fix: resolve 15 bugs and gaps in video scraper pipeline
- Fix extract_visual_data returning 2-tuple instead of 3 (ValueError crash) - Move pytesseract from core deps to [video-full] optional group - Add 30-min timeout + user feedback to video enhancement subprocess - Add scrape_video_impl to MCP server fallback import block - Detect auto-generated YouTube captions via is_generated property - Forward --vision-ocr and --video-playlist through create command - Fix filename collision for non-ASCII video titles (fallback to video_id) - Make _vision_used a proper dataclass field on FrameSubSection - Expose 6 visual params in MCP scrape_video tool - Add install instructions on missing video deps in unified scraper - Update MCP docstring tool counts (25→33, 7 categories) - Add video and word commands to main.py docstring - Document video-full exclusion from [all] deps in pyproject.toml - Update parser registry test count (22→23 for video parser) All 2437 tests passing, 0 failures. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -3,20 +3,21 @@
|
||||
Skill Seeker MCP Server (FastMCP Implementation)
|
||||
|
||||
Modern, decorator-based MCP server using FastMCP for simplified tool registration.
|
||||
Provides 25 tools for generating Claude AI skills from documentation.
|
||||
Provides 33 tools for generating Claude AI skills from documentation.
|
||||
|
||||
This is a streamlined alternative to server.py (2200 lines → 708 lines, 68% reduction).
|
||||
All tool implementations are delegated to modular tool files in tools/ directory.
|
||||
|
||||
**Architecture:**
|
||||
- FastMCP server with decorator-based tool registration
|
||||
- 25 tools organized into 6 categories:
|
||||
- 33 tools organized into 7 categories:
|
||||
* Config tools (3): generate_config, list_configs, validate_config
|
||||
* Scraping tools (8): estimate_pages, scrape_docs, scrape_github, scrape_pdf, scrape_codebase, detect_patterns, extract_test_examples, build_how_to_guides, extract_config_patterns
|
||||
* Scraping tools (10): estimate_pages, scrape_docs, scrape_github, scrape_pdf, scrape_video, scrape_codebase, detect_patterns, extract_test_examples, build_how_to_guides, extract_config_patterns
|
||||
* Packaging tools (4): package_skill, upload_skill, enhance_skill, install_skill
|
||||
* Splitting tools (2): split_config, generate_router
|
||||
* Source tools (4): fetch_config, submit_config, add_config_source, list_config_sources, remove_config_source
|
||||
* Source tools (5): fetch_config, submit_config, add_config_source, list_config_sources, remove_config_source
|
||||
* Vector Database tools (4): export_to_weaviate, export_to_chroma, export_to_faiss, export_to_qdrant
|
||||
* Workflow tools (5): list_workflows, get_workflow, create_workflow, update_workflow, delete_workflow
|
||||
|
||||
**Usage:**
|
||||
# Stdio transport (default, backward compatible)
|
||||
@@ -140,6 +141,7 @@ except ImportError:
|
||||
scrape_docs_impl,
|
||||
scrape_github_impl,
|
||||
scrape_pdf_impl,
|
||||
scrape_video_impl,
|
||||
split_config_impl,
|
||||
submit_config_impl,
|
||||
upload_skill_impl,
|
||||
@@ -250,7 +252,7 @@ async def validate_config(config_path: str) -> str:
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# SCRAPING TOOLS (4 tools)
|
||||
# SCRAPING TOOLS (10 tools)
|
||||
# ============================================================================
|
||||
|
||||
|
||||
@@ -432,6 +434,12 @@ async def scrape_video(
|
||||
description: str | None = None,
|
||||
languages: str | None = None,
|
||||
from_json: str | None = None,
|
||||
visual: bool = False,
|
||||
whisper_model: str | None = None,
|
||||
visual_interval: float | None = None,
|
||||
visual_min_gap: float | None = None,
|
||||
visual_similarity: float | None = None,
|
||||
vision_ocr: bool = False,
|
||||
) -> str:
|
||||
"""
|
||||
Scrape video content and build Claude skill.
