "langchain callbacks tracing"
• Custom chains: "custom runnable class"
• Caching: "langchain caching responses"
• Fallbacks: "chain fallback retry"