feat: Add ZeroGPU, SOTA model fallbacks, and UX improvements

- Add ZeroGPU support (@spaces.GPU decorator) for faster processing
- Add model fallback chain: Qwen2.5-72B -> Llama-3.1-70B
- Auto-validate YouTube URLs with helpful error messages
- Auto-enable frame analysis (removed manual checkbox)
- Better error handling with specific messages
- Comprehensive YAML frontmatter with tags, models, scopes
- Add spaces package to dependencies
- Update tests for new URL validation (36 tests pass)

README.md

@@ -5,37 +5,61 @@ colorFrom: blue
 colorTo: purple
 sdk: gradio
 sdk_version: "6.2.0"
+python_version: "3.11"
 app_file: app.py
 pinned: false
-private: false
+license: mit
+suggested_hardware: zero-a10g
+suggested_storage: small
 hf_oauth: true
+hf_oauth_scopes:
+  - read-repos
+  - inference-api
 hf_oauth_expiration_minutes: 480
+tags:
+  - video
+  - youtube
+  - transcription
+  - whisper
+  - rag
+  - chatbot
+models:
+  - openai/whisper-base
+  - Salesforce/blip-image-captioning-base
+  - Qwen/Qwen2.5-72B-Instruct
+short_description: Download, transcribe, and chat with YouTube videos using AI
 ---
 
 # Video Analyzer
 
-A Gradio application for downloading, transcribing, and analyzing YouTube videos using AI.
+Download, transcribe, and chat with YouTube videos using AI.
 
 ## Features
 
-- **YouTube Video Download**: Download videos or entire playlists
-- **Speech-to-Text**: Transcribe audio using OpenAI Whisper
-- **Visual Analysis**: Extract and describe key frames using BLIP vision model
-- **Knowledge Base**: Store analyzed content in a vector database (ChromaDB)
-- **RAG Chatbot**: Ask questions about your analyzed videos using Qwen2.5-72B
+- **YouTube Video Download**: Supports videos, playlists, and shorts
+- **Speech-to-Text**: Automatic transcription using OpenAI Whisper
+- **Visual Analysis**: Key frame extraction and captioning with BLIP
+- **Knowledge Base**: Vector storage with ChromaDB for semantic search
+- **RAG Chatbot**: Ask questions about your videos using Qwen2.5-72B
 
 ## How to Use
 
-1. **Sign in** with your HuggingFace account (required)
-2. **Analyze Videos** tab:
-   - Paste a YouTube video or playlist URL
-   - Enable/disable frame analysis
-   - Click "Analyze Video" to process
-3. **Chat with Videos** tab:
-   - Ask questions about videos you've analyzed
-   - The AI will search the knowledge base and provide answers
+1. **Sign in** with your HuggingFace account
+2. **Paste** a YouTube URL in the Analyze tab
+3. **Wait** for processing (transcription + frame analysis)
+4. **Chat** about the video content in the Chat tab
 
-## Requirements
+## Tech Stack
 
-- HuggingFace account for OAuth authentication
-- FFmpeg (for audio extraction)
+- **Gradio**: Web UI framework
+- **Whisper**: Speech recognition
+- **BLIP**: Image captioning
+- **ChromaDB**: Vector database
+- **Sentence Transformers**: Text embeddings
+- **HuggingFace Inference API**: SOTA language model
+
+## Limitations
+
+- Works best with videos under 10 minutes
+- Requires HuggingFace login for authentication
+- Knowledge base is session-based (resets on Space restart)

app.py

@@ -16,6 +16,13 @@ from PIL import Image
 from sentence_transformers import SentenceTransformer
 from transformers import BlipForConditionalGeneration, BlipProcessor, pipeline
 
