chore: commit all local changes

src/sales_assistant/agent_main/tools_node.py

@@ -15,6 +15,8 @@ load_dotenv()
 from ..agent_tools.execute_sql_query import execute_sql_query
 from ..agent_tools.get_exchange_rates import exchange_converter
 from ..agent_tools.create_quote import create_quote
+from ..agent_tools.tavily_search_tool import tavily_search_product_specs
+from ..agent_tools.tavily_web_extract_tool import tavily_extract_product_content
 
 
 class ToolConfig(BaseModel):
@@ -67,7 +69,9 @@ def get_all_tools(config: Optional[ToolConfig] = None) -> List[BaseTool]:
     core_tools = [
         execute_sql_query,
         exchange_converter, 
-        create_quote
+        create_quote,
+        tavily_search_product_specs,
+        tavily_extract_product_content
     ]
     
     # Create registry with validation

src/sales_assistant/agent_tools/tavily_search_tool.py

@@ -0,0 +1,68 @@
+"""
+Tavily Search Tool for finding product specifications and tech information.
+https://python.langchain.com/docs/integrations/tools/tavily_search/
+"""
+import os
+import requests
+from langchain_core.tools import tool
+from pydantic import BaseModel, Field
+from dotenv import load_dotenv
+
+load_dotenv()
+
+class TavilySearchInput(BaseModel):
+    """Input schema for Tavily search tool."""
+    query: str = Field(description="Search query for product specifications, comparisons, or technical details")
+
+@tool(args_schema=TavilySearchInput)
+def tavily_search_product_specs(query: str) -> str:
+    """
+    Search the web for product specifications, comparisons, and technical details.
+    
+    Use this tool when:
+    - User asks for product comparisons
+    - User needs detailed specifications not available in database
+    - User wants latest product information or reviews
+    - User asks to compare products with competitors
+    
+    Focus on tech specification sites, manufacturer websites, and review sites.
+    """
+    try:
+        api_key = os.getenv("TAVILY_API_KEY")
+        if not api_key:
+            return "Error: TAVILY_API_KEY not found in environment variables."
+        
+        # Enhance query for better product spec results
+        enhanced_query = f"product specifications technical details {query}"
+        
+        # Tavily API endpoint
+        url = "https://api.tavily.com/search"
+        
+        payload = {
+            "api_key": api_key,
+            "query": enhanced_query,
+            "search_depth": "advanced",
+            "max_results": 5,
+            "include_answer": True
+        }
+        
+        response = requests.post(url, json=payload)
+        response.raise_for_status()
+        
+        data = response.json()
+        results = data.get("results", [])
+        
+        if not results:
+            return "No search results found for the given query."
+        
+        # Format results for the agent
+        formatted_results = "Web Search Results:\n\n"
+        for i, result in enumerate(results, 1):
+            formatted_results += f"{i}. **{result.get('title', 'No title')}**\n"
+            formatted_results += f"   URL: {result.get('url', 'No URL')}\n"
+            formatted_results += f"   Content: {result.get('content', 'No content')}\n\n"
+        
+        return formatted_results
+        
+    except Exception as e:
+        return f"Error performing search: {str(e)}"

src/sales_assistant/agent_tools/tavily_web_extract_tool.py

@@ -0,0 +1,61 @@
+"""
+Tavily Web Extract Tool for extracting content from product specification pages.
+https://python.langchain.com/docs/integrations/tools/tavily_extract/
+"""
+import os
+import requests
+from langchain_core.tools import tool
+from pydantic import BaseModel, Field
+from dotenv import load_dotenv
+
+load_dotenv()
+
+class TavilyExtractInput(BaseModel):
+    """Input schema for Tavily web extract tool."""
+    url: str = Field(description="URL of the webpage to extract product specifications from")
+
+@tool(args_schema=TavilyExtractInput)
+def tavily_extract_product_content(url: str) -> str:
+    """
+    Extract content from product specification pages and tech review sites.
+    
+    Use this tool when:
+    - You have found relevant URLs from tavily_search_product_specs
+    - User wants detailed content from a specific product page
+    - Need to extract specifications from manufacturer websites
+    - Want to get full content from tech review articles
+    
+    Extracts clean, readable content focused on product specifications.
+    """
+    try:
+        api_key = os.getenv("TAVILY_API_KEY")
+        if not api_key:
+            return "Error: TAVILY_API_KEY not found in environment variables."
+        
+        # Tavily Extract API endpoint
+        extract_url = "https://api.tavily.com/extract"
+        
+        payload = {
+            "api_key": api_key,
+            "urls": [url]
+        }
+        
+        response = requests.post(extract_url, json=payload)
+        response.raise_for_status()
+        
+        data = response.json()
+        results = data.get("results", [])
+        
+        if not results:
+            return f"No content could be extracted from the URL: {url}"
+        
+        # Format extracted content
+        extracted_content = results[0]
+        formatted_content = f"**Extracted Content from: {url}**\n\n"
+        formatted_content += f"**Title:** {extracted_content.get('title', 'No title')}\n\n"
+        formatted_content += f"**Content:**\n{extracted_content.get('raw_content', 'No content available')}\n"
+        
+        return formatted_content
+        
+    except Exception as e:
+        return f"Error extracting content from {url}: {str(e)}"

