Create app.py

app.py

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+import json
+from sentence_transformers import SentenceTransformer, util
+from groq import Groq
+import datetime
+import requests
+from io import BytesIO
+from PIL import Image, ImageDraw, ImageFont
+import numpy as np
+from dotenv import load_dotenv
+import os
+
+# Load environment variables
+load_dotenv()
+
+# Initialize Groq client
+groq_client = Groq(api_key=os.getenv("GROQ_API_KEY"))
+
+# Load models and dataset
+similarity_model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
+
+# Load dataset (automatically using the path)
+with open('dataset.json', 'r') as f:
+    dataset = json.load(f)
+
+# Precompute embeddings
+dataset_questions = [item.get("input", "").lower().strip() for item in dataset]
+dataset_answers = [item.get("response", "") for item in dataset]
+dataset_embeddings = similarity_model.encode(dataset_questions, convert_to_tensor=True)
+
+def query_groq_llm(prompt, model_name="llama3-70b-8192"):
+    try:
+        chat_completion = groq_client.chat.completions.create(
+            messages=[{
+                "role": "user",
+                "content": prompt
+            }],
+            model=model_name,
+            temperature=0.7,
+            max_tokens=500
+        )
+        return chat_completion.choices[0].message.content.strip()
+    except Exception as e:
+        print(f"Error querying Groq API: {e}")
+        return ""
+
+def get_best_answer(user_input):
+    user_embedding = similarity_model.encode(user_input.lower().strip(), convert_to_tensor=True)
+    similarities = util.pytorch_cos_sim(user_embedding, dataset_embeddings)[0]
+    best_match_idx = similarities.argmax().item()
+    best_score = similarities[best_match_idx].item()
+
+    if best_score >= 0.65:
+        original_answer = dataset_answers[best_match_idx]
+        prompt = f"""As an official assistant for University of Education Lahore, provide a clear response:
+        Question: {user_input}
+        Original Answer: {original_answer}
+        Improved Answer:"""
+    else:
+        prompt = f"""As an official assistant for University of Education Lahore, provide a helpful response:
+        Include relevant details about university policies.
+        If unsure, direct to official channels.
+        
+        Question: {user_input}
+        
+        Official Answer:"""
+
+    llm_response = query_groq_llm(prompt)
+    
+    if llm_response:
+        for marker in ["Improved Answer:", "Official Answer:"]:
+            if marker in llm_response:
+                response = llm_response.split(marker)[-1].strip()
+                break
+        else:
+            response = llm_response
+    else:
+        response = dataset_answers[best_match_idx] if best_score >= 0.65 else """For official information:
+        📞 +92-42-99262231-33
+        ✉️ info@ue.edu.pk
+        🌐 ue.edu.pk"""
+    
+    return response