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atest.py

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+#!/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))