update

app.py

@@ -8,14 +8,15 @@ import requests
 from PIL import Image
 import gradio as gr
 import re
-
+import tempfile
+from urllib.parse import urlparse
 
 # =========================
 # Config
 # =========================
 DEFAULT_API_URL = os.environ.get("API_URL")
 TOKEN = os.environ.get("TOKEN")
-LOGO_IMAGE_PATH = './assets/logo.jpg'
+LOGO_IMAGE_PATH = "./assets/logo.jpg"
 GOOGLE_FONTS_URL = "<link href='https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@400;700&display=swap' rel='stylesheet'>"
 LATEX_DELIMS = [
     {"left": "$$", "right": "$$", "display": True},
@@ -23,19 +24,18 @@ LATEX_DELIMS = [
     {"left": "\\(", "right": "\\)", "display": False},
     {"left": "\\[", "right": "\\]", "display": True},
 ]
-AUTH_HEADER = {"Authorization": f"bearer {TOKEN}"}
-JSON_HEADERS = {**AUTH_HEADER, "Content-Type": "application/json"}
-
+AUTH_HEADER = {"Authorization": f"bearer {TOKEN}"} if TOKEN else {}
+JSON_HEADERS = {**AUTH_HEADER, "Content-Type": "application/json"} if AUTH_HEADER else {"Content-Type": "application/json"}
 
 # =========================
-# Base64 and Example Loading Logic
+# Base64 & Examples (URL直链渲染)
 # =========================
 def image_to_base64_data_url(filepath: str) -> str:
-    """Reads a local image file and encodes it into a Base64 Data URL."""
+    """仅用于本地上传预览的兼容方案；URL 预览不会用到它。"""
     try:
         ext = os.path.splitext(filepath)[1].lower()
-        mime_types = {'.jpg': 'image/jpeg', '.jpeg': 'image/jpeg', '.png': 'image/png', '.gif': 'image/gif'}
-        mime_type = mime_types.get(ext, 'image/jpeg')
+        mime_types = {".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".png": "image/png", ".gif": "image/gif", ".webp": "image/webp", ".bmp": "image/bmp"}
+        mime_type = mime_types.get(ext, "image/jpeg")
         with open(filepath, "rb") as image_file:
             encoded_string = base64.b64encode(image_file.read()).decode("utf-8")
         return f"data:{mime_type};base64,{encoded_string}"
@@ -44,77 +44,121 @@ def image_to_base64_data_url(filepath: str) -> str:
         return ""
 
 def _escape_inequalities_in_math(md: str) -> str:
-    """
-    Finds math blocks in a Markdown string and replaces < and > with
-    their LaTeX equivalents, \lt and \gt, to prevent markdown parsing errors.
-    """
+    """把数学块中的 < > 替换为 \\lt \\gt，避免被 Markdown 误解析。"""
     _MATH_PATTERNS = [
         re.compile(r"\$\$([\s\S]+?)\$\$"),
         re.compile(r"\$([^\$]+?)\$"),
         re.compile(r"\\\[([\s\S]+?)\\\]"),
         re.compile(r"\\\(([\s\S]+?)\\\)"),
     ]
+
     def fix(s: str) -> str:
         s = s.replace("<=", r" \le ").replace(">=", r" \ge ")
         s = s.replace("≤", r" \le ").replace("≥", r" \ge ")
-        s = s.replace("<",  r" \lt ").replace(">",  r" \gt ")
+        s = s.replace("<", r" \lt ").replace(">", r" \gt ")
         return s
+
     for pat in _MATH_PATTERNS:
         md = pat.sub(lambda m: m.group(0).replace(m.group(1), fix(m.group(1))), md)
     return md
 
 def _get_examples_from_dir(dir_path: str) -> List[List[str]]:
+    """
+    从本地目录读取文件名，拼出远程直链 URL（不下载、不转码），用于 <img src="URL"> 直接渲染。
+    你原来使用的 BOS 基础路径保留。
+    """
+    BASE_URL = "https://paddle-model-ecology.bj.bcebos.com/PPOCRVL/dataset/examples"
     supported_exts = {".png", ".jpg", ".jpeg", ".bmp", ".webp"}
     examples = []
-    if not os.path.exists(dir_path): return []
+    if not os.path.exists(dir_path):
+        print(f"Warning: example dir {dir_path} not found.")
+        return []
     for filename in sorted(os.listdir(dir_path)):
-        if os.path.splitext(filename)[1].lower() in supported_exts:
-            examples.append([os.path.join(dir_path, filename)])
+        ext = os.path.splitext(filename)[1].lower()
+        if ext in supported_exts:
+            subdir = os.path.basename(dir_path.rstrip("/"))
+            img_url = f"{BASE_URL}/{subdir}/{filename}"
+            examples.append([img_url])
     return examples
 
