Update app.py

app.py

@@ -25,19 +25,13 @@ User: {question}
 Assistant:"""
 prompt = PromptTemplate(template=prompt_template, input_variables=["question"])
 chain = LLMChain(llm=llm, prompt=prompt)
-
-# Load and split the document for the retrieval-based QA system
 with open("brookline_data.txt", "r") as f:
     data = f.read()
 text_splitter = RecursiveCharacterTextSplitter(chunk_size=100, chunk_overlap=20)
 splitted_data = text_splitter.split_text(data)
-
-# Generate embeddings for the split text
 embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-mpnet-base-v2')
 metadatas = [{"source": f"source_{i}"} for i in range(len(splitted_data))]
 documents = [Document(page_content=text, metadata=metadata) for text, metadata in zip(splitted_data, metadatas)]
-
-# Initialize Qdrant vector store
 qdrant = Qdrant.from_documents(
     documents,
     embeddings,
@@ -46,7 +40,7 @@ qdrant = Qdrant.from_documents(
 )
 retriever = qdrant.as_retriever()
 qna = RetrievalQA.from_chain_type(
-    llm=HuggingFaceHub(repo_id="ahmadmac/Trained-T5-large", model_kwargs={"temperature": 0.5, "max_length": 512}, 
+    llm=HuggingFaceHub(repo_id="ahmadmac/Trained-T5-large", model_kwargs={"temperature": 0.8, "max_length": 512}, 
                        huggingfacehub_api_token=os.environ["HUGGINGFACEHUB_API_TOKEN"]),
     chain_type="stuff",
     retriever=retriever
@@ -55,11 +49,15 @@ def chatbot(question, chat_history):
     response = chain.run(question)
     retrieval_result = qna(question)
     retrieval_answer = retrieval_result['result']
-    combined_response = f"{response}\n\nBased on the information available:\n{retrieval_answer}"
+    if retrival_answer.strip():
+        combined_response=f"Based on the information available:\n{retrieval_answer}"
+    else:
+        combined_response=f"Response through LLM:\n{response}"
+    #combined_response = f"{response}\n\nBased on the information available:\n{retrieval_answer}"
     return combined_response
 demo = gr.ChatInterface(
     fn=chatbot,
     title="Chatbot",
-    description="AI Assistant!!"
+    description="AI Assistant!"
 )
 demo.launch()