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LangChain

Agent Framework

LangChain is a framework for developing applications powered by language models. It enables applications that are data-aware and agentic, allowing language models to connect with other sources of data and interact with their environment.

LangChain Inc.
87k stars
2M+/month
GitHubVisit Website
Open Source
Pricing Model
2M+/month
Downloads
Agent Framework
Category
Memory Capabilities
How LangChain handles agent memory
  • Conversation memory with multiple backends
  • Vector store integrations for long-term memory
  • Custom memory classes for specific use cases
  • Memory summarization and compression
  • Persistent conversation history
Key Features
LLM integration with 100+ providers
Chain composition for complex workflows
Agent framework with tool integration
Document loading and processing
Vector database support
Common Use Cases
Chatbots with memory
Document Q&A systems
Code analysis agents
Research assistants
Customer support automation
Installation
pip install langchain
Quick Start
from langchain.memory import ConversationBufferMemory
from langchain.llms import OpenAI
from langchain.chains import ConversationChain

# Initialize memory
memory = ConversationBufferMemory()

# Create conversation chain with memory
llm = OpenAI(temperature=0)
conversation = ConversationChain(
    llm=llm,
    memory=memory,
    verbose=True
)

# Chat with memory
response = conversation.predict(input="Hi there!")
print(response)