Update app.py

app.py

@@ -1,319 +1,320 @@
-"""
-BabelDocs x Agentic AI MCP - Gradio Application
-
-PDF Translation with Google Drive Integration.
-Accepts public GDrive links or local file uploads.
-
-For Anthropic Hackathon - Track 1: Building MCP
-
-Usage:
-    python app.py
-"""
-
-import os
-import re
-import base64
-import tempfile
-import httpx
-import gradio as gr
-from pathlib import Path
-from datetime import datetime
-from dotenv import load_dotenv
-
-load_dotenv()
-
-# Modal endpoint configuration
-# Set BABELDOCS_MODAL_URL as HuggingFace Space secret for production
-MODAL_BASE_URL = os.getenv("BABELDOCS_MODAL_URL")
-if not MODAL_BASE_URL:
-    raise ValueError("BABELDOCS_MODAL_URL environment variable required. Set it as a HuggingFace Space secret.")
-MODAL_TRANSLATE_URL = f"{MODAL_BASE_URL}-babeldocstranslator-api.modal.run"
-MODAL_HEALTH_URL = f"{MODAL_BASE_URL}-babeldocstranslator-health.modal.run"
-
-# Max pages limit (test phase)
-MAX_PAGES = 20
-
-# Supported languages
-LANGUAGES = {
-    "fr": "French",
-    "en": "English",
-    "es": "Spanish",
-    "de": "German",
-    "it": "Italian",
-    "pt": "Portuguese",
-    "zh": "Chinese",
-    "ja": "Japanese",
-    "ko": "Korean",
-    "ru": "Russian",
-    "ar": "Arabic",
-}
-
-
-def log_message(logs: list, message: str) -> list:
-    """Add timestamped message to logs."""
-    timestamp = datetime.now().strftime("%H:%M:%S")
-    logs.append(f"[{timestamp}] {message}")
-    return logs
-
-
-def extract_gdrive_file_id(url: str) -> str | None:
-    """Extract file ID from Google Drive URL."""
-    patterns = [
-        r"/file/d/([a-zA-Z0-9_-]+)",
-        r"id=([a-zA-Z0-9_-]+)",
-        r"/d/([a-zA-Z0-9_-]+)",
-    ]
-    for pattern in patterns:
-        match = re.search(pattern, url)
-        if match:
-            return match.group(1)
-    return None
-
-
-async def download_gdrive_public(url: str) -> tuple[bytes, str]:
-    """Download file from public Google Drive link.
-
-    Returns (file_bytes, filename).
-    """
-    file_id = extract_gdrive_file_id(url)
-    if not file_id:
-        raise ValueError("Invalid Google Drive URL")
-
-    # Direct download URL
-    download_url = f"https://drive.google.com/uc?export=download&id={file_id}"
-
-    async with httpx.AsyncClient(timeout=120.0, follow_redirects=True) as client:
-        response = await client.get(download_url)
-        response.raise_for_status()
-
-        # Try to get filename from Content-Disposition header
-        content_disp = response.headers.get("Content-Disposition", "")
-        filename_match = re.search(r'filename="?([^";\n]+)"?', content_disp)
-        if filename_match:
-            filename = filename_match.group(1)
-        else:
-            filename = f"gdrive_{file_id}.pdf"
-
-        return response.content, filename
-
-
-async def translate_pdf_modal(
-    pdf_file,
-    gdrive_url: str,
-    target_lang: str,
-    progress=gr.Progress()
-) -> tuple:
-    """Translate PDF using Modal cloud."""
-    logs = []
-
-    # Validate input
-    if not pdf_file and not gdrive_url:
-        return None, None, "Please upload a PDF or provide a Google Drive link", "", "\n".join(logs)
-
-    if pdf_file and gdrive_url:
-        return None, None, "Please use either file upload OR Google Drive link, not both", "", "\n".join(logs)
-
-    try:
-        logs = log_message(logs, "Starting translation...")
-
-        # Get PDF bytes and filename
-        if gdrive_url:
-            logs = log_message(logs, f"Downloading from Google Drive...")
-            progress(0.05, desc="Downloading from Google Drive...")
