import asyncio
import os
import sys
from dotenv import load_dotenv

if sys.stdout.encoding != 'utf-8':
    try:
        sys.stdout.reconfigure(encoding='utf-8')
    except Exception:
        pass

load_dotenv()

async def test_sarvam_v2():
    api_key = os.getenv("SARVAM_API_KEY")
    import httpx2
    client = httpx2.AsyncClient(timeout=15.0)
    headers = {
        "api-subscription-key": api_key,
        "Content-Type": "application/json",
    }
    payload = {
        "inputs": ["வணக்கம், உங்கள் உடல்நலம் எப்படி உள்ளது?"],
        "target_language_code": "ta-IN",
        "speaker": "kavya",
        "model": "bulbul:v2",
    }
    res = await client.post(
        "https://api.sarvam.ai/text-to-speech",
        json=payload,
        headers=headers,
    )
    if res.status_code == 200:
        audios = res.json().get("audios", [])
        print(f"[OK] Sarvam TTS bulbul:v2 WORKS! Generated {len(audios)} audio clips.")
        return True
    else:
        print(f"[FAIL] Sarvam error {res.status_code}: {res.text}")
        return False

async def test_gemini_models():
    api_key = os.getenv("GEMINI_API_KEY")
    from google import genai
    genai.configure(api_key=api_key)
    for model_name in ["gemini-3.6-flash", "gemini-flash-latest", "gemini-2.5-flash-lite", "gemma-4-26b-a4b-it"]:
        try:
            m = genai.GenerativeModel(model_name)
            res = await m.generate_content_async("Hello")
            print(f"[OK] Gemini '{model_name}' WORKS! Response: {res.text.strip()}")
            return model_name
        except Exception as e:
            print(f"[X] Gemini '{model_name}' failed: {e}")
    return None

async def test_anthropic_models():
    api_key = os.getenv("ANTHROPIC_API_KEY")
    from anthropic import AsyncAnthropic
    client = AsyncAnthropic(api_key=api_key)
    for model_name in [
        "claude-3-7-sonnet-20250219",
        "claude-3-5-sonnet-20240620",
        "claude-3-sonnet-20240229",
        "claude-2.1",
        "claude-instant-1.2"
    ]:
        try:
            res = await client.messages.create(
                model=model_name,
                max_tokens=20,
                messages=[{"role": "user", "content": "Hi"}],
            )
            print(f"[OK] Anthropic '{model_name}' WORKS! Response: {res.content[0].text.strip()}")
            return model_name
        except Exception as e:
            print(f"[X] Anthropic '{model_name}' failed: {e}")
    return None

async def main():
    print("--- Testing Sarvam v2 ---")
    await test_sarvam_v2()
    print("\n--- Testing Gemini Models ---")
    await test_gemini_models()
    print("\n--- Testing Anthropic Models ---")
    await test_anthropic_models()

if __name__ == "__main__":
    asyncio.run(main())