Update app.py

app.py

@@ -19,7 +19,6 @@ def init_embedding_model():
 @st.cache_resource
 def init_groq_client():
     return Groq(api_key=os.environ.get("GROQ_API_KEY"))
-
 class RAGSystem:
     def __init__(self):
         self.embedding_model = init_embedding_model()
@@ -28,6 +27,7 @@ class RAGSystem:
         
     def load_knowledge_base(self) -> List[Dict]:
         """Load and preprocess knowledge base into a list of documents"""
+        # Your existing knowledge base dictionary
         kb = {
             "spalling": [
                 {
@@ -296,6 +296,19 @@ class RAGSystem:
         
         return index
     
+    def create_vector_store(self):
+        """Create FAISS vector store from knowledge base"""
+        # Generate embeddings for all documents
+        texts = [doc["text"] for doc in self.knowledge_base]
+        embeddings = self.embedding_model.encode(texts)
+        
+        # Initialize FAISS index
+        dimension = embeddings.shape[1]
+        index = faiss.IndexFlatL2(dimension)
+        index.add(np.array(embeddings).astype('float32'))
+        
+        return index
+        
     def get_relevant_context(self, query: str, k: int = 3) -> str:
         """Retrieve relevant context based on query"""
         # Generate query embedding
@@ -308,17 +321,14 @@ class RAGSystem:
         context = "\n\n".join([self.knowledge_base[i]["text"] for i in I[0]])
         return context
 
-def get_groq_response(query: str, context: str) -> str:
+    def get_groq_response(query: str, context: str) -> str:
     """Get response from Groq LLM"""
     client = init_groq_client()
     try:
         prompt = f"""Based on the following context about construction defects, please answer the question.
-
 Context:
 {context}
-
 Question: {query}
-
 Please provide a detailed and specific answer based on the given context."""
 
         response = client.chat.completions.create(
@@ -338,7 +348,7 @@ Please provide a detailed and specific answer based on the given context."""
     except Exception as e:
         return f"Error: {str(e)}"
 
-def main():
+ef main():
     st.set_page_config(
         page_title="Construction Defect RAG Analyzer",
         page_icon="🏗️",
@@ -384,25 +394,28 @@ def main():
         
         with col1:
             st.subheader("Image Analysis")
-            # Your existing image analysis code here
+            # Image analysis placeholder
             st.info("Image analysis results would appear here")
 
         with col2:
             st.subheader("AI Assistant Response")
-            # Get relevant context from knowledge base
-            context = str(KNOWLEDGE_BASE)  # Simplified for example
-            
-            # Get response from Groq
-            with st.spinner("Getting AI response..."):
-                response = get_groq_response(user_query, context)
-                st.write(response)
+            if user_query:  # Only show response if there's a query
+                # Get relevant context from knowledge base
+                context = st.session_state.rag_system.get_relevant_context(user_query)
+                
+                # Get response from Groq
+                with st.spinner("Getting AI response..."):
+                    response = get_groq_response(user_query, context)
+                    st.write(response)
+
         # Display knowledge base sections
         if st.checkbox("Show Knowledge Base"):
-        st.subheader("Available Knowledge Base")
-        for category, details in KNOWLEDGE_BASE.items():
-            with st.expander(category.title()):
-                st.write(details)
-
+            st.subheader("Available Knowledge Base")
+            kb_data = st.session_state.rag_system.knowledge_base
+            for doc in kb_data:
+                category = doc["metadata"]["category"]
+                with st.expander(category.title()):
+                    st.text(doc["text"])
 
 if __name__ == "__main__":
     main()