Merge pull request #106 from ValerieRossDEV/main

support other prompt languages in new backend

backend/LANGUAGE_PROMPT.py

@@ -0,0 +1,19 @@
+from langchain.prompts.prompt import PromptTemplate
+
+_template = """Given the following conversation and a follow up question, answer the follow up question in the initial language of the question. If you don't know the answer, just say that you don't know, don't try to make up an answer.
+
+Chat History:
+{chat_history}
+Follow Up Input: {question}
+Standalone question:"""
+CONDENSE_QUESTION_PROMPT = PromptTemplate.from_template(_template)
+
+prompt_template = """Use the following pieces of context to answer the question in the language of the question. If you don't know the answer, just say that you don't know, don't try to make up an answer. 
+
+{context}
+
+Question: {question}
+Helpful Answer:"""
+QA_PROMPT = PromptTemplate(
+    template=prompt_template, input_variables=["context", "question"]
+    )

backend/api.py

@@ -11,6 +11,7 @@ from langchain.llms import OpenAI
 from fastapi.openapi.utils import get_openapi
 from tempfile import SpooledTemporaryFile
 import shutil
+import LANGUAGE_PROMPT
 import pypandoc
 
 from parsers.common import file_already_exists
@@ -73,7 +74,6 @@ class ChatMessage(BaseModel):
 
 
 
-
 file_processors = {
     ".txt": process_txt,
     ".csv": process_csv,
@@ -115,6 +115,10 @@ async def upload_file(file: UploadFile):
 async def chat_endpoint(chat_message: ChatMessage):
     history = chat_message.history
     # Logic from your Streamlit app goes here. For example:
+
+    #this overwrites the built-in prompt of the ConversationalRetrievalChain
+    ConversationalRetrievalChain.prompts = LANGUAGE_PROMPT
+
     qa = None
     if chat_message.model.startswith("gpt"):
         qa = ConversationalRetrievalChain.from_llm(