Spaces:
Running
Running
| import base64 | |
| import os | |
| import re | |
| from pathlib import Path | |
| import numpy as np | |
| import openai | |
| from dotenv import load_dotenv | |
| from fastrtc import ( | |
| AdditionalOutputs, | |
| ReplyOnPause, | |
| audio_to_bytes, | |
| ) | |
| from groq import Groq | |
| load_dotenv() | |
| groq_client = Groq(api_key=os.environ.get("GROQ_API_KEY")) | |
| client = openai.OpenAI( | |
| api_key=os.environ.get("SAMBANOVA_API_KEY"), | |
| base_url="https://api.sambanova.ai/v1", | |
| ) | |
| path = Path(__file__).parent / "assets" | |
| spinner_html = open(path / "spinner.html").read() | |
| system_prompt = "You are an AI coding assistant. Your task is to write single-file HTML applications based on a user's request. Only return the necessary code. Include all necessary imports and styles. You may also be asked to edit your original response." | |
| user_prompt = "Please write a single-file HTML application to fulfill the following request.\nThe message:{user_message}\nCurrent code you have written:{code}" | |
| def extract_html_content(text): | |
| """ | |
| Extract content including HTML tags. | |
| """ | |
| match = re.search(r"<!DOCTYPE html>.*?</html>", text, re.DOTALL) | |
| return match.group(0) if match else None | |
| def display_in_sandbox(code): | |
| encoded_html = base64.b64encode(code.encode("utf-8")).decode("utf-8") | |
| data_uri = f"data:text/html;charset=utf-8;base64,{encoded_html}" | |
| return f'<iframe src="{data_uri}" width="100%" height="600px"></iframe>' | |
| def generate(user_message: tuple[int, np.ndarray], history: list[dict], code: str): | |
| yield AdditionalOutputs(history, spinner_html) | |
| text = groq_client.audio.transcriptions.create( | |
| file=("audio-file.mp3", audio_to_bytes(user_message)), | |
| model="whisper-large-v3-turbo", | |
| response_format="verbose_json", | |
| ).text | |
| user_msg_formatted = user_prompt.format(user_message=text, code=code) | |
| history.append({"role": "user", "content": user_msg_formatted}) | |
| response = client.chat.completions.create( | |
| model="Meta-Llama-3.1-70B-Instruct", | |
| messages=history, # type: ignore | |
| temperature=0.1, | |
| top_p=0.1, | |
| ) | |
| output = response.choices[0].message.content | |
| html_code = extract_html_content(output) | |
| history.append({"role": "assistant", "content": output}) | |
| yield AdditionalOutputs(history, html_code) | |
| CodeHandler = ReplyOnPause(generate) # type: ignore | |