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"prompt": "Explore how pipeline runs are currently tracked in the codebase:\n\n1. Check the database schema for pipeline_runs table in ki_content or ki_dev\n2. Look at PipelineRepository - how are runs created, updated, and queried?\n3. What fields are available for tracking progress (documents_processed, current_step, etc.)?\n4. How does the Python pipeline.py update run status?\n\nFocus on understanding what data is already being tracked and what would need to be added for live progress updates.",
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"text": "Perfect! Now I have a comprehensive view of the codebase. Let me create a detailed analysis document based on my findings.\n\n## Pipeline Run Tracking Analysis\n\nBased on my exploration of the codebase, here's a comprehensive report on how pipeline runs are currently tracked:\n\n---\n\n## 1. Database Schema for Pipeline Runs\n\n### pipeline_runs Table (ki_content database)\n\n**Current Structure:**\n```sql\nCREATE TABLE `pipeline_runs` (\n `id` int(11) NOT NULL AUTO_INCREMENT,\n `pipeline_id` int(11) NOT NULL,\n `status` enum('pending','running','completed','failed','cancelled') DEFAULT 'pending',\n `started_at` datetime DEFAULT NULL,\n `completed_at` datetime DEFAULT NULL,\n `documents_total` int(11) DEFAULT 0,\n `documents_processed` int(11) DEFAULT 0,\n `documents_failed` int(11) DEFAULT 0,\n `chunks_created` int(11) DEFAULT 0,\n `error_log` text DEFAULT NULL,\n `created_at` datetime DEFAULT current_timestamp(),\n PRIMARY KEY (`id`),\n KEY `idx_pipeline_status` (`pipeline_id`,`status`),\n KEY `idx_created` (`created_at`)\n)\n```\n\n**Available Tracking Fields:**\n- `status`: Run state (pending, running, completed, failed, cancelled)\n- `started_at` \/ `completed_at`: Timestamps for run lifecycle\n- `documents_total`: Total documents to process\n- `documents_processed`: Count of successfully processed documents\n- `documents_failed`: Count of failed documents\n- `chunks_created`: Count of chunks generated\n- `error_log`: Text field for error accumulation\n\n**Current Data Example (Run #1):**\n```\nstatus: running (since 2025-12-23 03:35:10)\ndocuments_total: 0\ndocuments_processed: 0\ndocuments_failed: 0\nchunks_created: 0\nerror_log: null\n```\n\n---\n\n## 2. Repository Implementation (PipelineRepository)\n\n**File:** `\/var\/www\/dev.campus.systemische-tools.de\/src\/Infrastructure\/Persistence\/PipelineRepository.php`\n\n### Run Creation Method\n```php\npublic function createRun(int $pipelineId): int\n{\n $stmt = $this->pdo->prepare(\n 'INSERT INTO pipeline_runs (pipeline_id, status, started_at) VALUES (?, ?, NOW())'\n );\n $stmt->execute([$pipelineId, 'running']);\n return (int) $this->pdo->lastInsertId();\n}\n```\n\n**Limitations:**\n- Only sets initial status to 'running' and started_at timestamp\n- No initial documents_total count is set during creation\n- Returns the run ID for external tracking\n\n### Run Update Method\n```php\npublic function updateRun(int $runId, array $data): void\n{\n \/\/ Supports updating:\n \/\/ - status\n \/\/ - completed_at\n \/\/ - documents_total\n \/\/ - documents_processed\n \/\/ - documents_failed\n \/\/ - chunks_created\n \/\/ - error_log\n \n \/\/ Dynamic field building based on provided data\n}\n```\n\n**Query Methods:**\n- `findRuns(pipelineId, limit=20)`: Get all runs for a pipeline\n- `findRunById(runId)`: Get specific run details\n- `findLatestRun(pipelineId)`: Get most recent run\n- `getStatistics()`: Aggregated statistics across all runs\n\n---\n\n## 3. Pipeline Execution Flow\n\n### PHP Controller (ContentPipelineController)\n**File:** `\/var\/www\/dev.campus.systemische-tools.de\/src\/Controller\/ContentPipelineController.php`\n\n**Key Flow (run method, lines 170-196):**\n```php\npublic function run(string $id): void\n{\n \/\/ 1. Validate pipeline exists\n $pipeline = $this->repository->findById((int) $id);\n \n \/\/ 2. Create run record in DB\n $runId = $this->repository->createRun((int) $id);\n \n \/\/ 3. Launch Python pipeline in background\n $cmd = sprintf(\n 'nohup %s %s all --pipeline-id=%d --run-id=%d > %s 2>&1 &',\n escapeshellarg('\/opt\/scripts\/pipeline\/venv\/bin\/python'),\n escapeshellarg('\/opt\/scripts\/pipeline\/pipeline.py'),\n (int) $id,\n $runId,\n escapeshellarg('\/tmp\/pipeline_run_' . $runId . '.log')\n );\n \n exec($cmd);\n \n \/\/ 4. Redirect with success message\n $_SESSION['success'] = 'Pipeline gestartet (Run #' . $runId . ')';\n}\n```\n\n**Status Monitoring (AJAX endpoint, lines 201-215):**\n```php\npublic function status(string $id): void\n{\n \/\/ Returns latest run status\n $this->json([\n 'pipeline_id' => (int) $id,\n 'run' => $this->repository->findLatestRun((int) $id),\n ]);\n}\n```\n\n**Critical Issue:** The controller passes `--run-id` to the Python script, but the Python code doesn't currently use these parameters!