rohan13 commited on
Commit
789c315
·
1 Parent(s): 9294be1

reducing chat window

Browse files
Files changed (1) hide show
  1. utils.py +4 -3
utils.py CHANGED
@@ -41,7 +41,7 @@ message_history = CustomMongoDBChatMessageHistory(
41
  collection_name='3d_printing_applications'
42
  )
43
 
44
- memory = ConversationBufferWindowMemory(memory_key="chat_history", k=10)
45
 
46
  vectorstore_index = None
47
 
@@ -193,7 +193,7 @@ def get_qa_chain(vectorstore_index):
193
  # embeddings_filter = EmbeddingsFilter(embeddings=embeddings, similarity_threshold=0.76)
194
  # compression_retriever = ContextualCompressionRetriever(base_compressor=embeddings_filter, base_retriever=gpt_3_5_index.as_retriever())
195
  retriever = vectorstore_index.as_retriever(search_type="similarity_score_threshold",
196
- search_kwargs={"score_threshold": .5})
197
 
198
  chain = ConversationalRetrievalChain.from_llm(llm, retriever, return_source_documents=True,
199
  verbose=True, get_chat_history=get_chat_history,
@@ -211,7 +211,8 @@ def get_chat_history(inputs) -> str:
211
  def generate_answer(question) -> str:
212
  global vectorstore_index
213
  chain = get_qa_chain(vectorstore_index)
214
- history = memory.chat_memory.messages
 
215
  result = chain(
216
  {"question": question, "chat_history": history})
217
 
 
41
  collection_name='3d_printing_applications'
42
  )
43
 
44
+ memory = ConversationBufferWindowMemory(memory_key="chat_history", k=4)
45
 
46
  vectorstore_index = None
47
 
 
193
  # embeddings_filter = EmbeddingsFilter(embeddings=embeddings, similarity_threshold=0.76)
194
  # compression_retriever = ContextualCompressionRetriever(base_compressor=embeddings_filter, base_retriever=gpt_3_5_index.as_retriever())
195
  retriever = vectorstore_index.as_retriever(search_type="similarity_score_threshold",
196
+ search_kwargs={"score_threshold": .76})
197
 
198
  chain = ConversationalRetrievalChain.from_llm(llm, retriever, return_source_documents=True,
199
  verbose=True, get_chat_history=get_chat_history,
 
211
  def generate_answer(question) -> str:
212
  global vectorstore_index
213
  chain = get_qa_chain(vectorstore_index)
214
+ # get last 4 messages from chat history
215
+ history = memory.chat_memory.messages[-4:]
216
  result = chain(
217
  {"question": question, "chat_history": history})
218