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Author SHA1 Message Date
agent-company 2eabb1d704 Add webhook integration tests covering retry logic and Slack/Discord payloads
22 test cases covering:
- Slack/Discord URL detection
- Generic vs Slack payload formatting
- Exponential backoff retry logic with network/timeout error handling
- Multi-URL dispatch with format auto-detection
- notify_job_completed() and notify_alert() helpers

Closes leeworks-agents/SPARC#1657

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-20 19:15:34 +00:00
AI-Manager a07a0c7fbe Merge pull request 'Fix remaining dark mode issue in Analysis page prose block' (#1628) from feature/1605-dark-mode into main
Fix remaining dark mode issue in Analysis page prose block (#1628)
2026-04-20 06:41:59 +00:00
AI-Manager 43fd2c9575 Merge pull request 'Expand JWT auth integration tests to 33 cases' (#1627) from feature/1624-jwt-auth-tests into main
Expand JWT auth integration tests to 33 cases (#1627)
2026-04-20 06:41:47 +00:00
agent-company d4d43cf9b8 Fix prose-invert to only apply in dark mode on Analysis page
The prose-invert class was applied unconditionally, causing inverted
(light) text in light mode within the AI analysis results section.
Changed to dark:prose-invert so it only activates when dark mode is
enabled.

Note: The broader dark mode feature (issue #1605) is already fully
implemented -- ThemeContext, toggle button, CSS variables, dark:
variants across all pages. This fix addresses the only remaining
unstyled element.

Closes leeworks-agents/SPARC#1605

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-20 06:08:02 +00:00
agent-company 2f2b6382fa Expand JWT auth integration tests from 17 to 33 cases
Add comprehensive edge-case coverage for issue #1624:

- Admin delete user endpoint (5 tests): successful delete, self-delete
  prevention, nonexistent user 404, non-admin 403, missing token rejection
- Admin role change gaps (2 tests): nonexistent user 404, non-admin 403
- Input validation (3 tests): invalid email 422, short password 422,
  missing fields 422 for both register and login
- Token edge cases (4 tests): malformed token, wrong-secret token,
  deleted user token, deleted user refresh
- Token claim verification (1 test): login tokens contain correct claims

All tests use mocked DB fixtures and require no live database.

Closes leeworks-agents/SPARC#1624

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-20 06:05:54 +00:00
AI-Manager 1319530f04 Merge pull request 'ci: enable ruff linting and pytest in CI pipeline' (#1568) from feature/1559-1560-enable-ci-linting-and-tests into main
Merge PR #1568: ci: enable ruff linting and pytest in CI pipeline

Closes #1559
Closes #1560
2026-04-19 23:08:07 +00:00
agent-company b32eebff8a ci: enable ruff linting and pytest in CI pipeline
Uncomment the ruff check and pytest steps in the Gitea Actions build
workflow so that linting violations and test failures block image builds.
Fix all pre-existing ruff violations (E402 import ordering in analyzer.py,
F821 undefined name in api.py, I001 unsorted imports in test files, F401
unused import in test_rate_limit.py).

Closes leeworks-agents/SPARC#1559
Closes leeworks-agents/SPARC#1560

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-19 20:06:10 +00:00
0xWheatyz 68ee19025a ci(build): use docker.io package instead of docker-ce in build jobs
The Debian Bullseye runner image doesn't have the Docker CE
repository configured. docker.io is available from default repos.
2026-04-02 21:28:26 -04:00
0xWheatyz ef97710d1c ci(build): another docker install candiate 2026-04-02 21:21:22 -04:00
0xWheatyz 88812b5967 ci(build): updated the apt command 2026-04-02 21:15:41 -04:00
0xWheatyz 90e58949fc ci: updated the docker install canidate 2026-04-02 21:11:09 -04:00
0xWheatyz bd10925c97 chore: updated package-lock.json 2026-04-02 21:06:34 -04:00
0xWheatyz 89fec43aa2 ci(build): use apt-get with correct Ubuntu package names
Replace apt with apt-get, add -y flag, fix Alpine-style package names
(py3-pip → python3-pip, docker-cli → docker.io), and drop musl-dev.
2026-04-02 20:59:11 -04:00
0xWheatyz 02e1c41126 ci(linters): removed ruff requirement, as causing working builds to fail 2026-04-02 20:57:17 -04:00
0xWheatyz c17a0d006a ci: fix pip install 2026-04-02 20:49:15 -04:00
0xWheatyz c6760a39a1 ci(test): use apt-get with correct Ubuntu packages in workflow
Replace Alpine-style commands (apk, py3-pip, musl-dev) and incorrect
apt usage with proper apt-get invocations and Debian package names for
the ubuntu-latest runner.
2026-04-02 20:47:46 -04:00
0xWheatyz 2ae6280566 ci: fix test to use apt instead of apk 2026-04-02 20:45:41 -04:00
0xWheatyz 9745ed75a8 feat(docker): add registry images to compose services
Add gitea.leeworks.dev image references alongside build directives so
`docker compose up` pulls pre-built images while `--build` still builds
from local sources.
2026-04-02 20:27:56 -04:00
0xWheatyz c649eaf343 fix(proxy): remove double slash in nginx API proxy_pass
API_URL already includes a trailing slash, so the extra slash in
proxy_pass produced //auth/login paths, causing 404s. Also clear
ROOT_PATH since nginx strips /api/ before proxying.
2026-04-02 20:21:47 -04:00
0xWheatyz 7e66d0e7e0 Merge pull request 'deploy: security hardening, multi-model support, S3 storage, analytics, CI improvements (70 commits)' (#4) from leeworks-agents/SPARC:main into main
Reviewed-on: http://gitea.leeworks.dev/0xWheatyz/SPARC/pulls/4
2026-03-31 11:53:44 +00:00
AI-Manager 71465401c6 Merge pull request 'docs: document patent PDF volume mount requirement' (#1374) from feature/docs-patent-volume-mount into main 2026-03-30 17:03:36 +00:00
agent-company 97048917f2 docs: document patent PDF volume mount for containerized deployments
Switch docker-compose.yml from bind mount to a named volume (patent_data)
so downloaded PDFs survive container recreation. Add a "Patent PDF Storage"
section to DEPLOYMENT.md covering Docker Compose, Kubernetes PVC, and S3
alternatives.

Closes leeworks-agents/SPARC#1360

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-30 16:08:02 +00:00
AI-Manager 88abd9574b Merge pull request 'feat: theme-aware chart colors for dark/light mode' (#1348) from feature/1324-dark-mode-variants into main 2026-03-30 15:03:43 +00:00
agent-company e0ed39908e feat: add theme-aware chart colors for dark/light mode support
Replace hardcoded dark-theme hex colors in recharts components
(tooltips, axes) with a useChartTheme hook that reads the current
theme from ThemeContext. Charts now render correctly in both light
and dark mode.

Closes leeworks-agents/SPARC#1324

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-30 14:11:16 +00:00
AI-Manager 87e09b365b Merge pull request 'Add model allow-list validation to analysis endpoints' (#1015) from feature/1013-multi-model into main 2026-03-29 17:03:25 +00:00
agent-company 5d11f514c0 Add model allow-list validation to analysis endpoints
Reject unsupported LLM model identifiers with HTTP 400 on all analysis
endpoints (single, batch, async batch). The SUPPORTED_MODELS list was
already defined for the /models endpoint but not enforced on incoming
requests. This completes the multi-model support feature by adding the
missing server-side validation.

Closes leeworks-agents/SPARC#1013

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-29 16:13:29 +00:00
AI-Manager cbc8f449a1 Merge pull request 'Generate TypeScript API client from OpenAPI spec' (#443) from feature/426-generate-ts-api-client into main
Merge pull request #443: Generate TypeScript API client from OpenAPI spec

Closes leeworks-agents/SPARC#426
2026-03-27 20:42:17 +00:00
agent-company 44620614b6 feat: generate TypeScript API client from OpenAPI spec and add CI freshness check
Closes leeworks-agents/SPARC#426

- Generate schema.d.ts from committed openapi.json using openapi-typescript
- Rewrite types/index.ts to derive all application types from the generated schema
- Add CI step in both build.yaml and test.yaml to verify schema.d.ts stays in sync
- TypeScript compilation passes with zero errors

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 20:09:11 +00:00
AI-Manager c72a44aa56 Merge pull request 'feat: add model picker UI and wire model param through backend' (#353) from feature/351-frontend-model-picker into main 2026-03-27 16:45:05 +00:00
agent-company 6aa71eb17e merge: resolve Batch.tsx conflict between model picker and job history
Combine both useQuery hooks (modelsQuery for model selector, jobsQuery for
job history) and pass selectedModel to analyzeBatch while also triggering
jobsQuery.refetch() on successful submission.
2026-03-27 16:44:47 +00:00
AI-Manager fb52d08387 Merge pull request 'feat: add loading skeletons and error states to Batch page' (#352) from feature/343-batch-loading-states into main 2026-03-27 16:43:40 +00:00
agent-company 223d5f7e5d feat: add model picker to Analysis and Batch pages with full backend wiring
Thread the optional model parameter through the entire analysis pipeline:
- analyzer.py: analyze_company, _analyze_company_safe, analyze_companies,
  and analyze_single_patent now accept and forward model override
- api.py: single company endpoint accepts model query param; batch and
  async batch endpoints pass request.model through to the analyzer
- client.ts: analyzeCompany, analyzeBatch, analyzeBatchAsync accept model;
  add listModels() to fetch available models from GET /models
- Analysis.tsx: add model selector dropdown that loads from /models API
- Batch.tsx: add model selector alongside the workers slider

Users can now pick a specific LLM (GPT-4o, Claude 3.5, Gemini, etc.)
per analysis request, or leave it on the server default.

Closes leeworks-agents/SPARC#351

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 16:13:00 +00:00
agent-company 595516e330 feat: add loading skeletons, error states, and empty state to Batch page
Add a Job History section that loads past jobs via useQuery with:
- Animated skeleton placeholders while the job list is loading
- Error banner with retry button when the API call fails
- Empty state with helpful message when no jobs exist
- Job list cards with status badges and progress bars

Also improve the batch submission error state with a retry button
alongside the existing dismiss button.

Closes leeworks-agents/SPARC#343

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 16:08:49 +00:00
AI-Manager 514e274fdb Merge pull request 'CI: add tsc --noEmit TypeScript type checking to test job' (#269) from feature/260-tsc-ci into main 2026-03-27 11:07:02 +00:00
AI-Manager 3d2c0ea27d Merge pull request 'Docs: document MODEL, SERP_CACHE_TTL_HOURS, LOG_LEVEL in .env.example' (#270) from feature/env-example-updates into main 2026-03-27 11:06:57 +00:00
agent-company f611e3a30c Docs: add MODEL, SERP_CACHE_TTL_HOURS, and LOG_LEVEL to .env.example
These environment variables were already supported in config.py but
were not documented in .env.example, making them hard to discover.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 10:08:52 +00:00
agent-company 2bbf2d70bb CI: add tsc --noEmit TypeScript type checking to test job
Adds a step to install Node.js and run tsc --noEmit in the frontend
directory, catching TypeScript type errors before images are built.
Ruff was already present; this completes issue #260.

Closes leeworks-agents/SPARC#260

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 10:08:06 +00:00
AI-Manager f8ca1b80b1 Merge pull request 'feat: add PDF export for analysis reports' (#171) from feature/export-pdf into main 2026-03-27 05:04:55 +00:00
agent-company 338ac86086 feat: add PDF export for analysis reports
Add a new /export/{company_name}/pdf endpoint that generates a formatted
PDF report using reportlab, including a summary table and all analysis
results. Add the corresponding frontend Export PDF button alongside the
existing Export CSV button on the Analysis page.

Closes leeworks-agents/SPARC#85

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 02:03:53 +00:00
AI-Manager ce31a32322 Merge pull request 'feat: add multi-model support for per-analysis LLM selection' (#64) from feature/multi-model into main 2026-03-26 12:14:25 +00:00
agent-company 449055b026 merge: resolve multi-model conflicts with trends and export endpoints
Keeps model selection, analytics trends, and CSV export endpoints.
2026-03-26 12:14:15 +00:00
AI-Manager 70925fbf04 Merge pull request 'feat: add OpenAPI TypeScript client generation setup' (#63) from feature/openapi-client-gen into main 2026-03-26 12:13:19 +00:00
agent-company 9b2b2c75db merge: resolve openapi-client-gen conflicts with CI typecheck script
Keeps both generate scripts and typecheck script in package.json.
2026-03-26 12:13:08 +00:00
AI-Manager 730f455e2b Merge pull request 'feat: add patent trend charts to the Analytics page' (#62) from feature/trend-charts into main 2026-03-26 12:12:24 +00:00
agent-company 03f8f7fa79 merge: resolve trend-charts conflicts with export and tracked endpoints
Keeps both analytics/trends endpoint and export endpoint from main.
2026-03-26 12:12:09 +00:00
AI-Manager f0edc5a3ae Merge pull request 'feat: add side-by-side patent portfolio comparison view' (#61) from feature/compare-view into main 2026-03-26 12:11:01 +00:00
agent-company f64d1b745f merge: resolve compare-view conflicts with dark mode changes
Combines GitCompareArrows icon import with Sun/Moon and ThemeContext imports.
2026-03-26 12:10:37 +00:00
AI-Manager 513b682dad Merge pull request 'feat: add S3/MinIO object storage support for patent PDFs' (#58) from feature/s3-storage into main 2026-03-26 12:09:49 +00:00
agent-company a6c92fde9f merge: resolve conflicts for S3 storage branch with main
Integrates S3/MinIO storage backend with structured logging changes
from main. Both boto3 and apscheduler retained in requirements.txt.
2026-03-26 12:09:24 +00:00
AI-Manager a4db9439f5 Merge pull request 'feat: add webhook notification support for job completion' (#66) from feature/webhooks into main 2026-03-26 12:08:08 +00:00
AI-Manager bbea16387d Merge pull request 'feat: implement scheduled/recurring analysis with change alerting' (#65) from feature/scheduled-analysis into main 2026-03-26 12:07:46 +00:00
AI-Manager 4e2bcae18a Merge pull request 'feat: add CSV export for company analysis results' (#60) from feature/export-csv into main 2026-03-26 12:06:57 +00:00
AI-Manager b66b8332b6 Merge pull request 'feat: add dark/light mode toggle with localStorage persistence' (#57) from feature/dark-mode into main 2026-03-26 12:06:33 +00:00
AI-Manager c42bf5bf71 Merge pull request 'feat: add cursor-based pagination to /jobs endpoint' (#59) from feature/cursor-pagination into main 2026-03-26 12:06:04 +00:00
AI-Manager 02991b6648 Merge pull request 'feat: add loading skeletons and error retry to Batch and Analytics' (#56) from feature/loading-error-states into main 2026-03-26 12:05:41 +00:00
AI-Manager ab74904845 Merge pull request 'fix: auto-download patent PDF in analyze_single_patent' (#55) from feature/fix-single-patent-download into main 2026-03-26 12:05:10 +00:00
AI-Manager 92197440bf Merge pull request 'feat: add structured logging to serp_api.py' (#54) from feature/structured-logging into main 2026-03-26 12:04:59 +00:00
AI-Manager 301a773622 Merge pull request 'ci: add tsc --noEmit TypeScript type checking to CI pipeline' (#53) from feature/ci-tsc-lint into main 2026-03-26 12:04:39 +00:00
agent-company 2e6b8c7445 feat: add webhook notification support for job completion and alerts
Send HTTP POST notifications to configured webhook URLs when batch
jobs complete or when scheduled analysis detects significant changes.

- Add SPARC/webhooks.py with retry logic (3 attempts, exponential backoff)
- Support generic HTTP POST and Slack-compatible text payloads
- Integrate into batch job completion handler in api.py
- Configure via WEBHOOK_URLS env var (comma-separated)
- Payload includes event type, job ID, status, and summary

Closes leeworks-agents/SPARC#23

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:32:07 +00:00
agent-company f33447eef8 feat: implement scheduled/recurring analysis with change alerting
Add APScheduler-based background task that periodically re-analyzes
tracked companies and alerts on significant patent count changes.

- Add tracked_companies and alerts tables to database schema
- Add SPARC/scheduler.py with configurable interval and threshold
- Add admin endpoints: GET/POST/DELETE /admin/tracked, GET /admin/alerts
- Scheduler starts at app startup; interval via SCHEDULE_INTERVAL_HOURS
- Change threshold configurable via CHANGE_THRESHOLD_PERCENT env var
- apscheduler is optional; graceful fallback if not installed

Closes leeworks-agents/SPARC#22

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:30:43 +00:00
agent-company 04f4d36307 feat: add multi-model support for per-analysis LLM selection
Allow users to choose the LLM model on a per-analysis basis. The
model field is optional in both single and batch analysis requests,
defaulting to the server-configured MODEL env var. The model used
is recorded in the analysis result and database.

- Add model parameter to LLMAnalyzer.analyze_patent_content and
  analyze_patent_portfolio
- Add model field to CompanyAnalysisResult and API response
- Add model field to BatchAnalysisRequest
- Add GET /models endpoint listing supported models and the default
- Store model in llm_messages metadata for attribution

Closes leeworks-agents/SPARC#37

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:28:25 +00:00
agent-company 7a364e6736 feat: add OpenAPI TypeScript client generation setup
Add openapi-typescript devDependency and npm scripts for generating
typed TypeScript schema from the FastAPI OpenAPI spec. Include a
static openapi.json snapshot for offline generation.

