Upload 2 files

app.py

@@ -0,0 +1,198 @@
+import gradio as gr
+import requests
+from PIL import Image
+import io
+import os 
+BASE_URL = "https://api.jigsawstack.com/v1"
+headers = {"x-api-key": os.getenv("")}
+
+# ----------------- JigsawStack API Wrappers ------------------
+
+def enhanced_ai_scrape(input_method, url, html, prompts_str, selector, page_pos):
+    def error_response(message):
+        return (
+            message,
+            gr.update(visible=False),
+            gr.update(visible=False),
+            gr.update(visible=False),
+            gr.update(visible=False),
+            gr.update(visible=False),
+        )
+    
+    try:
+        # Validate element prompts
+        prompts = [p.strip() for p in prompts_str.split(",") if p.strip()]
+        if not prompts:
+            return error_response("Error: No element prompts provided.")
+        
+        if len(prompts) > 5:
+            return error_response("Error: Maximum 5 element prompts allowed.")
+
+        payload = {
+            "element_prompts": prompts,
+            "root_element_selector": selector or "main",
+            "page_position": int(page_pos) if str(page_pos).strip().isdigit() else 1
+        }
+
+        # Add URL or HTML based on input method
+        if input_method == "URL":
+            if not url or not url.strip():
+                return error_response("Error: URL is required when using URL input method.")
+            payload["url"] = url.strip()
+        elif input_method == "HTML Content":
+            if not html or not html.strip():
+                return error_response("Error: HTML content is required when using HTML input method.")
+            payload["html"] = html.strip()
+
+        response = requests.post(f"{BASE_URL}/ai/scrape", headers=headers, json=payload)
+        response.raise_for_status()
+
+        result = response.json()
+
+        if not result.get("success"):
+            return error_response(f"Error: Scraping failed - {result.get('message', 'Unknown error')}")
+
+        # Extract all the data
+        context = result.get("context", {})
+        selectors = result.get("selectors", {})
+        data = result.get("data", [])
+        links = result.get("link", [])
+        current_page = result.get("page_position", 1)
+        total_pages = result.get("page_position_length", 1)
+        
+        # Format pagination info
+        pagination_text = f"Page {current_page} of {total_pages}"
+        if total_pages > 1:
+            pagination_text += f" (Total pages available: {total_pages})"
+        
+        status_text = f"✅ Successfully scraped {len(data)} data items"
+        if context:
+            status_text += f" with {len(context)} context elements"
+        
+        return (
+            status_text,
+            gr.update(value=context, visible=True if context else False),
+            gr.update(value=selectors, visible=True if selectors else False),
+            gr.update(value=data, visible=True if data else False),
+            gr.update(value=links, visible=True if links else False),
+            gr.update(value=pagination_text, visible=True),
+        )
+
+    except requests.exceptions.RequestException as req_err:
+        return error_response(f"Request failed: {str(req_err)}")
+    except Exception as e:
+        return error_response(f"Unexpected error: {str(e)}")
+
+# ----------------- Gradio UI ------------------
+
+with gr.Blocks() as demo:
+    gr.Markdown("""
+    <div style='text-align: center; margin-bottom: 24px;'>
+        <h1 style='font-size:2.2em; margin-bottom: 0.2em;'>🧩 JigsawStack AI Scraper</h1>
+        <p style='font-size:1.2em; margin-top: 0;'>Extract structured data from web pages with advanced AI models.</p>
+        <p style='font-size:1em; margin-top: 0.5em;'>For more details and API usage, see the <a href='https://jigsawstack.com/docs/api-reference/ai/scrape' target='_blank'>documentation</a>.</p>
+    </div>
+    """)
+
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("#### Input Method")
+            input_method_scraper = gr.Radio(
+                choices=["URL", "HTML Content"], 
+                label="Choose Input Method", 
+                value="URL"
+            )
+            
+            # Conditional inputs based on selection
+            url_scraper = gr.Textbox(
+                label="Page URL", 
+                placeholder="https://example.com/pricing",
+                info="URL of the page to scrape"
+            )
+            html_content = gr.Textbox(
+                label="HTML Content", 
+                lines=8, 
+                placeholder="<html>...</html>",
+                visible=False,
+                info="Raw HTML content to scrape"
+            )
+            
+            gr.Markdown("#### Scraping Configuration")
+            element_prompts = gr.Textbox(
+                label="Element Prompts (comma-separated)", 
+                lines=3,
+                placeholder="Plan title, Plan price, Features, Button text",
+                info="Items to scrape (max 5). E.g., 'Plan price', 'Plan title'"
+            )
+            
+            root_selector = gr.Textbox(
+                label="Root Element Selector", 
+                value="main",
+                placeholder="main, .container, #content",
+                info="CSS selector to limit scraping scope (default: main)"
+            )
+            
+            page_position = gr.Number(
+                label="Page Position", 
+                value=1,
+                minimum=1,
+                info="For pagination, current page number (min: 1)"
+            )
+
+        with gr.Column():
+            gr.Markdown("#### Results")
+            scrape_status = gr.Textbox(
+                label="Status", 
+                interactive=False,
+                placeholder="Ready to scrape..."
+            )
+            
+            gr.Markdown("#### Extracted Data")
+            context_output = gr.JSON(
+                label="Context Data",
+                visible=False
+            )
+            selectors_output = gr.JSON(
+                label="CSS Selectors Used",
+                visible=False
+            )
+            detailed_data = gr.JSON(
+                label="Detailed Scrape Data",
+                visible=False
+            )
+            links_data = gr.JSON(
+                label="Detected Links",
+                visible=False
+            )
+            
+            gr.Markdown("#### Pagination Info")
+            pagination_info = gr.Textbox(
+                label="Page Information",
+                interactive=False,
+                visible=False
+            )
+
+    scrape_btn = gr.Button("Scrape with AI", variant="primary")
+    
+    # Function to show/hide input groups based on selection
+    def update_scraper_input_visibility(method):
+        if method == "URL":
+            return gr.Textbox(visible=True), gr.Textbox(visible=False)
+        elif method == "HTML Content":
+            return gr.Textbox(visible=False), gr.Textbox(visible=True)
+        else:
+            return gr.Textbox(visible=True), gr.Textbox(visible=False)
+    
+    input_method_scraper.change(
+        update_scraper_input_visibility,
+        inputs=input_method_scraper,
+        outputs=[url_scraper, html_content]
+    )
+    
+    scrape_btn.click(
+        enhanced_ai_scrape,
+        inputs=[input_method_scraper, url_scraper, html_content, element_prompts, root_selector, page_position],
+        outputs=[scrape_status, context_output, selectors_output, detailed_data, links_data, pagination_info]
+    )
+
+demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+requests
+Pillow