Update app.py

app.py

@@ -40,25 +40,37 @@ Respond ONLY in this JSON format:
 """
 
 def evaluate_prompt(user_prompt):
+    # Format the input prompt
+    formatted_prompt = PROMPT_TEMPLATE.format(user_prompt=user_prompt)
+
     payload = {
-        "inputs": PROMPT_TEMPLATE.format(user_prompt=user_prompt),
-        "parameters": {"max_new_tokens": 512, "temperature": 0.7}
+        "messages": [
+            {
+                "role": "user",
+                "content": formatted_prompt
+            }
+        ],
+        "model": "deepseek/deepseek-v3-0324"
     }
 
-    response = requests.post(HF_API_URL, headers=HEADERS, json=payload)
-    result = response.json()
-
-    # Handle streaming/text output
-    if isinstance(result, list) and "generated_text" in result[0]:
-        raw_text = result[0]["generated_text"]
-        try:
-            # Try to parse the JSON segment only
-            json_part = raw_text[raw_text.index("{"):]
-            return json.loads(json_part)
-        except:
-            return {"error": "Failed to parse model output."}
-    else:
+    try:
+        # Send request to DeepSeek API
+        response = requests.post(API_URL, headers=HEADERS, json=payload)
+        response.raise_for_status()
+
+        result = response.json()
+
+        # Extract JSON formatted evaluation
+        if isinstance(result, dict) and "choices" in result:
+            raw_text = result["choices"][0]["message"]["content"]
+            try:
+                json_part = raw_text[raw_text.index("{"):]
+                return json.loads(json_part)
+            except (ValueError, json.JSONDecodeError) as e:
+                return {"error": f"Failed to parse model output: {str(e)}"}
         return result
+    except requests.exceptions.RequestException as e:
+        return {"error": f"API request failed: {str(e)}"}
 
 # --- Streamlit UI ---
 st.set_page_config(page_title="👮 PromptPolice", layout="centered")
@@ -67,7 +79,7 @@ st.title("👮 PromptPolice: Prompt Evaluator")
 user_prompt = st.text_area("Paste your AI prompt here:", height=200)
 
 if st.button("Evaluate Prompt") and user_prompt:
-    with st.spinner("Evaluating your prompt with Mistral..."):
+    with st.spinner("Evaluating your prompt with DeepSeek..."):
         evaluation_result = evaluate_prompt(user_prompt)
 
     st.subheader("Evaluation Result (JSON):")