global variable

.gitignore

@@ -0,0 +1,8 @@
+data/*
+./idea
+.DS_Store
+*/.DS_Store
+.idea/
+*/__pycache__/*
+*/*/__pycache__/*
+__pycache__/

app.py

@@ -25,7 +25,7 @@ from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 API_URL = "https://api.openai.com/v1/chat/completions"
 cohere_key = '5IRbILAbjTI0VcqTsktBfKsr13Lych9iBAFbLpkj'
 faiss_store = './output/'
-global doc_search
+docsearch = None
 
 
 def process(files, openai_api_key, max_tokens, n_sample):
@@ -64,8 +64,6 @@ def get_question(docs, openai_api_key, max_tokens, n_sample=5):
 
 def get_summary(docs, openai_api_key, max_tokens, n_sample=5, verbose=None):
     llm = ChatOpenAI(openai_api_key=openai_api_key, max_tokens=max_tokens)
-    # chain = load_summarize_chain(llm, chain_type="map_reduce")
-    # summary = chain.run(docs[:n_sample])
     print('Generating Summary from template')
     map_prompt = PromptTemplate(template=MyTemplate['summary_template'], input_variables=["text"])
     combine_prompt = PromptTemplate(template=MyTemplate['summary_template'], input_variables=["text"])
@@ -89,12 +87,13 @@ def get_summary(docs, openai_api_key, max_tokens, n_sample=5, verbose=None):
 
 
 def predict(inputs, openai_api_key, max_tokens, chat_counter, chatbot=[], history=[]):
+    global docsearch
     print(f"chat_counter - {chat_counter}")
     print(f'Histroy - {history}')  # History: Original Input and Output in flatten list
     print(f'chatbot - {chatbot}')  # Chat Bot： 上一轮回复的[[user, AI]]
 
     history.append(inputs)
-    if doc_search is None:
+    if docsearch is None:
         print(f'loading faiss store from {faiss_store}')
         docsearch = FAISS.load_local(faiss_store, OpenAIEmbeddings(openai_api_key=openai_api_key))
     else:

prompts/qa_sys_prompt.txt

@@ -1,5 +1,5 @@
 You are a smart assistant designed to help high school teachers come up with reading comprehension questions.
-Given a piece of text, you must come up with a question and answer in finance area, relevant to economy, politic, finance market, corporate finance, etc.
+Given a piece of text, you must come up with a question and answer in finance-related area, including but not limited to economics, politics, financial markets, corporate finance, etc.
 When coming up with this question/answer pair, you must respond in the following format, and always respond in chinese:
 ```
 {{

prompts/summary_prompt.txt

@@ -1,4 +1,4 @@
-Write a concise summary of the following in chinese, ignore the content in footnote, appendix or sidebar:
+Write a concise summary of the following in chinese:
 
 
 "{text}"