+def _on_gallery_select(example_paths: List[str], evt: gr.SelectData):
+    """
+    与原版不同：直接返回 URL，不再下载到本地临时文件。
+    """
+    idx = evt.index
+    selected = example_paths[idx]
+    if isinstance(selected, list):
+        selected = selected[0]
+    return selected  # 直接是 https://... URL
+
 TARGETED_EXAMPLES_DIR = "examples/targeted"
 COMPLEX_EXAMPLES_DIR = "examples/complex"
 targeted_recognition_examples = _get_examples_from_dir(TARGETED_EXAMPLES_DIR)
 complex_document_examples = _get_examples_from_dir(COMPLEX_EXAMPLES_DIR)
 
 # =========================
-# UI Helpers
+# UI Helpers（URL直链渲染）
 # =========================
-def render_uploaded_image_div(file_path: str) -> str:
-    data_url = image_to_base64_data_url(file_path)
+def render_uploaded_image_div(path_or_url: str) -> str:
+    """
+    支持两种输入：
+    - 远程 URL：直接用 <img src="URL"> 渲染
+    - 本地文件：为兼容旧逻辑，依然转 data: URL 预览（也可以改为 File 组件，这里先保持一致）
+    """
+    if not path_or_url:
+        return ""
+    is_url = isinstance(path_or_url, str) and path_or_url.startswith(("http://", "https://"))
+    if is_url:
+        src = path_or_url  # 直接远程URL
+    else:
+        src = image_to_base64_data_url(path_or_url)  # 本地上传时的兼容
     return f"""
     <div class="uploaded-image">
-        <img src="{data_url}" alt="Uploaded image" style="width:100%;height:100%;object-fit:contain;"/>
+        <img src="{src}" alt="Preview image" style="width:100%;height:100%;object-fit:contain;" loading="lazy"/>
     </div>
     """
 
-def update_preview_visibility(file_path: Optional[str]) -> Dict:
-    if file_path:
-        html_content = render_uploaded_image_div(file_path)
+def update_preview_visibility(path_or_url: Optional[str]) -> Dict:
+    if path_or_url:
+        html_content = render_uploaded_image_div(path_or_url)
         return gr.update(value=html_content, visible=True)
     else:
         return gr.update(value="", visible=False)
 
-def _on_gallery_select(example_paths: List[str], evt: gr.SelectData):
-    try:
-        idx = evt.index
-        return example_paths[idx]
-    except Exception:
-        return None
-
 # =========================
-# API Call Logic
+# API 调用逻辑（支持URL或本地文件）
 # =========================
-def _file_to_b64_image_only(file_path: str) -> Tuple[str, int]:
-    if not file_path: raise ValueError("Please upload an image first.")
-    ext = os.path.splitext(file_path)[1].lower()
-    if ext not in {".png", ".jpg", ".jpeg", ".bmp", ".webp"}: raise ValueError("Only image files are supported.")
-    with open(file_path, "rb") as f:
-        return base64.b64encode(f.read()).decode("utf-8"), 1
-
-def _call_api(api_url: str, file_path: str, use_layout_detection: bool,
+def _file_to_b64_image_only(path_or_url: str) -> Tuple[str, int]:
+    """
+    输入可以是本地文件路径或远程URL。
+    - URL：仅在发请求给后端时下载字节转Base64（不影响前端渲染）。
+    - 本地：读取文件字节。
+    """
+    if not path_or_url:
+        raise ValueError("Please upload an image first.")
+
+    is_url = isinstance(path_or_url, str) and path_or_url.startswith(("http://", "https://"))
+    content: bytes
+    if is_url:
+        r = requests.get(path_or_url, timeout=600)
+        r.raise_for_status()
+        content = r.content
+        ext = os.path.splitext(urlparse(path_or_url).path)[1].lower()
+    else:
+        ext = os.path.splitext(path_or_url)[1].lower()
+        with open(path_or_url, "rb") as f:
+            content = f.read()
+
+    # 放宽后缀限制：有些URL可能没有后缀，这里仅在极端情况下提示
+    supported = {".png", ".jpg", ".jpeg", ".bmp", ".webp"}
+    if ext and (ext not in supported):
+        print(f"Warning: file extension {ext} not in supported set {supported}, continue anyway.")
+
+    return base64.b64encode(content).decode("utf-8"), 1  # 1 = image 类型
+
+def _call_api(api_url: str, path_or_url: str, use_layout_detection: bool,
               prompt_label: Optional[str], use_chart_recognition: bool = False) -> Dict[str, Any]:
-    b64, file_type = _file_to_b64_image_only(file_path)
+    b64, file_type = _file_to_b64_image_only(path_or_url)
     payload = {
         "file": b64,
         "useLayoutDetection": bool(use_layout_detection),
@@ -133,13 +177,11 @@ def _call_api(api_url: str, file_path: str, use_layout_detection: bool,
         start_time = time.time()
         resp = requests.post(api_url, json=payload, headers=JSON_HEADERS, timeout=600)
         end_time = time.time()
-        duration = end_time - start_time
-        print(f"Received API response in {duration:.2f} seconds.")
-        
+        print(f"Received API response in {end_time - start_time:.2f} seconds.")
         resp.raise_for_status()
         data = resp.json()
     except requests.exceptions.RequestException as e:
-        raise gr.Error(f"API request failed:{e}")
+        raise gr.Error(f"API request failed: {e}")
     except json.JSONDecodeError:
         raise gr.Error(f"Invalid JSON response from server:\n{getattr(resp, 'text', '')}")
 
