A package for creating rich, multi-component chat messages in Streamlit
Project description
Streamlit Rich Message History
A Python package for creating rich, multi-component chat messages in Streamlit.
Installation
pip install streamlit-rich-message-history
Basic Usage
import streamlit as st
from streamlit_rich_message_history import MessageHistory, UserMessage, AssistantMessage
# Initialize message history
history = MessageHistory()
# Add a simple user message
history.add_user_message_create("👤", "Hello, I need data analysis help")
# Create a rich assistant response
assistant_msg = AssistantMessage("🤖")
assistant_msg.add_text("I'd be happy to help! Here's a sample dataframe:")
import pandas as pd
import numpy as np
# Create a sample dataframe
df = pd.DataFrame({
'A': np.random.randn(5),
'B': np.random.randn(5),
'C': np.random.randn(5)
})
# Add components to the message
assistant_msg.add_dataframe(df, title="Sample Data")
assistant_msg.add_code("import pandas as pd\ndf = pd.read_csv('data.csv')",
language="python",
title="Loading Data Code")
# Add the message to history
history.add_assistant_message(assistant_msg)
# Render all messages
history.render_all()
Features
- Multi-component chat messages
- Automatic type detection
- Support for various content types:
- Text and Markdown
- DataFrames and Series
- Matplotlib and Plotly figures
- Code blocks with syntax highlighting
- Error messages
- Metrics
- And more!
Documentation
For more examples and detailed documentation, visit our documentation site.
License
MIT
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