Merge pull request #324 from imjwang/chat-history-buffer

Adding Conversation History

run_localGPT.py

@@ -7,6 +7,8 @@
 from langchain.chains import RetrievalQA
 from langchain.embeddings import HuggingFaceInstructEmbeddings
 from langchain.llms import HuggingFacePipeline, LlamaCpp
+from langchain.memory import ConversationBufferMemory
+from langchain.prompts import PromptTemplate
 
 # from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
 from langchain.vectorstores import Chroma
@@ -224,9 +226,27 @@ def main(device_type, show_sources):
  model_id = "TheBloke/Llama-2-7B-Chat-GGML"
  model_basename = "llama-2-7b-chat.ggmlv3.q4_0.bin"
 
+ template = """Use the following pieces of context to answer the question at the end. If you don't know the answer,\
+just say that you don't know, don't try to make up an answer.
+
+{context}
+
+{history}
+Question: {question}
+Helpful Answer:"""
+
+ prompt = PromptTemplate(input_variables=["history", "context", "question"], template=template)
+ memory = ConversationBufferMemory(input_key="question", memory_key="history")
+
  llm = load_model(device_type, model_id=model_id, model_basename=model_basename)
 
- qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True)
+ qa = RetrievalQA.from_chain_type(
+ llm=llm,
+ chain_type="stuff",
+ retriever=retriever,
+ return_source_documents=True,
+ chain_type_kwargs={"prompt": prompt, "memory": memory},
+ )
  # Interactive questions and answers
  while True:
  query = input("\nEnter a query: ")