@@ -147,68 +189,62 @@ def _call_api(api_url: str, file_path: str, use_layout_detection: bool,
         raise gr.Error("API returned an error:")
     return data
 
-
 def _process_api_response_page(result: Dict[str, Any]) -> Tuple[str, str, str]:
     """
-    Processes the API response.
-    1. Replaces markdown image placeholders with their direct URLs.
-    2. Constructs an HTML <img> tag string for the visualization image URL.
+    处理后端返回结果：
+    1) 把 markdown 里的占位图路径替换为真实URL
+    2) 构造一个可视化<img>（如果有）
     """
     layout_results = (result or {}).get("layoutParsingResults", [])
     if not layout_results:
         return "No content was recognized.", "<p>No visualization available.</p>", ""
 
     page0 = layout_results[0] or {}
-
-    # Step 1: Process Markdown content (unchanged from previous optimization)
     md_data = page0.get("markdown") or {}
     md_text = md_data.get("text", "") or ""
     md_images_map = md_data.get("images", {})
+
     if md_images_map:
         for placeholder_path, image_url in md_images_map.items():
             md_text = md_text.replace(f'src="{placeholder_path}"', f'src="{image_url}"') \
                              .replace(f']({placeholder_path})', f']({image_url})')
 
-    # 【核心改动点】 Step 2: Process Visualization images by creating an HTML string
     output_html = "<p style='text-align:center; color:#888;'>No visualization image available.</p>"
     out_imgs = page0.get("outputImages") or {}
-    
-    # Get all image URLs and sort them
     sorted_urls = [img_url for _, img_url in sorted(out_imgs.items()) if img_url]
 
-    # Logic to select the final visualization image URL
     output_image_url: Optional[str] = None
     if len(sorted_urls) >= 2:
         output_image_url = sorted_urls[1]
     elif sorted_urls:
         output_image_url = sorted_urls[0]
 
-    # If a URL was found, create the <img> tag
     if output_image_url:
         print(f"Found visualization image URL: {output_image_url}")
-        # The CSS will style this `img` tag because of the `#vis_image_doc img` selector
-        output_html = f'<img src="{output_image_url}" alt="Detection Visualization">'
-    else:
-        print("Warning: No visualization image URL found in the API response.")
+        output_html = f'<img src="{output_image_url}" alt="Detection Visualization" loading="lazy">'
 
     md_text = _escape_inequalities_in_math(md_text)
     return md_text or "(Empty result)", output_html, md_text
 
