npmai 0.1.2

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 10 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() 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

for Documentation visit:- https://npmai.netlify.app or https://npmai.onrender.com

Basic Examples for Python:-

1.Import npmai Module 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)

#If you want to use npmai through other languages consider hitting this api endpoint:- https://npmai-api.onrender.com

example:- with other languages #Java Script- async function callApi() { const payload = { prompt: "hey my name is sonu kumar what do you think about Narendra Modi", model: "llama3.2", temperature: 0.4, };

const response = await fetch("https://npmai-api.onrender.com/llm", { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify(payload) });

const data = await response.json(); console.log(data.response); }

callApi();

#C++ #include <httplib.h> #include <nlohmann/json.hpp> #include

int main() { httplib::Client cli("https://npmai-api.onrender.com"); nlohmann::json payload = { {"prompt", "hey my name is sonu kumar what do you think about Narendra Modi"}, {"model", "llama3.2"}, {"temperature", 0.4} };

auto res = cli.Post("/llm", payload.dump(), "application/json");
if (res) {
    auto data = nlohmann::json::parse(res->body);
    std::cout << data["response"] << std::endl;
}
return 0;

}

#Java import java.net.URI; import java.net.http.HttpClient; import java.net.http.HttpRequest; import java.net.http.HttpResponse;

public class Main { public static void main(String[] args) throws Exception { String json = "{"prompt": "hey my name is sonu kumar what do you think about Narendra Modi", "model": "llama3.2", "temperature": 0.4}";

    HttpClient client = HttpClient.newHttpClient();
    HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create("https://npmai-api.onrender.com/llm"))
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(json))
            .build();

    HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
    // Note: For simple output, print full body; for parsing, use a library like Jackson or Gson
    System.out.println(response.body());
}

}

#C #include <stdio.h> #include <curl/curl.h>

int main(void) { CURL *curl = curl_easy_init(); if(curl) { struct curl_slist *headers = NULL; headers = curl_slist_append(headers, "Content-Type: application/json");

    const char *data = "{\"prompt\": \"hey my name is sonu kumar what do you think about Narendra Modi\", \"model\": \"llama3.2\", \"temperature\": 0.4}";

    curl_easy_setopt(curl, CURLOPT_URL, "https://npmai-api.onrender.com/llm");
    curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);
    curl_easy_setopt(curl, CURLOPT_POSTFIELDS, data);

    CURLcode res = curl_easy_perform(curl);
    if(res != CURLE_OK) fprintf(stderr, "Request failed: %s\n", curl_easy_strerror(res));

    curl_easy_cleanup(curl);
    curl_slist_free_all(headers);
}
return 0;

}

#Latest Update : version 0.1.2 Here in this version we added Memory concept so that you do not need to define memory concept and no need to rely on Agentic Frameworks for Memory.

⚠️ 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.