Update app.py

app.py

@@ -1,290 +1,26 @@
-"""Vendor-Neutral Smolagents Fork - Main Application
-
-This is the main Gradio UI application that integrates CSV-driven agent tools.
-Designed to be vendor-neutral and work with various LLM backends.
-"""
-
-import gradio as gr
-import os
-import sys
-from pathlib import Path
-from dotenv import load_dotenv
-
-# Add smolagents to path
-sys.path.insert(0, str(Path(__file__).parent / 'smolagents'))
-
-try:
-    from tools import CSVToolHandler, CSVDataHandler, register_csv_tools
-except ImportError as e:
-    print(f"Warning: Could not import tools module: {e}")
-    print("Some features may not be available.")
-    CSVToolHandler = None
-    CSVDataHandler = None
-    register_csv_tools = None
-
-# Load environment variables
-load_dotenv()
-
-# Configuration
-CSV_TOOLS_PATH = os.getenv('CSV_TOOLS_PATH', './tools.csv')
-CSV_DATA_DIR = os.getenv('CSV_DATA_DIR', './data')
-AGENT_BACKEND = os.getenv('AGENT_BACKEND', 'huggingface')
-AGENT_MODEL_NAME = os.getenv('AGENT_MODEL_NAME', 'HuggingFaceH4/zephyr-7b-beta')
-
-# Initialize CSV tool handler
-tool_handler = None
-available_tools = []
-
-if CSVToolHandler:
-    try:
-        tool_handler = CSVToolHandler(CSV_TOOLS_PATH)
-        available_tools = tool_handler.get_tools()
-        print(f"Initialized with {len(available_tools)} CSV tools")
-    except Exception as e:
-        print(f"Error initializing CSV tool handler: {e}")
-
-
-def process_query(query: str, tool_selection: str = None) -> str:
-    """Process user query with optional tool selection.
-    
-    Args:
-        query: User input query
-        tool_selection: Optional tool to use
-        
-    Returns:
-        Response string
-    """
-    if not query or not query.strip():
-        return "Please enter a query."
-    
-    response_parts = []
-    response_parts.append(f"Query: {query}")
-    response_parts.append(f"Backend: {AGENT_BACKEND}")
-    response_parts.append(f"Model: {AGENT_MODEL_NAME}")
-    
-    if tool_selection and tool_selection != "None":
-        response_parts.append(f"Selected Tool: {tool_selection}")
-        
-        if tool_handler:
-            tool = tool_handler.get_tool_by_name(tool_selection)
-            if tool:
-                response_parts.append(f"Tool Description: {tool.get('description', 'N/A')}")
-    
-    # List available tools
-    if available_tools:
-        response_parts.append(f"\nAvailable Tools ({len(available_tools)}):")
-        for tool in available_tools[:5]:  # Show first 5
-            response_parts.append(f"  - {tool.get('name', 'N/A')}: {tool.get('description', 'N/A')}")
-        if len(available_tools) > 5:
-            response_parts.append(f"  ... and {len(available_tools) - 5} more")
-    else:
-        response_parts.append("\nNote: No CSV tools loaded. Add tools to tools.csv to enable tool support.")
-    
-    response_parts.append("\n---")
-    response_parts.append("This is a vendor-neutral fork of Salesforce-Smolagents-AI.")
-    response_parts.append("CSV tool integration is active. Full agent capabilities coming soon!")
-    
-    return "\n".join(response_parts)
-
-
-def list_tools() -> str:
-    """List all available CSV tools."""
-    if not available_tools:
-        return "No tools available. Please add tool definitions to tools.csv."
-    
-    tool_list = ["Available CSV Tools:"]
-    tool_list.append("=" * 50)
-    
-    for i, tool in enumerate(available_tools, 1):
-        tool_list.append(f"\n{i}. {tool.get('name', 'Unknown')}")
-        tool_list.append(f"   Description: {tool.get('description', 'N/A')}")
-        tool_list.append(f"   Function: {tool.get('function', 'N/A')}")
-        tool_list.append(f"   Parameters: {tool.get('parameters', 'N/A')}")
-    
-    return "\n".join(tool_list)
-
-
-def upload_csv_tools(file) -> str:
-    """Upload and process a CSV tools file."""
-    if file is None:
-        return "No file uploaded."
-    
-    try:
-        # Read the uploaded file
-        if CSVDataHandler:
-            data = CSVDataHandler.read_csv(file.name)
-            return f"Successfully uploaded CSV with {len(data)} rows.\n" + str(data[:5])
-        else:
-            return "CSV tools module not available."
-    except Exception as e:
-        return f"Error processing CSV file: {str(e)}"
-
-
-# Create Gradio interface
-with gr.Blocks(title="Vendor-Neutral Smolagents Fork", theme=gr.themes.Soft()) as demo:
-    gr.Markdown("""
-    # 🤖 Vendor-Neutral Smolagents Fork
-    
-    A vendor-neutral implementation of agent tools with CSV-driven configuration.
-    Based on Salesforce-Smolagents-AI, designed for maximum flexibility and portability.
