Update app.py

app.py

@@ -191,51 +191,49 @@ def predict(user_input,company):
     ]
     
     # Get response from the LLM
-    try:
-        url = "https://api.fireworks.ai/inference/v1/chat/completions"
-        payload = {
-           "model": "accounts/fireworks/models/llama-v3p3-70b-instruct",
-            "temperature": 0.6,
-            "top_p": 1,
-            "top_k": 40,
-            "presence_penalty": 0,
-            "frequency_penalty": 0,
-            "messages": [
-        {
-            "role": "user",
-            "content": f"{prompt}"
-        }
+    
+    url = "https://api.fireworks.ai/inference/v1/chat/completions"
+    payload = {
+       "model": "accounts/fireworks/models/llama-v3p3-70b-instruct",
+        "temperature": 0.6,
+        "top_p": 1,
+        "top_k": 40,
+        "presence_penalty": 0,
+        "frequency_penalty": 0,
+        "messages": [
+    {
+        "role": "user",
+        "content": f"{prompt}"
+    }
     ]
-}
-        headers = {
-            "Accept": "application/json",
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}"
-}
-
-        response = requests.post(url, headers=headers, json=payload)
+    }
+    headers = {
+        "Accept": "application/json",
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
 
-        prediction = response.json()["choices"][0]["message"]["content"]
+    response = requests.post(url, headers=headers, json=payload)
 
-    except Exception as e:
-        prediction = {
-            "error_type": type(e).__name__,
-            "error_message": str(e),
-            "traceback": traceback.format_exc()
-        }
+    prediction = response.json()["choices"][0]["message"]["content"]
 
-    # Log safely
-    with scheduler.lock:
-        with log_file.open("a") as f:
-            f.write(json.dumps(
-                {
-                    'user_input': user_input,
-                    'retrieved_context': context_for_query,
-                    'model_response': prediction
-                },
-                indent=2
-            ))
-            f.write("\n")
+    
+    if response.ok:
+        print(response.json()["choices"][0]["message"]["content"])
+    else:
+        print(f"❌ Error {response.status_code}: {response.text}")
+    # # Log safely
+    # with scheduler.lock:
+    #     with log_file.open("a") as f:
+    #         f.write(json.dumps(
+    #             {
+    #                 'user_input': user_input,
+    #                 'retrieved_context': context_for_query,
+    #                 'model_response': prediction
+    #             },
+    #             indent=2
+    #         ))
+    #         f.write("\n")
     
     return prediction