-            pdf_bytes, source_filename = await download_gdrive_public(gdrive_url.strip())
-            logs = log_message(logs, f"Downloaded: {source_filename}")
-        else:
-            pdf_path = Path(pdf_file)
-            pdf_bytes = pdf_path.read_bytes()
-            source_filename = pdf_path.name
-
-        pdf_base64 = base64.b64encode(pdf_bytes).decode("utf-8")
-
-        logs = log_message(logs, f"Input: {source_filename}")
-        logs = log_message(logs, f"Size: {len(pdf_bytes) / 1024:.1f} KB")
-        logs = log_message(logs, f"Target: {LANGUAGES.get(target_lang, target_lang)}")
-
-        progress(0.1, desc="Uploading to Modal...")
-
-        payload = {
-            "pdf_base64": pdf_base64,
-            "target_lang": target_lang,
-        }
-
-        logs = log_message(logs, "Translating on Modal cloud...")
-        logs = log_message(logs, "(This may take several minutes)")
-
-        progress(0.2, desc="Translating...")
-        start_time = datetime.now()
-
-        async with httpx.AsyncClient(timeout=900.0, follow_redirects=True) as client:
-            response = await client.post(MODAL_TRANSLATE_URL, json=payload)
-            response.raise_for_status()
-            result = response.json()
-
-        duration = (datetime.now() - start_time).total_seconds()
-        progress(0.8, desc="Processing result...")
-
-        if not result.get("success"):
-            error_msg = result.get("message", "Unknown error")
-            logs = log_message(logs, f"ERROR: {error_msg}")
-            return None, None, "Translation failed", "", "\n".join(logs)
-
-        # Process mono_img PDF
-        mono_img_path = None
-        mono_img_base64 = result.get("mono_img_pdf_base64")
-        if mono_img_base64:
-            mono_img_bytes = base64.b64decode(mono_img_base64)
-            stem = Path(source_filename).stem
-            mono_img_filename = f"{stem}_translated.{target_lang}.pdf"
-            mono_img_file = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
-            mono_img_file.write(mono_img_bytes)
-            mono_img_file.close()
-            mono_img_path = mono_img_file.name
-            logs = log_message(logs, f"Mono: {mono_img_filename} ({len(mono_img_bytes) / 1024:.1f} KB)")
-
-        # Process dual_img PDF
-        dual_img_path = None
-        dual_img_base64 = result.get("dual_img_pdf_base64")
-        if dual_img_base64:
-            dual_img_bytes = base64.b64decode(dual_img_base64)
-            stem = Path(source_filename).stem
-            dual_img_filename = f"{stem}_translated.{target_lang}.dual.pdf"
-            dual_img_file = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
-            dual_img_file.write(dual_img_bytes)
-            dual_img_file.close()
-            dual_img_path = dual_img_file.name
-            logs = log_message(logs, f"Dual: {dual_img_filename} ({len(dual_img_bytes) / 1024:.1f} KB)")
-
-        if not mono_img_path and not dual_img_path:
-            logs = log_message(logs, "ERROR: No output PDF in response")
-            return None, None, "Translation failed", "", "\n".join(logs)
-
-        logs = log_message(logs, f"Duration: {duration:.1f} seconds")
-
-        stats_msg = f"""**Translation completed!**
-
-- **Duration:** {duration:.1f} seconds
-- **Target:** {LANGUAGES.get(target_lang, target_lang)}"""
-
-        progress(1.0, desc="Done!")
-
-        return mono_img_path, dual_img_path, "Translation successful!", stats_msg, "\n".join(logs)
-
-    except httpx.TimeoutException:
-        logs = log_message(logs, "ERROR: Translation timed out")
-        return None, None, "Translation timed out", "", "\n".join(logs)
-    except httpx.HTTPStatusError as e:
-        logs = log_message(logs, f"ERROR: HTTP {e.response.status_code}")
-        return None, None, f"HTTP error: {e.response.status_code}", "", "\n".join(logs)
-    except Exception as e:
-        logs = log_message(logs, f"ERROR: {str(e)}")
-        return None, None, f"Error: {str(e)}", "", "\n".join(logs)
-
-
-# Gradio Interface
-with gr.Blocks(title="BabelDocs x Agentic AI MCP") as demo:
-
-    gr.Markdown("""
-# BabelDocs x Agentic AI MCP - PDF Translation with Google Drive Integration
-
-**Translate PDFs directly from Google Drive and save back automatically**
-
----
-
-## Key Feature: Full Google Drive Workflow in CLAUDE Desktop MCP
-
-```
-"Translate my Q3 report to French and save it to Translations folder"
-                              ↓
-        Claude searches → downloads → translates → uploads → done!