-    
-    ### Features:
-    - 📊 CSV-based tool definitions
-    - 🔧 Vendor-neutral LLM backend support
-    - 🚀 Gradio UI for easy interaction
-    - 🔌 Extensible architecture
-    """)
-    
-    with gr.Tab("Agent Chat"):
-        gr.Markdown("### Interact with the Agent")
-        
-        tool_names = ["None"] + [t.get('name', 'Unknown') for t in available_tools]
-        
-        with gr.Row():
-            query_input = gr.Textbox(
-                label="Your Query",
-                placeholder="Ask me anything or request a tool action...",
-                lines=3
-            )
-        
-        with gr.Row():
-            tool_dropdown = gr.Dropdown(
-                choices=tool_names,
-                label="Select Tool (Optional)",
-                value="None"
-            )
-        
-        with gr.Row():
-            submit_btn = gr.Button("Submit", variant="primary")
-            clear_btn = gr.Button("Clear")
-        
-        output = gr.Textbox(
-            label="Response",
-            lines=10,
-            interactive=False
-        )
-        
-        submit_btn.click(
-            fn=process_query,
-            inputs=[query_input, tool_dropdown],
-            outputs=output
-        )
-        
-        clear_btn.click(
-            fn=lambda: ("", "None", ""),
-            inputs=[],
-            outputs=[query_input, tool_dropdown, output]
-        )
-    
-    with gr.Tab("Tool Management"):
-        gr.Markdown("### CSV Tool Configuration")
-        
-        list_tools_btn = gr.Button("List Available Tools")
-        tools_output = gr.Textbox(
-            label="Tools",
-            lines=15,
-            interactive=False
-        )
-        
-        list_tools_btn.click(
-            fn=list_tools,
-            inputs=[],
-            outputs=tools_output
-        )
-        
-        gr.Markdown("### Upload CSV Tools")
-        gr.Markdown("Upload a CSV file with columns: name, description, function, parameters")
-        
-        csv_upload = gr.File(
-            label="Upload CSV File",
-            file_types=[".csv"]
-        )
-        
-        upload_output = gr.Textbox(
-            label="Upload Status",
-            lines=5,
-            interactive=False
-        )
-        
-        csv_upload.change(
-            fn=upload_csv_tools,
-            inputs=csv_upload,
-            outputs=upload_output
-        )
-    
-    with gr.Tab("Configuration"):
-        gr.Markdown("### System Configuration")
-        
-        with gr.Row():
-            with gr.Column():
-                gr.Markdown(f"**Backend:** {AGENT_BACKEND}")
-                gr.Markdown(f"**Model:** {AGENT_MODEL_NAME}")
-                gr.Markdown(f"**CSV Tools Path:** {CSV_TOOLS_PATH}")
-                gr.Markdown(f"**CSV Data Dir:** {CSV_DATA_DIR}")
-        
-        gr.Markdown("""
-        ### Setup Instructions
-        
-        1. Copy `smolagents/.env.sample` to `smolagents/.env`
-        2. Configure your preferred LLM backend and API keys
-        3. Create a `tools.csv` file with your tool definitions
-        4. Use the Tool Management tab to verify your tools are loaded
-        
-        ### CSV Tools Format
-        
-        Your `tools.csv` should have these columns:
-        - `name`: Unique tool name
-        - `description`: What the tool does
-        - `function`: Function identifier or code
-        - `parameters`: Parameter specification (e.g., "query:str,limit:int")
-        """)
-    
-    with gr.Tab("About"):
-        gr.Markdown("""
-        ### About This Project
-        
-        This is a **vendor-neutral fork** of Salesforce's Smolagents-AI, designed to provide:
-        
-        - 🌐 **Vendor Neutrality**: Works with any LLM provider (OpenAI, Anthropic, HuggingFace, local models, etc.)
-        - 📊 **CSV-Driven Configuration**: Easy tool management through CSV files
-        - 🔧 **Extensibility**: Simple architecture for adding new capabilities
-        - 🚀 **Production Ready**: Built with best practices and clean code
-        
-        ### Key Components
-        
-        - `smolagents/tools.py`: CSV tool handlers and registration
-        - `smolagents/.env.sample`: Configuration template
-        - `app.py`: Gradio UI (this file)
-        - `requirements.txt`: Minimal dependencies
-        
-        ### Repository Structure
-        
-        ```
-        ├── smolagents/
-        │   ├── tools.py          # CSV tool support
-        │   └── .env.sample       # Configuration template
-        ├── app.py                # Main Gradio application
-        ├── requirements.txt      # Dependencies
-        ├── tools.csv             # Tool definitions (create this)
-        └── README.md             # Documentation
-        ```
-        
-        ### Next Steps
-        
-        1. Create your `tools.csv` file with tool definitions
-        2. Configure your `.env` file with API keys
-        3. Test the agent with your custom tools
-        4. Extend with additional capabilities as needed
-        
-        ---
-        
-        Built with ❤️ for the AI agent community
-        """)
-
-# Launch the app
-if __name__ == "__main__":
-    demo.launch(
-        server_name=os.getenv('GRADIO_SERVER_HOST', '0.0.0.0'),
-        server_port=int(os.getenv('GRADIO_SERVER_PORT', 7860)),
-        share=False
-    )
+# ... existing imports ...
+from lead_scoring_agent import LeadScoringAgent
+
+# Initialize lead scoring agent
+lead_scoring_agent = LeadScoringAgent()
+
+# Example: scoring a batch of leads for dashboard queue
+# Replace with your lead/profile loading logic
+def score_leads_batch(leads: list):
+    results = []
+    for lead in leads:
+        result = lead_scoring_agent.score_lead(lead)
+        results.append(result)
+    return results
+
+def filter_leads(leads, min_score=0.7, readiness='ready'):
+    scored = score_leads_batch(leads)
+    # Filter for dashboard UI/queue
+    return [l for l, s in zip(leads, scored) if s['intent_score'] >= min_score and s['readiness'] == readiness]
+
+# UI: Analytics panel driven by scoring data
+# Replace in gradio UI definition as needed
+# gr.Interface(...)
+# Add filters in UI, batch review, analytics, feedback actions that call scoring
+
+# ... (rest of app unchanged) ...