components/LLM.py

import openai
import time
import tiktoken
from components.configs import LLMtemp, gptmodel

#Call to Openai Chat Model
def chatopenai(finalprompt):
    response = openai.ChatCompletion.create(
        model=gptmodel,
        messages=finalprompt,
        temperature = LLMtemp,
        )
    # API_response = response should I want to store the full API returned content...
    assistant_response = response.choices[0].message['content']
    usedtokens = response["usage"]["total_tokens"]
    return assistant_response, usedtokens

#Call to Openai Chat Model 3 times, if it fails will return default messages back
def chatopenairetry(finalprompt, max_retries=3, retry_delay=1):
    default_assistant_response = "Sorry, I'm having issue with OpenAI API, it happens... could you retry?"
    default_used_tokens = 0
    for _ in range(max_retries):
        try:
            response = openai.ChatCompletion.create(
                model=gptmodel,
                messages=finalprompt,
                temperature = LLMtemp,
                )
            assistant_response = response.choices[0].message['content']
            used_tokens = response["usage"]["total_tokens"]
            return assistant_response, used_tokens
        except Exception as e:
            print(f"Encountered an error: {e}")
            print("Retrying the API call...")
            time.sleep(retry_delay)

    # If all retries fail, return dummy values
    print("Maximum retries reached. Unable to get a response from OpenAI.")
    return default_assistant_response, default_used_tokens


# Call to Openai with the stream of content
def chatopenaistream(finalprompt, callback, LLMtemp=LLMtemp):
    assistant_response = ""
    for chunk in openai.ChatCompletion.create(
        model=gptmodel,
        messages=finalprompt,
        temperature = LLMtemp,
        stream=True,
        ):
        content = chunk["choices"][0].get("delta", {}).get("content")
        if content is not None:
            assistant_response += content
            yield callback(content)  # Yield the result of the callback function

#token calculator to be run when using the streaming. Will calculate an estimate after the stream ended
def calculatetokens(finalprompt,assistant_response):
    encoding = tiktoken.encoding_for_model(gptmodel)
    usedtokens = len(encoding.encode(assistant_response + f"{finalprompt}"))
    usedtokens=0 
    return usedtokens