Create app.py

app.py

@@ -0,0 +1,271 @@
+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):
+        self.df: Optional[pd.DataFrame] = None
+        # Initialize Augini with the API key directly
+        self.augini = Augini(
+            api_key=os.environ.get('OPENROUTER_TOKEN'),
+            use_openrouter=True,
+            model='gpt-4o-mini',
+            temperature=0.7
+        )
+    
+    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 create_app():
+    # Initialize the chat handler
+    chat_handler = AuginiChat()
+    
+    # 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>
+    """
+    
+    # Create the Gradio interface with dark theme script in head
+    with gr.Blocks(head=dark_mode_script) as app:
+        gr.Markdown("""
+        # 🤖 **augini** - your 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.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)