\n\n---\n\n## 4. Python Pipeline (pipeline.py)\n\n**File:** `\/opt\/scripts\/pipeline\/pipeline.py`\n\n**Current Status:**\n- **Does NOT accept or process `--run-id` or `--pipeline-id` arguments**\n- Command signature (line 189): `python pipeline.py all --pipeline-id={id} --run-id={id}`\n- Actual main() function (lines 183-246): Only processes simple commands (scan, process, embed, all, file, status)\n- No integration with `PipelineRepository` or `pipeline_runs` table\n- Python uses its own `db` module (db.py) for MySQL operations, not the PHP repository\n\n**What Python Currently Does:**\n```python\ndef run_full_pipeline():\n \"\"\"Run complete pipeline: scan → process → embed.\"\"\"\n files = run_scan() # Scans for documents\n if files:\n process_queue() # Processes queued items\n else:\n print(\"\\n[2\/3] No new documents to process\")\n embedded = embed_pending_chunks() # Embeds chunks\n print(\"\\nPipeline complete!\")\n```\n\n**Logging to Python Pipeline (db.py, lines 177-209):**\n```python\ndef log(self, level, message, context=None):\n \"\"\"Write to pipeline log (ki_dev database).\"\"\"\n # Writes to ki_dev.pipeline_log table\n # NOT to ki_content.pipeline_runs\n```\n\n---\n\n## 5. Pipeline Steps Configuration\n\n**File:** `pipeline_steps` table (ki_content)\n\n**Example Steps for \"Schulungsunterlagen\" Pipeline (ID=2):**\n- Step 1: detect (Find files)\n- Step 2: validate (Check readability)\n- Step 3: page_split (Split PDFs to images)\n- Step 4: vision_analyze (Vision LLM analysis)\n- Step 5: extract (OCR text extraction)\n- Step 6: structure (Detect headings\/lists)\n- Step 7: segment (Segment by sections)\n- Step 8: chunk (Create semantic chunks)\n- Step 9: metadata_store (Store metadata)\n- Step 10: embed (Create embeddings)\n- Steps 11-17: Additional enrichment steps\n\n**Each Step has:**\n- `step_type`: The processing type\n- `config`: JSON configuration (model, parameters, etc.)\n- `sort_order`: Execution order\n- `enabled`: Whether step runs\n\n---\n\n## 6. Frontend Display\n\n**File:** `\/var\/www\/dev.campus.systemische-tools.de\/src\/View\/content-pipeline\/show.php`\n\n**Run Display Table (lines 131-169):**\n```\nColumns Shown:\n- ID\n- Status (badge colored by status)\n- Gestartet (started_at)\n- Beendet (completed_at)\n- Dokumente (documents_processed \/ documents_total)\n- Chunks (chunks_created)\n- Error indication (documents_failed count)\n```\n\n**Current Limitation:** Displays only static data fetched once when page loads. No live updates implemented.\n\n---\n\n## 7. Current Data Flow Gap\n\n### What's Missing:\n\n1. **Python doesn't read `--run-id` or `--pipeline-id` arguments**\n - These are passed but ignored\n - No way for Python to update the `pipeline_runs` table\n\n2. **No run progress updates from Python**\n - Python logs to `pipeline_log` (ki_dev) but not `pipeline_runs` (ki_content)\n - No mechanism to update `documents_processed`, `documents_failed`, `chunks_created` during execution\n - Run stays in \"running\" state indefinitely\n\n3. **No current_step tracking**\n - No field in `pipeline_runs` to track which step is currently executing\n - No way to know if pipeline is stuck\n\n4. **No per-document progress**\n - `documents_processed` is all-or-nothing\n - No granularity on which document is being processed\n\n5. **No WebSocket\/Server-Sent Events**\n - Frontend polling with AJAX, but no live push updates\n - Status is stale by default\n\n---\n\n## 8. Available Fields for Enhancement\n\n**Currently Available (Can Update):**\n- `status` → Could track: pending, scanning, processing, embedding, analyzing, completed, failed\n- `documents_total` → Set during scan phase\n- `documents_processed` → Update per document\n- `documents_failed` → Track failures\n- `chunks_created` → Track chunk generation\n- `error_log` → Accumulate errors\n\n**Should Add (For Live Progress):**\n- `current_step` (VARCHAR) → Which pipeline step is executing\n- `current_step_progress` (INT) → Step-level progress percentage\n- `last_update_at` (DATETIME) → Heartbeat to detect stalled runs\n- `documents_queued` (INT) → Items in queue vs processed\n- `chunks_processed` (INT) → Chunk processing progress (not just total)\n- `estimated_completion_at` (DATETIME) → ETA based on progress rate\n\n---\n\n## 9. Database Statistics Method\n\nThe repository has a `getStatistics()` method (lines 337-370) that aggregates:\n- Total pipelines count\n- Total runs count\n- Completed vs failed runs\n- Total documents processed (summed across all runs)\n- Total chunks created (summed across all runs)\n\nThis shows the system is designed for aggregate reporting, but individual run progress is not tracked.\n\n---\n\n## Summary: What's Needed for Live Progress Updates\n\n### For Backend (Python):\n1. Parse `--run-id` and `--pipeline-id` command-line arguments\n2. After each major phase, update `pipeline_runs` table with progress\n3. Track which step is executing\n4. Implement heartbeat updates to `last_update_at`\n\n### For Frontend:\n1. Poll `\/content-pipeline\/{id}\/status` endpoint more frequently\n2. Display current step name\n3. Show time elapsed and estimated remaining time\n4. Add real-time progress bars per phase\n\n### For Database:\n1. Add new columns for step-level tracking\n2. Add `last_update_at` for staleness detection\n3. Consider `current_document_id` for detailed progress\n\nThis modular approach allows implementing live updates incrementally without major refactoring."
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