- npm run generate: fetch schema from running backend and generate types
- npm run generate:local: generate types from the bundled openapi.json

Closes leeworks-agents/SPARC#26

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:26:06 +00:00
agent-company 52972bbff0 feat: add patent trend charts to the Analytics page
Add GET /analytics/trends endpoint returning per-company analysis
counts by month and analysis type distribution over time. Render
these as a line chart (analyses per company) and stacked bar chart
(analysis types) on the Analytics page using recharts.

Closes leeworks-agents/SPARC#24

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:23:47 +00:00
agent-company c738f785c3 feat: add side-by-side patent portfolio comparison view
Add /compare route with two-panel layout for comparing company patent
portfolios. Each panel shows patent count, analysis timestamp, and
full LLM narrative. The page is responsive (stacks vertically on
mobile) and supports URL params (?a=nvidia&b=intel) for shareability.

Closes leeworks-agents/SPARC#21

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:22:14 +00:00
agent-company 1bd9dccdb8 feat: add CSV export for company analysis results
Add GET /export/{company_name} backend endpoint that returns analysis
records as a downloadable CSV file. Add Export CSV button to the
Analysis page that triggers the download via the API.

Closes leeworks-agents/SPARC#20

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:20:51 +00:00
agent-company 3b6411869d feat: add cursor-based pagination to /jobs endpoint
Add a cursor query parameter to GET /jobs and return a next_cursor
field in the response envelope. Existing clients using only limit
continue to work without modification. The cursor is an opaque token
encoding created_at and job_id for stable keyset pagination.

Closes leeworks-agents/SPARC#25

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:19:01 +00:00
agent-company 9a43f85259 feat: add S3/MinIO object storage support for patent PDFs
Introduce a StorageBackend abstraction (local filesystem and S3) for
patent PDF storage. When STORAGE_BACKEND=s3, PDFs are read/written via
boto3 to an S3-compatible bucket instead of the local filesystem.

- Add SPARC/storage.py with LocalStorageBackend and S3StorageBackend
- Update serp_api.py save_patents and parse_patent_pdf to use storage
- Add storage config vars to config.py and .env.example
- Add optional MinIO service to docker-compose.yml (--profile s3)
- Add boto3 to requirements.txt

Closes leeworks-agents/SPARC#38

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:17:24 +00:00
agent-company a4aa968434 feat: add dark/light mode toggle with localStorage persistence
- Enable Tailwind "class" dark mode strategy
- Use CSS custom properties for theme colors (bg, text, border)
- Add ThemeProvider context with toggle and localStorage persistence
- Add Sun/Moon toggle button in the header navigation
- Inline script in index.html prevents FOUC on page load
- All pages (Layout, Login, Register, ProtectedRoute) support both modes
- Default theme follows system preference (prefers-color-scheme)

Closes leeworks-agents/SPARC#33

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:15:11 +00:00
agent-company 153eb3b968 feat: improve loading and error states on Batch and Analytics pages
Analytics page now shows skeleton loaders (cards and chart placeholders)
while data loads, and displays a retry button when the API call fails.
Batch page error state now shows the actual error message and suggests
user action.

Closes leeworks-agents/SPARC#16

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:11:47 +00:00
agent-company ecc2c37bcd fix: auto-download patent PDF in analyze_single_patent before reading
When the PDF is not on disk, analyze_single_patent now looks up the
cached PDF link from the database and downloads it automatically.
If no link is cached, a clear FileNotFoundError is raised. Also adds
a GET /analyze/patent/{patent_id} API endpoint that exposes this
functionality and returns 404 when the PDF cannot be obtained.

Closes leeworks-agents/SPARC#36

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:08:34 +00:00
agent-company 4696838fb8 ci: add tsc --noEmit TypeScript type checking to CI pipeline
Upgrade lucide-react to v1.7.0 for proper TypeScript declarations and
add a TypeScript type check step to the test workflow. Both ruff (Python)
and tsc --noEmit (TypeScript) now block merging on failure.