-# =========================
-# Handlers
-# =========================
-def handle_complex_doc(file_path: str, use_chart_recognition: bool) -> Tuple[str, str, str]:
-    if not file_path: raise gr.Error("Please upload an image first.")
-    data = _call_api(DEFAULT_API_URL, file_path, use_layout_detection=True, prompt_label=None, use_chart_recognition=use_chart_recognition)
+def handle_complex_doc(path_or_url: str, use_chart_recognition: bool) -> Tuple[str, str, str]:
+    if not path_or_url:
+        raise gr.Error("Please upload an image first.")
+    data = _call_api(DEFAULT_API_URL, path_or_url, use_layout_detection=True,
+                     prompt_label=None, use_chart_recognition=use_chart_recognition)
     result = data.get("result", {})
-    # Note the return types now align with the new function signature
     return _process_api_response_page(result)
 
-def handle_targeted_recognition(file_path: str, prompt_choice: str) -> Tuple[str, str]:
-    if not file_path: raise gr.Error("Please upload an image first.")
-    mapping = {"Text Recognition": "ocr", "Formula Recognition": "formula", "Table Recognition": "table", "Chart Recognition": "chart"}
+def handle_targeted_recognition(path_or_url: str, prompt_choice: str) -> Tuple[str, str]:
+    if not path_or_url:
+        raise gr.Error("Please upload an image first.")
+    mapping = {
+        "Text Recognition": "ocr",
+        "Formula Recognition": "formula",
+        "Table Recognition": "table",
+        "Chart Recognition": "chart",
+    }
     label = mapping.get(prompt_choice, "ocr")
-    data = _call_api(DEFAULT_API_URL, file_path, use_layout_detection=False, prompt_label=label)
+    data = _call_api(DEFAULT_API_URL, path_or_url, use_layout_detection=False, prompt_label=label)
     result = data.get("result", {})
     md_preview, _, md_raw = _process_api_response_page(result)
     return md_preview, md_raw
@@ -217,11 +253,7 @@ def handle_targeted_recognition(file_path: str, prompt_choice: str) -> Tuple[str
 # CSS & UI
 # =========================
 custom_css = """
-/* 全局字体 */
-body, .gradio-container {
-  font-family: "Noto Sans SC", "Microsoft YaHei", "PingFang SC", sans-serif;
-}
-/* ... (rest of the CSS is unchanged) ... */
+body, .gradio-container { font-family: "Noto Sans SC", "Microsoft YaHei", "PingFang SC", sans-serif; }
 .app-header { text-align: center; max-width: 900px; margin: 0 auto 8px !important; }
 .gradio-container { padding: 4px 0 !important; }
 .gradio-container [data-testid="tabs"], .gradio-container .tabs { margin-top: 0 !important; }
@@ -243,12 +275,13 @@ body, .gradio-container {
 """
 
