Update app.py

app.py

@@ -14,7 +14,7 @@ def respond(message, history):
     top_results = get_top_chunks( message , chunk_embeddings, cleaned_chunks) # Complete this line
     # Print the top results
     print(top_results)
-    messages = [{"role": "system", "content": "You are a chatbot that encourage people to live more sustainably. Base your response on the following action {top_results}"}]
+    messages = [{"role": "system", "content": "You are a chatbot that encourage people to live more sustainably. Base your response on the following action", {top_results}}]
     
     if history:
         messages.extend(history)
@@ -71,7 +71,7 @@ def create_embeddings(text_chunks):
 
   # Return the chunk_embeddings
   return chunk_embeddings
-create_embeddings(cleaned_chunks)
+chunk_embeddings = create_embeddings(cleaned_chunks)
 # Define a function to find the most relevant text chunks for a given query, chunk_embeddings, and text_chunks
 def get_top_chunks(query, chunk_embeddings, text_chunks):
   # Convert the query text into a vector embedding
@@ -100,7 +100,7 @@ def get_top_chunks(query, chunk_embeddings, text_chunks):
 
   # Loop through the top indices and retrieve the corresponding text chunks
   for indices in top_indices:
-    relevant_info = cleaned_chunks
+    relevant_info = cleaned_chunks[indices]
     top_chunks.append(relevant_info)