🦜️🧰 langchain-dev-utils
🚀 High-efficiency toolkit designed for LangChain and LangGraph developers
This is the English version. For the Chinese version, please visit 中文版本
✨ Why choose langchain-dev-utils?
Tired of writing repetitive code in LangChain development? langchain-dev-utils is the solution you need! This lightweight yet powerful toolkit is designed to enhance the development experience of LangChain and LangGraph, helping you:
- ⚡ Boost development efficiency - Reduce boilerplate code, allowing you to focus on core functionality
- 🧩 Simplify complex workflows - Easily manage multi-model, multi-tool, and multi-agent applications
- 🔧 Enhance code quality - Improve consistency and readability, reducing maintenance costs
- 🎯 Accelerate prototype development - Quickly implement ideas, iterate and validate faster
🎯 Core Features
- 🔌 Unified model management - Specify model providers through strings, easily switch and combine different models
- 💬 Flexible message handling - Support for chain-of-thought concatenation, streaming processing, and message formatting
- 🛠️ Powerful tool calling - Built-in tool call detection, parameter parsing, and human review functionality
- 🤖 Efficient Agent development - Simplify agent creation process, expand more common middleware
- 📊 Convenient State Graph Construction - Provides pre-built functions to easily create sequential or parallel state graphs
⚡ Quick Start
This library is primarily used to connect to models that expose an OpenAI-Compatible API. The example below uses a qwen2.5-7b model served by vLLM.
1. Install langchain-dev-utils
pip install -U "langchain-dev-utils[standard]"
Note: This feature requires installing langchain-dev-utils[standard].
2. Start using
from langchain.tools import tool
from langchain_core.messages import HumanMessage
from langchain_dev_utils.chat_models import register_model_provider, load_chat_model
from langchain_dev_utils.agents import create_agent
# Register model provider
register_model_provider("vllm", "openai-compatible", base_url="http://localhost:8000/v1")
@tool
def get_current_weather(location: str) -> str:
"""Get the current weather for the specified location"""
return f"25 degrees, {location}"
# Dynamically load model using string
model = load_chat_model("vllm:qwen2.5-7b")
response = model.invoke("Hello")
print(response)
# Create agent
agent = create_agent("vllm:qwen2.5-7b", tools=[get_current_weather])
response = agent.invoke({"messages": [HumanMessage(content="What's the weather like in New York today?")]})
print(response)
For more features of this library, please visit the full documentation
🛠️ GitHub Repository
Visit the GitHub repository to view the source code and report issues.
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Release files for langchain-dev-utils 1.4.6
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Source distribution (sdist)
| File | Size | Uploaded | |
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| langchain_dev_utils-1.4.6.tar.gz | 276.7 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| langchain_dev_utils-1.4.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 334.3 kB
Release files / langchain_dev_utils-1.4.6.tar.gz
| Download URL | langchain_dev_utils-1.4.6.tar.gz |
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| Size | 276.7 kB |
| Tags | Source |
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Release files / langchain_dev_utils-1.4.6-py3-none-any.whl
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| Tags | Python 3 |
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