+# Try to import spaces for ZeroGPU support
+try:
+    import spaces
+    ZEROGPU_AVAILABLE = True
+except ImportError:
+    ZEROGPU_AVAILABLE = False
+
 # Initialize ChromaDB client (persistent storage)
 chroma_client = chromadb.Client()
 collection = chroma_client.get_or_create_collection(
@@ -73,8 +80,11 @@ def get_vision_model():
     return processor, model
 
 
-# SOTA chat model via HuggingFace Inference API
-CHAT_MODEL = "Qwen/Qwen2.5-72B-Instruct"
+# Chat models - tested and working with HF Inference API
+CHAT_MODELS = [
+    "Qwen/Qwen2.5-72B-Instruct",  # Primary - works with token
+    "meta-llama/Llama-3.1-70B-Instruct",  # Fallback
+]
 
 
 def download_video(url: str, output_dir: str) -> list[dict]:
@@ -247,25 +257,52 @@ def search_knowledge(query: str, n_results: int = 5) -> list[dict]:
     return matches
 
 
-def process_youtube(
+def is_valid_youtube_url(url: str) -> tuple[bool, str]:
+    """Validate and normalize YouTube URL."""
+    url = url.strip()
+    if not url:
+        return False, "Please enter a YouTube URL."
+
+    # Common YouTube URL patterns
+    valid_patterns = [
+        "youtube.com/watch",
+        "youtube.com/playlist",
+        "youtube.com/shorts",
+        "youtu.be/",
+        "youtube.com/embed",
+        "youtube.com/v/",
+    ]
+
+    if not any(pattern in url.lower() for pattern in valid_patterns):
+        if "youtube" in url.lower() or "youtu" in url.lower():
+            return False, "Invalid YouTube URL format. Please use a full video or playlist URL."
+        return False, "Please enter a valid YouTube URL (e.g., https://youtube.com/watch?v=...)"
+
+    if not url.startswith(("http://", "https://")):
+        url = "https://" + url
+
+    return True, url
+
+
+def _process_youtube_impl(
     url: str,
-    analyze_frames: bool,
     num_frames: int,
     profile: gr.OAuthProfile | None,
     progress: gr.Progress = gr.Progress(),
 ) -> str:
+    """Internal implementation of video processing."""
     if profile is None:
-        return "Please log in to use this feature."
+        return "**Please log in first** using the button at the top right."
 
-    if not url or not url.strip():
-        return "Please enter a YouTube URL."
+    is_valid, result = is_valid_youtube_url(url)
+    if not is_valid:
+        return result
+    url = result  # Use normalized URL
 
     try:
         progress(0, desc="Loading models...")
         whisper_model = get_whisper_model()
-
-        if analyze_frames:
-            vision_processor, vision_model = get_vision_model()
+        vision_processor, vision_model = get_vision_model()
 
         with tempfile.TemporaryDirectory() as tmpdir:
             progress(0.1, desc="Downloading video...")
@@ -302,17 +339,16 @@ def process_youtube(
                     video_result.append("### Transcript")
                     video_result.append(transcript)
 
-                # Analyze frames if enabled
-                if analyze_frames:
-                    progress(base_progress + 0.6 * (1/total), desc=f"Analyzing frames: {item['title']}")
-                    frames = extract_frames(video_path, num_frames)
+                # Analyze frames (always enabled for better context)
+                progress(base_progress + 0.6 * (1/total), desc=f"Analyzing frames: {item['title']}")
+                frames = extract_frames(video_path, num_frames)
 
-                    if frames:
-                        video_result.append("\n### Visual Context")
-                        for j, frame in enumerate(frames):
-                            caption = describe_frame(frame, vision_processor, vision_model)
-                            visual_contexts.append(caption)
-                            video_result.append(f"**Frame {j+1}:** {caption}")
+                if frames:
+                    video_result.append("\n### Visual Context")
+                    for j, frame in enumerate(frames):
+                        caption = describe_frame(frame, vision_processor, vision_model)
+                        visual_contexts.append(caption)
+                        video_result.append(f"**Frame {j+1}:** {caption}")
 
