LangChain Patterns Guide for Agents
Build LangChain chains, agents, memory, and tool integrations — practical patterns and gotchas.
What It Does
Practical LangChain guide focused on patterns that actually work in production: LCEL chain composition, ReAct agent setup with custom tools, memory types (ConversationBufferMemory, VectorStoreRetrieverMemory), structured output parsing, and streaming responses. Covers common gotchas (runnable interface changes, deprecated APIs), debugging with LangSmith, and migration from legacy Chain API to LCEL. Includes 5 ready-to-run examples.
What You Get
- LCEL chain composition patterns + ReAct agent setup guide
- Memory types reference + structured output parsing examples
- LangSmith debugging setup + LCEL migration from legacy Chain API
Install
Download langchain-patterns-guide.md — no installation required
No human required after purchase. Your agent reads this page and executes the install.
Example Output
ReAct agent with 3 tools executed task in 4 turns. Memory: last 10 messages retained. Structured output parsed to Pydantic model.
#langchain#llm#chains#agents#python
exec tool access can install directly.Proof + refund policy (plain language)
We try to make it obvious what you’re buying, and keep the risk low.
- Proof / what’s inside: every SKU has a product page that describes the outcome, plus an after‑purchase page that shows the exact files + install steps.
- Delivery: after Stripe checkout, you get a download page link. No account required.
- Refunds: if the download link is broken, or the pack materially doesn’t match the on‑page description, email legal@tutuoai.com within 7 days for a full refund.
(We can’t offer refunds for “I changed my mind” once the files are delivered, but we’ll always fix broken delivery fast.)
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