src/sales_assistant/prompts/system_prompt.py

@@ -38,6 +38,16 @@ Help users explore products in a MySQL database and provide comprehensive sales
 - Use create_quote tool for generating professional quotes with customer information
 - Both tools have detailed descriptions with examples
 
+## Web Search for Product Information (Use Sparingly, Carefully, try to limit to 1, max 2 searches per conversation)
+- Use `tavily_search_product_specs` only when user specifically asks for:
+  * Product comparisons explicitly
+  * Some info is missing from database
+  * Detailed specifications not available in database
+  * Latest product reviews or information
+- Use `tavily_extract_product_content` to get full content from specific URLs found in search (this is the most costly tool, limit usage)
+- **Always prioritize database information first** - only use web search when database lacks needed details or you need to confirm specifics or when you need to compare products
+- Focus searches on tech specification sites and manufacturer websites
+
 <thinking>
 Remember: Your tools already contain detailed descriptions and examples. 
 Focus on reasoning through the user's request and choosing the right tool with appropriate parameters.
@@ -49,6 +59,7 @@ Focus on reasoning through the user's request and choosing the right tool with a
 - or if a user asks for shorter answer you can leave out some of the fields.
 - description can be summarized do not write out what is there use your common senese
 - Use LIMITS in your SQL queries to avoid overwhelming results to use less tokens, if you need more results you can always ask for more.
+- you can use markdown formatting to make the answers more readable e.g for product comparisions you can create a table
 
 ## Different manufacturers categorize differently e.g.:
 - This is why you need to be creative with SQL queries and start broad to look at the categories and sub_categories used by different manufacturers

src/sales_assistant/ui_dashboard/gradio_app.py

@@ -261,6 +261,7 @@ class SalesAssistantChat:
     def get_intermediate_logs(self) -> str:
         """Get console logs for intermediate updates."""
         return self.get_console_logs()
+    
 def create_chat_assistant():
     """Create a new chat assistant instance for a session."""
     return SalesAssistantChat()
@@ -391,28 +392,6 @@ def create_gradio_interface():
                     )
                     send_btn = gr.Button("Send", variant="primary", scale=1)
                 
-                # Console logs section
-                with gr.Accordion("🔍 Console Logs & Processing Info", open=False):
-                    console_display = gr.Textbox(
-                        value="Console logs will appear here...",
-                        label="Real-time Processing Logs",
-                        lines=20,
-                        max_lines=30,
-                        interactive=False,
-                        elem_classes=["console-logs"],
-                        show_copy_button=True,
-                        autoscroll=True
-                    )
-                    
-                    with gr.Row():
-                        refresh_logs_btn = gr.Button("🔄 Refresh Logs", variant="secondary", scale=1)
-                        clear_logs_btn = gr.Button("🗑️ Clear Logs", variant="secondary", scale=1)
-                        auto_refresh_checkbox = gr.Checkbox(
-                            label="Auto-refresh logs (every 2 seconds)",
-                            value=False,
-                            scale=1
-                        )
-                
                 # Example queries
                 with gr.Row():
                     gr.Examples(
@@ -428,6 +407,28 @@ def create_gradio_interface():
                         inputs=msg_input,
                         label="Example Questions"
                     )
+
+                # Console logs section
+                with gr.Accordion("🔍 Console Logs & Processing Info", open=False):
+                        console_display = gr.Textbox(
+                            value="Console logs will appear here...",
+                            label="Real-time Processing Logs",
+                            lines=20,
+                            max_lines=30,
+                            interactive=False,
+                            elem_classes=["console-logs"],
+                            show_copy_button=True,
+                            autoscroll=True
+                )
+                    
+                with gr.Row():
+                        refresh_logs_btn = gr.Button("🔄 Refresh Logs", variant="secondary", scale=1)
+                        clear_logs_btn = gr.Button("🗑️ Clear Logs", variant="secondary", scale=1)
+                        auto_refresh_checkbox = gr.Checkbox(
+                            label="Auto-refresh logs (every 2 seconds)",
+                            value=False,
+                            scale=1
+                )
             
             # Generated Quotes Tab
             with gr.TabItem("📄 Generated Quotes", id="quotes_tab"):