Update app.py

app.py

@@ -1,21 +1,15 @@
-""" Chatbot X"
-@author: Davis Ogega
-@email: ogegadavis23@gmail.com
+""" Simple Chatbot
+@author: Nigel Gebodh
+@email: nigel.gebodh@gmail.com
 """
 
 import streamlit as st
-from openai import OpenAI
 import os
-from dotenv import load_dotenv
+import requests
+import json
 
 load_dotenv()
 
-# Initialize the client
-client = OpenAI(
-  base_url="https://api-inference.huggingface.co/v1",
-  api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')
-)
-
 def reset_conversation():
     '''
     Resets Conversation
@@ -33,20 +27,24 @@ model_info = {
         'description': """The Mistral model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
                          \nIt was created by the [**Mistral AI**](https://mistral.ai/news/announcing-mistral-7b/) team as has over  **7 billion parameters.** \n""",
         'logo': 'https://mistral.ai/images/logo_hubc88c4ece131b91c7cb753f40e9e1cc5_2589_256x0_resize_q97_h2_lanczos_3.webp'
+    },
+    "BibleLearnerAI": {
+        'description': """You're now chatting with **BibleLearnerAI**. This AI is focused on religion, specifically Christianity, and provides relevant Bible verses. When greeted, it responds with a religious greeting and introduces itself. It knows the Bible more than anything else.""",
+        'logo': 'https://your-bible-teacher.com/wp-content/uploads/2019/03/teacher-300x300.png'
     }
 }
 
-# Create model description for Mistral
-st.sidebar.write("You're now chatting with **Mistral**")
-st.sidebar.markdown(model_info["Mistral"]['description'])
-st.sidebar.image(model_info["Mistral"]['logo'])
+# Create model description for selected model
+selected_model = st.sidebar.selectbox("Select Model", ["Mistral", "BibleLearnerAI"])
+
+# Create model description for selected model
+st.sidebar.write(f"You're now chatting with **{selected_model}**")
+st.sidebar.markdown(model_info[selected_model]['description'])
+st.sidebar.image(model_info[selected_model]['logo'])
 st.sidebar.markdown("*Generated content may be inaccurate or false.*")
 st.sidebar.markdown("\nLearn how to build this chatbot [here](https://ngebodh.github.io/projects/2024-03-05/).")
 st.sidebar.markdown("\nRun into issues? Try the [back-up](https://huggingface.co/spaces/ngebodh/SimpleChatbot-Backup).")
 
-# If model is not already selected, set it to Mistral
-selected_model = "Mistral"
-
 # Initialize chat history
 if "messages" not in st.session_state:
     st.session_state.messages = []
@@ -56,6 +54,18 @@ for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
+# Pre-instructions for addiction recovery
+pre_instructions = "Welcome to the Addiction Recovery AI. I'm here to help you recover from your worst addictions. Feel free to ask me anything related to your recovery journey."
+
+# Pre-instructions for BibleLearnerAI
+pre_instructions_bible = "Welcome to BibleLearnerAI. I'm here to assist you in learning more about the Bible and Christianity. Feel free to ask me anything related to religion and spirituality."
+
+# Add pre-instructions to chat history based on the selected model
+if selected_model == "Mistral":
+    st.session_state.messages.append({"role": "assistant", "content": pre_instructions})
+elif selected_model == "BibleLearnerAI":
+    st.session_state.messages.append({"role": "assistant", "content": pre_instructions_bible})
+
 # Accept user input
 if prompt := st.chat_input(f"Hi, I'm {selected_model}, ask me a question"):
     # Display user message in chat message container
@@ -66,16 +76,13 @@ if prompt := st.chat_input(f"Hi, I'm {selected_model}, ask me a question"):
 
     # Display assistant response in chat message container
     with st.chat_message("assistant"):
-        stream = client.chat.completions.create(
-            model="mistralai/Mistral-7B-Instruct-v0.2",
-            messages=[
-                {"role": m["role"], "content": m["content"]}
-                for m in st.session_state.messages
-            ],
-            temperature=0.5,
-            stream=True,
-            max_tokens=1000,
-        )
+        # Call the appropriate model based on the selected_model
+        if selected_model == "Mistral":
+            # Code to call Mistral model
+            pass
+        elif selected_model == "BibleLearnerAI":
+            stream = get_streamed_response(prompt, [(prompt, pre_instructions_bible)])
+            for response in stream:
+                st.write(response)
 
-        response = st.write_stream(stream)
     st.session_state.messages.append({"role": "assistant", "content": response})