feat:Add streamlit+groq+llama3 to build use case of simple chatbot

example/streamlit-groq-llama3-chatbot/README.md

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+# Build a mathematical chatbot using streamlit and pne
+
+The `app.py` is an example of building a mathematical chatbot using streamlit、groq and llama3.
+
+# Quick Start
+
+1. Clone the repository and install the dependencies
+
+```shell
+git clone https://www.github.com/Undertone0809/promptulate
+```
+
+2. Switch the current directory to the example
+
+```shell
+cd ./example/streamlit-groq-llama3-chatbot
+```
+
+3. Install the dependencies
+
+```shell
+pip install -r requirements.txt
+```
+
+4. Run the application
+
+```shell
+streamlit run app.py
+```

example/streamlit-groq-llama3-chatbot/app.py

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+import streamlit as st
+
+import promptulate as pne
+
+# Create a sidebar to place the user parameter configuration
+with st.sidebar:
+    groq_api_key = st.text_input("Groq API Key", key="chatbot_api_key", type="password")
+
+# Set title
+st.title("💬 Chat")
+st.caption("🚀 Hi there! 👋 I am a simple chatbot by groq and llama3 to help you ")
+
+# Determine whether to initialize the message variable
+# otherwise initialize a message dictionary
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [
+        {"role": "assistant", "content": "How can I help you?"}
+    ]
+
+# Traverse messages in session state
+for msg in st.session_state.messages:
+    st.chat_message(msg["role"]).write(msg["content"])
+
+# User input
+if prompt := st.chat_input():
+    if not groq_api_key:
+        st.info("Please add your Groq API key to continue.")
+        st.stop()
+
+    # Add the message entered by the user to the list of messages in the session state
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    # Display in the chat interface
+    st.chat_message("user").write(prompt)
+
+    response: str = pne.chat(
+        model="groq/llama3-8b-8192",
+        messages=prompt,
+        model_config={"api_key": groq_api_key},
+    )
+
+    st.session_state.messages.append({"role": "assistant", "content": response})
+    st.chat_message("assistant").write(response)

example/streamlit-groq-llama3-chatbot/requirements.txt

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+streamlit>=1.28
+promptulate
+groq