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LangChain is a framework for developing applications powered by large language models (LLMs). For these applications, LangChain simplifies the entire application lifecycle: Open-source libraries: Build your applications using LangChain's open-source building blocks, components, and third-party integrations .
Build context-aware, reasoning applications with LangChain’s flexible abstractions and AI-first toolkit. The LangChain Libraries: LangChain (Python) LangChain.js (JavaScript/TypeScript) Our Products: LangSmith - the platform for building production-grade LLM applications. Extensions:
LangChain is a framework for developing applications powered by large language models (LLMs). LangChain simplifies every stage of the LLM application lifecycle: Development: Build your applications using LangChain's open-source building blocks, components, and third-party integrations.
LangChain provides a standard interface for memory, a collection of memory implementations, and examples of chains/agents that use memory. 🧐 Evaluation: [BETA] Generative models are notoriously hard to evaluate with traditional metrics.
🦜🔗 Build context-aware reasoning applications. Contribute to langchain-ai/langchain development by creating an account on GitHub.
LangChain is a framework for developing applications powered by language models. It enables applications that: Are context-aware: connect a language model to sources of context (prompt instructions, few shot examples, content to ground its response in, etc.)
🦜🔗 LangChain - Comprehensive Guide. Overview. LangChain now integrates with Multion API, enhancing its NLP application development capabilities. This addition complements the existing OpenAI API, offering advanced functionalities for chatbots and automated writing assistants. For detailed information, visit: LangChain Introduction.
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence.
Issues. Pull requests. Scripts for fine-tuning Meta Llama3 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment.
Moturu-Sumanth. on Aug 10, 2023. I want to download the langchain documentation because of the rate at which it is updating. Some of the functions I used earlier are no longer visible in the documentation and it is very difficult for me to maintain the code for the applications that I develop and integrate some new functionalities to it.
