app.py

# Reference:
#
# https://vimeo.com/990334325/56b552bc7a
# https://platform.openai.com/playground/assistants
# https://cookbook.openai.com/examples/assistants_api_overview_python
# https://platform.openai.com/docs/api-reference/assistants/createAssistant
# https://platform.openai.com/docs/assistants/tools

import gradio as gr

import os

from openai import OpenAI

from assistants import (
    openai_client,
    assistant,
    thread,
    create_assistant,
    load_assistant,
    create_thread,
    create_message,
    create_run,
    wait_on_run,
    get_run_steps,
    recurse_execute_tool_calls,
    get_messages,
    extract_content_values,
)

def chat(message, history, openai_api_key):
    if not openai_api_key:
        raise gr.Error("OpenAI API Key is required (see additional inputs below).")
    if not message:
        raise gr.Error("Message is required.")

    #raise gr.Error("Please clone and bring your own credentials.")
    
    global openai_client, assistant, thread

    print("openai_client=")
    print(openai_client)
    if openai_client == None:
        openai_client = OpenAI(api_key=openai_api_key)
    print("openai_client=")
    print(openai_client)
    
    # On first run, create assistant and update assistant_id,
    # see https://platform.openai.com/playground/assistants.
    # On subsequent runs, load assistant.
    if assistant == None:
        #assistant = create_assistant()
        assistant = load_assistant()

    # TODO: Use Gradio session to support multiple users
    if thread == None or len(history) == 0:
        thread = create_thread()
        
    create_message(thread, message)
    run = create_run(assistant, thread)
    run = wait_on_run(thread, run)
    run_steps = get_run_steps(thread, run)
    recurse_execute_tool_calls(thread, run, run_steps, 0)
    messages = get_messages(thread)
    text_values, image_values = extract_content_values(messages)

    download_link = ""

    # TODO: Handle multiple images and other file types
    if len(image_values) > 0:
        download_link = f"<hr>[Download](https://platform.openai.com/storage/files/{image_values[0]})"

    del os.environ["OPENAI_API_KEY"]
    
    #return f"{'<hr>'.join(list(reversed(text_values))[1:])}{download_link}"
    return f"{text_values[0]}{download_link}"

gr.ChatInterface(
        fn=chat,
        chatbot=gr.Chatbot(height=250),
        textbox=gr.Textbox(placeholder="Ask anything", container=False, scale=7),
        title="Python Coding Assistant",
        description=os.environ.get("DESCRIPTION"),
        clear_btn="Clear",
        retry_btn=None,
        undo_btn=None,
        examples=[
                  ["Generate: Code to fine-tune model meta-llama/Meta-Llama-3.1-8B on dataset gretelai/synthetic_text_to_sql using QLoRA"],
                  ["Explain: r\"^(?=.*[A-Z])(?=.*[a-z])(?=.*[0-9])(?=.*[\\W]).{8,}$\""],
                  ["Fix: x = [5, 2, 1, 3, 4]; print(x.sort())"],
                  ["Optimize: x = []; for i in range(0, 10000): x.append(i)"],
                  ["1. Execute: Calculate the first 25 Fibbonaci numbers. 2. Show the code."],
                  ["1. Execute with tools: Create a plot showing stock gain QTD for NVDA and AMD, x-axis is \"Day\" and y-axis is \"Gain %\". 2. Show the code."],
                  ["1. Execute with tools: Get key announcements from latest OpenAI Dev Day. 2. Show the web references."]
                 ],
        cache_examples=False,
        additional_inputs=[
            gr.Textbox("", label="OpenAI API Key")
        ],
    ).launch()