Update app.py

app.py

@@ -1,5 +1,3 @@
-# 👮 PromptPolice MVP - Streamlit App with Mistral Backend (JSON Output)
-
 import streamlit as st
 import requests
 import json
@@ -12,22 +10,17 @@ HEADERS = {
     "Content-Type": "application/json"
 }
 
+# Correctly format the prompt string with {user_prompt} placeholder inside the string
 PROMPT_TEMPLATE = """
 You are a prompt evaluation assistant. Evaluate the following user prompt in JSON format using the structure provided below.
-
 Prompt:
-
-"""
 {user_prompt}
-"""
-
 Evaluate based on the following criteria:
 - Clarity (1-5)
 - Context (1-5)
 - Specificity (1-5)
 - Intent (1-5)
 Also include a suggestion for improving the prompt.
-
 Respond ONLY in this JSON format:
 {
   "prompt": "...",
@@ -42,7 +35,7 @@ Respond ONLY in this JSON format:
 """
 
 def evaluate_prompt(user_prompt):
-    # Format the input prompt
+    # Format the input prompt by inserting the user_prompt dynamically
     formatted_prompt = PROMPT_TEMPLATE.format(user_prompt=user_prompt)
 
     payload = {
@@ -57,7 +50,7 @@ def evaluate_prompt(user_prompt):
 
     try:
         # Send request to DeepSeek API
-        response = requests.post(API_URL, headers=HEADERS, json=payload)
+        response = requests.post(HF_API_URL, headers=HEADERS, json=payload)
         response.raise_for_status()
 
         result = response.json()
@@ -91,4 +84,4 @@ if st.button("Evaluate Prompt") and user_prompt:
     if st.button("💾 Save to Dataset"):
         with open("crowdsourced_prompts.jsonl", "a", encoding="utf-8") as f:
             f.write(json.dumps(evaluation_result) + "\n")
-        st.success("Prompt evaluation saved!")
+        st.success("Prompt evaluation saved!")