reapxdev/pypi-scraper huggingface dataset:
langchain 1.3.14 — Building applications with LLMs through composability
License: MIT 
Requires Python: <4.0.0,>=3.10.0
Dependencies: langchain-core<2.0.0,>=1.4.9, langgraph<1.3.0,>=1.2.5, pydantic<3.0.0,>=2.7.4, langchain-anthropic; extra == "anthropic", langchain-aws; extra == "aws", langchain-azure-ai; extra == "azure-ai", langchain-baseten>=0.2.0; extra == "baseten", langchain-community; extra == "community", langchain-deepseek; extra == "deepseek", langchain-fireworks; extra == "fireworks", langchain-google-genai; extra == "google-genai", langchain-google-vertexai; extra == "google-vertexai", langchain-groq; extra == "groq", langchain-huggingface; extra == "huggingface", langchain-meta; extra == "meta", langchain-mistralai; extra == "mistralai", langchain-ollama; extra == "ollama", langchain-openai; extra == "openai", langchain-perplexity; extra == "perplexity", langchain-together; extra == "together", langchain-xai; extra == "xai"

# 🦜️🔗 LangChain

[![PyPI - Version](https://img.shields.io/pypi/v/langchain?label=%20)](https://pypi.org/project/langchain/#history)
[![PyPI - License](https://img.shields.io/pypi/l/langchain)](https://opensource.org/licenses/MIT)
[![PyPI - Downloads](https://img.shields.io/pepy/dt/langchain)](https://pypistats.org/packages/langchain)
[![Twitter](https://img.shields.io/twitter/url/https/twitter.com/langchain_oss.svg?style=social&label=Follow%20%40LangChain)](https://x.com/langchain_oss)

Looking for the JS/TS version? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).

To help you ship LangChain apps to production faster, check out [LangSmith](https://www.langchain.com/langsmith).
[LangSmith](https://www.langchain.com/langsmith) is a unified developer platform for building, testing, and monitoring LLM applications.

## Quick Install

```bash
uv add langchain
```

## 🤔 What is this?

LangChain is the easiest way to start building agents and applications powered by LLMs. With under 10 lines of code, you can connect to OpenAI, Anthropic, Google, and [more](https://docs.langchain.com/oss/python/integrations/providers/overview). LangChain provides a pre-built agent architecture and model integrations to help you get started quickly and seamlessly incorporate LLMs into your agents and applications.

We recommend you use LangChain if you want to quickly build agents and autonomous applications. Use [LangGraph](https://docs.langchain.com/oss/python/langgraph/overview), our low-level agent orchestration framework and runtime, when you have more advanced needs that require a combination of deterministic and agentic workflows, heavy customization, and carefully controlled latency.

LangChain [agents](https://docs.langchain.com/oss/python/langchain/agents) are built on top of LangGraph in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. (You do not need to know LangGraph for basic LangChain agent usage.)

## 📖 Document
lark 1.3.1 — a modern parsing library
License: MIT 
Keywords: Earley, LALR, parser, parsing, ast
Requires Python: >=3.8
Dependencies: regex; extra == "regex", js2py; extra == "nearley", atomicwrites; extra == "atomic-cache", interegular<0.4.0,>=0.3.1; extra == "interegular"

Lark is a modern general-purpose parsing library for Python.
With Lark, you can parse any context-free grammar, efficiently, with very little code.
Main Features:
- Builds a parse-tree (AST) automagically, based on the structure of the grammar
- Earley parser
- Can parse all context-free grammars
- Full support for ambiguous grammars
- LALR(1) parser
- Fast and light, competitive with PLY
- Can generate a stand-alone parser
- CYK parser, for highly ambiguous grammars
- EBNF grammar
- Unicode fully supported
- Automatic line & column tracking
- Standard library of terminals (strings, numbers, names, etc.)
- Import grammars from Nearley.js
- Extensive test suite
- And much more!
Since version 1.2, only Python versions 3.8 and up are supported.