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How to Get an Answer to RP2040 in 4 Seconds with Groq

This project demonstrates using Groq's innovative LPU chip and Meta's LLaMA3 model to achieve fast response times with the RP2040 microcontroller, ideal for AIoT applications.

Project Overview

Utilizing the cutting-edge technology from Groq and Meta, this project aims to replace traditional response mechanisms on the maker site with a much faster and efficient alternative using the RP2040 connected to Groq's cloud services.

Hardware Components

  • WIZnet - W5100S-EVB-Pico x 1

Software and Libraries

  • MicroPython
  • Groq API

Setup Instructions

  1. GroqCloud Setup

    • Visit the Groq Cloud homepage.
    • Sign up and obtain your API KEY.
    • Ensure the Groq library is installed (not applicable directly on Pico, use API communication).

  2. Ethernet Initialization

    • Use the following MicroPython code to initialize your Ethernet connection via WIZnet hardware:
    from machine import Pin, SPI
import network
import utime

def init_ethernet(timeout=10):
    spi = SPI(0, 2_000_000, mosi=Pin(19), miso=Pin(16), sck=Pin(18))
    nic = network.WIZNET5K(spi, Pin(17), Pin(20))
    nic.active(True)
    start_time = utime.ticks_ms()
    while not nic.isconnected():
        if (utime.ticks_diff(utime.ticks_ms(), start_time) > timeout * 1000):
            raise Exception("Ethernet connection timed out.")
        utime.sleep(1)
    print('Ethernet connected. IP:', nic.ifconfig())

API Communication Example

  • Here is how you can send a chat request to the Groq API and handle responses: 
    def send_chat_request(api_key, user_message):
    url = "https://api.groq.com/openai/v1/chat/completions"
    headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
    payload = {"messages": [{"role": "user", "content": user_message}], "model": "llama3-70b-8192"}
    start_time = utime.ticks_ms()
    response = urequests.post(url, headers=headers, json=payload)
    elapsed_time = utime.ticks_diff(utime.ticks_ms(), start_time)
    if response.status_code == 200:
        try:
            content = response.json()['choices'][0]['message']['content']
            return content, elapsed_time
        except Exception as e:
            raise Exception("Failed to decode JSON from response: " + str(e))
    else:
        raise Exception(f"API error ({response.status_code}): {response.reason}")

Running the Project

  • Input your API key in the main function and initiate the chat sequence: 
    def main():
    api_key = 'your_api_key_here'
    init_ethernet()
    while True:
        user_input = input("User: ").strip()
        if user_input.lower() == "exit":
            print("Exiting...")
            break
        elif not user_input:
            continue
        try:
            response_content, time_taken = send_chat_request(api_key, user_input)
            print(f"LLaMA Response: {response_content} (Processed in {time_taken} ms)")
        except Exception as e:
            print("Error: ", e)

if __name__ == "__main__":
    main()