app.py

# Tech Trends Curator Chatbot with Audio (Hugging Face Compatible)

import os
import uuid
import gradio as gr
import requests
from gtts import gTTS

# Fetch API key from environment
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")

# Function to query Groq LLM via REST API
def query_groq(messages):
    url = "https://api.groq.com/openai/v1/chat/completions"
    headers = {
        "Authorization": f"Bearer {GROQ_API_KEY}",
        "Content-Type": "application/json"
    }

    data = {
        "model": "llama3-8b-8192",
        "messages": messages
    }

    response = requests.post(url, headers=headers, json=data)
    result = response.json()
    return result["choices"][0]["message"]["content"]

# Chatbot function with audio output
def chat_with_audio(user_input, history):
    system_prompt = {
        "role": "system",
        "content": (
            "You are a tech trend curator. Summarize the latest AI tools, GitHub projects, "
            "and startup news in an engaging tone. If asked for fake/funny trends, be creative and witty."
        )
    }

    messages = [system_prompt]
    for user, assistant in history:
        messages.append({"role": "user", "content": user})
        messages.append({"role": "assistant", "content": assistant})
    messages.append({"role": "user", "content": user_input})

    response_text = query_groq(messages)

    # Generate audio
    tts = gTTS(response_text)
    audio_file = f"/tmp/{uuid.uuid4()}.mp3"
    tts.save(audio_file)

    return response_text, audio_file

# Gradio ChatInterface with audio output
with gr.Blocks(theme="soft") as demo:
    gr.Markdown("# 📈 Tech Trends Curator\nChat about trending AI tools, GitHub projects, and startup news — with audio!")
    chatbot = gr.Chatbot(height=400)
    msg = gr.Textbox(placeholder="Ask for top trends, tools, or fake news")
    audio = gr.Audio(label="Audio Summary")
    state = gr.State([])

    def user_message(user_input, history):
        reply, audio_path = chat_with_audio(user_input, history)
        history.append([user_input, reply])
        return history, history, audio_path

    msg.submit(user_message, [msg, state], [chatbot, state, audio])

# Launch the app
demo.launch()