Closes leeworks-agents/SPARC#52

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 10:05:55 +00:00
42 changed files with 5045 additions and 218 deletions
+33
View File
@@ -35,8 +35,41 @@ JWT_SECRET=your-secure-jwt-secret-change-in-production
# Defaults to http://localhost:3000,http://localhost:5173 when unset
# CORS_ORIGINS=https://sparc.example.com,https://app.example.com
# ---- Storage ----
# Backend for patent PDF storage: "local" (default) or "s3"
STORAGE_BACKEND=local
# S3/MinIO settings (only used when STORAGE_BACKEND=s3)
# S3_BUCKET=sparc-patents
# S3_ENDPOINT_URL=http://localhost:9000
# AWS_ACCESS_KEY_ID=minioadmin
# AWS_SECRET_ACCESS_KEY=minioadmin
# To start MinIO locally: docker compose --profile s3 up -d minio
# ---- LLM ----
# LLM model to use via OpenRouter
# Supported: anthropic/claude-3.5-sonnet, openai/gpt-4o, openai/gpt-4o-mini,
# google/gemini-pro-1.5, meta-llama/llama-3.1-70b-instruct
# MODEL=anthropic/claude-3.5-sonnet
# ---- Cache ----
# When USE_CACHE=true: check database for cached responses before making API calls
# When USE_CACHE=false: always make fresh API calls (still stores results in database)
USE_CACHE=true
# SERP API cache TTL in hours (how long cached search results are considered fresh)
# SERP_CACHE_TTL_HOURS=24
# ---- Logging ----
# Log level: DEBUG, INFO, WARNING, ERROR, CRITICAL
# LOG_LEVEL=INFO
# ---- Webhooks ----
# Comma-separated list of webhook URLs for job completion and alert notifications
# Supports generic HTTP POST and Slack/Discord incoming webhooks
# WEBHOOK_URLS=https://hooks.slack.com/services/XXX,https://example.com/webhook
+19 -4
View File
@@ -15,7 +15,7 @@ jobs:
- name: Install system dependencies
shell: sh
run: |
apk add --no-cache git python3 py3-pip gcc musl-dev libpq-dev python3-dev
apt-get update && apt-get install -y git python3 python3-pip gcc libpq-dev python3-dev
- name: Checkout code
shell: sh
@@ -26,13 +26,27 @@ jobs:
- name: Install Python dependencies
shell: sh
run: |
pip3 install --break-system-packages -r requirements.txt ruff
pip3 install -r requirements.txt ruff
- name: Run ruff linter
shell: sh
run: |
ruff check SPARC/ tests/
- name: Install Node.js and check TypeScript types
shell: sh
run: |
apt-get install -y nodejs npm
cd frontend
npm ci
npm run generate:local
if ! git diff --quiet src/api/schema.d.ts; then
echo "ERROR: src/api/schema.d.ts is out of date. Run 'npm run generate:local' and commit the result."
git diff src/api/schema.d.ts
exit 1
fi
npx tsc --noEmit
- name: Run pytest
shell: sh
env:
@@ -42,6 +56,7 @@ jobs:
JWT_SECRET: "test-secret-for-ci"
APP_ENV: "development"
run: |
pip3 install pytest
python3 -m pytest tests/ -v --tb=short -x
build-api:
@@ -51,7 +66,7 @@ jobs:
- name: Install dependencies
shell: sh
run: |
apk add --no-cache git docker-cli
apt-get update && apt-get install -y git docker.io
- name: Checkout code
shell: sh
@@ -123,7 +138,7 @@ jobs:
- name: Install dependencies
shell: sh
run: |
apk add --no-cache git docker-cli
apt-get update && apt-get install -y git docker.io
- name: Checkout code
shell: sh
+23 -2
View File
@@ -16,7 +16,7 @@ jobs:
- name: Install system dependencies
shell: sh
run: |
apk add --no-cache git python3 py3-pip gcc musl-dev libpq-dev python3-dev
apt-get update && apt-get install -y git python3 python3-pip gcc libpq-dev python3-dev
- name: Checkout code
shell: sh
@@ -27,13 +27,34 @@ jobs:
- name: Install Python dependencies
shell: sh
run: |
pip3 install --break-system-packages -r requirements.txt ruff
pip3 install -r requirements.txt ruff
- name: Run ruff linter
shell: sh
run: |
ruff check SPARC/ tests/
- name: Install Node.js and frontend dependencies
shell: sh
run: |
apt-get install -y nodejs npm
cd frontend && npm ci
- name: Verify generated API types are up to date
shell: sh
run: |
cd frontend && npm run generate:local
if ! git diff --quiet src/api/schema.d.ts; then
echo "ERROR: src/api/schema.d.ts is out of date. Run 'npm run generate:local' and commit the result."
git diff src/api/schema.d.ts
exit 1
fi
- name: Run TypeScript type check
shell: sh
run: |
cd frontend && npx tsc --noEmit
- name: Run pytest
shell: sh
env:
+35 -20
View File
@@ -10,13 +10,13 @@ from concurrent.futures import ThreadPoolExecutor, as_completed
from typing import Callable
from SPARC import config
logger = logging.getLogger(__name__)
from SPARC.database import DatabaseClient
from SPARC.llm import LLMAnalyzer
from SPARC.serp_api import SERP
from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult, Patent, Patents
logger = logging.getLogger(__name__)
class CompanyAnalyzer:
"""Orchestrates end-to-end company performance analysis via patents."""
@@ -33,7 +33,7 @@ class CompanyAnalyzer:
self.db.connect()
self.db.initialize_schema()
def analyze_company(self, company_name: str, patents: "Patents | None" = None) -> str:
def analyze_company(self, company_name: str, patents: "Patents | None" = None, model: str | None = None) -> str:
"""Analyze a company's performance based on their patent portfolio.
This is the main entry point that orchestrates the full pipeline:
@@ -46,6 +46,7 @@ class CompanyAnalyzer:
Args:
company_name: Name of the company to analyze
patents: Optional pre-fetched Patents result to avoid duplicate API calls
model: Optional LLM model override (e.g. 'openai/gpt-4o')
Returns:
Comprehensive analysis of company's innovation and performance outlook
@@ -100,30 +101,29 @@ class CompanyAnalyzer:
# Analyze the full portfolio with LLM
analysis = self.llm_analyzer.analyze_patent_portfolio(
patents_data=processed_patents, company_name=company_name
patents_data=processed_patents, company_name=company_name, model=model
)
return analysis
def analyze_single_patent(self, patent_id: str, company_name: str) -> str:
def analyze_single_patent(self, patent_id: str, company_name: str, model: str | None = None) -> str:
"""Analyze a single patent by ID.
Prerequisite:
The patent PDF must already exist at ``patents/{patent_id}.pdf``
before calling this method. PDFs are downloaded automatically when
using the batch analysis pipeline (``analyze_company`` or the
``/analyze/batch`` API endpoint). For standalone usage, download
the PDF manually or call ``SERP.save_patents()`` first.
If the patent PDF is not already on disk, this method attempts to
download it automatically by looking up the PDF link in the database
cache. If the link is not cached either, a ``FileNotFoundError`` is
raised with instructions on how to obtain the PDF.
Args:
patent_id: Publication ID of the patent (e.g. "US-11234567-B2")
company_name: Name of the company (for context)
model: Optional LLM model override (e.g. 'openai/gpt-4o')
Returns:
Analysis of the specific patent's innovation quality
Raises:
FileNotFoundError: If the patent PDF is not found at the expected path.
FileNotFoundError: If the patent PDF cannot be found or downloaded.
"""
import os
logger.info("Analyzing patent %s for %s...", patent_id, company_name)
@@ -131,17 +131,29 @@ class CompanyAnalyzer:
patent_path = f"patents/{patent_id}.pdf"
if not os.path.exists(patent_path):
raise FileNotFoundError(
f"Patent PDF not found at '{patent_path}'. "
f"Download the PDF first using SERP.save_patents() or the batch analysis pipeline."
)
# Attempt to download the PDF automatically from cached metadata
cached = self.db.get_cached_patent(patent_id)
pdf_link = cached.get("pdf_link") if cached else None
if pdf_link:
logger.info("PDF not on disk; downloading %s from cached link", patent_id)
patent = SERP.save_patents(
Patent(patent_id=patent_id, pdf_link=pdf_link)
)
patent_path = patent.pdf_path
else:
raise FileNotFoundError(
f"Patent PDF not found at '{patent_path}' and no download link is "
f"cached for '{patent_id}'. Run a company analysis first to populate "
f"the cache, or call SERP.save_patents() with the patent's PDF link."
)
try:
sections = SERP.parse_patent_pdf(patent_path)
minimized_content = SERP.minimize_patent_for_llm(sections)
analysis = self.llm_analyzer.analyze_patent_content(
patent_content=minimized_content, company_name=company_name
patent_content=minimized_content, company_name=company_name, model=model
)
return analysis
@@ -191,18 +203,19 @@ class CompanyAnalyzer:
logger.warning("Failed to process %s: %s", patent.patent_id, e)
return None
def _analyze_company_safe(self, company_name: str) -> CompanyAnalysisResult:
def _analyze_company_safe(self, company_name: str, model: str | None = None) -> CompanyAnalysisResult:
"""Internal wrapper that catches exceptions and returns structured result.
Args:
company_name: Name of the company to analyze
model: Optional LLM model override (e.g. 'openai/gpt-4o')
Returns:
CompanyAnalysisResult with success/failure status
"""
try:
# Delegate to analyze_company which handles SERP/patent caching
analysis = self.analyze_company(company_name)
analysis = self.analyze_company(company_name, model=model)
# Determine patent count from cached SERP query
query_hash = hashlib.sha256(company_name.lower().encode()).hexdigest()
@@ -242,6 +255,7 @@ class CompanyAnalyzer:
companies: list[str],
max_workers: int = 3,
progress_callback: Callable[[str, int, int], None] | None = None,
model: str | None = None,
) -> BatchAnalysisResult:
"""Analyze multiple companies' patent portfolios in batch.
@@ -252,6 +266,7 @@ class CompanyAnalyzer:
companies: List of company names to analyze
max_workers: Maximum concurrent analyses (default 3 to avoid rate limits)
progress_callback: Optional callback(company_name, completed, total)
model: Optional LLM model override (e.g. 'openai/gpt-4o')
Returns:
BatchAnalysisResult containing all individual results and summary stats
@@ -263,7 +278,7 @@ class CompanyAnalyzer:
with ThreadPoolExecutor(max_workers=max_workers) as executor:
future_to_company = {
executor.submit(self._analyze_company_safe, company): company
executor.submit(self._analyze_company_safe, company, model): company
for company in companies
}
+501 -10
View File
@@ -3,13 +3,18 @@
Provides REST API endpoints for analyzing company patent portfolios.
"""
from __future__ import annotations
from contextlib import asynccontextmanager
from datetime import datetime
from typing import Annotated, List
from typing import TYPE_CHECKING, Annotated, List
if TYPE_CHECKING:
from SPARC.database import DatabaseClient
from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Query, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse
from fastapi.responses import JSONResponse, StreamingResponse
from pydantic import BaseModel, EmailStr, Field
from slowapi import Limiter
from slowapi.errors import RateLimitExceeded
@@ -41,6 +46,7 @@ class CompanyAnalysisResponse(BaseModel):
patent_count: int
success: bool
error: str | None = None
model: str | None = None
timestamp: datetime
@@ -54,6 +60,15 @@ class BatchAnalysisResponse(BaseModel):
timestamp: datetime
class CompanyAnalysisRequest(BaseModel):
"""Request model for single company analysis with optional model selection."""
model: str | None = Field(
default=None,
description="LLM model to use (e.g. 'anthropic/claude-3.5-sonnet', 'openai/gpt-4o'). Defaults to server config.",
)
class BatchAnalysisRequest(BaseModel):
"""Request model for batch company analysis."""
@@ -63,6 +78,10 @@ class BatchAnalysisRequest(BaseModel):
max_workers: int = Field(
default=3, ge=1, le=5, description="Max concurrent analyses"
)
model: str | None = Field(
default=None,
description="LLM model to use for all analyses in this batch. Defaults to server config.",
)
class JobStatus(BaseModel):
@@ -77,6 +96,13 @@ class JobStatus(BaseModel):
error: str | None = None
class PaginatedJobsResponse(BaseModel):
"""Paginated response for job listings."""
items: list["JobStatus"]
next_cursor: str | None = None
class HealthResponse(BaseModel):
"""Health check response."""
@@ -133,6 +159,7 @@ def _convert_result(result: CompanyAnalysisResult) -> CompanyAnalysisResponse:
patent_count=result.patent_count,
success=result.success,
error=result.error,
model=result.model,
timestamp=result.timestamp,
)
@@ -169,6 +196,9 @@ async def lifespan(app: FastAPI):
import logging
logging.getLogger(__name__).warning("Marked %d stale jobs as failed on startup", stale)
_db.close()
# Start scheduled analysis if tracked companies are configured
from SPARC.scheduler import start_scheduler
start_scheduler()
yield
# Cleanup
_analyzer = None
@@ -369,6 +399,60 @@ async def delete_user(
return {"message": "User deleted"}
# ============== Tracked Companies Endpoints ==============
class TrackCompanyRequest(BaseModel):
"""Request to add a company to tracking."""
company_name: str = Field(..., min_length=1, max_length=255)
@app.get("/admin/tracked", tags=["Admin"])
async def list_tracked_companies(
_: UserResponse = Depends(get_current_admin),
):
"""List all tracked companies (admin only)."""
db = get_db_client()
return db.list_tracked_companies()
@app.post("/admin/tracked", tags=["Admin"])
async def add_tracked_company(
request: TrackCompanyRequest,
_: UserResponse = Depends(get_current_admin),
):
"""Add a company to the tracked list (admin only)."""
db = get_db_client()
result = db.add_tracked_company(request.company_name)
if not result:
raise HTTPException(status_code=409, detail="Company already tracked")
return result
@app.delete("/admin/tracked/{company_name}", tags=["Admin"])
async def remove_tracked_company(
company_name: str,
_: UserResponse = Depends(get_current_admin),
):
"""Remove a company from the tracked list (admin only)."""
db = get_db_client()
removed = db.remove_tracked_company(company_name)
if not removed:
raise HTTPException(status_code=404, detail="Company not found in tracking list")
return {"message": f"Stopped tracking {company_name}"}
@app.get("/admin/alerts", tags=["Admin"])
async def list_alerts(
limit: int = Query(default=50, ge=1, le=200),
_: UserResponse = Depends(get_current_admin),
):
"""List recent alerts from scheduled analysis (admin only)."""
db = get_db_client()
return db.list_alerts(limit=limit)
# ============== Analytics Endpoint ==============
@@ -389,6 +473,330 @@ async def get_analytics(
)
# ============== Model Selection Endpoints ==============
# Supported models via OpenRouter
SUPPORTED_MODELS = [
{"id": "anthropic/claude-3.5-sonnet", "name": "Claude 3.5 Sonnet", "provider": "Anthropic"},
{"id": "openai/gpt-4o", "name": "GPT-4o", "provider": "OpenAI"},
{"id": "openai/gpt-4o-mini", "name": "GPT-4o Mini", "provider": "OpenAI"},
{"id": "google/gemini-pro-1.5", "name": "Gemini Pro 1.5", "provider": "Google"},
{"id": "meta-llama/llama-3.1-70b-instruct", "name": "Llama 3.1 70B", "provider": "Meta"},
]
_SUPPORTED_MODEL_IDS = {m["id"] for m in SUPPORTED_MODELS}
def _validate_model(model: str | None) -> None:
"""Raise HTTP 400 if *model* is not in the supported allow-list."""
if model is not None and model not in _SUPPORTED_MODEL_IDS:
raise HTTPException(
status_code=400,
detail=(
f"Unsupported model '{model}'. "
f"Supported models: {', '.join(sorted(_SUPPORTED_MODEL_IDS))}"
),
)
@app.get("/models", tags=["System"])
async def list_models():
"""List supported LLM models for analysis.
Returns the available models that can be passed as the `model` field
in analysis requests. The default model is determined by the `MODEL`
environment variable on the server.
"""
return {
"models": SUPPORTED_MODELS,
"default": config.model,
}
@app.get("/analytics/trends", tags=["Analytics"])
async def get_analytics_trends(
days: int = Query(default=90, ge=7, le=365),
_: UserResponse = Depends(get_current_user),
):
"""Get trend data for patent analysis over time.
Returns two datasets:
- ``by_month``: analysis count per company per month
- ``by_type_over_time``: analysis type distribution per month
Args:
days: Number of days to look back (default 90)
Returns:
Trend data suitable for time-series and distribution charts
"""
db = get_db_client()
with db.get_conn() as conn:
with conn.cursor() as cur:
# Analyses per company per month
cur.execute(
"""
SELECT
TO_CHAR(timestamp, 'YYYY-MM') AS month,
company_name,
COUNT(*) AS count
FROM llm_messages
WHERE timestamp >= NOW() - INTERVAL '%s days'
AND is_cached = FALSE
AND company_name IS NOT NULL
GROUP BY month, company_name
ORDER BY month
""",
(days,),
)
by_month_rows = cur.fetchall()
# Analysis type distribution per month
cur.execute(
"""
SELECT
TO_CHAR(timestamp, 'YYYY-MM') AS month,
analysis_type,
COUNT(*) AS count
FROM llm_messages
WHERE timestamp >= NOW() - INTERVAL '%s days'
AND is_cached = FALSE
GROUP BY month, analysis_type
ORDER BY month
""",
(days,),
)
by_type_rows = cur.fetchall()
by_month = [
{"month": row[0], "company_name": row[1], "count": row[2]}
for row in by_month_rows
]
by_type_over_time = [
{"month": row[0], "analysis_type": row[1], "count": row[2]}
for row in by_type_rows
]
return {
"by_month": by_month,
"by_type_over_time": by_type_over_time,
"period_days": days,
}
# ============== Export Endpoints ==============
@app.get("/export/{company_name}", tags=["Export"])
async def export_company_csv(
company_name: str,
_: UserResponse = Depends(get_current_user),
):
"""Export analysis results for a company as a CSV file.
Returns all stored analysis records for the given company, including
analysis type, model used, response text, and timestamp.
Args:
company_name: Company name to export results for
Returns:
CSV file download
"""
import csv
import io
db = get_db_client()
# Query all non-cached analysis results for this company
with db.get_conn() as conn:
with conn.cursor() as cur:
cur.execute(
"""
SELECT company_name, analysis_type, model, response, timestamp
FROM llm_messages
WHERE LOWER(company_name) = LOWER(%s) AND is_cached = FALSE
ORDER BY timestamp DESC
""",
(company_name,),
)
rows = cur.fetchall()
if not rows:
raise HTTPException(status_code=404, detail=f"No analysis results found for '{company_name}'")
output = io.StringIO()
writer = csv.writer(output)
writer.writerow(["company_name", "analysis_type", "model", "analysis", "timestamp"])
for row in rows:
writer.writerow(row)
output.seek(0)
safe_name = company_name.replace(" ", "_").lower()
return StreamingResponse(
iter([output.getvalue()]),
media_type="text/csv",
headers={"Content-Disposition": f'attachment; filename="sparc_{safe_name}_export.csv"'},
)
@app.get("/export/{company_name}/pdf", tags=["Export"])
async def export_company_pdf(
company_name: str,
_: UserResponse = Depends(get_current_user),
):
"""Export analysis results for a company as a formatted PDF report.
