Upload 3 files

app.py

@@ -0,0 +1,121 @@
+import os
+import streamlit as st
+from datetime import datetime
+import json
+import requests
+import uuid
+from datetime import date, datetime
+import requests
+from pydantic import BaseModel, Field
+from typing import Optional
+
+welcomeMessage = "Welcome to the Ford Car Selection AI Agent I am here to talk about your motoring needs, please start by giving me your key requirement"
+
+
+placeHolderPersona1 = """# MISSION
+You are a car sales chatbot focusing on gaining enough information to make a selection. Your mission is to ask questions to help a customer fully articulate their needs in a clear manner.
+When they ask you a question or give you a need ask a suitable follow up question
+
+# RULES
+Ask only one question at a time.
+Provide some context or clarification around the follow-up questions you ask.
+Do not converse with the customer.
+Be as concise as possible"""
+
+placeHolderPersona2 = """# MISSION
+You are a car selection expert you will be given a dialoge between a customer and a sales executive. Your job is to select the perfect car for the customer based on their conversation
+# RULES
+You will need to select 1 primary choice car and one secondary choice car
+You will need to give some justification as to why you have chosen these cars
+Do not converse with the customer.
+Be as concise as possible"""
+
+
+
+class ChatRequestClient(BaseModel):
+    user_id: str
+    user_input: str
+    numberOfQuestions: int
+    welcomeMessage: str
+    llm1: str
+    tokens1: int
+    temperature1: float
+    persona1SystemMessage: str
+    persona2SystemMessage: str
+    userMessage2: str
+    llm2: str
+    tokens2: int
+    temperature2: float
+
+def call_chat_api(data: ChatRequestClient):
+    url = "http://localhost:8000/chat/"
+    # Validate and convert the data to a dictionary
+    validated_data = data.dict()
+    
+    # Make the POST request to the FastAPI server
+    response = requests.post(url, json=validated_data)
+    
+    if response.status_code == 200:
+        return response.json()  # Return the JSON response if successful
+    else:
+        return "An error occured"  # Return the raw response text if not successful
+
+def genuuid ():
+    return uuid.uuid4()
+    
+# Title of the application
+# st.image('agentBuilderLogo.png')
+st.title('LLM-Powered Agent Interaction')
+
+# Sidebar for inputting personas
+st.sidebar.image('agentBuilderLogo.png')
+st.sidebar.header("Agent Personas Design")
+st.sidebar.subheader("Welcome Message")
+welcomeMessage = st.sidebar.text_area("Define Persona 1", value=welcomeMessage, height=150)
+st.sidebar.subheader("Personas 1 Settings")
+numberOfQuestions = st.sidebar.slider("Number of Questions", min_value=0, max_value=2, step=1, value=5, key='persona1_questions')
+persona1SystemMessage = st.sidebar.text_area("Define Persona 1", value=placeHolderPersona1, height=150)
+llm1 = st.sidebar.selectbox("Model Selection", ['GPT-4', 'GPT3.5'], key='persona1_size')
+temp1 = st.sidebar.slider("Tempreature", min_value=0.0, max_value=1.0, step=0.1, value=0.6, key='persona1_temp')
+tokens1 = st.sidebar.slider("Tokens", min_value=0, max_value=4000, step=100, value=500, key='persona1_tokens')
+
+# Persona 2
+st.sidebar.subheader("Personas 2 Settings")
+persona2SystemMessage = st.sidebar.text_area("Define Persona 2", value=placeHolderPersona2, height=150)
+llm2 = st.sidebar.selectbox("Model Selection", ['GPT-4', 'GPT3.5'], key='persona2_size')
+temp2 = st.sidebar.slider("Tempreature", min_value=0.0, max_value=1.0, step=0.1, value=0.5, key='persona2_temp')
+tokens2 = st.sidebar.slider("Tokens", min_value=0, max_value=4000, step=100, value=500, key='persona2_tokens')
+userMessage2 = st.sidebar.text_area("Define User Message", value="This is the conversation todate, ", height=150)
+st.sidebar.caption(f"Session ID: {genuuid()}")
+# Main chat interface
+st.header("Chat with the Agents")
+user_id = st.text_input("User ID:", key="user_id")
+user_input = st.text_input("Write your message here:", key="user_input")
+
+if 'history' not in st.session_state:
+    st.session_state.history = []
+
+if st.button("Send"):
+    # Placeholder for processing the input and generating a response
+    data = ChatRequestClient(
+        user_id=user_id,
+        user_input=user_input,
+        numberOfQuestions=numberOfQuestions,
+        welcomeMessage=welcomeMessage,
+        llm1=llm1,
+        tokens1=tokens1,
+        temperature1=temp1,
+        persona1SystemMessage=persona1SystemMessage,
+        persona2SystemMessage=persona2SystemMessage,
+        userMessage2=userMessage2,
+        llm2=llm2,
+        tokens2=tokens2,
+        temperature2=temp2
+    )
+    response = call_chat_api(data)
+    st.session_state.history.append("You: " + user_input)
+    st.session_state.history.append("Agent: " + response)  # Using 'response' after it's defined
+
+# Display the chat history
+for message in st.session_state.history:
+    st.text(message)

requirements.txt

@@ -0,0 +1,3 @@
+streamlit
+requests
+pydantic