 with gr.Blocks(head=GOOGLE_FONTS_URL, css=custom_css, theme=gr.themes.Soft()) as demo:
+    # 顶部 Logo
     logo_data_url = image_to_base64_data_url(LOGO_IMAGE_PATH) if os.path.exists(LOGO_IMAGE_PATH) else ""
     gr.HTML(f"""<div class="app-header"><img src="{logo_data_url}" alt="App Logo" style="max-height:10%; width: auto; margin: 10px auto; display: block;"></div>""")
-    gr.HTML("""<div class="notice"><strong>Heads up:</strong> The Hugging Face demo can be slow at times. For a faster experience, please try <a href="https://aistudio.baidu.com/application/detail/98365" target="_blank" rel="noopener noreferrer">Baidu AI Studio</a> or <a href="https://modelscope.cn/studios/PaddlePaddle/PaddleOCR-VL_Online_Demo/summary" target="_blank" rel="noopener noreferrer">ModelScope</a>.</div>""")
-    gr.HTML("""<div class="quick-links"><a href="https://github.com/PaddlePaddle/PaddleOCR" target="_blank">GitHub</a> | <a href="https://ernie.baidu.com/blog/publication/PaddleOCR-VL_Technical_Report.pdf" target="_blank">Technical Report</a> | <a href="https://huggingface.co/PaddlePaddle/PaddleOCR-VL" target="_blank">Model</a></div>""")
-    
+    gr.HTML("""<div class="quick-links"><a href="https://github.com/PaddlePaddle/PaddleOCR" target="_blank">GitHub</a> | <a href="https://ernie.baidu.com/blog/publication/PaddleOCR-VL_Technical_Report.pdf" target="_blank">Technical Report</a> | <a href="https://www.modelscope.cn/models/PaddlePaddle/PaddleOCR-VL" target="_blank">Model</a></div>""")
+
     with gr.Tabs():
+        # ===================== Document Parsing =====================
         with gr.Tab("Document Parsing"):
             with gr.Row():
                 with gr.Column(scale=5):
@@ -256,29 +289,69 @@ with gr.Blocks(head=GOOGLE_FONTS_URL, css=custom_css, theme=gr.themes.Soft()) as
                     preview_doc_html = gr.HTML(value="", elem_id="image_preview_doc", visible=False)
                     gr.Markdown("_( Use this mode for recognizing full-page documents with structured layouts, such as reports, papers, or magazines.)_")
                     gr.Markdown("💡 *To recognize a single, pre-cropped element (e.g., a table or formula), switch to the 'Element-level Recognition' tab for better results.*")
+
+                    example_url_doc = gr.State(value=None)
+
                     with gr.Row(variant="panel"):
                         chart_parsing_switch = gr.Checkbox(label="Enable chart parsing", value=False, scale=1)
                         btn_parse = gr.Button("Parse Document", variant="primary", scale=2)
+
                     if complex_document_examples:
-                        complex_paths = [e[0] for e in complex_document_examples]
+                        complex_paths = [e[0] for e in complex_document_examples]  # 这里是 List[str]
                         complex_state = gr.State(complex_paths)
-                        gr.Markdown("**Document Examples (Click an image to load)**")
-                        gallery_complex = gr.Gallery(value=complex_paths, columns=4, height=400, preview=False, label=None, allow_preview=False)
-                        gallery_complex.select(fn=_on_gallery_select, inputs=[complex_state], outputs=[file_doc])
+
+                        gallery_complex = gr.Gallery(
+                            value=complex_paths, columns=4, height=400,
+                            preview=False, label=None, allow_preview=False
+                        )
+
+                        # 2) 回调：用 evt.index 到 paths（State）里取 URL
+                        def on_gallery_select_for_doc(paths, evt: gr.SelectData):
+                            # 某些版本 evt.index 可能是 (row, col) 或 list，做个兜底
+                            idx = evt.index
+                            if isinstance(idx, (list, tuple)):
+                                # 常见是一个 int；如果是 (row, col) 形式，通常线性下标 == row
+                                idx = idx[0]
+                            try:
+                                url = paths[int(idx)]
+                            except Exception:
+                                raise gr.Error(f"Invalid index from gallery: {evt.index}")
+
+                            # 更新状态 & 预览
+                            return url, update_preview_visibility(url)
+
+                        # 3) 绑定：把 State 作为 inputs 传给回调，outputs 写入 example_url_doc 和预览 HTML
+                        gallery_complex.select(
+                            fn=on_gallery_select_for_doc,
+                            inputs=[complex_state],
+                            outputs=[example_url_doc, preview_doc_html],
+                        )
+
 
                 with gr.Column(scale=7):
                     with gr.Tabs():
                         with gr.Tab("Markdown Preview"):
                             md_preview_doc = gr.Markdown("Please upload an image and click 'Parse Document'.", latex_delimiters=LATEX_DELIMS, elem_id="md_preview_doc")
                         with gr.Tab("Visualization"):
-                            # 【核心改动点】: 将 gr.Image 替换为 gr.HTML
                             vis_image_doc = gr.HTML(label="Detection Visualization", elem_id="vis_image_doc")
                         with gr.Tab("Markdown Source"):
                             md_raw_doc = gr.Code(label="Markdown Source Code", language="markdown")
 
-            file_doc.change(fn=update_preview_visibility, inputs=[file_doc], outputs=[preview_doc_html])
-            btn_parse.click(fn=handle_complex_doc, inputs=[file_doc, chart_parsing_switch], outputs=[md_preview_doc, vis_image_doc, md_raw_doc])
+            def on_file_doc_change(fp):
+                return None, update_preview_visibility(fp)
+
+            file_doc.change(fn=on_file_doc_change, inputs=[file_doc], outputs=[example_url_doc, preview_doc_html])
+
+            def parse_doc_router(fp, example_url, use_chart):
+                src = fp if fp else example_url
+                if not src:
+                    raise gr.Error("Please upload an image or pick an example first.")
+                return handle_complex_doc(src, use_chart)
 