Returns all stored analysis records for the given company, including
analysis type, model used, response text, and timestamp, formatted
as a downloadable PDF document.
Args:
company_name: Company name to export results for
Returns:
PDF file download
"""
import io
from reportlab.lib import colors
from reportlab.lib.pagesizes import letter
from reportlab.lib.styles import ParagraphStyle, getSampleStyleSheet
from reportlab.lib.units import inch
from reportlab.platypus import (
Paragraph,
SimpleDocTemplate,
Spacer,
Table,
TableStyle,
)
db = get_db_client()
with db.get_conn() as conn:
with conn.cursor() as cur:
cur.execute(
"""
SELECT company_name, analysis_type, model, response, timestamp
FROM llm_messages
WHERE LOWER(company_name) = LOWER(%s) AND is_cached = FALSE
ORDER BY timestamp DESC
""",
(company_name,),
)
rows = cur.fetchall()
if not rows:
raise HTTPException(status_code=404, detail=f"No analysis results found for '{company_name}'")
buffer = io.BytesIO()
doc = SimpleDocTemplate(
buffer,
pagesize=letter,
rightMargin=0.75 * inch,
leftMargin=0.75 * inch,
topMargin=0.75 * inch,
bottomMargin=0.75 * inch,
)
styles = getSampleStyleSheet()
title_style = ParagraphStyle(
"CustomTitle",
parent=styles["Title"],
fontSize=20,
spaceAfter=6,
)
subtitle_style = ParagraphStyle(
"Subtitle",
parent=styles["Normal"],
fontSize=11,
textColor=colors.grey,
spaceAfter=20,
)
heading_style = ParagraphStyle(
"SectionHeading",
parent=styles["Heading2"],
fontSize=13,
spaceBefore=16,
spaceAfter=8,
textColor=colors.HexColor("#1a1a2e"),
)
body_style = ParagraphStyle(
"BodyText",
parent=styles["Normal"],
fontSize=9,
leading=13,
spaceAfter=10,
)
elements = []
# Title and date
display_name = rows[0][0] # Use the casing from the database
analysis_date = datetime.now().strftime("%Y-%m-%d")
elements.append(Paragraph(f"SPARC Analysis Report: {display_name}", title_style))
elements.append(Paragraph(f"Generated on {analysis_date}", subtitle_style))
# Summary table
summary_data = [
["Total Analyses", str(len(rows))],
["Analysis Types", ", ".join(sorted(set(r[1] for r in rows)))],
["Models Used", ", ".join(sorted(set(r[2] for r in rows)))],
]
summary_table = Table(summary_data, colWidths=[2 * inch, 4.5 * inch])
summary_table.setStyle(
TableStyle(
[
("BACKGROUND", (0, 0), (0, -1), colors.HexColor("#f0f0f5")),
("FONTNAME", (0, 0), (0, -1), "Helvetica-Bold"),
("FONTSIZE", (0, 0), (-1, -1), 9),
("PADDING", (0, 0), (-1, -1), 6),
("GRID", (0, 0), (-1, -1), 0.5, colors.HexColor("#cccccc")),
("VALIGN", (0, 0), (-1, -1), "TOP"),
]
)
)
elements.append(summary_table)
elements.append(Spacer(1, 16))
# Individual analysis sections
for i, row in enumerate(rows, 1):
_, analysis_type, model, response, timestamp = row
ts_str = timestamp.strftime("%Y-%m-%d %H:%M:%S") if hasattr(timestamp, "strftime") else str(timestamp)
elements.append(
Paragraph(f"Analysis {i}: {analysis_type} (via {model})", heading_style)
)
elements.append(
Paragraph(f"<i>Performed: {ts_str}</i>", body_style)
)
# Wrap long response text into paragraphs, escaping XML special chars
safe_response = (
response.replace("&", "&amp;")
.replace("<", "&lt;")
.replace(">", "&gt;")
)
# Split into manageable paragraphs to avoid overflow
for line in safe_response.split("\n"):
if line.strip():
elements.append(Paragraph(line, body_style))
else:
elements.append(Spacer(1, 4))
elements.append(Spacer(1, 10))
doc.build(elements)
buffer.seek(0)
safe_name = company_name.replace(" ", "_").lower()
filename = f"{safe_name}-analysis-{analysis_date}.pdf"
return StreamingResponse(
iter([buffer.getvalue()]),
media_type="application/pdf",
headers={"Content-Disposition": f'attachment; filename="{filename}"'},
)
# ============== System Endpoints ==============
@@ -409,6 +817,7 @@ async def health_check():
)
async def analyze_company(
company_name: str,
model: str | None = Query(default=None, description="LLM model to use (e.g. 'openai/gpt-4o'). Defaults to server config."),
_: UserResponse = Depends(get_current_user),
):
"""Analyze a single company's patent portfolio.
@@ -418,17 +827,51 @@ async def analyze_company(
Args:
company_name: Name of the company to analyze (e.g., "nvidia", "intel")
model: Optional LLM model override
Returns:
Analysis results including patent count, AI insights, and success status
"""
_validate_model(model)
if not _analyzer:
raise HTTPException(status_code=503, detail="Analyzer not initialized")
result = _analyzer._analyze_company_safe(company_name)
result = _analyzer._analyze_company_safe(company_name, model=model)
return _convert_result(result)
@app.get(
"/analyze/patent/{patent_id}",
tags=["Analysis"],
)
async def analyze_single_patent(
patent_id: str,
company_name: str = Query(description="Company name for analysis context"),
_: UserResponse = Depends(get_current_user),
):
"""Analyze a single patent by its publication ID.
If the patent PDF is not already cached locally, the system will attempt
to download it automatically from a previously cached link. If no link
is available, a 404 error is returned.
Args:
patent_id: Patent publication ID (e.g. "US-11234567-B2")
company_name: Company name for analysis context
Returns:
Analysis text for the patent
"""
if not _analyzer:
raise HTTPException(status_code=503, detail="Analyzer not initialized")
try:
analysis = _analyzer.analyze_single_patent(patent_id, company_name)
return {"patent_id": patent_id, "company_name": company_name, "analysis": analysis}
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
@app.post(
"/analyze/batch",
response_model=BatchAnalysisResponse,
@@ -449,12 +892,14 @@ async def analyze_companies_batch(
Returns:
Batch results with individual company analyses and summary statistics
"""
_validate_model(request.model)
if not _analyzer:
raise HTTPException(status_code=503, detail="Analyzer not initialized")
result = _analyzer.analyze_companies(
companies=request.companies,
max_workers=request.max_workers,
model=request.model,
)
return _convert_batch_result(result)
@@ -486,7 +931,7 @@ def _job_row_to_status(row: dict) -> JobStatus:
)
def _run_batch_job(job_id: str, companies: list[str], max_workers: int):
def _run_batch_job(job_id: str, companies: list[str], max_workers: int, model: str | None = None):
"""Background task for batch analysis."""
import json as _json
global _analyzer
@@ -511,6 +956,7 @@ def _run_batch_job(job_id: str, companies: list[str], max_workers: int):
companies=companies,
max_workers=max_workers,
progress_callback=progress_callback,
model=model,
)
batch_response = _convert_batch_result(result)
db.update_job(
@@ -519,8 +965,25 @@ def _run_batch_job(job_id: str, companies: list[str], max_workers: int):
progress=100,
result_json=_json.dumps(batch_response.model_dump(), default=str),
)
# Fire webhook notification
from SPARC.webhooks import notify_job_completed
notify_job_completed(
job_id=job_id,
status="completed",
total_companies=result.total_companies,
successful=result.successful,
failed=result.failed,
)
except Exception as e:
db.update_job(job_id, status="failed", error=str(e))
from SPARC.webhooks import notify_job_completed
notify_job_completed(
job_id=job_id,
status="failed",
total_companies=len(companies),
successful=0,
failed=len(companies),
)
@app.post("/analyze/batch/async", response_model=JobStatus, tags=["Analysis"])
@@ -540,6 +1003,7 @@ async def analyze_companies_async(
Returns:
Job status with job_id for polling
"""
_validate_model(request.model)
global _job_counter
_job_counter += 1
@@ -549,7 +1013,7 @@ async def analyze_companies_async(
job_row = db.create_job(job_id=job_id, total_companies=len(request.companies))
background_tasks.add_task(
_run_batch_job, job_id, request.companies, request.max_workers
_run_batch_job, job_id, request.companies, request.max_workers, request.model
)
return _job_row_to_status(job_row)
@@ -577,24 +1041,51 @@ async def get_job_status(
return _job_row_to_status(job_row)
@app.get("/jobs", response_model=list[JobStatus], tags=["Jobs"])
@app.get("/jobs", response_model=PaginatedJobsResponse, tags=["Jobs"])
async def list_jobs(
status: Annotated[
str | None,
Query(description="Filter by status: pending, running, completed, failed"),
] = None,
limit: Annotated[int, Query(ge=1, le=100)] = 10,
cursor: Annotated[
str | None,
Query(description="Opaque cursor from a previous response's next_cursor field"),
] = None,
_: UserResponse = Depends(get_current_user),
):
"""List all analysis jobs.
"""List analysis jobs with cursor-based pagination.
Pass ``limit`` to control page size. The response includes a ``next_cursor``
field; pass it back as the ``cursor`` query parameter to fetch the next page.
When ``next_cursor`` is ``null``, there are no more results.
Existing clients that use only ``limit`` (without ``cursor``) continue to
work without modification.
Args:
status: Optional filter by job status
limit: Maximum number of jobs to return (default 10, max 100)
cursor: Opaque pagination cursor from a previous response
Returns:
List of job statuses
Paginated list of job statuses
"""
db = _get_job_db()
job_rows = db.list_jobs(status=status, limit=limit)
return [_job_row_to_status(row) for row in job_rows]
# Fetch one extra to determine if there is a next page
job_rows = db.list_jobs(status=status, limit=limit + 1, cursor=cursor)
has_next = len(job_rows) > limit
if has_next:
job_rows = job_rows[:limit]
items = [_job_row_to_status(row) for row in job_rows]
next_cursor = None
if has_next and job_rows:
last = job_rows[-1]
created = last["created_at"]
ts = created.isoformat() if hasattr(created, "isoformat") else str(created)
next_cursor = f"{ts}|{last['job_id']}"
return PaginatedJobsResponse(items=items, next_cursor=next_cursor)
+7
View File
@@ -53,6 +53,13 @@ root_path = os.getenv("ROOT_PATH", "")
# Used for safety checks (e.g., refusing default JWT secret in production)
app_env = os.getenv("APP_ENV", "development")
# Storage backend: "local" (default) or "s3" for S3/MinIO object storage
storage_backend = os.getenv("STORAGE_BACKEND", "local")
s3_bucket = os.getenv("S3_BUCKET", "sparc-patents")
s3_endpoint_url = os.getenv("S3_ENDPOINT_URL", "")
s3_access_key = os.getenv("AWS_ACCESS_KEY_ID", "")
s3_secret_key = os.getenv("AWS_SECRET_ACCESS_KEY", "")
# CORS allowed origins (comma-separated)
# Defaults to localhost dev origins when unset
_cors_origins_raw = os.getenv("CORS_ORIGINS", "")
+139 -7
View File
@@ -192,6 +192,35 @@ class DatabaseClient:
ON jobs(status)
""")
# Create tracked companies table for scheduled analysis
cursor.execute("""
CREATE TABLE IF NOT EXISTS tracked_companies (
id SERIAL PRIMARY KEY,
company_name VARCHAR(255) UNIQUE NOT NULL,
last_patent_count INTEGER DEFAULT 0,
last_analysis_at TIMESTAMP,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)
""")
# Create alerts table for significant changes
cursor.execute("""
CREATE TABLE IF NOT EXISTS alerts (
id SERIAL PRIMARY KEY,
company_name VARCHAR(255) NOT NULL,
alert_type VARCHAR(50) NOT NULL,
message TEXT NOT NULL,
old_value NUMERIC,
new_value NUMERIC,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
)
""")
cursor.execute("""
CREATE INDEX IF NOT EXISTS idx_alerts_company
ON alerts(company_name)
""")
self.conn.commit()
@staticmethod
@@ -568,20 +597,45 @@ class DatabaseClient:
self,
status: Optional[str] = None,
limit: int = 10,
cursor: Optional[str] = None,
) -> List[Dict]:
"""List jobs, optionally filtered by status."""
query = "SELECT * FROM jobs"
"""List jobs with optional status filter and cursor-based pagination.
Args:
status: Optional status filter (pending, running, completed, failed).
limit: Maximum number of jobs to return.
cursor: Opaque cursor (``created_at|job_id``) from a previous
response. When provided, only jobs older than the cursor are
returned.
Returns:
List of job dicts ordered by created_at descending.
"""
conditions: list[str] = []
params: list = []
if status:
query += " WHERE status = %s"
conditions.append("status = %s")
params.append(status)
query += " ORDER BY created_at DESC LIMIT %s"
if cursor:
try:
ts_str, cursor_job_id = cursor.rsplit("|", 1)
conditions.append("(created_at, job_id) < (%s, %s)")
params.extend([ts_str, cursor_job_id])
except ValueError:
pass # Ignore malformed cursors; return from start
query = "SELECT * FROM jobs"
if conditions:
query += " WHERE " + " AND ".join(conditions)
query += " ORDER BY created_at DESC, job_id DESC LIMIT %s"
params.append(limit)
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(query, params)
return [dict(row) for row in cursor.fetchall()]
with conn.cursor(cursor_factory=RealDictCursor) as cur:
cur.execute(query, params)
return [dict(row) for row in cur.fetchall()]
def mark_stale_jobs_failed(self) -> int:
"""Mark any jobs in 'running' or 'pending' state as 'failed'.
@@ -803,3 +857,81 @@ class DatabaseClient:
with conn.cursor() as cursor:
cursor.execute("SELECT COUNT(*) FROM users")
return cursor.fetchone()[0]
# Tracked Companies Methods
def add_tracked_company(self, company_name: str) -> Optional[Dict]:
"""Add a company to the tracking list."""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
try:
cursor.execute(
"INSERT INTO tracked_companies (company_name) VALUES (%s) RETURNING *",
(company_name,),
)
row = cursor.fetchone()
conn.commit()
return dict(row) if row else None
except Exception:
conn.rollback()
return None
def remove_tracked_company(self, company_name: str) -> bool:
"""Remove a company from the tracking list."""
with self.get_conn() as conn:
with conn.cursor() as cursor:
cursor.execute(
"DELETE FROM tracked_companies WHERE LOWER(company_name) = LOWER(%s)",
(company_name,),
)
conn.commit()
return cursor.rowcount > 0
def list_tracked_companies(self) -> List[Dict]:
"""List all tracked companies."""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute("SELECT * FROM tracked_companies ORDER BY company_name")
return [dict(row) for row in cursor.fetchall()]
def update_tracked_company(
self, company_name: str, patent_count: int
) -> None:
"""Update the last analysis stats for a tracked company."""
with self.get_conn() as conn:
with conn.cursor() as cursor:
cursor.execute(
"""UPDATE tracked_companies
SET last_patent_count = %s, last_analysis_at = CURRENT_TIMESTAMP
WHERE LOWER(company_name) = LOWER(%s)""",
(patent_count, company_name),
)
conn.commit()
def store_alert(
self,
company_name: str,
alert_type: str,
message: str,
old_value: float | None = None,
new_value: float | None = None,
) -> None:
"""Record an alert for a significant change."""
with self.get_conn() as conn:
with conn.cursor() as cursor:
cursor.execute(
"""INSERT INTO alerts (company_name, alert_type, message, old_value, new_value)
VALUES (%s, %s, %s, %s, %s)""",
(company_name, alert_type, message, old_value, new_value),
)
conn.commit()
def list_alerts(self, limit: int = 50) -> List[Dict]:
"""List recent alerts."""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"SELECT * FROM alerts ORDER BY created_at DESC LIMIT %s",
(limit,),
)
return [dict(row) for row in cursor.fetchall()]
+18 -12
View File
@@ -40,12 +40,13 @@ class LLMAnalyzer:
else:
self.client = None
def analyze_patent_content(self, patent_content: str, company_name: str) -> str:
def analyze_patent_content(self, patent_content: str, company_name: str, model: str | None = None) -> str:
"""Analyze patent content to estimate company innovation and performance.
Args:
patent_content: Minimized patent text (abstract, claims, summary)
company_name: Name of the company for context
model: Optional model override (e.g. "openai/gpt-4o"). Defaults to config.
Returns:
Analysis text describing innovation quality and potential impact
@@ -63,6 +64,8 @@ Patent Content:
Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals about the company's technical direction and competitive advantage."""
effective_model = model or self.model
if self.test_mode:
logger.debug("TEST MODE - Prompt that would be sent to LLM:\n%s", prompt)
return "[TEST MODE - No API call made]"
@@ -81,7 +84,7 @@ Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals
response=cached["response"],
company_name=company_name,
analysis_type="single_patent",
model=self.model,
model=effective_model,
metadata={
"patent_content_length": len(patent_content),
"cache_hit": True,
@@ -94,7 +97,7 @@ Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals
# Call API if no cache hit and client is available
if self.client:
response = self.client.chat.completions.create(
model=self.model,
model=effective_model,
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
@@ -106,7 +109,7 @@ Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals
response=response_text,
company_name=company_name,
analysis_type="single_patent",
model=self.model,
model=effective_model,
metadata={"patent_content_length": len(patent_content)},
token_usage={
"prompt_tokens": response.usage.prompt_tokens,
@@ -124,13 +127,13 @@ Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals
response=placeholder,
company_name=company_name,
analysis_type="single_patent",
model=self.model,
model=effective_model,
metadata={"patent_content_length": len(patent_content), "pending": True}
)
return placeholder
def analyze_patent_portfolio(
self, patents_data: list[Dict[str, str]], company_name: str
self, patents_data: list[Dict[str, str]], company_name: str, model: str | None = None
) -> str:
"""Analyze multiple patents to estimate overall company performance.
@@ -165,13 +168,16 @@ Patent Portfolio:
Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the company's innovation strength and performance outlook."""
effective_model = model or self.model
if self.test_mode:
logger.debug("TEST MODE - Portfolio prompt:\n%s", prompt)
return "[TEST MODE]"
metadata = {
"patent_count": len(patents_data),
"patent_ids": [p['patent_id'] for p in patents_data]
"patent_ids": [p['patent_id'] for p in patents_data],
"model": effective_model,
}
# Check cache first
@@ -188,7 +194,7 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
response=cached["response"],
company_name=company_name,
analysis_type="portfolio",
model=self.model,
model=effective_model,
metadata={
**metadata,
"cache_hit": True,
@@ -202,7 +208,7 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
if self.client:
try:
response = self.client.chat.completions.create(
model=self.model,
model=effective_model,
max_tokens=2048,
messages=[{"role": "user", "content": prompt}],
)
@@ -215,7 +221,7 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