                 # Store in vector DB
                 progress(base_progress + 0.8 * (1/total), desc=f"Storing in knowledge base: {item['title']}")
@@ -322,10 +358,39 @@ def process_youtube(
                 results.append("\n\n".join(video_result))
 
             progress(1.0, desc="Done!")
-            return "\n\n---\n\n".join(results) if results else "No content found to analyze."
+            if results:
+                summary = "\n\n---\n\n".join(results)
+                summary += "\n\n---\n\n**Analysis complete!** Switch to the Chat tab to ask questions about this video."
+                return summary
+            return "No content found to analyze."
 
     except Exception as e:
-        return f"Error: {e!s}"
+        error_msg = str(e)
+        if "unavailable" in error_msg.lower():
+            return "Video unavailable. It may be private, age-restricted, or removed."
+        if "copyright" in error_msg.lower():
+            return "Video blocked due to copyright restrictions."
+        return f"Error analyzing video: {error_msg}"
+
+
+# Apply ZeroGPU decorator if available
+if ZEROGPU_AVAILABLE:
+    @spaces.GPU(duration=300)  # 5 minute timeout for video processing
+    def process_youtube(
+        url: str,
+        num_frames: int,
+        profile: gr.OAuthProfile | None,
+        progress: gr.Progress = gr.Progress(),
+    ) -> str:
+        return _process_youtube_impl(url, num_frames, profile, progress)
+else:
+    def process_youtube(
+        url: str,
+        num_frames: int,
+        profile: gr.OAuthProfile | None,
+        progress: gr.Progress = gr.Progress(),
+    ) -> str:
+        return _process_youtube_impl(url, num_frames, profile, progress)
 
 
 def chat_with_videos(
@@ -361,41 +426,59 @@ def chat_with_videos(
 
     context = "\n\n".join(context_parts)
 
-    # Generate response using SOTA model via HF Inference API
-    try:
-        client = InferenceClient(token=oauth_token.token)
+    # Generate response using HF Inference API with fallback models
+    client = InferenceClient(token=oauth_token.token)
 
-        system_prompt = """You are a helpful assistant that answers questions about video content.
+    system_prompt = """You are a helpful assistant that answers questions about video content.
 You have access to transcripts and visual descriptions from analyzed videos.
 Answer based only on the provided context. If the context doesn't contain enough information, say so.
 Be concise but thorough."""
 
-        user_prompt = f"""Based on the following video content, answer the question.
+    user_prompt = f"""Based on the following video content, answer the question.
 
 Video Content:
 {context}
 
 Question: {message}"""
 
-        response = client.chat.completions.create(
-            model=CHAT_MODEL,
-            messages=[
-                {"role": "system", "content": system_prompt},
-                {"role": "user", "content": user_prompt},
-            ],
-            max_tokens=1024,
-        )
-
-        answer = response.choices[0].message.content
-
-        # Add sources
-        sources = list(set(m["title"] for m in matches))
-        answer += f"\n\n*Sources: {', '.join(sources)}*"
-
-        return answer
-
-    except Exception as e:
-        return f"Error generating response: {e!s}"
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_prompt},
+    ]
+
+    last_error = None
+    used_model = None
+
+    for model in CHAT_MODELS:
+        try:
+            response = client.chat.completions.create(
+                model=model,
+                messages=messages,
+                max_tokens=1024,
+            )
+            answer = response.choices[0].message.content
+            used_model = model.split("/")[-1]  # Get model name without org
+            break
+        except Exception as e:
+            last_error = e
+            continue
+    else:
+        # All models failed
+        error_msg = str(last_error) if last_error else "Unknown error"
+        if "401" in error_msg or "unauthorized" in error_msg.lower():
+            return "Authentication error. Please try logging out and back in."
+        if "429" in error_msg or "rate" in error_msg.lower():
+            return "Rate limit exceeded. Please wait a moment and try again."
+        if "503" in error_msg or "unavailable" in error_msg.lower():
+            return "Model service temporarily unavailable. Please try again later."
+        return f"Could not generate response. Error: {error_msg}"
+
+    # Add sources and model info
+    sources = list(set(m["title"] for m in matches))
+    answer += f"\n\n*Sources: {', '.join(sources)}*"
+    answer += f"\n*Model: {used_model}*"
+
+    return answer
 
 
 def get_knowledge_stats() -> str:
@@ -473,34 +556,29 @@ def create_demo() -> gr.Blocks:
                             lines=1,
                         )
 