-```
-
----
-    """)
-
-    with gr.Row():
-        with gr.Column(scale=1):
-            gr.Markdown("### Input")
-
-            gdrive_url = gr.Textbox(
-                label="Google Drive Link (public)",
-                placeholder="https://drive.google.com/file/d/... or leave empty",
-                info="Paste a public GDrive link, OR upload a local file below",
-            )
-
-            gr.Markdown("**OR**")
-
-            pdf_input = gr.File(
-                label="Upload PDF",
-                file_types=[".pdf"],
-                type="filepath",
-            )
-
-            target_lang = gr.Dropdown(
-                choices=list(LANGUAGES.keys()),
-                value="fr",
-                label="Target Language",
-            )
-
-            translate_btn = gr.Button(
-                "Translate PDF",
-                variant="primary",
-                size="lg",
-            )
-
-        with gr.Column(scale=1):
-            gr.Markdown("### Result")
-
-            status_output = gr.Textbox(
-                label="Status",
-                interactive=False,
-            )
-
-            stats_output = gr.Markdown(label="Statistics")
-
-            gr.Markdown("**Downloads:**")
-            with gr.Row():
-                mono_img_output = gr.File(label="Mono (translated + images)")
-                dual_img_output = gr.File(label="Dual (bilingual + images)")
-
-            logs_output = gr.Textbox(
-                label="Logs",
-                interactive=False,
-                lines=10,
-                max_lines=15,
-            )
-
-    gr.Markdown("""
----
-
-### How it works
-
-```
-1. Upload PDF or paste GDrive link
-       ↓
-2. Send to Modal cloud (serverless)
-       ↓
-3. BabelDOC with Agentic AI translates text + images, preserves layout
-       ↓
-4. Download translated PDF
-```
-
----
-
-**Built with:** BabelDOC, Modal, Nebius AI, Gradio | **Hackathon:** Anthropic MCP Track 1
-    """)
-
-    translate_btn.click(
-        fn=translate_pdf_modal,
-        inputs=[pdf_input, gdrive_url, target_lang],
-        outputs=[mono_img_output, dual_img_output, status_output, stats_output, logs_output],
-    )
-
-
-if __name__ == "__main__":
-    demo.launch(
-        server_name="127.0.0.1",
-        server_port=7860,
-        share=False,
-    )
+"""
+BabelDocs x Agentic AI MCP - Gradio Application
+
+PDF Translation with Google Drive Integration.
+Accepts public GDrive links or local file uploads.
+
+For Anthropic Hackathon - Track 1: Building MCP
+
+Usage:
+    python app.py
+"""
+
+import os
+import re
+import base64
+import tempfile
+import httpx
+import gradio as gr
+from pathlib import Path
+from datetime import datetime
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# Modal endpoint configuration
+# Set BABELDOCS_MODAL_URL as HuggingFace Space secret for production
+MODAL_BASE_URL = os.getenv("BABELDOCS_MODAL_URL")
+if not MODAL_BASE_URL:
+    raise ValueError("BABELDOCS_MODAL_URL environment variable required. Set it as a HuggingFace Space secret.")
+MODAL_TRANSLATE_URL = f"{MODAL_BASE_URL}-babeldocstranslator-api.modal.run"
+MODAL_HEALTH_URL = f"{MODAL_BASE_URL}-babeldocstranslator-health.modal.run"
+
+# Max pages limit (test phase)
+MAX_PAGES = 20
+
+# Supported languages
+LANGUAGES = {
+    "fr": "French",
+    "en": "English",
+    "es": "Spanish",
+    "de": "German",
+    "it": "Italian",
+    "pt": "Portuguese",
+    "zh": "Chinese",
+    "ja": "Japanese",
+    "ko": "Korean",
+    "ru": "Russian",
+    "ar": "Arabic",
+}
+
+
+def log_message(logs: list, message: str) -> list:
+    """Add timestamped message to logs."""
+    timestamp = datetime.now().strftime("%H:%M:%S")
+    logs.append(f"[{timestamp}] {message}")
+    return logs
+
+
+def extract_gdrive_file_id(url: str) -> str | None:
+    """Extract file ID from Google Drive URL."""
+    patterns = [
+        r"/file/d/([a-zA-Z0-9_-]+)",
+        r"id=([a-zA-Z0-9_-]+)",
+        r"/d/([a-zA-Z0-9_-]+)",
+    ]
+    for pattern in patterns:
+        match = re.search(pattern, url)
+        if match:
+            return match.group(1)
+    return None
+
+
+async def download_gdrive_public(url: str) -> tuple[bytes, str]:
+    """Download file from public Google Drive link.
