#!/usr/bin/env python3
import requests
import sys
import os

# ---- Config ----
LMSTUDIO_URL = "http://172.22.22.210:1234/v1"
AUDIO_FILE = "/Users/despiegk/Downloads/harvard.wav"   # change to your input file

# ---- Step 1: List available models ----
models_resp = requests.get(f"{LMSTUDIO_URL}/models")
models_resp.raise_for_status()
models = [m["id"] for m in models_resp.json().get("data", [])]

print("Available models:", models)

# ---- Step 2: Find Whisper ----
whisper_model = None
for m in models:
    if "whisper" in m.lower():
        whisper_model = m
        break

if not whisper_model:
    print("❌ No Whisper model found in LM Studio. Please download/start one.")
    sys.exit(1)

print(f"✅ Found Whisper model: {whisper_model}")

# ---- Step 3: Transcribe ----
if not os.path.exists(AUDIO_FILE):
    print(f"❌ Audio file '{AUDIO_FILE}' not found.")
    sys.exit(1)

with open(AUDIO_FILE, "rb") as f:
    files = {"file": f}
    data = {"model": whisper_model}
    headers = {"Authorization": "Bearer no-key"}  # LM Studio ignores key
    resp = requests.post(f"{LMSTUDIO_URL}/audio/transcriptions", 
                         headers=headers, 
                         files=files, 
                         data=data)
    resp.raise_for_status()
    result = resp.json()

print("📝 Transcription result:")
print(result.get("text", result))