-                        gr.Markdown("### Analysis Options")
                         with gr.Row():
-                            analyze_frames = gr.Checkbox(
-                                label="Analyze video frames",
-                                value=True,
-                                info="Extract and describe key frames",
+                            submit_btn = gr.Button(
+                                "Analyze Video",
+                                variant="primary",
+                                size="lg",
+                                scale=3,
                             )
                             num_frames = gr.Slider(
-                                label="Number of frames",
-                                minimum=1,
+                                label="Frames to analyze",
+                                minimum=3,
                                 maximum=10,
                                 value=5,
                                 step=1,
+                                scale=1,
                             )
 
-                        submit_btn = gr.Button(
-                            "Analyze Video",
-                            variant="primary",
-                            size="lg",
-                        )
-
                     with gr.Column(scale=1):
-                        gr.Markdown("### Quick Start")
+                        gr.Markdown("### What happens")
                         gr.Markdown(
-                            "Try these example videos:\n"
-                            "- Short educational clips work best\n"
-                            "- Playlists are supported\n"
-                            "- Videos under 10 min recommended"
+                            "1. Download video\n"
+                            "2. Transcribe audio (Whisper)\n"
+                            "3. Analyze key frames (BLIP)\n"
+                            "4. Store in knowledge base"
                         )
                         gr.Markdown("### Knowledge Base")
                         kb_status_analyze = gr.Markdown()
@@ -512,13 +590,13 @@ def create_demo() -> gr.Blocks:
 
                 gr.Markdown("### Results")
                 output = gr.Markdown(
-                    value="*Results will appear here after analysis*",
+                    value="*Paste a YouTube URL and click Analyze Video*",
                 )
 
                 # Wire up analyze tab
                 submit_btn.click(
                     fn=process_youtube,
-                    inputs=[url_input, analyze_frames, num_frames],
+                    inputs=[url_input, num_frames],
                     outputs=[output],
                 ).then(
                     fn=get_knowledge_stats,

pyproject.toml

@@ -16,6 +16,7 @@ dependencies = [
     "Pillow>=10.0.0",
     "chromadb>=0.4.0",
     "sentence-transformers>=2.2.0",
+    "spaces>=0.19.0",
 ]
 
 [project.optional-dependencies]

requirements.txt

@@ -9,3 +9,4 @@ opencv-python-headless>=4.8.0
 Pillow>=10.0.0
 chromadb>=0.4.0
 sentence-transformers>=2.2.0
+spaces>=0.19.0

tests/test_app.py

@@ -334,6 +334,54 @@ class TestChatWithVideos:
             assert "no videos have been analyzed" in result.lower()
 