+
+    Returns (file_bytes, filename).
+    """
+    file_id = extract_gdrive_file_id(url)
+    if not file_id:
+        raise ValueError("Invalid Google Drive URL")
+
+    # Direct download URL
+    download_url = f"https://drive.google.com/uc?export=download&id={file_id}"
+
+    async with httpx.AsyncClient(timeout=120.0, follow_redirects=True) as client:
+        response = await client.get(download_url)
+        response.raise_for_status()
+
+        # Try to get filename from Content-Disposition header
+        content_disp = response.headers.get("Content-Disposition", "")
+        filename_match = re.search(r'filename="?([^";\n]+)"?', content_disp)
+        if filename_match:
+            filename = filename_match.group(1)
+        else:
+            filename = f"gdrive_{file_id}.pdf"
+
+        return response.content, filename
+
+
+async def translate_pdf_modal(
+    pdf_file,
+    gdrive_url: str,
+    target_lang: str,
+    progress=gr.Progress()
+) -> tuple:
+    """Translate PDF using Modal cloud."""
+    logs = []
+
+    # Validate input
+    if not pdf_file and not gdrive_url:
+        return None, None, "Please upload a PDF or provide a Google Drive link", "", "\n".join(logs)
+
+    if pdf_file and gdrive_url:
+        return None, None, "Please use either file upload OR Google Drive link, not both", "", "\n".join(logs)
+
+    try:
+        logs = log_message(logs, "Starting translation...")
+
+        # Get PDF bytes and filename
+        if gdrive_url:
+            logs = log_message(logs, f"Downloading from Google Drive...")
+            progress(0.05, desc="Downloading from Google Drive...")
+            pdf_bytes, source_filename = await download_gdrive_public(gdrive_url.strip())
+            logs = log_message(logs, f"Downloaded: {source_filename}")
+        else:
+            pdf_path = Path(pdf_file)
+            pdf_bytes = pdf_path.read_bytes()
+            source_filename = pdf_path.name
+
+        pdf_base64 = base64.b64encode(pdf_bytes).decode("utf-8")
+
+        logs = log_message(logs, f"Input: {source_filename}")
+        logs = log_message(logs, f"Size: {len(pdf_bytes) / 1024:.1f} KB")
+        logs = log_message(logs, f"Target: {LANGUAGES.get(target_lang, target_lang)}")
+
+        progress(0.1, desc="Uploading to Modal...")
+
+        payload = {
+            "pdf_base64": pdf_base64,
+            "target_lang": target_lang,
+        }
+
+        logs = log_message(logs, "Translating on Modal cloud...")
+        logs = log_message(logs, "(This may take several minutes)")
+
+        progress(0.2, desc="Translating...")
+        start_time = datetime.now()
+
+        async with httpx.AsyncClient(timeout=900.0, follow_redirects=True) as client:
+            response = await client.post(MODAL_TRANSLATE_URL, json=payload)
+            response.raise_for_status()
+            result = response.json()
+
+        duration = (datetime.now() - start_time).total_seconds()
+        progress(0.8, desc="Processing result...")
+
+        if not result.get("success"):
+            error_msg = result.get("message", "Unknown error")
+            logs = log_message(logs, f"ERROR: {error_msg}")
+            return None, None, "Translation failed", "", "\n".join(logs)
+
+        # Process mono_img PDF
+        mono_img_path = None
+        mono_img_base64 = result.get("mono_img_pdf_base64")
+        if mono_img_base64:
+            mono_img_bytes = base64.b64decode(mono_img_base64)
+            stem = Path(source_filename).stem
+            mono_img_filename = f"{stem}_translated.{target_lang}.pdf"
+            mono_img_file = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
+            mono_img_file.write(mono_img_bytes)
+            mono_img_file.close()
+            mono_img_path = mono_img_file.name
+            logs = log_message(logs, f"Mono: {mono_img_filename} ({len(mono_img_bytes) / 1024:.1f} KB)")
+
+        # Process dual_img PDF
+        dual_img_path = None
+        dual_img_base64 = result.get("dual_img_pdf_base64")
+        if dual_img_base64:
+            dual_img_bytes = base64.b64decode(dual_img_base64)
+            stem = Path(source_filename).stem
+            dual_img_filename = f"{stem}_translated.{target_lang}.dual.pdf"
+            dual_img_file = tempfile.NamedTemporaryFile(delete=False, suffix=".pdf")
+            dual_img_file.write(dual_img_bytes)
+            dual_img_file.close()
+            dual_img_path = dual_img_file.name
+            logs = log_message(logs, f"Dual: {dual_img_filename} ({len(dual_img_bytes) / 1024:.1f} KB)")
+
+        if not mono_img_path and not dual_img_path:
+            logs = log_message(logs, "ERROR: No output PDF in response")
+            return None, None, "Translation failed", "", "\n".join(logs)
+
+        logs = log_message(logs, f"Duration: {duration:.1f} seconds")
+
+        stats_msg = f"""**Translation completed!**
+
+- **Duration:** {duration:.1f} seconds
+- **Target:** {LANGUAGES.get(target_lang, target_lang)}"""
+
+        progress(1.0, desc="Done!")
