improvements

code/main.py

@@ -96,7 +96,7 @@ async def start():
     model = config["llm_params"]["local_llm_params"]["model"]
     msg = cl.Message(content=f"Starting the bot {model}...")
     await msg.send()
-    msg.content = f"Hey, What Can I Help You With?\n\nYou can me ask me questions about the course logistics, course content, about the final project, or anything else! You can find me at {model}"
+    msg.content = f"Hey, What Can I Help You With?\n\nYou can me ask me questions about the course logistics, course content, about the final project, or anything else!"
     await msg.update()
 
     cl.user_session.set("chain", chain)

code/modules/constants.py

@@ -10,17 +10,17 @@ OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
 # Prompt Templates
 
-# prompt_template = """Use the following pieces of information to answer the user's question.
-# If you don't know the answer, just say that you don't know.
+openai_prompt_template = """Use the following pieces of information to answer the user's question.
+If you don't know the answer, just say that you don't know.
 
-# Context: {context}
-# Question: {question}
+Context: {context}
+Question: {question}
 
-# Only return the helpful answer below and nothing else.
-# Helpful answer:
-# """
+Only return the helpful answer below and nothing else.
+Helpful answer:
+"""
 
-prompt_template_with_history = """Use the following pieces of information to answer the user's question.
+openai_prompt_template_with_history = """Use the following pieces of information to answer the user's question.
 If you don't know the answer, just say that you don't know, don't try to make up an answer.
 Use the history to answer the question if you can.
 Chat History:
@@ -32,10 +32,31 @@ Only return the helpful answer below and nothing else.
 Helpful answer:
 """
 
-prompt_template = """
+tinyllama_prompt_template = """
+<|im_start|>system
+Assistant is an intelligent chatbot designed to help students with questions regarding the course. Only answer questions using the context below and if you're not sure of an answer, you can say "I don't know". Always give a breif and concise answer to the question. Use the history to answer the question if you can.
+
+Context:
+{context}
+<|im_end|>
+<|im_start|>user
+Question: Who is the instructor for this course?
+<|im_end|>
+<|im_start|>assistant
+The instructor for this course is Prof. Thomas Gardos.
+<|im_end|>
+<|im_start|>user
+Question: {question}
+<|im_end|>
+<|im_start|>assistant
+"""
+
+tinyllama_prompt_template_with_history = """
 <|im_start|>system
 Assistant is an intelligent chatbot designed to help students with questions regarding the course. Only answer questions using the context below and if you're not sure of an answer, you can say "I don't know". Always give a breif and concise answer to the question.
 
+Chat History:
+{chat_history}
 Context:
 {context}
 <|im_end|>
@@ -51,6 +72,7 @@ Question: {question}
 <|im_start|>assistant
 """
 
+
 # Model Paths
 
 LLAMA_PATH = "storage/models/tinyllama-1.1b-chat-v1.0.Q5_K_M.gguf"

code/modules/helpers.py

@@ -3,6 +3,8 @@ from bs4 import BeautifulSoup
 from tqdm import tqdm
 from urllib.parse import urlparse
 import chainlit as cl
+from langchain import PromptTemplate
+from modules.constants import *
 
 """
 Ref: https://python.plainenglish.io/scraping-the-subpages-on-a-website-ea2d4e3db113
@@ -95,6 +97,30 @@ def get_base_url(url):
     base_url = f"{parsed_url.scheme}://{parsed_url.netloc}/"
     return base_url
 
+def get_prompt(config):
+    if config["llm_params"]["use_history"]:
+        if config["llm_params"]["llm_loader"] == "local_llm":
+            custom_prompt_template = tinyllama_prompt_template_with_history
+        elif config["llm_params"]["llm_loader"] == "openai":
+            custom_prompt_template = openai_prompt_template_with_history
+        # else:
+        #     custom_prompt_template = tinyllama_prompt_template_with_history # default
+        prompt = PromptTemplate(
+            template=custom_prompt_template,
+            input_variables=["context", "chat_history", "question"],
+        )
+    else:
+        if config["llm_params"]["llm_loader"] == "local_llm":
+            custom_prompt_template = tinyllama_prompt_template
+        elif config["llm_params"]["llm_loader"] == "openai":
+            custom_prompt_template = openai_prompt_template
+        # else:
+        #     custom_prompt_template = tinyllama_prompt_template
+        prompt = PromptTemplate(
+            template=custom_prompt_template,
+            input_variables=["context", "question"],
+        )
+    return prompt
 
 def get_sources(res, answer):
     source_elements_dict = {}

code/modules/llm_tutor.py

@@ -10,6 +10,7 @@ from langchain.chains.conversational_retrieval.prompts import QA_PROMPT
 import os
 
 from modules.constants import *
+from modules.helpers import get_prompt
 from modules.chat_model_loader import ChatModelLoader
 from modules.vector_db import VectorDB
 
@@ -26,14 +27,7 @@ class LLMTutor:
         """
         Prompt template for QA retrieval for each vectorstore
         """
-        if self.config["llm_params"]["use_history"]:
-            custom_prompt_template = prompt_template_with_history
-        else:
-            custom_prompt_template = prompt_template
-        prompt = PromptTemplate(
-            template=custom_prompt_template,
-            input_variables=["context", "chat_history", "question"],
-        )
+        prompt = get_prompt(self.config)
         # prompt = QA_PROMPT
 
         return prompt