 
+class TestUrlValidation:
+    """Tests for YouTube URL validation."""
+
+    def test_valid_watch_url(self):
+        """Test valid watch URL."""
+        from app import is_valid_youtube_url
+
+        is_valid, result = is_valid_youtube_url("https://youtube.com/watch?v=abc123")
+        assert is_valid is True
+
+    def test_valid_short_url(self):
+        """Test valid short URL."""
+        from app import is_valid_youtube_url
+
+        is_valid, result = is_valid_youtube_url("https://youtu.be/abc123")
+        assert is_valid is True
+
+    def test_valid_playlist_url(self):
+        """Test valid playlist URL."""
+        from app import is_valid_youtube_url
+
+        is_valid, result = is_valid_youtube_url("https://youtube.com/playlist?list=abc")
+        assert is_valid is True
+
+    def test_empty_url(self):
+        """Test empty URL returns error."""
+        from app import is_valid_youtube_url
+
+        is_valid, result = is_valid_youtube_url("")
+        assert is_valid is False
+        assert "enter" in result.lower()
+
+    def test_invalid_url(self):
+        """Test invalid URL returns error."""
+        from app import is_valid_youtube_url
+
+        is_valid, result = is_valid_youtube_url("https://example.com/video")
+        assert is_valid is False
+
+    def test_url_without_protocol(self):
+        """Test URL without protocol gets normalized."""
+        from app import is_valid_youtube_url
+
+        is_valid, result = is_valid_youtube_url("youtube.com/watch?v=abc123")
+        assert is_valid is True
+        assert result.startswith("https://")
+
+
 class TestProcessYoutube:
     """Tests for the process_youtube function."""
 
@@ -342,7 +390,7 @@ class TestProcessYoutube:
         from app import process_youtube
 
         mock_progress = MagicMock()
-        result = process_youtube("https://youtube.com/test", True, 5, None, mock_progress)
+        result = process_youtube("https://youtube.com/watch?v=test", 5, None, mock_progress)
         assert "log in" in result.lower()
 
     def test_empty_url_returns_prompt(self):
@@ -350,13 +398,13 @@ class TestProcessYoutube:
         from app import process_youtube
 
         mock_progress = MagicMock()
-        result = process_youtube("", True, 5, MagicMock(), mock_progress)
-        assert "enter a youtube url" in result.lower()
+        result = process_youtube("", 5, MagicMock(), mock_progress)
+        assert "enter" in result.lower()
 
-    def test_whitespace_url_returns_prompt(self):
-        """Test returns prompt for whitespace-only URL."""
+    def test_invalid_url_returns_error(self):
+        """Test returns error for invalid URL."""
         from app import process_youtube
 
         mock_progress = MagicMock()
-        result = process_youtube("   ", True, 5, MagicMock(), mock_progress)
-        assert "enter a youtube url" in result.lower()
+        result = process_youtube("not-a-url", 5, MagicMock(), mock_progress)
+        assert "valid youtube url" in result.lower()

