ryanrwatkins commited on
Commit
20f289e
1 Parent(s): 56d9758

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +4 -7
app.py CHANGED
@@ -608,10 +608,7 @@ memory.save_context(
608
  DTC can handle a variety of e-commerce products and can generate images using in-the-wild images & references.
609
  It is superior to existing zero-shot personalization methods, especially in preserving the fine-grained details of items."""}
610
  )
611
- memory.save_context(
612
- inputs={"question":"what does Vit-all stand for?"},
613
- outputs={"answer":"Virtual Try-All"}
614
- )
615
 
616
  memory.load_memory_variables({})
617
 
@@ -712,8 +709,8 @@ chain = ConversationalRetrievalChain.from_llm(
712
 
713
 
714
  # let's invoke the chain
715
- response = chain.invoke({"question":"what does Google stand for?"})
716
- print(response)
717
 
718
 
719
  chain.memory.load_memory_variables({})
@@ -794,7 +791,7 @@ def submit_message(prompt, prompt_template, temperature, max_tokens, context_len
794
 
795
  prompt_template = prompt_templates[prompt_template]
796
 
797
-
798
  #chain = load_qa_chain(ChatOpenAI(temperature=temperature, max_tokens=max_tokens, model_name="gpt-3.5-turbo"), chain_type="stuff")
799
  #completion = chain.run(input_documents=docs, question=query)
800
 
 
608
  DTC can handle a variety of e-commerce products and can generate images using in-the-wild images & references.
609
  It is superior to existing zero-shot personalization methods, especially in preserving the fine-grained details of items."""}
610
  )
611
+
 
 
 
612
 
613
  memory.load_memory_variables({})
614
 
 
709
 
710
 
711
  # let's invoke the chain
712
+ #response = chain.invoke({"question":"what does Google stand for?"})
713
+ #print(response)
714
 
715
 
716
  chain.memory.load_memory_variables({})
 
791
 
792
  prompt_template = prompt_templates[prompt_template]
793
 
794
+ completion = chain.invoke({"question":prompt})
795
  #chain = load_qa_chain(ChatOpenAI(temperature=temperature, max_tokens=max_tokens, model_name="gpt-3.5-turbo"), chain_type="stuff")
796
  #completion = chain.run(input_documents=docs, question=query)
797