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| from __future__ import annotations | |
| import gradio as gr | |
| import pandas as pd | |
| import os | |
| from typing import Optional, Iterable | |
| import sys | |
| from pathlib import Path | |
| from gradio.themes.base import Base | |
| from gradio.themes.utils import colors, fonts, sizes | |
| from augini import Augini | |
| # Create custom dark theme | |
| class AuginiDarkTheme(Base): | |
| def __init__( | |
| self, | |
| *, | |
| primary_hue: colors.Color | str = colors.indigo, | |
| secondary_hue: colors.Color | str = colors.indigo, | |
| neutral_hue: colors.Color | str = colors.gray, | |
| spacing_size: sizes.Size | str = sizes.spacing_md, | |
| radius_size: sizes.Size | str = sizes.radius_lg, | |
| text_size: sizes.Size | str = sizes.text_md, | |
| font: fonts.Font | str | Iterable[fonts.Font | str] = ( | |
| fonts.GoogleFont("Inter"), | |
| "ui-sans-serif", | |
| "sans-serif", | |
| ), | |
| ): | |
| super().__init__( | |
| primary_hue=primary_hue, | |
| secondary_hue=secondary_hue, | |
| neutral_hue=neutral_hue, | |
| spacing_size=spacing_size, | |
| radius_size=radius_size, | |
| text_size=text_size, | |
| font=font, | |
| ) | |
| self.name = "augini_dark" | |
| self.set( | |
| # Dark theme colors | |
| body_background_fill="*neutral_950", | |
| body_text_color="*neutral_200", | |
| background_fill_primary="*neutral_900", | |
| background_fill_secondary="*neutral_800", | |
| border_color_primary="*neutral_700", | |
| # Components | |
| block_background_fill="*neutral_900", | |
| block_border_color="*neutral_700", | |
| block_border_width="1px", | |
| block_label_background_fill="*neutral_900", | |
| block_label_text_color="*neutral_200", | |
| block_title_text_color="*neutral_200", | |
| # Buttons | |
| button_primary_background_fill="*primary_600", | |
| button_primary_background_fill_hover="*primary_500", | |
| button_primary_text_color="white", | |
| button_secondary_background_fill="*neutral_700", | |
| button_secondary_background_fill_hover="*neutral_600", | |
| button_secondary_text_color="*neutral_200", | |
| # Inputs | |
| input_background_fill="*neutral_800", | |
| input_background_fill_focus="*neutral_800", | |
| input_border_color="*neutral_700", | |
| input_border_color_focus="*primary_500", | |
| input_placeholder_color="*neutral_500", | |
| # Shadows and effects | |
| shadow_spread="1px", | |
| block_shadow="0 1px 2px 0 rgb(0 0 0 / 0.05)", | |
| button_shadow="0 1px 2px 0 rgb(0 0 0 / 0.05)", | |
| ) | |
| class AuginiChat: | |
| def __init__(self, model: str, temperature: float = 0.7): | |
| self.df: Optional[pd.DataFrame] = None | |
| self.model = model | |
| self.temperature = temperature | |
| # Initialize Augini with the API key directly | |
| self.augini = Augini( | |
| api_key=os.environ.get('OPENROUTER_TOKEN'), | |
| use_openrouter=True, | |
| model=self.model, | |
| temperature=self.temperature, | |
| max_tokens=1500, | |
| ) | |
| def upload_file(self, file) -> str: | |
| """Handle file upload and return preview""" | |
| try: | |
| if file is None: | |
| return "Please upload a file" | |
| file_path = file.name | |
| file_extension = os.path.splitext(file_path)[1].lower() | |
| # Read the file based on its extension | |
| if file_extension == '.csv': | |
| self.df = pd.read_csv(file_path) | |
| elif file_extension in ['.xlsx', '.xls']: | |
| self.df = pd.read_excel(file_path) | |
| else: | |
| return "❌ Unsupported file format. Please upload a CSV or Excel file." | |
| return "✅ File uploaded successfully!" | |
| except Exception as e: | |
| return f"❌ Error uploading file: {str(e)}" | |
| def chat_with_data(self, message: str, history: list) -> tuple[str, list]: | |
| """Process chat messages and return responses""" | |
| try: | |
| if not message or message.strip() == "": | |
| return "", history | |
| if self.df is None: | |
| return "", history + [(message, "⚠️ Please upload a CSV file first.")] | |
| # Get response from Augini | |
| response = self.augini.chat(message, self.df) | |
| # Update history and clear the message | |
| new_history = history + [(message, response)] | |
| return "", new_history | |
| except Exception as e: | |
| error_msg = f"❌ Error processing message: {str(e)}" | |
| return "", history + [(message, error_msg)] | |
| def update_model_settings(self, model_name: str, temperature: float) -> None: | |
| """Update the model settings and reinitialize Augini.""" | |
| self.model = model_name | |
| self.temperature = temperature | |
| self.augini = Augini( | |
| api_key=os.environ.get('OPENROUTER_TOKEN'), | |
| use_openrouter=True, | |
| model=self.model, | |
| temperature=self.temperature, | |
| ) | |
| def create_app(): | |
| # Initialize the chat handler with default settings | |
| chat_handler = AuginiChat(model='openai/gpt-4o-mini', temperature=0.7) | |
| # JavaScript to force dark theme - added to head | |
| dark_mode_script = """ | |
| <script> | |
| function setDarkTheme() { | |