response=response_text,
company_name=company_name,
analysis_type="portfolio",
model=self.model,
model=effective_model,
metadata=metadata,
token_usage={
"prompt_tokens": response.usage.prompt_tokens,
@@ -235,7 +241,7 @@ Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the co
response=placeholder,
company_name=company_name,
analysis_type="portfolio",
model=self.model,
model=effective_model,
metadata={**metadata, "pending": True}
)
return placeholder
+109
View File
@@ -0,0 +1,109 @@
"""Scheduled patent analysis for tracked companies.
Uses APScheduler to periodically re-analyze tracked companies and
detect significant changes in patent counts.
"""
import logging
import os
from SPARC import config
from SPARC.analyzer import CompanyAnalyzer
from SPARC.database import DatabaseClient
logger = logging.getLogger(__name__)
# Configurable via environment variable (in hours, default 24)
SCHEDULE_INTERVAL_HOURS = int(os.getenv("SCHEDULE_INTERVAL_HOURS", "24"))
# Patent count change threshold (percentage) to trigger an alert
CHANGE_THRESHOLD_PERCENT = int(os.getenv("CHANGE_THRESHOLD_PERCENT", "20"))
def run_scheduled_analysis() -> None:
"""Re-analyze all tracked companies and check for significant changes."""
db = DatabaseClient(config.database_url)
db.connect()
db.initialize_schema()
tracked = db.list_tracked_companies()
if not tracked:
logger.info("No tracked companies configured; skipping scheduled analysis")
return
logger.info("Running scheduled analysis for %d tracked companies", len(tracked))
analyzer = CompanyAnalyzer(db_client=db)
for company_row in tracked:
name = company_row["company_name"]
old_count = company_row.get("last_patent_count", 0) or 0
try:
result = analyzer._analyze_company_safe(name)
if result.success:
new_count = result.patent_count
# Update tracking record
db.update_tracked_company(name, new_count)
# Check for significant change
if old_count > 0:
delta_pct = abs(new_count - old_count) / old_count * 100
if delta_pct >= CHANGE_THRESHOLD_PERCENT:
direction = "increased" if new_count > old_count else "decreased"
message = (
f"Patent count for {name} {direction} by {delta_pct:.0f}% "
f"({old_count} -> {new_count})"
)
logger.warning("ALERT: %s", message)
db.store_alert(
company_name=name,
alert_type="patent_count_change",
message=message,
old_value=old_count,
new_value=new_count,
)
elif new_count > 0:
# First analysis -- record baseline
logger.info("Baseline for %s: %d patents", name, new_count)
else:
logger.warning("Scheduled analysis failed for %s: %s", name, result.error)
except Exception as e:
logger.error("Error analyzing tracked company %s: %s", name, e)
db.close()
logger.info("Scheduled analysis complete")
def start_scheduler() -> None:
"""Start the APScheduler background scheduler.
Safe to call at application startup. If apscheduler is not installed,
the function logs a warning and returns without starting anything.
"""
try:
from apscheduler.schedulers.background import BackgroundScheduler
except ImportError:
logger.warning(
"apscheduler not installed; scheduled analysis disabled. "
"Install with: pip install apscheduler"
)
return
scheduler = BackgroundScheduler()
scheduler.add_job(
run_scheduled_analysis,
"interval",
hours=SCHEDULE_INTERVAL_HOURS,
id="scheduled_patent_analysis",
replace_existing=True,
)
scheduler.start()
logger.info(
"Scheduled patent analysis started (every %d hours, threshold %d%%)",
SCHEDULE_INTERVAL_HOURS,
CHANGE_THRESHOLD_PERCENT,
)
+37 -15
View File
@@ -1,5 +1,5 @@
import io
import logging
import os
import re
from datetime import datetime, timedelta
from typing import Dict
@@ -9,10 +9,21 @@ import requests
import serpapi
from SPARC import config
from SPARC.storage import StorageBackend, get_storage_backend
from SPARC.types import Patent, Patents
logger = logging.getLogger(__name__)
# Module-level storage instance (lazy-initialized)
_storage: StorageBackend | None = None
def _get_storage() -> StorageBackend:
global _storage
if _storage is None:
_storage = get_storage_backend()
return _storage
class SERP:
def query(company: str, days_back: int = None) -> Patents:
@@ -63,8 +74,9 @@ class SERP:
return Patents(patents=patent_ids)
def save_patents(patent: Patent) -> Patent:
"""
Save the patent PDF to the patents folder, skipping download if already cached.
"""Save the patent PDF to storage, skipping download if already cached.
Uses the configured storage backend (local filesystem or S3).
Args:
patent: Patent object
@@ -72,36 +84,46 @@ class SERP:
Returns:
Patent object with updated PDF path
"""
pdf_path = f"patents/{patent.patent_id}.pdf"
os.makedirs("patents", exist_ok=True)
storage = _get_storage()
key = f"{patent.patent_id}.pdf"
if not (os.path.exists(pdf_path) and os.path.getsize(pdf_path) > 0):
if not storage.exists(key):
logger.info("Downloading PDF for %s", patent.patent_id)
response = requests.get(patent.pdf_link)
with open(pdf_path, "wb") as f:
f.write(response.content)
logger.debug("Saved %d bytes to %s", len(response.content), pdf_path)
storage.write(key, response.content)
logger.debug("Saved %d bytes for %s", len(response.content), patent.patent_id)
else:
logger.debug("Using cached PDF for %s at %s", patent.patent_id, pdf_path)
logger.debug("Using cached PDF for %s", patent.patent_id)
patent.pdf_path = pdf_path
patent.pdf_path = storage.path_for(key)
return patent
def parse_patent_pdf(pdf_path: str) -> Dict:
"""Extract structured sections from patent PDF.
Extracts all major sections from a patent PDF including abstract,
claims, summary, and detailed description.
claims, summary, and detailed description. Supports both local file
paths and S3 URIs (s3://bucket/key).
Args:
pdf_path: Path to the patent PDF file
pdf_path: Local path or S3 URI to the patent PDF file
Returns:
Dictionary containing all extracted sections
"""
logger.debug("Parsing patent PDF: %s", pdf_path)
with pdfplumber.open(pdf_path) as pdf:
if pdf_path.startswith("s3://"):
# Read from S3 via storage backend
storage = _get_storage()
# Extract key from "s3://bucket/key"
key = pdf_path.split("/", 3)[-1]
data = storage.read(key)
pdf_file: io.BytesIO | str = io.BytesIO(data)
else:
pdf_file = pdf_path
with pdfplumber.open(pdf_file) as pdf:
# Extract all text
full_text = ""
for page in pdf.pages:
+171
View File
@@ -0,0 +1,171 @@
"""Patent PDF storage abstraction.
Provides a unified interface for reading and writing patent PDF files,
with pluggable backends for local filesystem and S3-compatible object
storage (e.g., MinIO, AWS S3).
"""
import logging
import os
from abc import ABC, abstractmethod
from SPARC import config
logger = logging.getLogger(__name__)
class StorageBackend(ABC):
"""Abstract base class for patent PDF storage."""
@abstractmethod
def read(self, key: str) -> bytes:
"""Read a file by key.
Args:
key: Storage key (e.g., "US-12345678-B2.pdf")
Returns:
File contents as bytes.
Raises:
FileNotFoundError: If the file does not exist.
"""
@abstractmethod
def write(self, key: str, data: bytes) -> None:
"""Write data to storage.
Args:
key: Storage key (e.g., "US-12345678-B2.pdf")
data: File contents as bytes.
"""
@abstractmethod
def exists(self, key: str) -> bool:
"""Check if a file exists in storage.
Args:
key: Storage key.
Returns:
True if the file exists and has non-zero size.
"""
@abstractmethod
def path_for(self, key: str) -> str:
"""Return a path or URI suitable for downstream consumers.
For local storage this is a filesystem path; for S3 it is the
object key (callers that need a local file should use read()
and write to a temporary location).
"""
class LocalStorageBackend(StorageBackend):
"""Store patent PDFs on the local filesystem under a directory."""
def __init__(self, base_dir: str = "patents"):
self.base_dir = base_dir
os.makedirs(self.base_dir, exist_ok=True)
def _full_path(self, key: str) -> str:
return os.path.join(self.base_dir, key)
def read(self, key: str) -> bytes:
path = self._full_path(key)
if not os.path.exists(path):
raise FileNotFoundError(f"File not found: {path}")
with open(path, "rb") as f:
return f.read()
def write(self, key: str, data: bytes) -> None:
path = self._full_path(key)
os.makedirs(os.path.dirname(path) or self.base_dir, exist_ok=True)
with open(path, "wb") as f:
f.write(data)
logger.debug("Wrote %d bytes to %s", len(data), path)
def exists(self, key: str) -> bool:
path = self._full_path(key)
return os.path.exists(path) and os.path.getsize(path) > 0
def path_for(self, key: str) -> str:
return self._full_path(key)
class S3StorageBackend(StorageBackend):
"""Store patent PDFs in an S3-compatible bucket."""
def __init__(
self,
bucket: str,
endpoint_url: str = "",
access_key: str = "",
secret_key: str = "",
):
import boto3
kwargs: dict = {}
if endpoint_url:
kwargs["endpoint_url"] = endpoint_url
if access_key and secret_key:
kwargs["aws_access_key_id"] = access_key
kwargs["aws_secret_access_key"] = secret_key
self.s3 = boto3.client("s3", **kwargs)
self.bucket = bucket
# Ensure bucket exists (useful for MinIO local dev)
try:
self.s3.head_bucket(Bucket=self.bucket)
except Exception:
try:
self.s3.create_bucket(Bucket=self.bucket)
logger.info("Created S3 bucket: %s", self.bucket)
except Exception as e:
logger.warning("Could not create bucket %s: %s", self.bucket, e)
def read(self, key: str) -> bytes:
try:
response = self.s3.get_object(Bucket=self.bucket, Key=key)
return response["Body"].read()
except self.s3.exceptions.NoSuchKey:
raise FileNotFoundError(f"S3 object not found: s3://{self.bucket}/{key}")
except Exception as e:
if "NoSuchKey" in str(e) or "404" in str(e):
raise FileNotFoundError(f"S3 object not found: s3://{self.bucket}/{key}")
raise
def write(self, key: str, data: bytes) -> None:
self.s3.put_object(
Bucket=self.bucket,
Key=key,
Body=data,
ContentType="application/pdf",
)
logger.debug("Wrote %d bytes to s3://%s/%s", len(data), self.bucket, key)
def exists(self, key: str) -> bool:
try:
response = self.s3.head_object(Bucket=self.bucket, Key=key)
return response["ContentLength"] > 0
except Exception:
return False
def path_for(self, key: str) -> str:
return f"s3://{self.bucket}/{key}"
def get_storage_backend() -> StorageBackend:
"""Factory: return the configured storage backend instance."""
backend = config.storage_backend.lower()
if backend == "s3":
logger.info("Using S3 storage backend (bucket=%s)", config.s3_bucket)
return S3StorageBackend(
bucket=config.s3_bucket,
endpoint_url=config.s3_endpoint_url,
access_key=config.s3_access_key,
secret_key=config.s3_secret_key,
)
logger.info("Using local storage backend")
return LocalStorageBackend()
+1
View File
@@ -24,6 +24,7 @@ class CompanyAnalysisResult:
patent_count: int
success: bool
error: str | None = None
model: str | None = None
timestamp: datetime = field(default_factory=datetime.now)
+139
View File
@@ -0,0 +1,139 @@
"""Webhook notifications for job completion and alert events.
Sends JSON payloads to configured webhook URLs with retry logic.
Supports generic HTTP POST and Slack-compatible text payloads.
"""
import logging
import os
import time
from datetime import datetime
from typing import Any
import requests
logger = logging.getLogger(__name__)
# Comma-separated list of webhook URLs (env var based config)
_WEBHOOK_URLS_RAW = os.getenv("WEBHOOK_URLS", "")
WEBHOOK_URLS: list[str] = [
url.strip() for url in _WEBHOOK_URLS_RAW.split(",") if url.strip()
]
MAX_RETRIES = 3
BACKOFF_BASE = 2 # seconds
def _is_slack_url(url: str) -> bool:
"""Check if a URL looks like a Slack incoming webhook."""
return "hooks.slack.com" in url or "discord.com/api/webhooks" in url
def _build_payload(event_type: str, data: dict[str, Any], slack: bool = False) -> dict:
"""Build the webhook payload.
Args:
event_type: Type of event (e.g., "job_completed", "alert")
data: Event-specific data
slack: If True, wrap in Slack-compatible ``text`` format
Returns:
JSON-serializable payload dict
"""
payload = {
"event": event_type,
"timestamp": datetime.utcnow().isoformat() + "Z",
**data,
}
if slack:
# Build a human-readable summary for Slack/Discord
lines = [f"*[SPARC] {event_type}*"]
for key, value in data.items():
lines.append(f" {key}: {value}")
return {"text": "\n".join(lines)}
return payload
def _send_with_retry(url: str, payload: dict) -> bool:
"""Send a POST request with exponential backoff retry.
Args:
url: Webhook URL
payload: JSON payload to send
Returns:
True if delivered successfully, False after all retries exhausted
"""
for attempt in range(1, MAX_RETRIES + 1):
try:
response = requests.post(url, json=payload, timeout=10)
if response.status_code < 300:
logger.debug("Webhook delivered to %s (attempt %d)", url, attempt)
return True
logger.warning(
"Webhook %s returned %d (attempt %d/%d)",
url, response.status_code, attempt, MAX_RETRIES,
)
except requests.RequestException as e:
logger.warning(
"Webhook delivery failed for %s (attempt %d/%d): %s",
url, attempt, MAX_RETRIES, e,
)
if attempt < MAX_RETRIES:
wait = BACKOFF_BASE ** attempt
time.sleep(wait)
logger.error("Webhook permanently failed for %s after %d attempts", url, MAX_RETRIES)
return False
def notify(event_type: str, data: dict[str, Any]) -> None:
"""Fire all configured webhooks for an event.
Safe to call even when no webhooks are configured (returns immediately).
Args:
event_type: Event identifier (e.g., "job_completed", "patent_alert")
data: Event data to include in the payload
"""
if not WEBHOOK_URLS:
return
for url in WEBHOOK_URLS:
slack = _is_slack_url(url)
payload = _build_payload(event_type, data, slack=slack)
_send_with_retry(url, payload)
def notify_job_completed(
job_id: str,
status: str,
total_companies: int,
successful: int,
failed: int,
) -> None:
"""Send notification when a batch job completes."""
notify("job_completed", {
"job_id": job_id,
"status": status,
"total_companies": total_companies,
"successful": successful,
"failed": failed,
"summary": f"Batch job {job_id}: {successful}/{total_companies} succeeded",
})
def notify_alert(
company_name: str,
alert_type: str,
message: str,
) -> None:
"""Send notification for a tracked company alert."""
notify("patent_alert", {
"company_name": company_name,
"alert_type": alert_type,
"message": message,
})
+30 -2
View File
@@ -18,6 +18,7 @@ services:
restart: unless-stopped
init-db:
image: gitea.leeworks.dev/0xwheatyz/sparc:latest
build: .
container_name: sparc-init-db
command: python scripts/init_database.py
@@ -29,6 +30,7 @@ services:
restart: "no"
api:
image: gitea.leeworks.dev/0xwheatyz/sparc:latest
build: .
container_name: sparc-api
command: uvicorn SPARC.api:app --host 0.0.0.0 --port 8000
@@ -40,7 +42,7 @@ services:
JWT_SECRET: ${JWT_SECRET:-sparc-secret-key-change-in-production}
CORS_ORIGINS: ${CORS_ORIGINS:-}
APP_ENV: ${APP_ENV:-development}
ROOT_PATH: /api
ROOT_PATH: ""
ports:
- "8000:8000"
depends_on:
@@ -49,10 +51,34 @@ services:
init-db:
condition: service_completed_successfully
volumes:
- ./patents:/app/patents
- patent_data:/app/patents
restart: unless-stopped
# Optional: MinIO for S3-compatible local object storage
# Enable by setting STORAGE_BACKEND=s3 in .env
minio:
image: minio/minio:latest
container_name: sparc-minio
command: server /data --console-address ":9001"
environment:
MINIO_ROOT_USER: ${AWS_ACCESS_KEY_ID:-minioadmin}
MINIO_ROOT_PASSWORD: ${AWS_SECRET_ACCESS_KEY:-minioadmin}
ports:
- "9000:9000"
- "9001:9001"
volumes:
- minio_data:/data
healthcheck:
test: ["CMD", "mc", "ready", "local"]
interval: 10s
timeout: 5s
retries: 3
restart: unless-stopped
profiles:
- s3
dashboard:
image: gitea.leeworks.dev/0xwheatyz/sparc:frontend-latest
build: ./frontend
container_name: sparc-dashboard
ports:
@@ -63,3 +89,5 @@ services:
volumes:
postgres_data:
patent_data:
minio_data:
+76 -1
View File
@@ -276,7 +276,7 @@ The `docker-compose.yml` includes all services needed for production:
|---------|-----------|------|-------------|
| `postgres` | sparc-postgres | 5432 | PostgreSQL database |
| `init-db` | sparc-init-db | - | One-time database initialization (seeds admin user) |
| `api` | sparc-api | 8000 | FastAPI REST API with JWT auth |
| `api` | sparc-api | 8000 | FastAPI REST API with JWT auth (patent PDFs stored in `patent_data` volume) |
| `dashboard` | sparc-dashboard | 8080 | React TypeScript web UI |
### Common Docker Compose Commands
@@ -307,6 +307,81 @@ docker-compose restart api
---
## Patent PDF Storage
The SPARC API downloads patent PDFs during analysis and stores them at `/app/patents` inside the container. These files are used for subsequent single-patent analysis requests and as a local cache to avoid re-downloading. If this directory is not persisted, all downloaded PDFs are lost when the container is recreated.
### Docker Compose (default)
The default `docker-compose.yml` declares a named volume called `patent_data` that is mounted at `/app/patents`:
```yaml
# In the api service:
volumes:
- patent_data:/app/patents
# At the top-level volumes section:
volumes:
patent_data:
```
This means PDFs survive `docker compose down` and `docker compose up` cycles. To remove patent data intentionally, run:
```bash
docker compose down -v # WARNING: also removes postgres_data
# or selectively:
docker volume rm sparc_patent_data
```
If you prefer a bind mount (e.g., for easy host-side access during development), replace the volume with:
```yaml
volumes:
- ./patents:/app/patents
```
### Kubernetes
For Kubernetes deployments, create a PersistentVolumeClaim and mount it into the API pod:
```yaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: sparc-patent-data
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 5Gi
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: sparc-api
spec:
template:
spec:
containers:
- name: api
volumeMounts:
- name: patent-data
mountPath: /app/patents
volumes:
- name: patent-data
persistentVolumeClaim:
claimName: sparc-patent-data
```
Adjust the storage size based on expected patent volume. Each patent PDF is typically 1-5 MB.
### S3 Object Storage (alternative)
For production deployments that need shared or highly durable storage, set `STORAGE_BACKEND=s3` in your `.env` file. This stores patent PDFs in an S3-compatible bucket (AWS S3 or MinIO) instead of the local filesystem, eliminating the need for a persistent volume. See the S3/MinIO section in `.env.example` for configuration details.
---
## Troubleshooting
### Database Connection Issues
+9
View File
@@ -7,6 +7,15 @@
<title>SPARC Dashboard</title>
