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README.md

@@ -1,13 +1,24 @@
 ---
-title: VOCR
-emoji: 🏃
-colorFrom: gray
-colorTo: red
+title: vOCR 
+emoji: 🔥
+colorFrom: indigo
+colorTo: green
 sdk: gradio
 sdk_version: 5.34.2
 app_file: app.py
 pinned: false
 license: mit
+tags:
+  - OCR
+  - vision
+  - text-recognition
+  - image-to-text
+  - document-processing
+  - gradio
+  - api
+  - jigsawstack
+short_description: Extract text from images with Vocr API
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference  
+Explore the Vocr API: https://jigsawstack.com/docs/api-reference/ai/voc

app.py

@@ -0,0 +1,222 @@
+import gradio as gr
+import requests
+import json
+import os
+import time
+from collections import defaultdict
+
+BASE_URL = "https://api.jigsawstack.com/v1"
+headers = {
+    "x-api-key":  os.getenv("JIGSAWSTACK_API_KEY")
+}
+
+
+# Rate limiting configuration
+request_times = defaultdict(list)
+MAX_REQUESTS = 1  # Maximum requests per time window
+TIME_WINDOW = 3600   # Time window in seconds (1 hour)
+
+def get_real_ip(request: gr.Request):
+    """Extract real IP address using x-forwarded-for header or fallback"""
+    if not request:
+        return "unknown"
+    
+    forwarded = request.headers.get("x-forwarded-for")
+    if forwarded:
+        ip = forwarded.split(",")[0].strip()  # First IP in the list is the client's
+    else:
+        ip = request.client.host  # fallback
+    return ip
+
+def check_rate_limit(request: gr.Request):
+    """Check if the current request exceeds rate limits"""
+    if not request:
+        return True, "Rate limit check failed - no request info"
+    
+    ip = get_real_ip(request)
+    now = time.time()
+
+    # Clean up old timestamps outside the time window
+    request_times[ip] = [t for t in request_times[ip] if now - t < TIME_WINDOW]
+    
+    print(f"Request times: {request_times[ip]}")
+
+    # Check if rate limit exceeded
+    if len(request_times[ip]) >= MAX_REQUESTS:
+        time_remaining = int(TIME_WINDOW - (now - request_times[ip][0]))
+        time_remaining_minutes = round(time_remaining / 60, 1)      
+        time_window_minutes = round(TIME_WINDOW / 60, 1)
+        
+        return False, f"Rate limit exceeded. You can make {MAX_REQUESTS} requests per {time_window_minutes} minutes. Try again in {time_remaining_minutes} minutes."
+    
+    # Add current request timestamp
+    request_times[ip].append(now)
+    return True, ""
+
+
+# ----------------- JigsawStack API Wrasppers ------------------
+
+def vocr(source_type, image_url, file_store_key, prompt_str, page_range_str, request: gr.Request):
+    # Check rate limit first
+    rate_limit_ok, rate_limit_msg = check_rate_limit(request)
+    if not rate_limit_ok:
+        return (
+            rate_limit_msg,  # status
+            None,            # image
+            gr.update(visible=False),  # context JSON
+            gr.update(visible=False),  # tags
+            gr.update(visible=False),  # has_text
+            gr.update(visible=False),  # sections JSON
+        )
+
+    def error_response(message, img_src):
+        return (
+            message,
+            img_src,
+            gr.update(visible=False),
+            gr.update(visible=False),
+            gr.update(visible=False),
+            gr.update(visible=False)
+        )
+
+    image_to_display = image_url if source_type == "URL" else None
+    
+    try:
+        payload = {}
+        # Validate prompts - ensure a prompt is always provided.
+        if not prompt_str or not prompt_str.strip():
+            return error_response("Error: Prompt is required.", image_to_display)
+        
+        prompts = [p.strip() for p in prompt_str.split(',') if p.strip()]
+        if not prompts:
+             return error_response("Error: Prompt cannot be empty or just commas.", image_to_display)
+        
+        # The API can handle an array of prompts, which is more robust
+        # and avoids potential issues with the response format.
+        payload["prompt"] = prompts
+
+        # Validate page range
+        if page_range_str and page_range_str.strip():
+            try:
+                parts = [int(p.strip()) for p in page_range_str.split(',')]
+                if len(parts) != 2:
+                    raise ValueError("Page range must be two numbers (e.g., 1,10).")
+                start_page, end_page = parts
+                if not (start_page > 0 and end_page > 0):
+                    raise ValueError("Page numbers must be positive.")
+                if start_page > end_page:
+                    raise ValueError("Start page cannot be greater than end page.")
+                if (end_page - start_page) >= 10:
+                    raise ValueError("Page range cannot span more than 10 pages.")
