add prompt and add chain_type_kwargs on `load_retriever`

app.py

@@ -23,9 +23,33 @@ from langchain.embeddings import HuggingFaceInstructEmbeddings
 from langchain import HuggingFacePipeline
 from langchain.chains import RetrievalQA
 
+from langchain.prompts import PromptTemplate
 
 
 
+
+prompt_template = """
+
+You are the chatbot and the face of Asian Institute of Technology (AIT). Your job is to give answers to prospective and current students about the school.
+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.
+Always make sure to be elaborate. And try to use vibrant, positive tone to represent good branding of the school.
+Never answer with any unfinished response.
+
+{context}
+
+Question: {question}
+
+Always make sure to elaborate your response and use vibrant, positive tone to represent good branding of the school.
+Never answer with any unfinished response.
+
+
+"""
+PROMPT = PromptTemplate(
+    template=prompt_template, input_variables=["context", "question"]
+)
+chain_type_kwargs = {"prompt": PROMPT}
+
+
 st.set_page_config(
     page_title = 'aitGPT',
     page_icon = '✅')
@@ -80,7 +104,8 @@ def load_llm_model():
 
 def load_retriever(llm, db):
     qa_retriever = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff",
-                            retriever=db.as_retriever())
+                            retriever=db.as_retriever(),
+                            chain_type_kwargs= chain_type_kwargs)
 
     return qa_retriever