app.py

import gradio as gr
import pandas as pd
import os
import json
import tempfile
from openai import OpenAI

# Initialize OpenAI client
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

# -------- Speech to Text --------
def transcribe_audio(file_path):
    with open(file_path, "rb") as audio:
        transcript = client.audio.transcriptions.create(
            model="whisper-1",
            file=audio
        )
    return transcript.text


# -------- Extract CRM Fields (SAFE JSON) --------
def extract_fields(text):
    prompt = f"""
    Extract the following fields from the conversation:

    Name, Phone, Product, Budget, Location, Intent.

    Return ONLY valid JSON like:
    {{
      "Name": "",
      "Phone": "",
      "Product": "",
      "Budget": "",
      "Location": "",
      "Intent": ""
    }}

    Conversation:
    {text}
    """

    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}],
        temperature=0
    )

    content = response.choices[0].message.content

    try:
        data = json.loads(content)
    except:
        data = {
            "Name": "",
            "Phone": "",
            "Product": "",
            "Budget": "",
            "Location": "",
            "Intent": ""
        }

    return data


# -------- Main Processing --------
def process_audio(audio_file):
    if audio_file is None:
        return "No audio provided", pd.DataFrame(), None

    try:
        file_path = audio_file  # Gradio gives filepath directly

        # Step 1: Transcription
        text = transcribe_audio(file_path)

        # Step 2: Extraction
        data = extract_fields(text)

        # Step 3: Convert to DataFrame
        df = pd.DataFrame([data])

        # Step 4: Save Excel
        excel_path = os.path.join(tempfile.gettempdir(), "crm_output.xlsx")
        df.to_excel(excel_path, index=False)

        return text, df, excel_path

    except Exception as e:
        return f"Error: {str(e)}", pd.DataFrame(), None


# -------- UI --------
with gr.Blocks() as app:
    gr.Markdown("# 🎙️ AI Voice to CRM Auto Filler")

    with gr.Tabs():
        # 🎤 Record
        with gr.Tab("🎤 Record Inquiry"):
            mic_input = gr.Audio(
                sources=["microphone"],
                type="filepath",
                label="Record Audio"
            )
            btn1 = gr.Button("Process Recording")

        # 📁 Upload
        with gr.Tab("📁 Upload Voice"):
            file_input = gr.Audio(
                sources=["upload"],
                type="filepath",
                label="Upload Audio File"
            )
            btn2 = gr.Button("Process File")

    # Outputs
    transcript_output = gr.Textbox(label="Transcription")
    table_output = gr.Dataframe(label="Extracted CRM Data")
    download_btn = gr.File(label="Download Excel")

    # Actions
    btn1.click(
        fn=process_audio,
        inputs=mic_input,
        outputs=[transcript_output, table_output, download_btn]
    )

    btn2.click(
        fn=process_audio,
        inputs=file_input,
        outputs=[transcript_output, table_output, download_btn]
    )

# Launch
app.launch()