+                payload["page_range"] = [start_page, end_page]
+            except (ValueError, TypeError) as e:
+                return error_response(f"Error: Invalid page range format - {e}", image_to_display)
+
+        if source_type == "URL":
+            if not image_url or not image_url.strip():
+                return error_response("Error: Image URL is required.", image_to_display)
+            payload["url"] = image_url.strip()
+        
+        elif source_type == "File Store Key":
+            if not file_store_key or not file_store_key.strip():
+                return error_response("Error: File Store Key is required.", image_to_display)
+            payload["file_store_key"] = file_store_key.strip()
+        else:
+            return error_response("Error: Invalid image source selected.", image_to_display)
+
+        response = requests.post(f"{BASE_URL}/vocr", headers=headers, json=payload)
+        response.raise_for_status()
+        result = response.json()
+
+        if not result.get("success"):
+            return error_response(f"Error: vOCR failed - {result.get('message', 'Unknown error')}", image_to_display)
+
+        context = result.get("context", {})
+        tags = ", ".join(result.get("tags", []))
+        has_text = str(result.get("has_text", "N/A"))
+        sections = result.get("sections", [])
+
+        status = "✅ Successfully processed image with vOCR."
+        
+        return (
+            status,
+            image_to_display,
+            gr.update(value=context, visible=True if context else False),
+            gr.update(value=tags, visible=True if tags else False),
+            gr.update(value=has_text, visible=True),
+            gr.update(value=sections, visible=True if sections else False)
+        )
+
+    except requests.exceptions.RequestException as e:
+        return error_response(f"Request failed: {str(e)}", image_to_display)
+    except Exception as e:
+        return error_response(f"An unexpected error occurred: {str(e)}", image_to_display)
+
+# ----------------- 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;'>🧩 vOCR</h1>
+        <p style='font-size:1.2em; margin-top: 0;'>Extract text from images 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/vocr' target='_blank'>documentation</a>.</p>
+    </div>
+    """)
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("#### Image Source")
+            vocr_source_type = gr.Radio(
+                choices=["URL", "File Store Key"],
+                label="Choose Image Source",
+                value="URL"
+            )
+            vocr_image_url = gr.Textbox(
+                label="Image URL",
+                placeholder="https://media.snopes.com/2021/08/239918331_10228097135359041_3825446756894757753_n.jpg",
+                visible=True
+            )
+            vocr_file_key = gr.Textbox(
+                label="File Store Key",
+                placeholder="your-file-store-key",
+                visible=False
+            )
+            vocr_prompts = gr.Textbox(
+                label="Prompts (comma-separated)",
+                placeholder="total_price, tax, store_name",
+                info="Prompts to guide data extraction from the image."
+            )
+            vocr_page_range = gr.Textbox(
+                label="Page Range (Optional)",
+                placeholder="e.g., 1,10",
+                info="For multi-page docs. Max 10 pages."
+            )
+            vocr_btn = gr.Button("Analyze Image", variant="primary")
+
+        with gr.Column(scale=2):
+            gr.Markdown("#### Analysis Results")
+            vocr_status = gr.Textbox(label="Status", interactive=False)
+            vocr_image_display = gr.Image(label="Analyzed Image")
+            vocr_context = gr.JSON(label="Extracted Context", visible=False)
+            vocr_tags = gr.Textbox(label="Detected Tags", interactive=False, visible=False)
+            vocr_has_text = gr.Textbox(label="Text Detected?", interactive=False, visible=False)
+            vocr_sections = gr.JSON(label="Full OCR Sections", visible=False)
+
+    def update_vocr_source(source_type):
+        is_url = source_type == "URL"
+        return gr.update(visible=is_url), gr.update(visible=not is_url)
+
+    vocr_source_type.change(
+        update_vocr_source,
+        inputs=vocr_source_type,
+        outputs=[vocr_image_url, vocr_file_key]
+    )
+
+    vocr_btn.click(
+        vocr,
+        inputs=[vocr_source_type, vocr_image_url, vocr_file_key, vocr_prompts, vocr_page_range],
+        outputs=[vocr_status, vocr_image_display, vocr_context, vocr_tags, vocr_has_text, vocr_sections]
+    )
+
+
+demo.launch()

requirements.txt

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