feat(12-02): modify Pipeline for platform-specific processing flow

- Add Bilibili video detection: platform=bilibili and content_type=video
- Skip analyze step for Bilibili videos, use srt step instead
- Skip srt step for non-Bilibili-video content
- Add SRTInput import and step input creation logic
- Update _populate_skipped_step_results for srt step
- Add output_file, paragraphs, tags, corrected to result fields

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

kb_workflow/pipeline/pipeline.py

@@ -21,7 +21,7 @@ from typing import Dict, List, Optional
 from kb_workflow.pipeline.config import get_settings
 from kb_workflow.pipeline.link_parser import LinkParser, ParsedLink
 from kb_workflow.pipeline.processors.base import BaseProcessor
-from kb_workflow.pipeline.schemas import PipelineConfig, PipelineInput, PipelineOutput
+from kb_workflow.pipeline.schemas import PipelineConfig, PipelineInput, PipelineOutput, SRTInput
 
 logger = logging.getLogger(__name__)
 
@@ -174,6 +174,20 @@ class Pipeline:
                 logger.info(f"Skipping ASR for text content type: {parsed.content_type}")
                 continue
 
+            # B站视频：跳过 analyze 步骤，使用 srt 步骤替代
+            is_bilibili_video = (
+                parsed.platform == "bilibili" and
+                parsed.content_type == "video"
+            )
+            if step_name == "analyze" and is_bilibili_video:
+                logger.info(f"Skipping analyze for Bilibili video, using SRT processor instead")
+                continue
+
+            # B站文章/知乎等：跳过 srt 步骤
+            if step_name == "srt" and not is_bilibili_video:
+                logger.info(f"Skipping SRT for non-Bilibili-video content: {parsed.platform}/{parsed.content_type}")
+                continue
+
             processor = self.processors[step_name]
 
             # Mark step as started
@@ -228,10 +242,26 @@ class Pipeline:
                         content_type=parsed.content_type,
                         output_file=str(content_dir / "analysis.md"),
                     )
+                elif step_name == "srt":
+                    # SRT needs srt file from ASR step and metadata
+                    download_result = results.get("download", {})
+                    asr_result = results.get("asr", {})
+                    metadata_file = download_result.get("metadata_file", "")
+                    # SRT file from ASR output
+                    srt_file = asr_result.get("output_files", {}).get("srt", "")
+
+                    step_input = SRTInput(
+                        content_id=parsed.content_id,
+                        platform=parsed.platform,
+                        srt_file=srt_file,
+                        metadata_file=metadata_file,
+                        output_file=str(content_dir / "analysis.md"),
+                        content_type=parsed.content_type,
+                    )
                 elif step_name == "archive":
-                    # Archive needs analysis file from analyze step
+                    # Archive needs analysis file from analyze step (or srt step for Bilibili video)
-                    analyze_result = results.get("analyze", {})
+                    analyze_result = results.get("analyze", {}) or results.get("srt", {})
-                    analysis_file = analyze_result.get("analysis_file", "")
+                    analysis_file = analyze_result.get("analysis_file", "") or analyze_result.get("output_file", "")
 
                     step_input = ArchiveInput(
                         content_id=parsed.content_id,
@@ -261,7 +291,7 @@ class Pipeline:
                     # Add output fields to results
                     for field_name in ["metadata_file", "content_file", "title", "author",
                                         "analysis_file", "summary", "output_files",
-                                        "archive_file", "skipped"]:
+                                        "archive_file", "skipped", "output_file", "paragraphs", "tags", "corrected"]:
                         if hasattr(step_output, field_name):
                             results[step_name][field_name] = getattr(step_output, field_name)
 
@@ -397,3 +427,14 @@ class Pipeline:
                     "analysis_file": str(analysis_path),
                 }
                 logger.info(f"Found existing analysis: {analysis_path}")
+
+        elif step_name == "srt":
+            # Scan for SRT output (same file as analyze - analysis.md)
+            analysis_path = content_dir / "analysis.md"
+            if analysis_path.exists():
+                results["srt"] = {
+                    "success": True,
+                    "error_message": None,
+                    "output_file": str(analysis_path),
+                }
+                logger.info(f"Found existing SRT output: {analysis_path}")