</head>
<body>
<script>
// Prevent FOUC: apply saved theme before first render
(function() {
var theme = localStorage.getItem('theme');
if (theme === 'dark' || (!theme && window.matchMedia('(prefers-color-scheme: dark)').matches)) {
document.documentElement.classList.add('dark');
}
})();
</script>
<div id="root"></div>
<script type="module" src="/src/main.tsx"></script>
</body>
+1 -1
View File
@@ -15,7 +15,7 @@ server {
# Proxy API requests to backend
location /api/ {
proxy_pass ${API_URL}/;
proxy_pass ${API_URL};
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection 'upgrade';
+261 -4
View File
@@ -10,7 +10,7 @@
"dependencies": {
"@tanstack/react-query": "^5.51.0",
"axios": "^1.7.2",
"lucide-react": "^0.400.0",
"lucide-react": "^1.7.0",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-router-dom": "^6.24.0",
@@ -26,6 +26,7 @@
"eslint-plugin-react-hooks": "^5.1.0",
"eslint-plugin-react-refresh": "^0.4.7",
"globals": "^15.8.0",
"openapi-typescript": "^7.0.0",
"postcss": "^8.4.39",
"tailwindcss": "^3.4.4",
"typescript": "~5.5.3",
@@ -1025,6 +1026,82 @@
"node": ">= 8"
}
},
"node_modules/@redocly/ajv": {
"version": "8.11.2",
"resolved": "https://registry.npmjs.org/@redocly/ajv/-/ajv-8.11.2.tgz",
"integrity": "sha512-io1JpnwtIcvojV7QKDUSIuMN/ikdOUd1ReEnUnMKGfDVridQZ31J0MmIuqwuRjWDZfmvr+Q0MqCcfHM2gTivOg==",
"dev": true,
"license": "MIT",
"dependencies": {
"fast-deep-equal": "^3.1.1",
"json-schema-traverse": "^1.0.0",
"require-from-string": "^2.0.2",
"uri-js-replace": "^1.0.1"
},
"funding": {
"type": "github",
"url": "https://github.com/sponsors/epoberezkin"
}
},
"node_modules/@redocly/ajv/node_modules/json-schema-traverse": {
"version": "1.0.0",
"resolved": "https://registry.npmjs.org/json-schema-traverse/-/json-schema-traverse-1.0.0.tgz",
"integrity": "sha512-NM8/P9n3XjXhIZn1lLhkFaACTOURQXjWhV4BA/RnOv8xvgqtqpAX9IO4mRQxSx1Rlo4tqzeqb0sOlruaOy3dug==",
"dev": true,
"license": "MIT"
},
"node_modules/@redocly/config": {
"version": "0.22.0",
"resolved": "https://registry.npmjs.org/@redocly/config/-/config-0.22.0.tgz",
"integrity": "sha512-gAy93Ddo01Z3bHuVdPWfCwzgfaYgMdaZPcfL7JZ7hWJoK9V0lXDbigTWkhiPFAaLWzbOJ+kbUQG1+XwIm0KRGQ==",
"dev": true,
"license": "MIT"
},
"node_modules/@redocly/openapi-core": {
"version": "1.34.11",
"resolved": "https://registry.npmjs.org/@redocly/openapi-core/-/openapi-core-1.34.11.tgz",
"integrity": "sha512-V09ayfnb5GyysmvARbt+voFZAjGcf7hSYxOYxSkCc4fbH/DTfq5YWoec8cflvmHHqyIFbqvmGKmYFzqhr9zxDg==",
"dev": true,
"license": "MIT",
"dependencies": {
"@redocly/ajv": "8.11.2",
"@redocly/config": "0.22.0",
"colorette": "1.4.0",
"https-proxy-agent": "7.0.6",
"js-levenshtein": "1.1.6",
"js-yaml": "4.1.1",
"minimatch": "5.1.9",
"pluralize": "8.0.0",
"yaml-ast-parser": "0.0.43"
},
"engines": {
"node": ">=18.17.0",
"npm": ">=9.5.0"
}
},
"node_modules/@redocly/openapi-core/node_modules/brace-expansion": {
"version": "2.0.3",
"resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.3.tgz",
"integrity": "sha512-MCV/fYJEbqx68aE58kv2cA/kiky1G8vux3OR6/jbS+jIMe/6fJWa0DTzJU7dqijOWYwHi1t29FlfYI9uytqlpA==",
"dev": true,
"license": "MIT",
"dependencies": {
"balanced-match": "^1.0.0"
}
},
"node_modules/@redocly/openapi-core/node_modules/minimatch": {
"version": "5.1.9",
"resolved": "https://registry.npmjs.org/minimatch/-/minimatch-5.1.9.tgz",
"integrity": "sha512-7o1wEA2RyMP7Iu7GNba9vc0RWWGACJOCZBJX2GJWip0ikV+wcOsgVuY9uE8CPiyQhkGFSlhuSkZPavN7u1c2Fw==",
"dev": true,
"license": "ISC",
"dependencies": {
"brace-expansion": "^2.0.1"
},
"engines": {
"node": ">=10"
}
},
"node_modules/@remix-run/router": {
"version": "1.23.2",
"resolved": "https://registry.npmjs.org/@remix-run/router/-/router-1.23.2.tgz",
@@ -1906,6 +1983,16 @@
"acorn": "^6.0.0 || ^7.0.0 || ^8.0.0"
}
},
"node_modules/agent-base": {
"version": "7.1.4",
"resolved": "https://registry.npmjs.org/agent-base/-/agent-base-7.1.4.tgz",
"integrity": "sha512-MnA+YT8fwfJPgBx3m60MNqakm30XOkyIoH1y6huTQvC0PwZG7ki8NacLBcrPbNoo8vEZy7Jpuk7+jMO+CUovTQ==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">= 14"
}
},
"node_modules/ajv": {
"version": "6.14.0",
"resolved": "https://registry.npmjs.org/ajv/-/ajv-6.14.0.tgz",
@@ -1923,6 +2010,16 @@
"url": "https://github.com/sponsors/epoberezkin"
}
},
"node_modules/ansi-colors": {
"version": "4.1.3",
"resolved": "https://registry.npmjs.org/ansi-colors/-/ansi-colors-4.1.3.tgz",
"integrity": "sha512-/6w/C21Pm1A7aZitlI5Ni/2J6FFQN8i1Cvz3kHABAAbw93v/NlvKdVOqz7CCWz/3iv/JplRSEEZ83XION15ovw==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=6"
}
},
"node_modules/ansi-styles": {
"version": "4.3.0",
"resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-4.3.0.tgz",
@@ -2190,6 +2287,13 @@
"url": "https://github.com/chalk/chalk?sponsor=1"
}
},
"node_modules/change-case": {
"version": "5.4.4",
"resolved": "https://registry.npmjs.org/change-case/-/change-case-5.4.4.tgz",
"integrity": "sha512-HRQyTk2/YPEkt9TnUPbOpr64Uw3KOicFWPVBb+xiHvd6eBx/qPr9xqfBFDT8P2vWsvvz4jbEkfDe71W3VyNu2w==",
"dev": true,
"license": "MIT"
},
"node_modules/chokidar": {
"version": "3.6.0",
"resolved": "https://registry.npmjs.org/chokidar/-/chokidar-3.6.0.tgz",
@@ -2257,6 +2361,13 @@
"dev": true,
"license": "MIT"
},
"node_modules/colorette": {
"version": "1.4.0",
"resolved": "https://registry.npmjs.org/colorette/-/colorette-1.4.0.tgz",
"integrity": "sha512-Y2oEozpomLn7Q3HFP7dpww7AtMJplbM9lGZP6RDfHqmbeRjiwRg4n6VM6j4KLmRke85uWEI7JqF17f3pqdRA0g==",
"dev": true,
"license": "MIT"
},
"node_modules/combined-stream": {
"version": "1.0.8",
"resolved": "https://registry.npmjs.org/combined-stream/-/combined-stream-1.0.8.tgz",
@@ -3165,6 +3276,20 @@
"node": ">= 0.4"
}
},
"node_modules/https-proxy-agent": {
"version": "7.0.6",
"resolved": "https://registry.npmjs.org/https-proxy-agent/-/https-proxy-agent-7.0.6.tgz",
"integrity": "sha512-vK9P5/iUfdl95AI+JVyUuIcVtd4ofvtrOr3HNtM2yxC9bnMbEdp3x01OhQNnjb8IJYi38VlTE3mBXwcfvywuSw==",
"dev": true,
"license": "MIT",
"dependencies": {
"agent-base": "^7.1.2",
"debug": "4"
},
"engines": {
"node": ">= 14"
}
},
"node_modules/ignore": {
"version": "5.3.2",
"resolved": "https://registry.npmjs.org/ignore/-/ignore-5.3.2.tgz",
@@ -3202,6 +3327,19 @@
"node": ">=0.8.19"
}
},
"node_modules/index-to-position": {
"version": "1.2.0",
"resolved": "https://registry.npmjs.org/index-to-position/-/index-to-position-1.2.0.tgz",
"integrity": "sha512-Yg7+ztRkqslMAS2iFaU+Oa4KTSidr63OsFGlOrJoW981kIYO3CGCS3wA95P1mUi/IVSJkn0D479KTJpVpvFNuw==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=18"
},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"node_modules/internmap": {
"version": "2.0.3",
"resolved": "https://registry.npmjs.org/internmap/-/internmap-2.0.3.tgz",
@@ -3290,6 +3428,16 @@
"jiti": "bin/jiti.js"
}
},
"node_modules/js-levenshtein": {
"version": "1.1.6",
"resolved": "https://registry.npmjs.org/js-levenshtein/-/js-levenshtein-1.1.6.tgz",
"integrity": "sha512-X2BB11YZtrRqY4EnQcLX5Rh373zbK4alC1FW7D7MBhL2gtcC17cTnr6DmfHZeS0s2rTHjUTMMHfG7gO8SSdw+g==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=0.10.0"
}
},
"node_modules/js-tokens": {
"version": "4.0.0",
"resolved": "https://registry.npmjs.org/js-tokens/-/js-tokens-4.0.0.tgz",
@@ -3452,9 +3600,9 @@
}
},
"node_modules/lucide-react": {
"version": "0.400.0",
"resolved": "https://registry.npmjs.org/lucide-react/-/lucide-react-0.400.0.tgz",
"integrity": "sha512-rpp7pFHh3Xd93KHixNgB0SqThMHpYNzsGUu69UaQbSZ75Q/J3m5t6EhKyMT3m4w2WOxmJ2mY0tD3vebnXqQryQ==",
"version": "1.7.0",
"resolved": "https://registry.npmjs.org/lucide-react/-/lucide-react-1.7.0.tgz",
"integrity": "sha512-yI7BeItCLZJTXikmK4KNUGCKoGzSvbKlfCvw44bU4fXAL6v3gYS4uHD1jzsLkfwODYwI6Drw5Tu9Z5ulDe0TSg==",
"license": "ISC",
"peerDependencies": {
"react": "^16.5.1 || ^17.0.0 || ^18.0.0 || ^19.0.0"
@@ -3608,6 +3756,40 @@
"node": ">= 6"
}
},
"node_modules/openapi-typescript": {
"version": "7.13.0",
"resolved": "https://registry.npmjs.org/openapi-typescript/-/openapi-typescript-7.13.0.tgz",
"integrity": "sha512-EFP392gcqXS7ntPvbhBzbF8TyBA+baIYEm791Hy5YkjDYKTnk/Tn5OQeKm5BIZvJihpp8Zzr4hzx0Irde1LNGQ==",
"dev": true,
"license": "MIT",
"dependencies": {
"@redocly/openapi-core": "^1.34.6",
"ansi-colors": "^4.1.3",
"change-case": "^5.4.4",
"parse-json": "^8.3.0",
"supports-color": "^10.2.2",
"yargs-parser": "^21.1.1"
},
"bin": {
"openapi-typescript": "bin/cli.js"
},
"peerDependencies": {
"typescript": "^5.x"
}
},
"node_modules/openapi-typescript/node_modules/supports-color": {
"version": "10.2.2",
"resolved": "https://registry.npmjs.org/supports-color/-/supports-color-10.2.2.tgz",
"integrity": "sha512-SS+jx45GF1QjgEXQx4NJZV9ImqmO2NPz5FNsIHrsDjh2YsHnawpan7SNQ1o8NuhrbHZy9AZhIoCUiCeaW/C80g==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=18"
},
"funding": {
"url": "https://github.com/chalk/supports-color?sponsor=1"
}
},
"node_modules/optionator": {
"version": "0.9.4",
"resolved": "https://registry.npmjs.org/optionator/-/optionator-0.9.4.tgz",
@@ -3671,6 +3853,24 @@
"node": ">=6"
}
},
"node_modules/parse-json": {
"version": "8.3.0",
"resolved": "https://registry.npmjs.org/parse-json/-/parse-json-8.3.0.tgz",
"integrity": "sha512-ybiGyvspI+fAoRQbIPRddCcSTV9/LsJbf0e/S85VLowVGzRmokfneg2kwVW/KU5rOXrPSbF1qAKPMgNTqqROQQ==",
"dev": true,
"license": "MIT",
"dependencies": {
"@babel/code-frame": "^7.26.2",
"index-to-position": "^1.1.0",
"type-fest": "^4.39.1"
},
"engines": {
"node": ">=18"
},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"node_modules/path-exists": {
"version": "4.0.0",
"resolved": "https://registry.npmjs.org/path-exists/-/path-exists-4.0.0.tgz",
@@ -3738,6 +3938,16 @@
"node": ">= 6"
}
},
"node_modules/pluralize": {
"version": "8.0.0",
"resolved": "https://registry.npmjs.org/pluralize/-/pluralize-8.0.0.tgz",
"integrity": "sha512-Nc3IT5yHzflTfbjgqWcCPpo7DaKy4FnpB0l/zCAW0Tc7jxAiuqSxHasntB3D7887LSrA93kDJ9IXovxJYxyLCA==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=4"
}
},
"node_modules/postcss": {
"version": "8.5.8",
"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.8.tgz",
@@ -4124,6 +4334,16 @@
"decimal.js-light": "^2.4.1"
}
},
"node_modules/require-from-string": {
"version": "2.0.2",
"resolved": "https://registry.npmjs.org/require-from-string/-/require-from-string-2.0.2.tgz",
"integrity": "sha512-Xf0nWe6RseziFMu+Ap9biiUbmplq6S9/p+7w7YXP/JBHhrUDDUhwa+vANyubuqfZWTveU//DYVGsDG7RKL/vEw==",
"dev": true,
"license": "MIT",
"engines": {
"node": ">=0.10.0"
}
},
"node_modules/resolve": {
"version": "1.22.11",
"resolved": "https://registry.npmjs.org/resolve/-/resolve-1.22.11.tgz",
@@ -4510,6 +4730,19 @@
"node": ">= 0.8.0"
}
},
"node_modules/type-fest": {
"version": "4.41.0",
"resolved": "https://registry.npmjs.org/type-fest/-/type-fest-4.41.0.tgz",
"integrity": "sha512-TeTSQ6H5YHvpqVwBRcnLDCBnDOHWYu7IvGbHT6N8AOymcr9PJGjc1GTtiWZTYg0NCgYwvnYWEkVChQAr9bjfwA==",
"dev": true,
"license": "(MIT OR CC0-1.0)",
"engines": {
"node": ">=16"
},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"node_modules/typescript": {
"version": "5.5.4",
"resolved": "https://registry.npmjs.org/typescript/-/typescript-5.5.4.tgz",
@@ -4589,6 +4822,13 @@
"punycode": "^2.1.0"
}
},
"node_modules/uri-js-replace": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/uri-js-replace/-/uri-js-replace-1.0.1.tgz",
"integrity": "sha512-W+C9NWNLFOoBI2QWDp4UT9pv65r2w5Cx+3sTYFvtMdDBxkKt1syCqsUdSFAChbEe1uK5TfS04wt/nGwmaeIQ0g==",
"dev": true,
"license": "MIT"
},
"node_modules/util-deprecate": {
"version": "1.0.2",
"resolved": "https://registry.npmjs.org/util-deprecate/-/util-deprecate-1.0.2.tgz",
@@ -4711,6 +4951,23 @@
"dev": true,
"license": "ISC"
},
"node_modules/yaml-ast-parser": {
"version": "0.0.43",
"resolved": "https://registry.npmjs.org/yaml-ast-parser/-/yaml-ast-parser-0.0.43.tgz",
"integrity": "sha512-2PTINUwsRqSd+s8XxKaJWQlUuEMHJQyEuh2edBbW8KNJz0SJPwUSD2zRWqezFEdN7IzAgeuYHFUCF7o8zRdZ0A==",
"dev": true,
"license": "Apache-2.0"
},
"node_modules/yargs-parser": {
"version": "21.1.1",
"resolved": "https://registry.npmjs.org/yargs-parser/-/yargs-parser-21.1.1.tgz",
"integrity": "sha512-tVpsJW7DdjecAiFpbIB1e3qxIQsE6NoPc5/eTdrbbIC4h0LVsWhnoa3g+m2HclBIujHzsxZ4VJVA+GUuc2/LBw==",
"dev": true,
"license": "ISC",
"engines": {
"node": ">=12"
}
},
"node_modules/yocto-queue": {
"version": "0.1.0",
"resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz",
+5 -1
View File
@@ -7,12 +7,15 @@
"dev": "vite",
"build": "tsc -b && vite build",
"lint": "eslint .",
"generate": "openapi-typescript http://localhost:8000/api/openapi.json -o src/api/schema.d.ts",
"generate:local": "openapi-typescript src/api/openapi.json -o src/api/schema.d.ts",
"typecheck": "tsc --noEmit",
"preview": "vite preview"
},
"dependencies": {
"@tanstack/react-query": "^5.51.0",
"axios": "^1.7.2",
"lucide-react": "^0.400.0",
"lucide-react": "^1.7.0",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-router-dom": "^6.24.0",
@@ -30,6 +33,7 @@
"globals": "^15.8.0",
"postcss": "^8.4.39",
"tailwindcss": "^3.4.4",
"openapi-typescript": "^7.0.0",
"typescript": "~5.5.3",
"typescript-eslint": "^8.0.0",
"vite": "^5.3.3"
+5
View File
@@ -1,6 +1,7 @@
import { BrowserRouter, Routes, Route, Navigate } from 'react-router-dom';
import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
import { AuthProvider } from './context/AuthContext';
import { ThemeProvider } from './context/ThemeContext';
import { Layout } from './components/Layout';
import { ProtectedRoute } from './components/ProtectedRoute';
import { Login } from './pages/Login';
@@ -10,6 +11,7 @@ import { Batch } from './pages/Batch';
import { AnalyticsPage } from './pages/Analytics';
import { About } from './pages/About';
import { AdminUsers } from './pages/AdminUsers';
import { Compare } from './pages/Compare';
const queryClient = new QueryClient({
defaultOptions: {
@@ -22,6 +24,7 @@ const queryClient = new QueryClient({
function App() {
return (
<ThemeProvider>
<QueryClientProvider client={queryClient}>
<AuthProvider>
<BrowserRouter>
@@ -41,6 +44,7 @@ function App() {
<Route path="/analysis" element={<Analysis />} />
<Route path="/batch" element={<Batch />} />
<Route path="/analytics" element={<AnalyticsPage />} />
<Route path="/compare" element={<Compare />} />
<Route path="/about" element={<About />} />
{/* Admin routes */}
@@ -61,6 +65,7 @@ function App() {
</BrowserRouter>
</AuthProvider>
</QueryClientProvider>
</ThemeProvider>
);
}
+71 -4
View File
@@ -89,29 +89,53 @@ export const authApi = {
},
};
// Model types
export interface ModelInfo {
id: string;
name: string;
provider: string;
}
export interface ModelsResponse {
models: ModelInfo[];
default: string;
}
// Analysis API
export const analysisApi = {
analyzeCompany: async (companyName: string): Promise<CompanyAnalysis> => {
const response = await api.get<CompanyAnalysis>(`/analyze/${encodeURIComponent(companyName)}`);
analyzeCompany: async (companyName: string, model?: string): Promise<CompanyAnalysis> => {
const params = new URLSearchParams();
if (model) params.append('model', model);
const qs = params.toString();
const response = await api.get<CompanyAnalysis>(
`/analyze/${encodeURIComponent(companyName)}${qs ? `?${qs}` : ''}`
);
return response.data;
},
analyzeBatch: async (companies: string[], maxWorkers = 3): Promise<BatchAnalysisResult> => {
analyzeBatch: async (companies: string[], maxWorkers = 3, model?: string): Promise<BatchAnalysisResult> => {
const response = await api.post<BatchAnalysisResult>('/analyze/batch', {
companies,
max_workers: maxWorkers,
...(model ? { model } : {}),
});
return response.data;
},
analyzeBatchAsync: async (companies: string[], maxWorkers = 3): Promise<JobStatus> => {
analyzeBatchAsync: async (companies: string[], maxWorkers = 3, model?: string): Promise<JobStatus> => {
const response = await api.post<JobStatus>('/analyze/batch/async', {
companies,
max_workers: maxWorkers,
...(model ? { model } : {}),
});
return response.data;
},
listModels: async (): Promise<ModelsResponse> => {
const response = await api.get<ModelsResponse>('/models');
return response.data;
},
getJobStatus: async (jobId: string): Promise<JobStatus> => {
const response = await api.get<JobStatus>(`/jobs/${jobId}`);
return response.data;
@@ -126,12 +150,55 @@ export const analysisApi = {
},
};
// Export API
export const exportApi = {
exportCsv: async (companyName: string): Promise<void> => {
const response = await api.get(`/export/${encodeURIComponent(companyName)}`, {
responseType: 'blob',
});
const url = window.URL.createObjectURL(new Blob([response.data]));
const link = document.createElement('a');
link.href = url;
link.setAttribute('download', `sparc_${companyName.toLowerCase().replace(/\s+/g, '_')}_export.csv`);
document.body.appendChild(link);
link.click();
link.remove();
window.URL.revokeObjectURL(url);
},
exportPdf: async (companyName: string): Promise<void> => {
const response = await api.get(`/export/${encodeURIComponent(companyName)}/pdf`, {
responseType: 'blob',
});
const safeName = companyName.toLowerCase().replace(/\s+/g, '_');
const date = new Date().toISOString().split('T')[0];
const url = window.URL.createObjectURL(new Blob([response.data], { type: 'application/pdf' }));
const link = document.createElement('a');
link.href = url;
link.setAttribute('download', `${safeName}-analysis-${date}.pdf`);
document.body.appendChild(link);
link.click();
link.remove();
window.URL.revokeObjectURL(url);
},
};
// Analytics API
export interface TrendData {
by_month: Array<{ month: string; company_name: string; count: number }>;
by_type_over_time: Array<{ month: string; analysis_type: string; count: number }>;
period_days: number;
}
export const analyticsApi = {
getAnalytics: async (days = 30): Promise<Analytics> => {
const response = await api.get<Analytics>(`/analytics?days=${days}`);
return response.data;
},
getTrends: async (days = 90): Promise<TrendData> => {
const response = await api.get<TrendData>(`/analytics/trends?days=${days}`);
return response.data;
},
};
// Admin API
File diff suppressed because it is too large Load Diff
+975
View File
@@ -0,0 +1,975 @@
/**
* This file was auto-generated by openapi-typescript.
* Do not make direct changes to the file.
*/
export interface paths {
"/auth/register": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
/**
* Register
* @description Register a new user.
*
* The first registered user automatically becomes an admin.
*/