uv.lock

@@ -2004,30 +2004,16 @@ wheels = [
 
 [[package]]
 name = "psutil"
-version = "7.2.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/be/7c/31d1c3ceb1260301f87565f50689dc6da3db427ece1e1e012af22abca54e/psutil-7.2.0.tar.gz", hash = "sha256:2e4f8e1552f77d14dc96fb0f6240c5b34a37081c0889f0853b3b29a496e5ef64", size = 489863, upload-time = "2025-12-23T20:26:24.616Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/a8/8e/b35aae6ed19bc4e2286cac4832e4d522fcf00571867b0a85a3f77ef96a80/psutil-7.2.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:c31e927555539132a00380c971816ea43d089bf4bd5f3e918ed8c16776d68474", size = 129593, upload-time = "2025-12-23T20:26:28.019Z" },
-    { url = "https://files.pythonhosted.org/packages/61/a2/773d17d74e122bbffe08b97f73f2d4a01ef53fb03b98e61b8e4f64a9c6b9/psutil-7.2.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:db8e44e766cef86dea47d9a1fa535d38dc76449e5878a92f33683b7dba5bfcb2", size = 130104, upload-time = "2025-12-23T20:26:30.27Z" },
-    { url = "https://files.pythonhosted.org/packages/0d/e3/d3a9b3f4bd231abbd70a988beb2e3edd15306051bccbfc4472bd34a56e01/psutil-7.2.0-cp313-cp313t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:85ef849ac92169dedc59a7ac2fb565f47b3468fbe1524bf748746bc21afb94c7", size = 180579, upload-time = "2025-12-23T20:26:32.628Z" },
-    { url = "https://files.pythonhosted.org/packages/66/f8/6c73044424aabe1b7824d4d4504029d406648286d8fe7ba8c4682e0d3042/psutil-7.2.0-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:26782bdbae2f5c14ce9ebe8ad2411dc2ca870495e0cd90f8910ede7fa5e27117", size = 183171, upload-time = "2025-12-23T20:26:34.972Z" },
-    { url = "https://files.pythonhosted.org/packages/48/7d/76d7a863340885d41826562225a566683e653ee6c9ba03c9f3856afa7d80/psutil-7.2.0-cp313-cp313t-win_amd64.whl", hash = "sha256:b7665f612d3b38a583391b95969667a53aaf6c5706dc27a602c9a4874fbf09e4", size = 139055, upload-time = "2025-12-23T20:26:36.848Z" },
-    { url = "https://files.pythonhosted.org/packages/a0/48/200054ada0ae4872c8a71db54f3eb6a9af4101680ee6830d373b7fda526b/psutil-7.2.0-cp313-cp313t-win_arm64.whl", hash = "sha256:4413373c174520ae28a24a8974ad8ce6b21f060d27dde94e25f8c73a7effe57a", size = 134737, upload-time = "2025-12-23T20:26:38.784Z" },
-    { url = "https://files.pythonhosted.org/packages/44/86/98da45dff471b93ef5ce5bcaefa00e3038295a7880a77cf74018243d37fb/psutil-7.2.0-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:2f2f53fd114e7946dfba3afb98c9b7c7f376009447360ca15bfb73f2066f84c7", size = 129692, upload-time = "2025-12-23T20:26:40.623Z" },
-    { url = "https://files.pythonhosted.org/packages/50/ee/10eae91ba4ad071c92db3c178ba861f30406342de9f0ddbe6d51fd741236/psutil-7.2.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:e65c41d7e60068f60ce43b31a3a7fc90deb0dfd34ffc824a2574c2e5279b377e", size = 130110, upload-time = "2025-12-23T20:26:42.569Z" },
-    { url = "https://files.pythonhosted.org/packages/87/3a/2b2897443d56fedbbc34ac68a0dc7d55faa05d555372a2f989109052f86d/psutil-7.2.0-cp314-cp314t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:cc66d21366850a4261412ce994ae9976bba9852dafb4f2fa60db68ed17ff5281", size = 181487, upload-time = "2025-12-23T20:26:44.633Z" },
-    { url = "https://files.pythonhosted.org/packages/11/66/44308428f7333db42c5ea7390c52af1b38f59b80b80c437291f58b5dfdad/psutil-7.2.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e025d67b42b8f22b096d5d20f5171de0e0fefb2f0ce983a13c5a1b5ed9872706", size = 184320, upload-time = "2025-12-23T20:26:46.83Z" },
-    { url = "https://files.pythonhosted.org/packages/18/28/d2feadc7f18e501c5ce687c377db7dca924585418fd694272b8e488ea99f/psutil-7.2.0-cp314-cp314t-win_amd64.whl", hash = "sha256:45f6b91f7ad63414d6454fd609e5e3556d0e1038d5d9c75a1368513bdf763f57", size = 140372, upload-time = "2025-12-23T20:26:49.334Z" },
-    { url = "https://files.pythonhosted.org/packages/b2/1d/48381f5fd0425aa054c4ee3de24f50de3d6c347019f3aec75f357377d447/psutil-7.2.0-cp314-cp314t-win_arm64.whl", hash = "sha256:87b18a19574139d60a546e88b5f5b9cbad598e26cdc790d204ab95d7024f03ee", size = 135400, upload-time = "2025-12-23T20:26:51.585Z" },
-    { url = "https://files.pythonhosted.org/packages/40/c5/a49160bf3e165b7b93a60579a353cf5d939d7f878fe5fd369110f1d18043/psutil-7.2.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:977a2fcd132d15cb05b32b2d85b98d087cad039b0ce435731670ba74da9e6133", size = 128116, upload-time = "2025-12-23T20:26:53.516Z" },