+            btn_parse.click(fn=parse_doc_router, inputs=[file_doc, example_url_doc, chart_parsing_switch],
+                            outputs=[md_preview_doc, vis_image_doc, md_raw_doc])
+
+        # ===================== Element-level Recognition =====================
         with gr.Tab("Element-level Recognition"):
             with gr.Row():
                 with gr.Column(scale=5):
@@ -286,18 +359,31 @@ with gr.Blocks(head=GOOGLE_FONTS_URL, css=custom_css, theme=gr.themes.Soft()) as
                     preview_vl_html = gr.HTML(value="", elem_id="image_preview_vl", visible=False)
                     gr.Markdown("_(Best for images with a **simple, single-column layout** (e.g., pure text), or for a **pre-cropped single element** like a table, formula, or chart.)_")
                     gr.Markdown("Choose a recognition type:")
+
                     with gr.Row(elem_classes=["prompt-grid"]):
                         btn_ocr = gr.Button("Text Recognition", variant="secondary")
-                        btn_formula = gr.Button("Formula Recognition", "secondary")
+                        btn_formula = gr.Button("Formula Recognition", variant="secondary")
                     with gr.Row(elem_classes=["prompt-grid"]):
                         btn_table = gr.Button("Table Recognition", variant="secondary")
                         btn_chart = gr.Button("Chart Recognition", variant="secondary")
+
+                    example_url_vl = gr.State(value=None)
+
                     if targeted_recognition_examples:
                         targeted_paths = [e[0] for e in targeted_recognition_examples]
                         targeted_state = gr.State(targeted_paths)
                         gr.Markdown("**Element-level Recognition Examples (Click an image to load)**")
                         gallery_targeted = gr.Gallery(value=targeted_paths, columns=4, height=400, preview=False, label=None, allow_preview=False)
-                        gallery_targeted.select(fn=_on_gallery_select, inputs=[targeted_state], outputs=[file_vl])
+
+                        def on_gallery_select_for_vl(paths, evt):
+                            url = _on_gallery_select(paths, evt)
+                            return url, update_preview_visibility(url)
+
+                        gallery_targeted.select(
+                            fn=on_gallery_select_for_vl,
+                            inputs=[targeted_state],
+                            outputs=[example_url_vl, preview_vl_html]
+                        )
 
                 with gr.Column(scale=7):
                     with gr.Tabs():
@@ -306,12 +392,22 @@ with gr.Blocks(head=GOOGLE_FONTS_URL, css=custom_css, theme=gr.themes.Soft()) as
                         with gr.Tab("Raw Output"):
                             md_raw_vl = gr.Code(label="Raw Output", language="markdown")
 
-            file_vl.change(fn=update_preview_visibility, inputs=[file_vl], outputs=[preview_vl_html])
-            btn_ocr.click(fn=handle_targeted_recognition, inputs=[file_vl, gr.State("Text Recognition")], outputs=[md_preview_vl, md_raw_vl])
-            btn_formula.click(fn=handle_targeted_recognition, inputs=[file_vl, gr.State("Formula Recognition")], outputs=[md_preview_vl, md_raw_vl])
-            btn_table.click(fn=handle_targeted_recognition, inputs=[file_vl, gr.State("Table Recognition")], outputs=[md_preview_vl, md_raw_vl])
-            btn_chart.click(fn=handle_targeted_recognition, inputs=[file_vl, gr.State("Chart Recognition")], outputs=[md_preview_vl, md_raw_vl])
+            def on_file_vl_change(fp):
+                return None, update_preview_visibility(fp)
+
+            file_vl.change(fn=on_file_vl_change, inputs=[file_vl], outputs=[example_url_vl, preview_vl_html])
+
+            def parse_vl_router(fp, example_url, prompt_choice):
+                src = fp if fp else example_url
+                if not src:
+                    raise gr.Error("Please upload an image or pick an example first.")
+                return handle_targeted_recognition(src, prompt_choice)
+
+            btn_ocr.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Text Recognition")], outputs=[md_preview_vl, md_raw_vl])
+            btn_formula.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Formula Recognition")], outputs=[md_preview_vl, md_raw_vl])
+            btn_table.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Table Recognition")], outputs=[md_preview_vl, md_raw_vl])
+            btn_chart.click(fn=parse_vl_router, inputs=[file_vl, example_url_vl, gr.State("Chart Recognition")], outputs=[md_preview_vl, md_raw_vl])
 
 if __name__ == "__main__":
     port = int(os.getenv("PORT", "7860"))
-    demo.queue(max_size=64).launch(server_name="0.0.0.0", server_port=port,share=False)
+    demo.queue(max_size=64).launch(server_name="0.0.0.0", server_port=port, share=False)