Added resource 2

app.py

@@ -24,17 +24,17 @@ model = SentenceTransformer('all-MiniLM-L6-v2')
 
 def create_embeddings(text_chunks):
   # Convert each text chunk into a vector embedding and store as a tensor
-  chunk_embeddings = model.encode(text_chunks, convert_to_tensor=True) # Replace ... with the cleaned_chunks list
+  chunk_embeddings = model.encode(text_chunks, convert_to_tensor=True) 
   # Return the chunk_embeddings
   return chunk_embeddings
 
 # Call the create_embeddings function and store the result in a new chunk_embeddings variable
-chunk_embeddings = create_embeddings(cleaned_chunks) #complete this line
+chunk_embeddings = create_embeddings(cleaned_chunks) 
 
 
 def get_top_chunks(query, chunk_embeddings, text_chunks):
   # Convert the query text into a vector embedding
-  query_embedding = model.encode(query, convert_to_tensor=True) # Complete this line
+  query_embedding = model.encode(query, convert_to_tensor=True) 
 
   # Normalize the query embedding to unit length for accurate similarity comparison
   query_embedding_normalized = query_embedding / query_embedding.norm()
@@ -43,7 +43,7 @@ def get_top_chunks(query, chunk_embeddings, text_chunks):
   chunk_embeddings_normalized = chunk_embeddings / chunk_embeddings.norm(dim=1, keepdim=True)
 
   # Calculate cosine similarity between query and all chunks using matrix multiplication
-  similarities = torch.matmul(chunk_embeddings_normalized, query_embedding_normalized) # Complete this line
+  similarities = torch.matmul(chunk_embeddings_normalized, query_embedding_normalized) 
 
   # Find the indices of the 3 chunks with highest similarity scores
   top_indices = torch.topk(similarities, k=3).indices
@@ -82,6 +82,7 @@ def respond(message, history):
 
 #EMMA'S PRACTICE EDITS#
 url = "https://mentalhealthfirstaid.org/mental-health-resources/"
+yt = "https://youtu.be/7CCTOvZH0KU?si=6G80QeaA4cKssFeX"
 
 
 about_text = f"""
@@ -95,6 +96,8 @@ support tool.</p>
 <p>All credits to the owner of the videos. We do not own any of the resources provided. 
 
 <p>Click <a href="{url}" target="_blank">Free Resources</a> to access Free Mental Health Resources.</p>
+<p>Click <a href="{url}" target="_blank">here</a> to learn more about mental health.</p>
+<p>You've got this! :) .</p>
 """
 
 with gr.Blocks() as demo: