- Replace 6847-line monolithic server.py with 26-line entry point
- All routes now in app/routers/ using Jinja2 templates
- Add plan_node.html template for step details
- Add plan node route to runs router with cache_id lookup
- Backup old server as server_legacy.py
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Changed node click to use cache_id in URL instead of step_id
- Updated route to lookup step by cache_id
- Added input media previews showing thumbnails of each input step
- Enhanced output preview with video/image/audio support
- Added parameters section showing step config
- Updated JavaScript to pass cacheId when clicking nodes
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Use await directly instead of asyncio.to_thread() since the
function is already async.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Provides /help index and /help/{doc_name} routes to view
L1 server and Common library READMEs in the web UI.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
/docs now correctly points to FastAPI's Swagger API docs.
README files can be viewed directly in the git repository.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add load_plan_for_run_with_fallback() that generates plan from recipe
when not found in cache
- Share this helper between plan page and node detail endpoint
- Removes code duplication
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add load_plan_for_run() helper that tries plan_id first, then matches by inputs
- Fix "plan not found" error when clicking plan nodes
- Add inline DAG visualization to recipe detail page with tabs (DAG View / YAML Source)
- Recipe page now uses render_page_with_cytoscape for proper DAG rendering
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Update README with comprehensive documentation covering IPFS-primary mode,
3-phase execution, storage providers, and all API endpoints
- Add /docs routes to serve markdown documentation as styled HTML
- Include common library documentation in web interface
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implements HybridStateManager providing fast local Redis operations
with background IPNS sync for eventual consistency across L1 nodes.
- hybrid_state.py: Centralized state management (cache, claims, analysis, plans, runs)
- Updated execute_cid.py, analyze_cid.py, orchestrate_cid.py to use state manager
- Background IPNS sync (configurable interval, disabled by default)
- Atomic claiming with Redis SETNX for preventing duplicate work
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add /run/{run_id}/plan/node/{step_id} endpoint for node details
- Node click updates URL without full page reload (pushState)
- Browser back/forward works correctly
- Refreshing page preserves selected node via ?node= parameter
- Node details loaded via fetch with partial HTML response
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Reads from environment or .env file.
Must be same on server and workers for consistent cache_ids.
Generate with: openssl rand -hex 32
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add output_ipfs_cid field to RunStatus model
- Handle output_cid from IPFS-primary task results
- Add /ipfs/{cid} redirect route to IPFS gateway
- Add /ipfs/{cid}/raw to fetch and serve IPFS content
- Show IPFS output in run detail when output_hash unavailable
- Display step CIDs on plan page for IPFS_PRIMARY runs
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When IPFS_PRIMARY=true:
- /api/run-recipe uses run_recipe_cid task
- Recipe registered on IPFS before execution
- Input CIDs fetched from cache manager
- Everything flows through IPFS, no local cache
Usage in docker-compose:
environment:
- IPFS_PRIMARY=true
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Complete pipeline with everything on IPFS:
- register_input_cid / register_recipe_cid
- generate_plan_cid (stores plan on IPFS)
- execute_plan_from_cid (fetches plan from IPFS)
- run_recipe_cid (full pipeline, returns output CID)
- run_from_local (convenience: local files → IPFS → run)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Changed default from /data/cache to ~/.artdag/cache for local runs.
Docker sets CACHE_DIR=/data/cache via environment variable.
Files updated:
- tasks/analyze.py
- tasks/orchestrate.py
- app/config.py
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Show numbered step list with cache_id links for each completed step
- Add collapsible "Show Plan JSON" section with full plan data
- Steps show type, name, status badge, and clickable output link
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add get_run_analysis() to RunService to load per-input analysis from
CACHE_DIR/analysis/{hash}.json files. Update runs router and template
to display tempo, beats, energy, and beat timeline visualization.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add get_run_plan() and get_run_artifacts() methods to RunService
- Merge step_results into plan steps to show cache_id per step
- Display output hash links under each completed step
- Use cache manager for artifact path lookups
- Fix RunService constructor to accept database param
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Full implementation of runs, recipes, cache routers with templates
- Auth and storage routers fully migrated
- Jinja2 templates for all L1 pages
- Service layer for auth and storage
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Simplified step execution where:
- Steps receive CIDs, produce CIDs
- No local cache management (IPFS handles it)
- Minimal Redis: just claims + cache_id→CID mapping
- Temp workspace for execution, cleaned up after
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Phase 2 of the full modernization:
- App factory pattern with create_app()
- Settings via dataclass with env vars
- Dependency injection container
- Router stubs for auth, storage, api, recipes, cache, runs
- Service layer stubs for run, recipe, cache
- Repository layer placeholder
Routes are stubs that import from legacy server.py during migration.
Next: Migrate each router fully with templates.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Added completed_count stat for steps executed during run (vs cached_count for
steps already in cache). Also fixed pending_count calculation to account for
completed steps.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- UI recipe run now uses tasks.orchestrate.run_recipe (3-phase)
- Deterministic run_id via compute_run_id for cache deduplication
- Check for already-completed runs before starting
- Rename /api/v2/* endpoints to /api/* (plan, execute, run-recipe, run)
- All recipe runs now go through: analyze → plan → execute
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Check cache_manager.has_content(cache_id) to determine if step is cached
- Show green border for cached nodes in completed runs
- Display artifact preview (video) when clicking on cached nodes
- Add "View" button to access cached artifacts directly
- Simplify node data structure (hasCached instead of outputs array)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
RunStatus now stores:
- plan_id, plan_name for linking to execution plan
- step_results for per-step execution status
- all_outputs for all artifacts from all steps
Plan visualization:
- Shows human-readable step names from recipe structure
- Video/audio artifact preview on node click
- Outputs list with links to cached artifacts
- Stats reflect actual execution status (completed/cached/pending)
Execution:
- Step results include outputs list with cache_ids
- run_plan returns all outputs from all steps
- Support for completed_by_other status
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Instead of only showing cached plans, now attempts to generate
a plan from the recipe if no cached plan is found. This works
for recipe-based runs even if they were started via the legacy
execute_dag path.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add Cytoscape.js infrastructure for interactive DAG visualization
- New run sub-pages: /run/{id}/plan, /run/{id}/analysis, /run/{id}/artifacts
- Plan page shows execution DAG with cached/pending status
- Analysis page displays tempo, beats, energy per input
- Artifacts page lists all cached items with thumbnails
- New /recipe/{id}/dag page for recipe structure visualization
- Add sub-tabs navigation to run detail page
- Add JSON API endpoints for future WebSocket support
- Architecture designed for real-time updates (global Cytoscape instance)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Flower provides a web UI to monitor:
- Active/completed/failed tasks
- Worker status and stats
- Task history and details
Accessible on port 5555.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Previously only displayed the first input. Now shows all inputs with
their names from the recipe (variable_inputs and fixed_inputs).
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add activity_id column to l2_shares table
- Store activity_id when publishing to L2
- Link to /activities/{activity_id} instead of /assets/{name}
- Falls back to asset link if no activity_id
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
After publishing, link to /activities/{activity_id} instead of
/assets/{asset_name} so user sees the published run.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The tasks/ directory for 3-phase execution was shadowing the old tasks.py.
Renamed to legacy_tasks.py and updated all imports.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
New files:
- claiming.py - Redis Lua scripts for atomic task claiming
- tasks/analyze.py - Analysis Celery task
- tasks/execute.py - Step execution with IPFS-backed cache
- tasks/orchestrate.py - Plan orchestration (run_plan, run_recipe)
New API endpoints (/api/v2/):
- POST /api/v2/plan - Generate execution plan
- POST /api/v2/execute - Execute a plan
- POST /api/v2/run-recipe - Full 3-phase pipeline
- GET /api/v2/run/{run_id} - Get run status
Features:
- Hash-based task claiming prevents duplicate work
- Parallel execution within dependency levels
- IPFS-backed cache for durability
- Integration with artdag planning module
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Copy storage_providers.py from L2 (Pinata, web3.storage, NFT.Storage,
Infura, Filebase, Storj, local storage providers)
- Add storage management endpoints: GET/POST/PATCH/DELETE /storage
- Add provider-specific pages at /storage/type/{provider_type}
- Include connection testing via POST /storage/{id}/test
- Add HTML UI pages with dark theme matching L2
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Database: Add description field, remove unique constraint to allow
multiple configs of same provider type
- UI: Main page shows provider types as cards with counts
- UI: Per-type page (/storage/type/{type}) for managing configs
- API: Add get_user_storage_by_type() for filtered queries
- Form: Add description field for distinguishing configs
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Properly unpack cache_manager.put() tuple to get IPFS CID and store
it in PostgreSQL via database.create_cache_item(). This fixes the
"Output has no IPFS CID - cannot publish" error when publishing
from L1 to L2.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Prepares L1 for distributed storage integration with user-provided
storage backends (Pinata, web3.storage, local). The storage config
is synced from L2 or can be configured locally per actor.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
