- Import spanAnnotations from schema
- Wrap all delete operations in db.transaction() for atomicity
- Delete spanAnnotations first to satisfy FK constraints, then annotations, candles, chart
- Mark task 4.8 as done in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Reject DELETE ?all=true without chartId with HTTP 400 to prevent
accidental deletion of annotations across all charts.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Import z from zod
- Add CandleSchema validating time, open, high, low, close (number), volume (optional number)
- Add PatternDetectRequestSchema validating candles array and patterns array of non-empty strings
- Use safeParse() and return HTTP 400 with error details on validation failure
- Forward only validated data to the inference service
- Mark task 4.5 as completed in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Validates model_type as a non-empty string using .safeParse(); returns
HTTP 400 with error details on invalid input. Marks task 4.4 as done.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Validate run_id in POST /api/model/load using Zod:
- run_id must be a non-empty string matching /^[a-zA-Z0-9_-]+$/
- Returns HTTP 400 with error details if validation fails
- Validated data is forwarded to the inference service
Marks task 4.3 as complete in tasks.md.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add BatchPredictRequestSchema with Zod to validate pair, timeframe,
start_date, and end_date fields. Returns HTTP 400 with flattened error
details on invalid input. Forward only validated data to the inference
service.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add CandleSchema validating time, open, high, low, close (number) and optional volume
- Add PredictRequestSchema validating pair (non-empty string), timeframe (non-empty string), candles array
- Use safeParse() and return HTTP 400 with error details on invalid input
- Forward only validated data to the inference service
- Mark task 4.1 as done in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add API_KEY environment variable with placeholder value 'change_me_to_a_strong_random_key'
- Include helpful comment explaining its purpose: authentication between Next.js and ML service
- Provide command for generating strong random value: openssl rand -hex 32
- Mark task 3.4 as completed
All 12 Next.js API routes that proxy requests to the ML service
(INFERENCE_API_URL / localhost:8001) now include the X-API-Key header
read from process.env.API_KEY. Affected routes:
- /api/predict
- /api/predict/batch
- /api/model/info
- /api/model/load
- /api/training/start
- /api/training/runs
- /api/training/runs/[run_id] (DELETE)
- /api/training/dataset-info
- /api/training/active
- /api/training/build-dataset
- /api/patterns/available
- /api/patterns/detect
Marks task 3.3 as complete in openspec/changes/code-review-fix/tasks.md.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Import Header, Depends, Security from fastapi
- Add verify_api_key dependency: reads API_KEY env var, checks X-API-Key
header, raises HTTP 401 if key mismatch; fail-open if env var not set
- Apply Depends(verify_api_key) to all 14 non-health endpoints
- /health endpoint remains unauthenticated for liveness probes
- Mark task 3.2 as complete in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Create src/middleware.ts with Next.js middleware
- Reads API_KEY env var and checks X-API-Key header on all /api/* routes
- Skips auth for /api/health endpoint
- Fails open (with warning) when API_KEY is not configured
- Returns 401 Unauthorized when key is missing or mismatched
- Mark task 3.1 as complete in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Replace hardcoded allow_origins=['*'] with dynamic configuration
- Read CORS_ORIGINS environment variable (comma-separated list)
- Default to 'http://localhost:3000' if CORS_ORIGINS is not set
- Support multiple origins by splitting and stripping whitespace from env var
- Validate filename ends with .csv (case-insensitive)
- Validate MIME type is text/* or application/csv or text/csv
- Return HTTP 400 with error message if validation fails
- Mark task 2.4 as complete
- Reject uploads larger than 10MB before reading file content
- Reject CSVs with more than 500,000 data rows after parsing
- Checks placed as early as possible in the handler flow
- Mark task 2.3 as done in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add `import re` to services/ml/app/main.py
- In POST /model/load: validate run_id matches ^[a-zA-Z0-9_-]+$ before DB lookup; use Path.resolve() + directory containment check before loading model artifact
- In DELETE /training/runs/{run_id}: validate run_id matches ^[a-zA-Z0-9_-]+$ before any processing; use Path.resolve() + directory containment check before deleting model artifact
- Both endpoints return HTTP 400 with {"detail": "Invalid run_id format"} on invalid input
- Mark task 2.2 as completed in openspec/changes/code-review-fix/tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Validate that run_id matches /^[a-zA-Z0-9_-]+$ regex before interpolating into the API URL.
Returns HTTP 400 with 'Invalid run_id format' error if validation fails.
This prevents potential URL injection attacks and invalid identifier usage.
Changes:
- Updated docker-compose.yml MLflow service port binding from 5000:5000 to 127.0.0.1:5000:5000
to restrict access to localhost only for security
- Marked task 1.7 as complete in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Changed PostgreSQL service port binding from 5432:5432 to 127.0.0.1:5432:5432 in docker-compose.yml
- This restricts PostgreSQL to listen only on localhost, improving security by preventing access from other interfaces
- Marked task 1.6 as completed
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
All DATABASE_URL values and postgres service env vars now use
\${POSTGRES_USER}, \${POSTGRES_PASSWORD}, \${POSTGRES_DB} interpolation
instead of hardcoded ml_user/ml_password/candle_annotator values.
Also updated pg_isready healthcheck to use the same env vars.
Closes task 1.5.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Remove hardcoded SQL comments containing 'ml_user' and 'ml_password'
- Remove fallback default credentials in DATABASE_URL construction
- Add fail-fast validation: raise RuntimeError if DATABASE_URL env var is missing or empty
- Mark task 1.4 as complete in code-review-fix/tasks.md
- Replace ml_password with change_me_to_a_strong_password placeholder
- Replace ml_user with your_db_user placeholder
- Mark task 1.3 as completed in tasks.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add build_dataset_from_db() that exports candles from DB, runs feature
engineering, and ingests span annotations into labeled CSV
- Call it automatically in _run_training_background before training starts
- Add POST /training/build-dataset endpoint for standalone use
- Add Next.js proxy route /api/training/build-dataset
- Update TrainingPanel: remove dataset-missing block on Start Training,
show informational message that dataset builds automatically
- Rewrite scripts/run-migrations.js for PostgreSQL (was better-sqlite3)
- Rewrite scripts/load-initial-data.js for PostgreSQL (was better-sqlite3)
- Make db connection lazy in src/lib/db/index.ts to avoid build-time errors
when DATABASE_URL is not available in Docker build stage
- Fix SpanAnnotationManager price range calculation: use direct candle
filtering by time range instead of dummy Candle objects that fell back
to 0/0 high/low, causing invisible rectangles
- Add handleDeleteAllAnnotations in page.tsx (deletes all span annotations
and regular annotations for current chart)
- Add 'Delete All Annotations' button in sidebar below TA-Lib panel