+
+        return mono_img_path, dual_img_path, "Translation successful!", stats_msg, "\n".join(logs)
+
+    except httpx.TimeoutException:
+        logs = log_message(logs, "ERROR: Translation timed out")
+        return None, None, "Translation timed out", "", "\n".join(logs)
+    except httpx.HTTPStatusError as e:
+        logs = log_message(logs, f"ERROR: HTTP {e.response.status_code}")
+        return None, None, f"HTTP error: {e.response.status_code}", "", "\n".join(logs)
+    except Exception as e:
+        logs = log_message(logs, f"ERROR: {str(e)}")
+        return None, None, f"Error: {str(e)}", "", "\n".join(logs)
+
+
+# Gradio Interface
+with gr.Blocks(title="BabelDocs x Agentic AI MCP") as demo:
+
+    gr.Markdown("""
+# BabelDocs x Agentic AI MCP - PDF Translation with Google Drive Integration
+
+**Translate PDFs directly from Google Drive and save back automatically**
+
+---
+
+## Key Feature: Full Google Drive Workflow in CLAUDE Desktop MCP
+
+```
+"Translate my Q3 report to French and save it to Translations folder"
+                              ↓
+        Claude searches → downloads → translates → uploads → done!
+```
+
+---
+    """)
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("### Input")
+
+            gdrive_url = gr.Textbox(
+                label="Google Drive Link (public)",
+                placeholder="https://drive.google.com/file/d/... or leave empty",
+                info="Paste a public GDrive link, OR upload a local file below",
+            )
+
+            gr.Markdown("**OR**")
+
+            pdf_input = gr.File(
+                label="Upload PDF",
+                file_types=[".pdf"],
+                type="filepath",
+            )
+
+            target_lang = gr.Dropdown(
+                choices=list(LANGUAGES.keys()),
+                value="fr",
+                label="Target Language",
+            )
+
+            translate_btn = gr.Button(
+                "Translate PDF",
+                variant="primary",
+                size="lg",
+            )
+
+        with gr.Column(scale=1):
+            gr.Markdown("### Result")
+
+            status_output = gr.Textbox(
+                label="Status",
+                interactive=False,
+            )
+
+            stats_output = gr.Markdown(label="Statistics")
+
+            gr.Markdown("**Downloads:**")
+            with gr.Row():
+                mono_img_output = gr.File(label="Mono (translated + images)")
+                dual_img_output = gr.File(label="Dual (bilingual + images)")
+
+            logs_output = gr.Textbox(
+                label="Logs",
+                interactive=False,
+                lines=10,
+                max_lines=15,
+            )
+
+    gr.Markdown("""
+---
+
+### How it works
+
+```
+1. Upload PDF or paste GDrive link
+       ↓
+2. Send to Modal cloud (serverless)
+       ↓
+3. BabelDOC with Agentic AI translates text + images, preserves layout
+       ↓
+4. Download translated PDF
+```
+
+---
+
+**Built with:** BabelDOC, Modal, Nebius AI, Gradio | **Hackathon:** Anthropic MCP Track 1
+    """)
+
+    translate_btn.click(
+        fn=translate_pdf_modal,
+        inputs=[pdf_input, gdrive_url, target_lang],
+        outputs=[mono_img_output, dual_img_output, status_output, stats_output, logs_output],
+    )
+
+
+if __name__ == "__main__":
+     demo.launch(
+        server_name="0.0.0.0", 
+        server_port=7860,
+        share=False,
+        ssr_mode=False,  
+    )