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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 (
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, tavily_api_key):
if not message:
raise gr.Error("Message is required.")
if not openai_api_key:
raise gr.Error("OpenAI API key is required.")
os.environ["OPENAI_API_KEY"] = openai_api_key
os.environ["TAVILY_API_KEY"] = tavily_api_key
global assistant, thread
# 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"]
del os.environ["TAVILY_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=350),
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: 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", type="password"),
gr.Textbox(label="Tavily API Key", type="password"),
],
).launch() |