-    { url = "https://files.pythonhosted.org/packages/10/a1/c75feb480f60cd768fb6ed00ac362a16a33e5076ec8475a22d8162fb2659/psutil-7.2.0-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:24151011c21fadd94214d7139d7c6c54569290d7e553989bdf0eab73b13beb8c", size = 128925, upload-time = "2025-12-23T20:26:55.573Z" },
-    { url = "https://files.pythonhosted.org/packages/12/ff/e93136587c00a543f4bc768b157fac2c47cd77b180d4f4e5c6efb6ea53a2/psutil-7.2.0-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:91f211ba9279e7c61d9d8f84b713cfc38fa161cb0597d5cb3f1ca742f6848254", size = 154666, upload-time = "2025-12-23T20:26:57.312Z" },
-    { url = "https://files.pythonhosted.org/packages/b8/dd/4c2de9c3827c892599d277a69d2224136800870a8a88a80981de905de28d/psutil-7.2.0-cp36-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f37415188b7ea98faf90fed51131181646c59098b077550246e2e092e127418b", size = 156109, upload-time = "2025-12-23T20:26:58.851Z" },
-    { url = "https://files.pythonhosted.org/packages/81/3f/090943c682d3629968dd0b04826ddcbc760ee1379021dbe316e2ddfcd01b/psutil-7.2.0-cp36-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:0d12c7ce6ed1128cd81fd54606afa054ac7dbb9773469ebb58cf2f171c49f2ac", size = 148081, upload-time = "2025-12-23T20:27:01.318Z" },
-    { url = "https://files.pythonhosted.org/packages/c4/88/c39648ebb8ec182d0364af53cdefe6eddb5f3872ba718b5855a8ff65d6d4/psutil-7.2.0-cp36-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:ca0faef7976530940dcd39bc5382d0d0d5eb023b186a4901ca341bd8d8684151", size = 147376, upload-time = "2025-12-23T20:27:03.347Z" },
-    { url = "https://files.pythonhosted.org/packages/01/a2/5b39e08bd9b27476bc7cce7e21c71a481ad60b81ffac49baf02687a50d7f/psutil-7.2.0-cp37-abi3-win_amd64.whl", hash = "sha256:abdb74137ca232d20250e9ad471f58d500e7743bc8253ba0bfbf26e570c0e437", size = 136910, upload-time = "2025-12-23T20:27:05.289Z" },
-    { url = "https://files.pythonhosted.org/packages/59/54/53839db1258c1eaeb4ded57ff202144ebc75b23facc05a74fd98d338b0c6/psutil-7.2.0-cp37-abi3-win_arm64.whl", hash = "sha256:284e71038b3139e7ab3834b63b3eb5aa5565fcd61a681ec746ef9a0a8c457fd2", size = 133807, upload-time = "2025-12-23T20:27:06.825Z" },
+version = "5.9.8"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/90/c7/6dc0a455d111f68ee43f27793971cf03fe29b6ef972042549db29eec39a2/psutil-5.9.8.tar.gz", hash = "sha256:6be126e3225486dff286a8fb9a06246a5253f4c7c53b475ea5f5ac934e64194c", size = 503247, upload-time = "2024-01-19T20:47:09.517Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e7/e3/07ae864a636d70a8a6f58da27cb1179192f1140d5d1da10886ade9405797/psutil-5.9.8-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:aee678c8720623dc456fa20659af736241f575d79429a0e5e9cf88ae0605cc81", size = 248702, upload-time = "2024-01-19T20:47:36.303Z" },
+    { url = "https://files.pythonhosted.org/packages/b3/bd/28c5f553667116b2598b9cc55908ec435cb7f77a34f2bff3e3ca765b0f78/psutil-5.9.8-cp36-abi3-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8cb6403ce6d8e047495a701dc7c5bd788add903f8986d523e3e20b98b733e421", size = 285242, upload-time = "2024-01-19T20:47:39.65Z" },
+    { url = "https://files.pythonhosted.org/packages/c5/4f/0e22aaa246f96d6ac87fe5ebb9c5a693fbe8877f537a1022527c47ca43c5/psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d06016f7f8625a1825ba3732081d77c94589dca78b7a3fc072194851e88461a4", size = 288191, upload-time = "2024-01-19T20:47:43.078Z" },
+    { url = "https://files.pythonhosted.org/packages/6e/f5/2aa3a4acdc1e5940b59d421742356f133185667dd190b166dbcfcf5d7b43/psutil-5.9.8-cp37-abi3-win32.whl", hash = "sha256:bc56c2a1b0d15aa3eaa5a60c9f3f8e3e565303b465dbf57a1b730e7a2b9844e0", size = 251252, upload-time = "2024-01-19T20:47:52.88Z" },
+    { url = "https://files.pythonhosted.org/packages/93/52/3e39d26feae7df0aa0fd510b14012c3678b36ed068f7d78b8d8784d61f0e/psutil-5.9.8-cp37-abi3-win_amd64.whl", hash = "sha256:8db4c1b57507eef143a15a6884ca10f7c73876cdf5d51e713151c1236a0e68cf", size = 255090, upload-time = "2024-01-19T20:47:56.019Z" },
+    { url = "https://files.pythonhosted.org/packages/05/33/2d74d588408caedd065c2497bdb5ef83ce6082db01289a1e1147f6639802/psutil-5.9.8-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:d16bbddf0693323b8c6123dd804100241da461e41d6e332fb0ba6058f630f8c8", size = 249898, upload-time = "2024-01-19T20:47:59.238Z" },
 ]
 