|
||||
@@ -444,6 +452,12 @@ async def scrape_video(
|
||||
description: Skill description
|
||||
languages: Transcript language preferences (comma-separated)
|
||||
from_json: Build from extracted JSON file
|
||||
visual: Enable visual frame extraction (requires video-full extras)
|
||||
whisper_model: Whisper model size for local transcription (e.g., base, small, medium, large)
|
||||
visual_interval: Seconds between frame captures (default: 5.0)
|
||||
visual_min_gap: Minimum seconds between kept frames (default: 2.0)
|
||||
visual_similarity: Similarity threshold to skip duplicate frames 0.0-1.0 (default: 0.95)
|
||||
vision_ocr: Use vision model for OCR on extracted frames
|
||||
|
||||
Returns:
|
||||
Video scraping results with file paths.
|
||||
@@ -463,6 +477,18 @@ async def scrape_video(
|
||||
args["languages"] = languages
|
||||
if from_json:
|
||||
args["from_json"] = from_json
|
||||
if visual:
|
||||
args["visual"] = visual
|
||||
if whisper_model:
|
||||
args["whisper_model"] = whisper_model
|
||||
if visual_interval is not None:
|
||||
args["visual_interval"] = visual_interval
|
||||
if visual_min_gap is not None:
|
||||
args["visual_min_gap"] = visual_min_gap
|
||||
if visual_similarity is not None:
|
||||
args["visual_similarity"] = visual_similarity
|
||||
if vision_ocr:
|
||||
args["vision_ocr"] = vision_ocr
|
||||
|
||||
result = await scrape_video_impl(args)
|
||||
if isinstance(result, list) and result:
|
||||
|
||||
@@ -372,6 +372,12 @@ async def scrape_video_tool(args: dict) -> list[TextContent]:
|
||||
- description (str, optional): Skill description
|
||||
- languages (str, optional): Language preferences (comma-separated)
|
||||
- from_json (str, optional): Build from extracted JSON file
|
||||
- visual (bool, optional): Enable visual frame extraction (default: False)
|
||||
- whisper_model (str, optional): Whisper model size (default: base)
|
||||
- visual_interval (float, optional): Seconds between frame captures (default: 5.0)
|
||||
- visual_min_gap (float, optional): Minimum seconds between kept frames (default: 2.0)
|
||||
- visual_similarity (float, optional): Similarity threshold to skip duplicate frames (default: 0.95)
|
||||
- vision_ocr (bool, optional): Use vision model for OCR on frames (default: False)
|
||||
|
||||
Returns:
|
||||
List[TextContent]: Tool execution results
|
||||
@@ -383,6 +389,12 @@ async def scrape_video_tool(args: dict) -> list[TextContent]:
|
||||
description = args.get("description")
|
||||
languages = args.get("languages")
|
||||
from_json = args.get("from_json")
|
||||
visual = args.get("visual", False)
|
||||
whisper_model = args.get("whisper_model")
|
||||
visual_interval = args.get("visual_interval")
|
||||
visual_min_gap = args.get("visual_min_gap")
|
||||
visual_similarity = args.get("visual_similarity")
|
||||
vision_ocr = args.get("vision_ocr", False)
|
||||
|
||||
# Build command
|
||||
cmd = [sys.executable, str(CLI_DIR / "video_scraper.py")]
|
||||
@@ -415,6 +427,20 @@ async def scrape_video_tool(args: dict) -> list[TextContent]:
|
||||
)
|
||||
]
|
||||
|
||||
# Visual extraction parameters
|
||||
if visual:
|
||||
cmd.append("--visual")
|
||||
if whisper_model:
|
||||
cmd.extend(["--whisper-model", whisper_model])
|
||||
if visual_interval is not None:
|
||||
cmd.extend(["--visual-interval", str(visual_interval)])
|
||||
if visual_min_gap is not None:
|
||||
cmd.extend(["--visual-min-gap", str(visual_min_gap)])
|
||||
if visual_similarity is not None:
|
||||
cmd.extend(["--visual-similarity", str(visual_similarity)])
|
||||
if vision_ocr:
|
||||
cmd.append("--vision-ocr")
|
||||
|
||||
# Run video_scraper.py with streaming
|
||||
timeout = 600 # 10 minutes for video extraction
|
||||
|
||||
|
||||
Reference in New Issue
Block a user