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from datetime import datetime
from Obnoxious_Agent import Obnoxious_Agent
from Relevant_Documents_Agent import Relevant_Documents_Agent
from Query_Agent import Query_Agent
from Answering_Agent import Answering_Agent
from datetime import datetime
from langchain.document_loaders import UnstructuredPDFLoader, OnlinePDFLoader
import streamlit as st
from openai import OpenAI
from Head_Agent import Head_Agent
st.title("Mini Project 2: Streamlit Chatbot")
# TODO: Replace with your actual OpenAI API key
client = OpenAI(api_key='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')
# Define a function to get the conversation history (Not required for Part-2, will be useful in Part-3)
def get_conversation():
# ... (code for getting conversation history)
history_conversation = []
for message in st.session_state.messages:
if message["sender"] == "user":
cur_map = dict()
cur_map['role']= "user"
cur_map['content'] = message['content']
history_conversation.append(cur_map)
elif message["sender"] == "assistant":
cur_map = dict()
cur_map['role'] = "assistant"
cur_map['content'] = message['content']
history_conversation.append(cur_map)
return history_conversation
def display_all_chat_messages():
for message in st.session_state.messages:
# st.text_area("", value=message["content"], key=message["sender"] + str(message["id"]))
if message["sender"] == "user":
with st.chat_message("user"): # 显示avatar
st.container().markdown(f"**You [{message['timestamp']}]:** {message['content']}")
elif message["sender"] == "assistant":
with st.chat_message("assistant"): # 显示avatar
st.container().markdown(f"**Assistant [{message['timestamp']}]:** {message['content']}")
# Initialize the Head Agent with necessary parameters
if 'head_agent' not in st.session_state:
openai_key = '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'
pinecone_key = "52ef9136-6188-4e51-af13-9639bf95c163"
pinecone_index_name = "ee596llm-project2"
st.session_state.head_agent = Head_Agent(openai_key, pinecone_key, pinecone_index_name)
# Your existing code for handling user input and displaying messages
# Replace the direct call to `get_completion` with `st.session_state.head_agent.process_query(prompt)`
# Example:
if prompt := st.chat_input("What would you like to chat about?"):
try:
if "messages" not in st.session_state:
st.session_state.messages = []
message_id = len(st.session_state.messages)
current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
user_message = {"id": message_id, "sender": "user", "content": prompt, "timestamp": current_time}
st.session_state.messages.append(user_message)
# Instantiate the Obnoxious Agent
obnoxious_agent = Obnoxious_Agent()
is_obnoxious = obnoxious_agent.check_query(prompt)
# Respond based on the check
if is_obnoxious:
response = "Yes"
else:
response = "No"
# You can then display this response to the user or use it as part of your application logic
is_obnoxious_response = "Is the query obnoxious? " + response
# st.write("Is the query obnoxious? " + response)
# display_message(user_message)
except Exception as e:
st.error("Failed to process your message. Please try again.")
# ... (display user message in the chat interface)
# display_message(user_message) # Use the display_message function to show the user's message
# Generate AI response
# with st.chat_message("assistant"): 删除掉 chat聊天框 不能嵌套
# ... (send request to OpenAI API)
# ... (get AI response and display it)
ai_response = st.session_state.head_agent.process_query(prompt, get_conversation())
# ... (append AI response to messages)
ai_message = {"id": len(st.session_state.messages), "sender": "assistant", "content": ai_response,
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
st.session_state.messages.append(ai_message)
print(ai_message)
# display_message(ai_message)
display_all_chat_messages()
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