 [[package]]
@@ -3014,6 +3000,24 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274", size = 11050, upload-time = "2024-12-04T17:35:26.475Z" },
 ]
 
+[[package]]
+name = "spaces"
+version = "0.45.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "gradio" },
+    { name = "httpx" },
+    { name = "packaging" },
+    { name = "psutil" },
+    { name = "pydantic" },
+    { name = "requests" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ae/58/d6a47a6ceb19585fd8d37e1c6d3d463791475760cac44ac33c6aaed17fe0/spaces-0.45.0.tar.gz", hash = "sha256:be411a0425b9f068150c3a4886783b0c1b3e6c15427e5aec306678483423a069", size = 85694, upload-time = "2025-12-19T20:43:18.765Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/b7/38/19d478be4926d6d09a7168679b738243a9b9ab2ea4720e98f0edc4a9f396/spaces-0.45.0-py3-none-any.whl", hash = "sha256:d3f7e1032d345244dadf389e59f528fb22e5a57efda9d4d24242664c6a82e872", size = 105702, upload-time = "2025-12-19T20:43:17.635Z" },
+]
+
 [[package]]
 name = "starlette"
 version = "0.50.0"
@@ -3380,6 +3384,7 @@ dependencies = [
     { name = "opencv-python-headless" },
     { name = "pillow" },
     { name = "sentence-transformers" },
+    { name = "spaces" },
     { name = "torch" },
     { name = "transformers" },
     { name = "yt-dlp" },
@@ -3407,6 +3412,7 @@ requires-dist = [
     { name = "pytest-cov", marker = "extra == 'dev'", specifier = ">=4.1.0" },
     { name = "pytest-playwright", marker = "extra == 'dev'", specifier = ">=0.4.0" },
     { name = "sentence-transformers", specifier = ">=2.2.0" },
+    { name = "spaces", specifier = ">=0.19.0" },
     { name = "torch", specifier = ">=2.0.0" },
     { name = "transformers", specifier = ">=4.36.0" },
     { name = "yt-dlp", specifier = ">=2024.1.0" },