feat: implement AI-orchestrated result extraction and service connectivity tests

2026-08-27 17:45:07 +05:30
parent 59c1372fe3
commit 3d2596ced1
11 changed files with 546 additions and 123 deletions
@@ -0,0 +1,95 @@
+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 diagnose_anthropic():
+    api_key = os.getenv("ANTHROPIC_API_KEY")
+    print("\n--- Testing Anthropic Models ---")
+    candidate_models = [
+        "claude-3-5-sonnet-latest",
+        "claude-3-5-haiku-latest",
+        "claude-3-haiku-20240307",
+        "claude-3-sonnet-20240229",
+        "claude-3-opus-20240229",
+    ]
+    from anthropic import AsyncAnthropic
+    client = AsyncAnthropic(api_key=api_key)
+    for model in candidate_models:
+        try:
+            res = await client.messages.create(
+                model=model,
+                max_tokens=20,
+                messages=[{"role": "user", "content": "Hi"}],
+            )
+            print(f"[OK] Anthropic Model '{model}' WORKS! Response: {res.content[0].text.strip()}")
+            return model
+        except Exception as e:
+            print(f"[X] '{model}' failed: {e}")
+    return None
+
+async def diagnose_gemini():
+    api_key = os.getenv("GEMINI_API_KEY")
+    print("\n--- Testing Gemini Models ---")
+    import google.generativeai as genai
+    genai.configure(api_key=api_key)
+    try:
+        models = [m.name for m in genai.list_models() if 'generateContent' in m.supported_generation_methods]
+        print(f"Available Gemini models: {models[:10]}")
+        for m_name in models[:5]:
+            try:
+                m = genai.GenerativeModel(m_name)
+                res = await m.generate_content_async("Hi")
+                print(f"[OK] Gemini Model '{m_name}' WORKS! Response: {res.text.strip()}")
+                return m_name
+            except Exception as e:
+                print(f"[X] Gemini Model '{m_name}' failed: {e}")
+    except Exception as e:
+        print(f"[FAIL] Listing Gemini models failed: {e}")
+    return None
+
+async def diagnose_sarvam():
+    api_key = os.getenv("SARVAM_API_KEY")
+    print("\n--- Testing Sarvam Speakers ---")
+    import httpx2
+    client = httpx2.AsyncClient(timeout=15.0)
+    headers = {
+        "api-subscription-key": api_key,
+        "Content-Type": "application/json",
+    }
+    payload = {
+        "inputs": ["வணக்கம்"],
+        "target_language_code": "ta-IN",
+        "speaker": "kavya",
+        "model": "bulbul:v1",
+    }
+    try:
+        res = await client.post(
+            "https://api.sarvam.ai/text-to-speech",
+            json=payload,
+            headers=headers,
+        )
+        if res.status_code == 200:
+            print("[OK] Sarvam TTS with speaker 'kavya' WORKS!")
+            return "kavya"
+        else:
+            print(f"[FAIL] Sarvam HTTP {res.status_code}: {res.text}")
+    except Exception as e:
+        print(f"[FAIL] Sarvam error: {e}")
+    return None
+
+async def main():
+    await diagnose_anthropic()
+    await diagnose_gemini()
+    await diagnose_sarvam()
+
+if __name__ == "__main__":
+    asyncio.run(main())