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langchain

by zechenzhangAGI

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering

Installation

Pick a client and clone the repository into its skills directory.

Installation

Quick info

Category
Testing
Views
123

About this skill

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

How to use

  1. Zainstaluj LangChain za pomocą pip — uruchom pip install -U langchain aby pobrać bibliotekę podstawową (wymaga Python 3.10+). 2. Dodaj wybrany dostawcę modelu — jeśli chcesz pracować z OpenAI, zainstaluj pip install langchain-openai, dla Anthropic użyj pip install langchain-anthropic. 3. Zainstaluj integracje, które będą ci potrzebne — pip install langchain-community daje dostęp do 500+ integracji, a pip install langchain-chroma umożliwia pracę z wektorową bazą danych. 4. Zainicjuj model w swoim kodzie — zaimportuj odpowiednią klasę (np. ChatAnthropic) i utwórz instancję modelu, którą będziesz używać w aplikacji. 5. Buduj łańcuchy i agentów — połącz model z narzędziami, pamięcią i źródłami danych aby stworzyć chatbota, system RAG lub autonomicznego agenta. 6. W produkcji włącz LangSmith — skonfiguruj obserwację aplikacji aby monitorować wydajność i debugować problemy w działającym systemie.

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