Inserting format of response and prompt template to request to llm

app.py

@@ -3,6 +3,7 @@ from langchain_openai import OpenAIEmbeddings, ChatOpenAI
 from pinecone import Pinecone
 from langchain.chains import RetrievalQAWithSourcesChain
 from langchain_community.vectorstores import Pinecone as PineconeVec
+from langchain.prompts import PromptTemplate
 import os
 
 openai_key = os.environ['openai_key']
@@ -32,15 +33,39 @@ llm = ChatOpenAI(
     temperature=0.0
 )
 
+#Prompt
+
+PROMPT_TEMPLATE = """ 
+You are called UEAid a first aid assistant helping a normal person to give first aid to some person.
+Give clear instructions step by step for the {question} strictly based on this context {summaries}. 
+Always place in the end: "instructions given by UEAid".
+"""
+
+PROMPT = PromptTemplate(
+    template=PROMPT_TEMPLATE, input_variables=["summaries ", "question"]
+)
+
+chain_type_kwargs = {"prompt": PROMPT}
+
 qa_with_sources = RetrievalQAWithSourcesChain.from_chain_type(
     llm=llm,
     chain_type="stuff",
-    retriever=vectorstore.as_retriever()
+    retriever=vectorstore.as_retriever(),
+    return_source_documents=True,
+    chain_type_kwargs=chain_type_kwargs
 )
 
+def format_response(response):
+    sources_info = ''
+    documents = response['source_documents']
+    for document in documents:
+      sources_info += "document: {}, page: {}\n".format(document.metadata['source'].rsplit("/")[-1], int(document.metadata['page'])) 
+    formated_response = response['answer'] + " Sources:\n" + sources_info
+    return formated_response
+
 def answer_question(query):
-    result = qa_with_sources.invoke(query)
-    return result['answer'] + 'sources: {}'.format(result['sources'])
+    response = qa_with_sources.invoke(query)
+    return format_response(response)
 
 
 iface = gr.Interface(