| const url = new URL(window.location); | |
| if (url.searchParams.get('__theme') !== 'dark') { | |
| url.searchParams.set('__theme', 'dark'); | |
| window.location.href = url.href; | |
| } | |
| } | |
| document.addEventListener('DOMContentLoaded', setDarkTheme); | |
| window.addEventListener('load', setDarkTheme); | |
| // Also try to set it immediately | |
| setDarkTheme(); | |
| </script> | |
| """ | |
| available_models = [ | |
| "mistralai/mistral-nemo", | |
| "meta-llama/llama-3.3-70b-instruct", | |
| "qwen/qwen-2.5-72b-instruct", | |
| "openai/gpt-4o-mini", | |
| "meta-llama/llama-3.2-3b-instruct", | |
| ] | |
| # Create the Gradio interface with dark theme script in head | |
| with gr.Blocks(head=dark_mode_script) as app: | |
| gr.Markdown(""" | |
| # 🤖 **augini** - your tabular AI data analysis assistant | |
| **augini** is an agentic AI system designed to help you analyze and understand your data through natural conversation. | |
| Upload your data file and start chatting to uncover insights! | |
| > 💡 **Tip**: Ask questions about patterns, relationships, or any aspect of your data. **augini** will provide detailed, evidence-based answers. | |
| """, elem_classes=["center-content"]) | |
| with gr.Accordion("⚙️ Model Settings", open=False): | |
| model_dropdown = gr.Dropdown( | |
| label="Select Model", | |
| choices=available_models, | |
| value="openai/gpt-4o-mini" | |
| ) | |
| temperature_slider = gr.Slider( | |
| label="Temperature", | |
| minimum=0.0, | |
| maximum=1.0, | |
| value=0.7, | |
| step=0.05 | |
| ) | |
| def update_settings(model_name, temperature): | |
| chat_handler.update_model_settings(model_name, temperature) | |
| return f"Model settings updated: {model_name}, Temperature: {temperature}" | |
| update_button = gr.Button("Update Model Settings") | |
| update_status = gr.Textbox(label="Update Status", interactive=False) | |
| update_button.click( | |
| update_settings, | |
| inputs=[model_dropdown, temperature_slider], | |
| outputs=[update_status] | |
| ) | |
| with gr.Row(elem_classes=["container"]): | |
| # Left sidebar for file upload | |
| with gr.Column(scale=1, elem_classes=["sidebar"]): | |
| gr.Markdown("### 📁 upload your data") | |
| file_upload = gr.File( | |
| label="Upload Data File", | |
| file_types=[".csv", ".xlsx", ".xls"], | |
| elem_classes=["file-upload"] | |
| ) | |
| file_status = gr.Textbox( | |
| label="Upload Status", | |
| interactive=False, | |
| elem_classes=["status-box"] | |
| ) | |
| # Main chat area | |
| with gr.Column(scale=3, elem_classes=["main-content"]): | |
| chatbot = gr.Chatbot( | |
| label="Chat History", | |
| height=500, | |
| elem_classes=["chat-window"] | |
| ) | |
| with gr.Row(): | |
| msg = gr.Textbox( | |
| label="your question", | |
| placeholder="ask me anything about your data...", | |
| lines=2, | |
| scale=4, | |
| elem_classes=["question-input"] | |
| ) | |
| submit_btn = gr.Button("send 📤", scale=1, elem_classes=["submit-btn"]) | |
| clear = gr.Button("clear chat 🗑️", elem_classes=["clear-btn"]) | |
| # Examples and Documentation in a collapsible section | |
| with gr.Accordion("📚 examples & features", open=False, elem_classes=["docs-section"]): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Markdown(""" | |
| ### 🎯 example questions | |
| **data overview** | |
| - "what are the key patterns in this dataset?" | |
| - "give me a summary of the main statistics" | |
| **data quality** | |
| - "are there any missing values?" | |
| - "how clean is this dataset?" | |
| **relationships** | |
| - "show me the correlations between columns" | |
| - "what variables are most related?" | |
| **deep analysis** | |
| - "what insights can you find about [column]?" | |
| - "is this a synthetic dataset?" | |
| """) | |
| with gr.Column(scale=1): | |
| gr.Markdown(""" | |
| ### ✨ features | |
| **smart analysis** | |
| - advanced statistical analysis | |
| - pattern recognition | |
| - anomaly detection | |
| **data support** | |
| - csv files | |
| - excel files (.xlsx, .xls) | |
| - automatic type detection | |
| **ai capabilities** | |
| - natural language understanding | |
| - context-aware responses | |
| - evidence-based insights | |
| """) | |
| # Add powered by link | |
| gr.Markdown(""" | |
| <div class="powered-by"> | |
| powered by <a href="https://tabularis.ai" target="_blank">tabularis.ai</a> | |
| </div> | |
| """, elem_classes=["footer"]) | |
| # Set up event handlers | |
| file_upload.upload( | |
| chat_handler.upload_file, | |
| inputs=[file_upload], | |
| outputs=[file_status] | |
| ) | |
| # Add both message submission methods | |
| msg.submit( | |
| chat_handler.chat_with_data, | |
| inputs=[msg, chatbot], | |
| outputs=[msg, chatbot] | |
| ) | |
| submit_btn.click( | |
| chat_handler.chat_with_data, | |
| inputs=[msg, chatbot], | |
| outputs=[msg, chatbot] | |
| ) | |
| clear.click(lambda: ([], None), None, [chatbot, msg], queue=False) | |
| return app | |
| if __name__ == "__main__": | |
| app = create_app() | |
| app.launch(share=True) |