Update app.py

app.py

@@ -18,7 +18,7 @@ text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=10
 
 system_template = """
 Use the following pieces of context to answer the user's question.
-Please respond as if you were Ken from the movie Barbie. Ken is a well-meaning but naive character who loves to Beach. He talks like a typical Californian Beach Bro, but he doesn't use the word "Dude" so much.
+Please respond as if you were Pris from the movie ’Bladerunner’.
 If you don't know the answer, just say that you don't know, don't try to make up an answer.
 You can make inferences based on the context as long as it still faithfully represents the feedback.
 
@@ -41,7 +41,7 @@ chain_type_kwargs = {"prompt": prompt}
 
 @cl.author_rename
 def rename(orig_author: str):
-    rename_dict = {"RetrievalQA": "Consulting The Kens"}
+    rename_dict = {"RetrievalQA": "Consulting.....?"}
     return rename_dict.get(orig_author, orig_author)
 
 @cl.on_chat_start
@@ -49,7 +49,7 @@ async def init():
     msg = cl.Message(content=f"Building Index...")
     await msg.send()
 
-    # build FAISS index from csv
+    # --build FAISS index from csv
     loader = CSVLoader(file_path="./data/barbie.csv", source_column="Review_Url")
     data = loader.load()
     documents = text_splitter.transform_documents(data)
@@ -58,11 +58,11 @@ async def init():
     embedder = CacheBackedEmbeddings.from_bytes_store(
         core_embeddings_model, store, namespace=core_embeddings_model.model
     )
-    # make async docsearch
+    # --make async docsearch
     docsearch = await cl.make_async(FAISS.from_documents)(documents, embedder)
 
     chain = RetrievalQA.from_chain_type(
-        ChatOpenAI(model="gpt-3.5-turbo", temperature=0, streaming=True),
+        ChatOpenAI(model="gpt-3.5-turbo-instruct", temperature=0.9, streaming=True),
         chain_type="stuff",
         return_source_documents=True,
         retriever=docsearch.as_retriever(),
@@ -97,7 +97,7 @@ async def main(message):
         if source in visited_sources:
             continue
         visited_sources.add(source)
-        # Create the text element referenced in the message
+        # --createtext element referenced in message
         source_elements.append(
             cl.Text(content="https://www.imdb.com" + source, name="Review URL")
         )
@@ -106,5 +106,7 @@ async def main(message):
         answer += f"\nSources: {', '.join([e.content.decode('utf-8') for e in source_elements])}"
     else:
         answer += "\nNo sources found"
+  
 
     await cl.Message(content=answer, elements=source_elements).send()
+    return