Create app.py

app.py

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+import streamlit as st
+import os
+import chainlit as cl
+from langchain import HuggingFaceHub, PromptTemplate, LLMChain
+
+# Define your AI assistant setup and configurations here
+os.environ['API_KEY'] = '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'
+model_id = 'tiiuae/falcon-7b-instruct'
+falcon_llm = HuggingFaceHub(huggingfacehub_api_token=os.environ['API_KEY'],
+                            repo_id=model_id,
+                            model_kwargs={"temperature": 0.8, "max_new_tokens": 2000})
+template = """
+You are an AI assistant that provides helpful answers to user queries.
+{conversation}
+"""
+
+prompt = PromptTemplate(template=template, input_variables=['conversation'])
+
+falcon_chain = LLMChain(llm=falcon_llm,
+                        prompt=prompt,
+                        verbose=True)
+
+# Define the Streamlit app
+def main():
+    st.title("Mouli's AI Assistant")
+    
+    # Initialize conversation history as a list
+    conversation_history = st.session_state.get("conversation_history", [])
+
+    # Create an input box at the bottom for user's message
+    user_message = st.text_input("Your message:")
+
+    # If the user's message is not empty, process it
+    if user_message:
+        # Add user's message to conversation history
+        conversation_history.append(("User", user_message))
+
+        # Combine conversation history to use as input for the AI assistant
+        conversation_input = "\n".join([f"{author}: {message}" for author, message in conversation_history])
+
+        # Use your AI assistant to generate a response based on the conversation
+        response = falcon_chain.run(conversation_input)
+        
+        # Add AI's response to conversation history
+        conversation_history.append(("AI", response))
+
+        # Store the updated conversation history in session state
+        st.session_state.conversation_history = conversation_history
+
+    # Display the conversation history
+    display_conversation(conversation_history)
+
+def display_conversation(conversation_history):
+    st.markdown("<style>.message-container { display: flex; flex-direction: row; padding: 16px; }</style>", unsafe_allow_html=True)
+    st.markdown("<style>.user-message { align: left; background-color: green; padding: 8px; border-radius: 8px; margin: 4px; }</style>", unsafe_allow_html=True)
+    st.markdown("<style>.ai-message { align: right; background-color: black; padding: 8px; border-radius: 8px; margin: 4px; }</style>", unsafe_allow_html=True)
+    
+    st.markdown("<div class='message-container'>", unsafe_allow_html=True)
+    
+    for author, message in conversation_history:
+        if author == "AI":
+            st.markdown(f"<div class='ai-message'>{message}</div>", unsafe_allow_html=True)
+        else:
+            st.markdown(f"<div class='user-message'>{message}</div>", unsafe_allow_html=True)
+    
+    st.markdown("</div>", unsafe_allow_html=True)
+
+if __name__ == "__main__":
+    main()