remove commented blocks; fix parameter names

langchain-streamlit-demo/app.py

@@ -323,7 +323,7 @@ with sidebar:
 if provider_api_key:
  if st.session_state.provider == "OpenAI":
  st.session_state.llm = ChatOpenAI(
- model=model,
+ model_name="test",
  openai_api_key=provider_api_key,
  temperature=temperature,
  streaming=True,
@@ -331,7 +331,7 @@ if provider_api_key:
  )
  elif st.session_state.provider == "Anthropic":
  st.session_state.llm = ChatAnthropic(
- model_name=model,
+ model=model,
  anthropic_api_key=provider_api_key,
  temperature=temperature,
  streaming=True,
@@ -339,7 +339,7 @@ if provider_api_key:
  )
  elif st.session_state.provider == "Anyscale Endpoints":
  st.session_state.llm = ChatAnyscale(
- model=model,
+ model_name=model,
  anyscale_api_key=provider_api_key,
  temperature=temperature,
  streaming=True,
@@ -365,7 +365,6 @@ if st.session_state.llm:
  if document_chat_chain_type == "Summarization":
  st.session_state.doc_chain = "summarization"
  elif document_chat_chain_type == "Q&A Generation":
- # st.session_state.doc_chain = get_qa_gen_chain(st.session_state.llm)
  st.session_state.doc_chain = get_rag_qa_gen_chain(
  st.session_state.retriever,
  st.session_state.llm,
@@ -440,16 +439,7 @@ if st.session_state.llm:
  )
  if st.session_state.provider == "Anthropic":
  config["max_concurrency"] = 5
- # raw_results = st.session_state.doc_chain.batch(
- # [
- # {"context": doc.page_content, "prompt": prompt}
- # for doc in st.session_state.texts
- # ],
- # config,
- # )
  raw_results = st.session_state.doc_chain.invoke(prompt, config)
- # print(raw_results)
- # results = combine_qa_pair_lists(raw_results).QuestionAnswerPairs
  results = raw_results.QuestionAnswerPairs
 
  def _to_str(idx, qap):

langchain-streamlit-demo/qagen.py

@@ -64,12 +64,6 @@ def combine_qa_pair_lists(
  )
 
 
-# def get_qa_gen_chain(llm: BaseLanguageModel) -> RunnableSequence:
-# return (
-# CHAT_PROMPT | llm | OutputFixingParser.from_llm(llm=llm, parser=PYDANTIC_PARSER)
-# )
-
-
 def get_rag_qa_gen_chain(
  retriever: BaseRetriever,
  llm: BaseLanguageModel,