npmai

0.1.8 · active · verified Wed Apr 15

npmai is a lightweight Python package (current version 0.1.8) designed to bridge the gap between users and open-source LLMs. It allows connection with Ollama and over 10 other powerful models instantly, without requiring local installation, user logins, or API keys. It also facilitates the development of RAG Agents without local or cloud installations, offering free and unlimited usage. The project shows a consistent release cadence with minor version updates addressing features and bug fixes.

Warnings

breaking Parameters of the `Rag` class have been updated across minor versions (e.g., in v0.1.7) to support new functionalities like sending multiple file types and integrating with Supabase. Existing RAG agent implementations relying on previous parameter signatures may break.
Fix: Review the latest documentation or `npmai`'s PyPI release notes for the `Rag` class's updated parameter list and adjust your code accordingly.
gotcha While `npmai` advertises 'zero setup, no API keys, no installation' for LLM access and RAG, it internally relies on hosted cloud services (e.g., Huggingface Server for RAG processes, Supabase for vectorized document storage). Users should be aware of these external dependencies for reliability and potential production considerations.
Fix: Understand that the 'zero setup' is achieved by abstracting external cloud services. For critical applications, investigate the stability and performance of the underlying services `npmai` uses. No direct code fix is required, but awareness is key.
gotcha As a library in its early development stage (v0.1.x), the API and class methods (e.g., `Memory` class methods like `clear_memory` added in v0.1.7) are subject to change in minor releases without explicit deprecation warnings or major version bumps. This can lead to unexpected behavior or breakage.
Fix: It is highly recommended to pin exact versions of `npmai` in your `requirements.txt` (e.g., `npmai==0.1.8`) to prevent unexpected changes. Regularly review the PyPI release history or GitHub for updates when upgrading.

Install

pip install npmai Install with pip

Imports

Ollama
```
from npmai import Ollama
```
Memory
```
from npmai import Memory
```
Introduced in v0.1.3 for native memory support.
Rag
```
from npmai import Rag
```
Used for Retrieval-Augmented Generation (RAG) functionalities.

Quickstart

This quickstart demonstrates how to use `npmai` to interact with an open-source LLM (like llama3.2) without any local setup. It initializes the `Ollama` class, sends a prompt, and prints the generated response.

from npmai import Ollama

# Initialize the Ollama model (llama3.2 is an example)
llm = Ollama(model="llama3.2", temperature=0.5)

# Define your prompt
prompts = "Hello, tell me a short summary of NPMAI"

# Invoke the LLM to get a response
result = llm.invoke(prompts)

# Print the result
print(result)

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