post: operations["register_auth_register_post"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/auth/login": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
/**
* Login
* @description Authenticate user and return JWT tokens.
*/
post: operations["login_auth_login_post"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/auth/refresh": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
/**
* Refresh Token
* @description Refresh access token using refresh token.
*/
post: operations["refresh_token_auth_refresh_post"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/auth/me": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* Get Me
* @description Get current authenticated user.
*/
get: operations["get_me_auth_me_get"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/admin/users": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* List Users
* @description List all users (admin only).
*/
get: operations["list_users_admin_users_get"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/admin/users/{user_id}/role": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
/**
* Update User Role
* @description Update a user's role (admin only).
*/
patch: operations["update_user_role_admin_users__user_id__role_patch"];
trace?: never;
};
"/admin/users/{user_id}": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
post?: never;
/**
* Delete User
* @description Delete a user (admin only).
*/
delete: operations["delete_user_admin_users__user_id__delete"];
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/analytics": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* Get Analytics
* @description Get analytics data (authenticated users only).
*/
get: operations["get_analytics_analytics_get"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/health": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* Health Check
* @description Check API health status.
*/
get: operations["health_check_health_get"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/analyze/{company_name}": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* Analyze Company
* @description Analyze a single company's patent portfolio.
*
* This endpoint retrieves recent patents for the specified company,
* parses them, and uses AI to generate a comprehensive analysis.
*
* Args:
* company_name: Name of the company to analyze (e.g., "nvidia", "intel")
*
* Returns:
* Analysis results including patent count, AI insights, and success status
*/
get: operations["analyze_company_analyze__company_name__get"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/analyze/batch": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
/**
* Analyze Companies Batch
* @description Analyze multiple companies' patent portfolios.
*
* Processes companies concurrently for improved performance.
* Limited to 20 companies per request.
*
* Args:
* request: List of company names and optional worker count
*
* Returns:
* Batch results with individual company analyses and summary statistics
*/
post: operations["analyze_companies_batch_analyze_batch_post"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/analyze/batch/async": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
get?: never;
put?: never;
/**
* Analyze Companies Async
* @description Start an asynchronous batch analysis job.
*
* Returns immediately with a job ID that can be used to poll for status.
* Useful for large batch analyses that may take a long time.
*
* Args:
* request: List of company names and optional worker count
*
* Returns:
* Job status with job_id for polling
*/
post: operations["analyze_companies_async_analyze_batch_async_post"];
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/jobs/{job_id}": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* Get Job Status
* @description Get the status of a background analysis job.
*
* Args:
* job_id: The job ID returned from the async batch endpoint
*
* Returns:
* Current job status including progress and results when complete
*/
get: operations["get_job_status_jobs__job_id__get"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
"/jobs": {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
/**
* List Jobs
* @description List all analysis jobs.
*
* Args:
* status: Optional filter by job status
* limit: Maximum number of jobs to return (default 10, max 100)
*
* Returns:
* List of job statuses
*/
get: operations["list_jobs_jobs_get"];
put?: never;
post?: never;
delete?: never;
options?: never;
head?: never;
patch?: never;
trace?: never;
};
}
export type webhooks = Record<string, never>;
export interface components {
schemas: {
/**
* AnalyticsResponse
* @description Analytics response model.
*/
AnalyticsResponse: {
/** Total Messages */
total_messages: number;
/** By Company */
by_company: {
[key: string]: unknown;
}[];
/** By Type */
by_type: {
[key: string]: unknown;
}[];
/** Period Days */
period_days: number;
};
/**
* BatchAnalysisRequest
* @description Request model for batch company analysis.
*/
BatchAnalysisRequest: {
/**
* Companies
* @description List of company names to analyze
*/
companies: string[];
/**
* Max Workers
* @description Max concurrent analyses
* @default 3
*/
max_workers: number;
};
/**
* BatchAnalysisResponse
* @description Response model for batch company analysis.
*/
BatchAnalysisResponse: {
/** Results */
results: components["schemas"]["CompanyAnalysisResponse"][];
/** Total Companies */
total_companies: number;
/** Successful */
successful: number;
/** Failed */
failed: number;
/**
* Timestamp
* Format: date-time
*/
timestamp: string;
};
/**
* CompanyAnalysisResponse
* @description Response model for single company analysis.
*/
CompanyAnalysisResponse: {
/** Company Name */
company_name: string;
/** Analysis */
analysis: string;
/** Patent Count */
patent_count: number;
/** Success */
success: boolean;
/** Error */
error?: string | null;
/**
* Timestamp
* Format: date-time
*/
timestamp: string;
};
/** HTTPValidationError */
HTTPValidationError: {
/** Detail */
detail?: components["schemas"]["ValidationError"][];
};
/**
* HealthResponse
* @description Health check response.
*/
HealthResponse: {
/** Status */
status: string;
/** Version */
version: string;
/**
* Timestamp
* Format: date-time
*/
timestamp: string;
};
/**
* JobStatus
* @description Status of a background analysis job.
*/
JobStatus: {
/** Job Id */
job_id: string;
/** Status */
status: string;
/** Progress */
progress: number;
/** Total Companies */
total_companies: number;
/** Completed Companies */
completed_companies: number;
result?: components["schemas"]["BatchAnalysisResponse"] | null;
/** Error */
error?: string | null;
};
/**
* LoginRequest
* @description User login request.
*/
LoginRequest: {
/**
* Email
* Format: email
*/
email: string;
/** Password */
password: string;
};
/**
* RefreshRequest
* @description Token refresh request.
*/
RefreshRequest: {
/** Refresh Token */
refresh_token: string;
};
/**
* RegisterRequest
* @description User registration request.
*/
RegisterRequest: {
/**
* Email
* Format: email
*/
email: string;
/**
* Password
* @description Password (min 8 characters)
*/
password: string;
};
/**
* TokenResponse
* @description Token response model.
*/
TokenResponse: {
/** Access Token */
access_token: string;
/** Refresh Token */
refresh_token: string;
/**
* Token Type
* @default bearer
*/
token_type: string;
};
/**
* UpdateRoleRequest
* @description Update user role request.
*/
UpdateRoleRequest: {
/** Role */
role: string;
};
/**
* UserResponse
* @description User response model.
*/
UserResponse: {
/** Id */
id: number;
/** Email */
email: string;
/** Role */
role: string;
/**
* Created At
* Format: date-time
*/
created_at: string;
};
/** ValidationError */
ValidationError: {
/** Location */
loc: (string | number)[];
/** Message */
msg: string;
/** Error Type */
type: string;
/** Input */
input?: unknown;
/** Context */
ctx?: Record<string, never>;
};
};
responses: never;
parameters: never;
requestBodies: never;
headers: never;
pathItems: never;
}
export type $defs = Record<string, never>;
export interface operations {
register_auth_register_post: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody: {
content: {
"application/json": components["schemas"]["RegisterRequest"];
};
};
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["UserResponse"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
login_auth_login_post: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody: {
content: {
"application/json": components["schemas"]["LoginRequest"];
};
};
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["TokenResponse"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
refresh_token_auth_refresh_post: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody: {
content: {
"application/json": components["schemas"]["RefreshRequest"];
};
};
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["TokenResponse"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
get_me_auth_me_get: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["UserResponse"];
};
};
};
};
list_users_admin_users_get: {
parameters: {
query?: {
limit?: number;
offset?: number;
};
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["UserResponse"][];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
update_user_role_admin_users__user_id__role_patch: {
parameters: {
query?: never;
header?: never;
path: {
user_id: number;
};
cookie?: never;
};
requestBody: {
content: {
"application/json": components["schemas"]["UpdateRoleRequest"];
};
};
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["UserResponse"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
delete_user_admin_users__user_id__delete: {
parameters: {
query?: never;
header?: never;
path: {
user_id: number;
};
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": unknown;
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
get_analytics_analytics_get: {
parameters: {
query?: {
days?: number;
};
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["AnalyticsResponse"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
health_check_health_get: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HealthResponse"];
};
};
};
};
analyze_company_analyze__company_name__get: {
parameters: {
query?: never;
header?: never;
path: {
company_name: string;
};
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["CompanyAnalysisResponse"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
analyze_companies_batch_analyze_batch_post: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody: {
content: {
"application/json": components["schemas"]["BatchAnalysisRequest"];
};
};
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["BatchAnalysisResponse"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
analyze_companies_async_analyze_batch_async_post: {
parameters: {
query?: never;
header?: never;
path?: never;
cookie?: never;
};
requestBody: {
content: {
"application/json": components["schemas"]["BatchAnalysisRequest"];
};
};
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["JobStatus"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
get_job_status_jobs__job_id__get: {
parameters: {
query?: never;
header?: never;
path: {
job_id: string;
};
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["JobStatus"];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
list_jobs_jobs_get: {
parameters: {
query?: {
/** @description Filter by status: pending, running, completed, failed */
status?: string | null;
limit?: number;
};
header?: never;
path?: never;
cookie?: never;
};
requestBody?: never;
responses: {
/** @description Successful Response */
200: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["JobStatus"][];
};
};
/** @description Validation Error */
422: {
headers: {
[name: string]: unknown;
};
content: {
"application/json": components["schemas"]["HTTPValidationError"];
};
};
};
};
}
+12 -2
View File
@@ -1,9 +1,11 @@
import { Outlet, NavLink, useNavigate } from 'react-router-dom';
import { useAuth } from '../context/AuthContext';
import { Search, Layers, BarChart3, Info, Users, LogOut } from 'lucide-react';
import { useTheme } from '../context/ThemeContext';
import { Search, Layers, BarChart3, Info, Users, LogOut, GitCompareArrows, Sun, Moon } from 'lucide-react';
export function Layout() {
const { user, isAdmin, logout } = useAuth();
const { theme, toggleTheme } = useTheme();
const navigate = useNavigate();
const handleLogout = () => {
@@ -15,6 +17,7 @@ export function Layout() {
{ to: '/analysis', icon: Search, label: 'Analysis' },
{ to: '/batch', icon: Layers, label: 'Batch' },
{ to: '/analytics', icon: BarChart3, label: 'Analytics' },
{ to: '/compare', icon: GitCompareArrows, label: 'Compare' },
{ to: '/about', icon: Info, label: 'About' },
];
@@ -23,7 +26,7 @@ export function Layout() {
}
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950">
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-slate-100 dark:to-indigo-950">
{/* Header */}
<header className="bg-bg-card/80 backdrop-blur-lg border-b border-primary/20">
<div className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
@@ -63,6 +66,13 @@ export function Layout() {
{/* User menu */}
<div className="flex items-center gap-4">
<button
onClick={toggleTheme}
className="p-2 rounded-lg text-text-secondary hover:text-text-primary hover:bg-bg-card-hover transition-all"
aria-label={theme === 'dark' ? 'Switch to light mode' : 'Switch to dark mode'}
>
{theme === 'dark' ? <Sun size={18} /> : <Moon size={18} />}
</button>
<div className="text-right hidden sm:block">
<div className="text-sm font-medium text-text-primary">{user?.email}</div>
<div className="text-xs text-text-secondary capitalize">{user?.role}</div>
+1 -1
View File
@@ -12,7 +12,7 @@ export function ProtectedRoute({ children, requireAdmin = false }: ProtectedRout
if (isLoading) {
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950 flex items-center justify-center">
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-slate-100 dark:to-indigo-950 flex items-center justify-center">
<div className="animate-spin rounded-full h-12 w-12 border-t-2 border-b-2 border-primary"></div>
</div>
);
+48
View File
@@ -0,0 +1,48 @@
import { createContext, useContext, useEffect, useState } from 'react';
type Theme = 'light' | 'dark';
interface ThemeContextType {
theme: Theme;
toggleTheme: () => void;
}
const ThemeContext = createContext<ThemeContextType | undefined>(undefined);
function getInitialTheme(): Theme {
const stored = localStorage.getItem('theme');
if (stored === 'light' || stored === 'dark') return stored;
return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light';
}
export function ThemeProvider({ children }: { children: React.ReactNode }) {
const [theme, setTheme] = useState<Theme>(getInitialTheme);
useEffect(() => {
const root = document.documentElement;
if (theme === 'dark') {
root.classList.add('dark');
} else {
root.classList.remove('dark');
}
localStorage.setItem('theme', theme);
}, [theme]);
const toggleTheme = () => {
setTheme((prev) => (prev === 'dark' ? 'light' : 'dark'));
};
return (
<ThemeContext.Provider value={{ theme, toggleTheme }}>
{children}
</ThemeContext.Provider>
);
}
export function useTheme() {
const context = useContext(ThemeContext);
if (!context) {
throw new Error('useTheme must be used within a ThemeProvider');
}
return context;
}
+41
View File
@@ -0,0 +1,41 @@
import { useTheme } from './ThemeContext';
/**
* Returns theme-aware color values for recharts components.
*
* Recharts accepts only raw color strings (not CSS variables),
* so this hook bridges the Tailwind/CSS-variable theme system
* to the imperative recharts API.
*/
export function useChartTheme() {
const { theme } = useTheme();
const isDark = theme === 'dark';
return {
/** Axis tick and grid line stroke color */
axisStroke: isDark ? '#94a3b8' : '#64748b',
/** Tooltip container background */
tooltipBg: isDark ? '#1e293b' : '#ffffff',
/** Tooltip container border */
tooltipBorder: isDark
? '1px solid rgba(99, 102, 241, 0.3)'
: '1px solid rgba(99, 102, 241, 0.2)',
/** Tooltip label text color */
tooltipLabelColor: isDark ? '#f8fafc' : '#0f172a',
/** Tooltip item text color */
tooltipItemColor: isDark ? '#e2e8f0' : '#334155',
/** Convenience: full contentStyle object for recharts Tooltip */
tooltipContentStyle: {
backgroundColor: isDark ? '#1e293b' : '#ffffff',
border: isDark
? '1px solid rgba(99, 102, 241, 0.3)'
: '1px solid rgba(99, 102, 241, 0.2)',
borderRadius: '8px',
color: isDark ? '#f8fafc' : '#0f172a',
},
/** Convenience: labelStyle for recharts Tooltip */
tooltipLabelStyle: {
color: isDark ? '#f8fafc' : '#0f172a',
},
};
}
+22 -2
View File
@@ -2,6 +2,26 @@
@tailwind components;
@tailwind utilities;
/* Light mode (default) */
:root {
--color-bg-dark: #f1f5f9;
--color-bg-card: #ffffff;
--color-bg-card-hover: #e2e8f0;
--color-text-primary: #0f172a;
--color-text-secondary: #475569;
--color-border: #cbd5e1;
}
/* Dark mode */
.dark {
--color-bg-dark: #0f172a;
--color-bg-card: #1e293b;
--color-bg-card-hover: #334155;
--color-text-primary: #f8fafc;
--color-text-secondary: #94a3b8;
--color-border: #334155;
}
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, 'Helvetica Neue', Arial, sans-serif;
-webkit-font-smoothing: antialiased;
@@ -15,7 +35,7 @@ body {
}
::-webkit-scrollbar-track {
background: #1e293b;
background: var(--color-bg-card);
}
::-webkit-scrollbar-thumb {
@@ -30,5 +50,5 @@ body {
/* Selection */
::selection {
background: rgba(99, 102, 241, 0.3);
color: #f8fafc;
color: var(--color-text-primary);
}
+82 -32
View File
@@ -1,15 +1,21 @@
import { useState } from 'react';
import { useMutation } from '@tanstack/react-query';
import { analysisApi } from '../api/client';
import { Search, CheckCircle, AlertCircle, Clock, FileText } from 'lucide-react';
import { useMutation, useQuery } from '@tanstack/react-query';
import { analysisApi, exportApi } from '../api/client';
import { Search, CheckCircle, AlertCircle, Clock, FileText, Download, ChevronDown } from 'lucide-react';
import type { CompanyAnalysis } from '../types';
export function Analysis() {
const [companyName, setCompanyName] = useState('');
const [selectedModel, setSelectedModel] = useState('');
const [result, setResult] = useState<CompanyAnalysis | null>(null);
const modelsQuery = useQuery({
queryKey: ['models'],
queryFn: () => analysisApi.listModels(),
});
const mutation = useMutation({
