client.py

client.py

import openai
import asyncio

async def get_choice_completion(prompt, choices):
    # Initialize an asynchronous OpenAI client
    async with openai.AsyncClient(base_url="http://127.0.0.1:8000/v1", api_key="abc") as client:
        choice_probs = {}

        # Calculate logprobs for each prompt + choice sequence
        for choice in choices:
            choice_prompt = prompt + choice
            response = await client.completions.create(
                model="meta-llama/Meta-Llama-3-8B",  # Specify the model
                prompt=choice_prompt,
                echo=True,
                logprobs=0,  # Request logprobs to get likelihoods for each token
                max_tokens=0,  # Set to 0 to prevent additional tokens from being generated
            )
            # Sum the logprobs for the tokens in the prompt part of the response
            prob = sum([x for x in response.choices[0].logprobs.token_logprobs if x is not None])
            choice_probs[choice] = prob

    # Select the choice with the highest probability (highest summed logprobs)
    best_choice = max(choice_probs, key=choice_probs.get)
    return best_choice, choice_probs

# Define main async function to test it
async def main():
    inputs = [
        ["What color is the sky on a clear day? The color is ", ["blue", "green", "red", "yellow"]],
        ["The capital of France is ", ["Paris", "Beijing"]],
    ]

    tasks = [get_choice_completion(prompt, choices) for prompt, choices in inputs]
    results = await asyncio.gather(*tasks)
    return results

# Run the main function
data = asyncio.run(main())
print(data)

Can we create like multiple threads to call the normal client.completions.create? Like we have one client only, but handling multiple requests? Not sure if this will work

threads are less efficient than coroutines here.