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| # 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 assistants import ( | |
| get_thread, | |
| set_openai_client, | |
| set_assistant, | |
| set_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.") | |
| text_values, image_values = [], [] | |
| download_link = "" | |
| try: | |
| # TODO: Use Gradio session | |
| if get_thread() == None or len(history) == 0: | |
| set_openai_client(openai_api_key) | |
| #set_assistant(create_assistant()) # first run | |
| set_assistant(load_assistant()) # subsequent runs | |
| set_thread(create_thread()) | |
| create_message(get_thread(), message) | |
| run = create_run(get_assistant(), get_thread()) | |
| run = wait_on_run(get_thread(), run) | |
| run_steps = get_run_steps(get_thread(), run) | |
| recurse_execute_tool_calls(get_thread(), run, run_steps, 0) | |
| messages = get_messages(get_thread()) | |
| text_values, image_values = extract_content_values(messages) | |
| # 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]})" | |
| except Exception as e: | |
| raise gr.Error(e) | |
| 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() |