Update app.py

app.py

@@ -4,58 +4,52 @@ import os
 
 # Define models
 MODEL_OPTIONS = {
-    "Gemma 3-4B": "google/gemma-3-4b-it",
-    "Mistral 7B": "mistralai/mistral-7b-instruct",
-    "Qwen 0.6B": "qwen/qwen3-0.6b-04-28",
-    "DeepSeek 70B": "deepseek/deepseek-r1-distill-llama-70b"
+    "Gemma 3-4B": "google/gemma-3-4b-it:free",
+    "Mistral 7B": "mistralai/mistral-7b-instruct:free",
+    "Qwen 0.6B": "qwen/qwen3-0.6b-04-28:free",
+    "DeepSeek 70B": "deepseek/deepseek-r1-distill-llama-70b:free"
 }
 
 EVALUATION_MODEL = "qwen/qwen3-32b"
 
-# Token (set your HF token as an environment variable or paste here directly)
-HF_TOKEN = os.getenv("HF_TOKEN")
+#Load the open router api
+OPENROUTERAI_API_KEY = os.getenv("OPENROUTERAI")
 
 # API query function
-def query_huggingface(prompt, model_id):
+def query_openrouter(prompt, model_id):
     headers = {
-        "Authorization": f"Bearer {HF_TOKEN}",
+        "Authorization": f"Bearer {OPENROUTER_API_KEY}",
         "Content-Type": "application/json"
     }
 
     payload = {
-        "inputs": prompt,
-        "parameters": {
-            "max_new_tokens": 150,
-            "do_sample": True,
-            "temperature": 0.7
-        }
+        "model": model_id,
+        "messages": [
+            {"role": "user", "content": prompt}
+        ]
     }
 
-    response = requests.post(
-        f"https://api-inference.huggingface.co/models/{model_id}",
-        headers=headers,
-        json=payload
-    )
+    response = requests.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=payload)
 
     result = response.json()
-    if isinstance(result, list) and "generated_text" in result[0]:
-        return result[0]["generated_text"]
-    else:
-        return f"❌ Error: {result.get('error', 'Unknown error')}"
+    try:
+        return result["choices"][0]["message"]["content"]
+    except Exception as e:
+        return f"❌ Error: {result.get('error', str(e))}"
 
 # Main logic
 def generate_and_evaluate(prompt, model_name):
     model_id = MODEL_OPTIONS[model_name]
 
     # Step 1: Generate math problem
-    generated = query_huggingface(prompt, model_id)
+    generated = query_openrouter(prompt, model_id)
 
     # Step 2: Evaluate using Qwen 32B
     eval_prompt = (
         f"Evaluate the following math problem for originality, clarity, and difficulty. "
         f"Give a score out of 10 with a short explanation:\n\n{generated}"
     )
-    evaluation = query_huggingface(eval_prompt, EVALUATION_MODEL)
+    evaluation = query_openrouter(eval_prompt, EVALUATION_MODEL)
 
     return generated.strip(), evaluation.strip()