npmai 0.1.1

A lightweight Ollama(no ollama installation needed) based LangChain-compatible LLM bridge ('LLaMA-3.2','CodeLLaMA-Instruct 7B','Gemma-2-Instruct 9B','Mistral 7B Instruct','Qwen-2.5-Coder 7B','Phi-3 Medium (8B)','Falcon 7B Instruct','Baichuan-2-7B','InternLM-Chat-7B','Vicuna 7B') built by Sonu Kumar.

npmai

npmai (by Sonu Kumar Ramashish) is a lightweight Python package that seamlessly connects you with Ollama and other open-source models without any Installation, Login/Signup or API problems.

🚀 Features

Execute prompts on multiple LLMs simultaneously:["LLaMA-3.2","CodeLLaMA-Instruct 7B","Gemma-2-Instruct 9B","Mistral 7B Instruct","Qwen-2.5-Coder 7B","Phi-3 Medium (8B)","Falcon 7B Instruct","Baichuan-2-7B","InternLM-Chat-7B","Vicuna 7B"]

Fully LangChain,CrewAI and other -compatible interface.

Simple and intuitive invoke() API for instant responses.

Support continuous conversation.

Encourages responsible usage.

#For documentation visit:- https://npmai.onrender.com

⚙️ Installation pip install npmai

Tip: For Python 3.13, make sure to use:

py -3.13 -m pip install npmai

💡 How to Use

Import the models

from npmai import Ollama

Initialize Ollama:

llm = Ollama()

prompts="" model="Llama3.2" you can keep other also

Invoke a prompt and get the response:

response = llm.invoke(prompts,model) print(response)

#Latest Update : version 0.1.1 Here in this version we fixed the bug and added Structured_Output schemas.

⚠️ Important Notes

Designed for educational ,small-scale experimentation, for demo projets and small scale users.

If using at a larger scale, consider supporting the original AI platforms—they invest heavily in research and infrastructure.

use responsibly to help us.

✅ npmai makes it effortless to connect Ollam models with Python, bringing automation, experimentation, and LangChain,Crew AI integration together in a single, easy-to-use package.