Update agent notebook, requirements

Author: titipata

agents/README.md

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+## Agent Example
+
+In `app.py`, we give an example how to create an agent to sell Khao Man Kai (Chicken with rice) using [Autogen](https://github.com/microsoft/autogen).
+You can run a web application using Streamlit as follows:
+
+```sh
+streamlit run app.py
+```

agents/app.py

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+import streamlit as st
+import autogen
+from autogen import AssistantAgent, UserProxyAgent
+
+def create_agents():
+    config_list = [
+        {
+            'model': 'gpt-4o',
+            'api_key': ''
+        }
+    ]
+    assistant = autogen.AssistantAgent(
+        name="ChickenRiceAssistant",
+        llm_config={
+            "config_list": config_list,
+            "temperature": 0.7,
+        },
+        system_message="""You are a friendly Thai-speaking chatbot for a chicken rice restaurant name ข้าวมันไก่ชาตรี. Your task is to greet customers, take their orders, summarize the order, and provide the total bill. Here's the menu:
+
+    ข้าวมันไก่ (Chicken with rice): 65 บาท
+    ไก่สับ (Chopped chicken): 200 บาท
+    ไก่สับจานใหญ่ (Large chopped chicken): 250 บาท
+
+    Follow these steps:
+    1. Greet the customer in Thai and ask for their order.
+    2. Take the order, confirming each item and its quantity.
+    3. If the customer asks for something not on the menu, politely inform them it's not available and suggest menu items.
+    4. When the order is complete e.g. user confirm the order, summarize the order and provide the total bill.
+    5. Thank the customer and ask if there's anything else they need.
+
+    Always respond in Thai, be polite, and maintain a friendly tone. If you're unsure about anything, ask for clarification.
+    Maintain context throughout the conversation and don't restart the order process unless explicitly told to do so."""
+    )
+
+    user_proxy = UserProxyAgent(
+        name="Customer",
+        human_input_mode="NEVER",
+        max_consecutive_auto_reply=0,
+        code_execution_config={"work_dir": "coding", "use_docker": False},
+    )
+    return assistant, user_proxy
+
+
+st.title("ร้านข้าวมันไก่ชาตรี - แชทบอทสั่งอาหาร")
+
+# Initialize agents
+if "assistant" not in st.session_state:
+    st.session_state.assistant, st.session_state.user_proxy = create_agents()
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = [
+        {"role": "assistant", "content": "ข้าวมันไก่ชาตรีสวัสดีครับ วันนี้ต้องการสั่งอะไรบ้างครับ"}
+    ]
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Accept user input
+if prompt := st.chat_input("พิมพ์ข้อความของคุณที่นี่..."):
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+    
+    # Generate assistant response
+    response = st.session_state.user_proxy.initiate_chat(
+            st.session_state.assistant,
+            message=prompt
+    )
+    assistant_response = st.session_state.assistant.last_message()["content"]
+    
+    with st.chat_message("assistant"):
+        st.markdown(assistant_response)
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": assistant_response})
+
+
+# Add a button to clear the chat history
+if st.button("เริ่มการสนทนาใหม่"):
+    st.session_state.messages = []
+    st.experimental_rerun()

requirements.txt

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+langchain
+langchain_community
+transformers
+attacut
+ssg
+datasets
+pyarrow==15.0.2
+pydub
+ipywebrtc
+openai
+yt-dlp
+gradio==3.44.3
+streamlit