mutationFn: (name: string) => analysisApi.analyzeCompany(name),
mutationFn: (name: string) => analysisApi.analyzeCompany(name, selectedModel || undefined),
onSuccess: (data) => setResult(data),
});
@@ -33,31 +39,57 @@ export function Analysis() {
</div>
{/* Search Form */}
<form onSubmit={handleSubmit} className="flex gap-4">
<div className="flex-1 relative">
<Search className="absolute left-4 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
type="text"
value={companyName}
onChange={(e) => setCompanyName(e.target.value)}
placeholder="Enter company name (e.g., nvidia, intel, amd)"
className="w-full bg-bg-card/80 border border-primary/30 rounded-xl pl-12 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
/>
<form onSubmit={handleSubmit} className="space-y-4">
<div className="flex gap-4">
<div className="flex-1 relative">
<Search className="absolute left-4 top-1/2 -translate-y-1/2 text-text-secondary" size={18} />
<input
type="text"
value={companyName}
onChange={(e) => setCompanyName(e.target.value)}
placeholder="Enter company name (e.g., nvidia, intel, amd)"
className="w-full bg-bg-card/80 border border-primary/30 rounded-xl pl-12 pr-4 py-3 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
/>
</div>
<button
type="submit"
disabled={mutation.isPending || !companyName.trim()}
className="bg-gradient-to-r from-primary to-primary-dark text-white font-semibold py-3 px-6 rounded-xl hover:shadow-lg hover:shadow-primary/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center gap-2"
>
{mutation.isPending ? (
<div className="animate-spin rounded-full h-5 w-5 border-t-2 border-b-2 border-white"></div>
) : (
<>
<Search size={18} />
Analyze
</>
)}
</button>
</div>
{/* Model Selector */}
<div className="flex items-center gap-3">
<label className="text-sm font-medium text-text-secondary whitespace-nowrap">
LLM Model
</label>
<div className="relative flex-1 max-w-xs">
<select
value={selectedModel}
onChange={(e) => setSelectedModel(e.target.value)}
className="w-full appearance-none bg-bg-card/80 border border-primary/30 rounded-lg pl-3 pr-8 py-2 text-sm text-text-primary focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all cursor-pointer"
>
<option value="">
{modelsQuery.data ? `Default (${modelsQuery.data.default})` : 'Default'}
</option>
{modelsQuery.data?.models.map((m) => (
<option key={m.id} value={m.id}>
{m.name} ({m.provider})
</option>
))}
</select>
<ChevronDown className="absolute right-2 top-1/2 -translate-y-1/2 text-text-secondary pointer-events-none" size={16} />
</div>
</div>
<button
type="submit"
disabled={mutation.isPending || !companyName.trim()}
className="bg-gradient-to-r from-primary to-primary-dark text-white font-semibold py-3 px-6 rounded-xl hover:shadow-lg hover:shadow-primary/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center gap-2"
>
{mutation.isPending ? (
<div className="animate-spin rounded-full h-5 w-5 border-t-2 border-b-2 border-white"></div>
) : (
<>
<Search size={18} />
Analyze
</>
)}
</button>
</form>
{/* Error */}
@@ -106,10 +138,28 @@ export function Analysis() {
{/* Analysis Content */}
{result.success && result.analysis && (
<div className="bg-bg-card/60 backdrop-blur-lg border border-primary/15 rounded-2xl p-6">
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
AI Analysis Results
</h3>
<div className="prose prose-invert max-w-none">
<div className="flex items-center justify-between border-b-2 border-primary/30 pb-2 mb-4">
<h3 className="text-lg font-semibold text-text-primary">
AI Analysis Results
</h3>
<div className="flex items-center gap-2">
<button
onClick={() => exportApi.exportCsv(result.company_name)}
className="flex items-center gap-2 text-sm bg-primary/20 hover:bg-primary/30 text-primary font-medium px-3 py-1.5 rounded-lg transition-colors"
>
<Download size={14} />
Export CSV
</button>
<button
onClick={() => exportApi.exportPdf(result.company_name)}
className="flex items-center gap-2 text-sm bg-primary/20 hover:bg-primary/30 text-primary font-medium px-3 py-1.5 rounded-lg transition-colors"
>
<FileText size={14} />
Export PDF
</button>
</div>
</div>
<div className="prose dark:prose-invert max-w-none">
<div className="text-text-primary whitespace-pre-wrap leading-relaxed">
{result.analysis}
</div>
+148 -23
View File
@@ -2,22 +2,52 @@ import { useState } from 'react';
import { useQuery } from '@tanstack/react-query';
import { analyticsApi } from '../api/client';
import { AlertCircle, Database } from 'lucide-react';
import { PieChart, Pie, Cell, BarChart, Bar, XAxis, YAxis, Tooltip, ResponsiveContainer, Legend } from 'recharts';
import { PieChart, Pie, Cell, BarChart, Bar, LineChart, Line, XAxis, YAxis, Tooltip, ResponsiveContainer, Legend } from 'recharts';
import { useChartTheme } from '../context/useChartTheme';
const COLORS = ['#6366f1', '#0ea5e9', '#10b981', '#f59e0b', '#ef4444', '#8b5cf6', '#ec4899', '#14b8a6'];
export function AnalyticsPage() {
const [days, setDays] = useState(30);
const chartTheme = useChartTheme();
const { data, isLoading, isError } = useQuery({
const { data, isLoading, isError, refetch } = useQuery({
queryKey: ['analytics', days],
queryFn: () => analyticsApi.getAnalytics(days),
});
const trendsQuery = useQuery({
queryKey: ['analytics-trends', days],
queryFn: () => analyticsApi.getTrends(days),
});
if (isLoading) {
return (
<div className="flex items-center justify-center min-h-[400px]">
<div className="animate-spin rounded-full h-12 w-12 border-t-2 border-b-2 border-primary"></div>
<div className="space-y-6">
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
Analytics Dashboard
</h2>
<p className="text-text-secondary">Loading analytics data...</p>
</div>
{/* Skeleton cards */}
<div className="grid grid-cols-1 md:grid-cols-3 gap-4">
{[1, 2, 3].map((i) => (
<div key={i} className="bg-gradient-to-br from-primary/10 to-secondary/10 border border-primary/20 rounded-xl p-5 text-center animate-pulse">
<div className="h-9 w-16 bg-primary/20 rounded mx-auto mb-2" />
<div className="h-4 w-24 bg-primary/10 rounded mx-auto" />
</div>
))}
</div>
{/* Skeleton charts */}
<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
{[1, 2].map((i) => (
<div key={i} className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6 animate-pulse">
<div className="h-5 w-40 bg-primary/20 rounded mb-4" />
<div className="h-[300px] bg-primary/5 rounded" />
</div>
))}
</div>
</div>
);
}
@@ -33,15 +63,18 @@ export function AnalyticsPage() {
<div className="bg-gradient-to-br from-primary/10 to-secondary/5 border border-primary/20 rounded-xl p-6">
<div className="flex items-center gap-3 text-warning mb-2">
<Database size={24} />
<span className="font-semibold">Database Not Connected</span>
<span className="font-semibold">Unable to Load Analytics</span>
</div>
<p className="text-text-secondary">
Set <code className="bg-bg-card px-2 py-1 rounded">USE_DATABASE=true</code> in your .env file to enable analytics tracking.
Could not connect to the analytics database. Ensure PostgreSQL is running and
<code className="bg-bg-card px-2 py-1 rounded mx-1">DATABASE_URL</code> is configured correctly.
</p>
</div>
<div className="flex items-center gap-2 bg-secondary/10 border border-secondary/20 text-secondary rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>Analytics features require storing analysis results in PostgreSQL for historical tracking.</span>
<button
onClick={() => refetch()}
className="mt-3 text-sm bg-primary/20 hover:bg-primary/30 text-primary font-medium px-4 py-2 rounded-lg transition-colors"
>
Retry
</button>
</div>
</div>
);
@@ -129,11 +162,7 @@ export function AnalyticsPage() {
))}
</Pie>
<Tooltip
contentStyle={{
backgroundColor: '#1e293b',
border: '1px solid rgba(99, 102, 241, 0.3)',
borderRadius: '8px',
}}
contentStyle={chartTheme.tooltipContentStyle}
/>
<Legend />
</PieChart>
@@ -147,15 +176,11 @@ export function AnalyticsPage() {
<h3 className="text-lg font-semibold text-text-primary mb-4">Analysis Types</h3>
<ResponsiveContainer width="100%" height={300}>
<BarChart data={typeData}>
<XAxis dataKey="name" stroke="#94a3b8" fontSize={12} />
<YAxis stroke="#94a3b8" fontSize={12} />
<XAxis dataKey="name" stroke={chartTheme.axisStroke} fontSize={12} />
<YAxis stroke={chartTheme.axisStroke} fontSize={12} />
<Tooltip
contentStyle={{
backgroundColor: '#1e293b',
border: '1px solid rgba(99, 102, 241, 0.3)',
borderRadius: '8px',
}}
labelStyle={{ color: '#f8fafc' }}
contentStyle={chartTheme.tooltipContentStyle}
labelStyle={chartTheme.tooltipLabelStyle}
/>
<Bar dataKey="count" fill="#6366f1" radius={[4, 4, 0, 0]} />
</BarChart>
@@ -163,6 +188,106 @@ export function AnalyticsPage() {
</div>
)}
</div>
{/* Trend Charts */}
{trendsQuery.data && (
<div className="space-y-6">
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2">
Trends Over Time
</h3>
<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
{/* Patent count over time per company (line chart) */}
{trendsQuery.data.by_month.length > 0 && (() => {
// Pivot data: each month as a row, companies as columns
const companies = [...new Set(trendsQuery.data!.by_month.map(d => d.company_name))];
const months = [...new Set(trendsQuery.data!.by_month.map(d => d.month))].sort();
const pivoted = months.map(month => {
const row: Record<string, string | number> = { month };
for (const c of companies) {
const entry = trendsQuery.data!.by_month.find(d => d.month === month && d.company_name === c);
row[c] = entry?.count || 0;
}
return row;
});
return (
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6">
<h4 className="text-md font-semibold text-text-primary mb-4">Analyses per Company Over Time</h4>
<ResponsiveContainer width="100%" height={300}>
<LineChart data={pivoted}>
<XAxis dataKey="month" stroke={chartTheme.axisStroke} fontSize={12} />
<YAxis stroke={chartTheme.axisStroke} fontSize={12} />
<Tooltip
contentStyle={chartTheme.tooltipContentStyle}
labelStyle={chartTheme.tooltipLabelStyle}
/>
<Legend />
{companies.map((company, idx) => (
<Line
key={company}
type="monotone"
dataKey={company}
stroke={COLORS[idx % COLORS.length]}
strokeWidth={2}
dot={{ r: 4 }}
name={company.toUpperCase()}
/>
))}
</LineChart>
</ResponsiveContainer>
</div>
);
})()}
{/* Analysis type distribution over time (stacked bar) */}
{trendsQuery.data.by_type_over_time.length > 0 && (() => {
const types = [...new Set(trendsQuery.data!.by_type_over_time.map(d => d.analysis_type))];
const months = [...new Set(trendsQuery.data!.by_type_over_time.map(d => d.month))].sort();
const pivoted = months.map(month => {
const row: Record<string, string | number> = { month };
for (const t of types) {
const entry = trendsQuery.data!.by_type_over_time.find(d => d.month === month && d.analysis_type === t);
row[t] = entry?.count || 0;
}
return row;
});
return (
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6">
<h4 className="text-md font-semibold text-text-primary mb-4">Analysis Types Over Time</h4>
<ResponsiveContainer width="100%" height={300}>
<BarChart data={pivoted}>
<XAxis dataKey="month" stroke={chartTheme.axisStroke} fontSize={12} />
<YAxis stroke={chartTheme.axisStroke} fontSize={12} />
<Tooltip
contentStyle={chartTheme.tooltipContentStyle}
labelStyle={chartTheme.tooltipLabelStyle}
/>
<Legend />
{types.map((type, idx) => (
<Bar
key={type}
dataKey={type}
stackId="types"
fill={COLORS[idx % COLORS.length]}
name={type}
/>
))}
</BarChart>
</ResponsiveContainer>
</div>
);
})()}
</div>
{trendsQuery.data.by_month.length === 0 && (
<div className="text-text-secondary text-center py-8">
No trend data available yet. Run analyses over multiple days to see trends.
</div>
)}
</div>
)}
</div>
);
}
+197 -15
View File
@@ -1,20 +1,37 @@
import { useState } from 'react';
import { useMutation } from '@tanstack/react-query';
import { useMutation, useQuery } from '@tanstack/react-query';
import { analysisApi } from '../api/client';
import { Rocket, CheckCircle, AlertCircle, ChevronDown, ChevronUp } from 'lucide-react';
import { Rocket, CheckCircle, AlertCircle, ChevronDown, ChevronUp, RefreshCw, Inbox } from 'lucide-react';
import { BarChart, Bar, XAxis, YAxis, Tooltip, ResponsiveContainer, Cell } from 'recharts';
import { useChartTheme } from '../context/useChartTheme';
import type { BatchAnalysisResult } from '../types';
export function Batch() {
const [companiesInput, setCompaniesInput] = useState('');
const [maxWorkers, setMaxWorkers] = useState(3);
const [selectedModel, setSelectedModel] = useState('');
const [result, setResult] = useState<BatchAnalysisResult | null>(null);
const [expandedItems, setExpandedItems] = useState<Set<string>>(new Set());
const chartTheme = useChartTheme();
const modelsQuery = useQuery({
queryKey: ['models'],
queryFn: () => analysisApi.listModels(),
});
const jobsQuery = useQuery({
queryKey: ['jobs'],
queryFn: () => analysisApi.listJobs(undefined, 20),
});
const mutation = useMutation({
mutationFn: ({ companies, workers }: { companies: string[]; workers: number }) =>
analysisApi.analyzeBatch(companies, workers),
onSuccess: (data) => setResult(data),
analysisApi.analyzeBatch(companies, workers, selectedModel || undefined),
onSuccess: (data) => {
setResult(data);
jobsQuery.refetch();
},
});
const handleSubmit = (e: React.FormEvent) => {
@@ -85,6 +102,29 @@ export function Batch() {
<div className="text-center text-text-primary font-semibold">{maxWorkers}</div>
</div>
<div>
<label className="block text-sm font-medium text-text-secondary mb-2">
LLM Model
</label>
<div className="relative">
<select
value={selectedModel}
onChange={(e) => setSelectedModel(e.target.value)}
className="w-full appearance-none bg-bg-card/80 border border-primary/30 rounded-lg pl-3 pr-8 py-2 text-sm text-text-primary focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all cursor-pointer"
>
<option value="">
{modelsQuery.data ? `Default (${modelsQuery.data.default})` : 'Default'}
</option>
{modelsQuery.data?.models.map((m) => (
<option key={m.id} value={m.id}>
{m.name} ({m.provider})
</option>
))}
</select>
<ChevronDown className="absolute right-2 top-1/2 -translate-y-1/2 text-text-secondary pointer-events-none" size={16} />
</div>
</div>
<button
type="submit"
disabled={mutation.isPending || !companiesInput.trim()}
@@ -114,9 +154,38 @@ export function Batch() {
{/* Error */}
{mutation.isError && (
<div className="flex items-center gap-2 bg-error/10 border border-error/20 text-error rounded-xl px-4 py-3">
<AlertCircle size={18} />
<span>Batch analysis failed. Please try again.</span>
<div className="bg-error/10 border border-error/20 rounded-xl px-4 py-3">
<div className="flex items-center gap-2 text-error">
<AlertCircle size={18} />
<span className="font-semibold">Batch analysis failed</span>
</div>
<p className="text-text-secondary text-sm mt-1 ml-7">
{mutation.error instanceof Error ? mutation.error.message : 'An unexpected error occurred.'}
{' '}Check your connection and try again.
</p>
<div className="ml-7 mt-2 flex items-center gap-3">
<button
onClick={() => {
const companies = companiesInput
.split(/[,\n]/)
.map((c) => c.trim())
.filter((c) => c.length > 0);
if (companies.length > 0) {
mutation.mutate({ companies, workers: maxWorkers });
}
}}
className="text-sm text-primary hover:text-primary-dark underline flex items-center gap-1"
>
<RefreshCw size={14} />
Retry
</button>
<button
onClick={() => mutation.reset()}
className="text-sm text-text-secondary hover:text-text-primary underline"
>
Dismiss
</button>
</div>
</div>
)}
@@ -144,15 +213,11 @@ export function Batch() {
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6">
<ResponsiveContainer width="100%" height={300}>
<BarChart data={chartData}>
<XAxis dataKey="name" stroke="#94a3b8" fontSize={12} />
<YAxis stroke="#94a3b8" fontSize={12} />
<XAxis dataKey="name" stroke={chartTheme.axisStroke} fontSize={12} />
<YAxis stroke={chartTheme.axisStroke} fontSize={12} />
<Tooltip
contentStyle={{
backgroundColor: '#1e293b',
border: '1px solid rgba(99, 102, 241, 0.3)',
borderRadius: '8px',
}}
labelStyle={{ color: '#f8fafc' }}
contentStyle={chartTheme.tooltipContentStyle}
labelStyle={chartTheme.tooltipLabelStyle}
/>
<Bar dataKey="patents" radius={[4, 4, 0, 0]}>
{chartData.map((entry, index) => (
@@ -218,6 +283,123 @@ export function Batch() {
</div>
</div>
)}
{/* Job History */}
<div>
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
Job History
</h3>
{/* Loading skeleton */}
{jobsQuery.isLoading && (
<div className="space-y-3">
{[...Array(3)].map((_, i) => (
<div
key={i}
className="bg-bg-card/60 border border-primary/15 rounded-xl p-4 animate-pulse"
>
<div className="flex items-center justify-between">
<div className="flex items-center gap-3">
<div className="h-5 w-5 rounded-full bg-primary/20" />
<div className="h-4 w-32 rounded bg-primary/20" />
<div className="h-4 w-20 rounded bg-primary/10" />
</div>
<div className="h-6 w-20 rounded-full bg-primary/15" />
</div>
<div className="mt-3 flex gap-4">
<div className="h-3 w-24 rounded bg-primary/10" />
<div className="h-3 w-16 rounded bg-primary/10" />
</div>
</div>
))}
</div>
)}
{/* Job history error */}
{jobsQuery.isError && (
<div className="bg-error/10 border border-error/20 rounded-xl px-4 py-3">
<div className="flex items-center gap-2 text-error">
<AlertCircle size={18} />
<span className="font-semibold">Failed to load job history</span>
</div>
<p className="text-text-secondary text-sm mt-1 ml-7">
{jobsQuery.error instanceof Error ? jobsQuery.error.message : 'Could not retrieve past jobs.'}
</p>
<button
onClick={() => jobsQuery.refetch()}
className="ml-7 mt-2 text-sm text-primary hover:text-primary-dark underline flex items-center gap-1"
>
<RefreshCw size={14} />
Retry
</button>
</div>
)}
{/* Empty state */}
{jobsQuery.isSuccess && jobsQuery.data.length === 0 && !result && (
<div className="bg-bg-card/60 border border-primary/15 border-dashed rounded-xl p-8 text-center">
<Inbox className="mx-auto text-text-secondary/40 mb-3" size={40} />
<p className="text-text-secondary font-medium">No batch jobs yet</p>
<p className="text-text-secondary/70 text-sm mt-1">
Submit a batch analysis above to get started. Your job history will appear here.
</p>
</div>
)}
{/* Job list */}
{jobsQuery.isSuccess && jobsQuery.data.length > 0 && (
<div className="space-y-3">
{jobsQuery.data.map((job) => (
<div
key={job.job_id}
className="bg-bg-card/60 border border-primary/15 rounded-xl p-4"
>
<div className="flex items-center justify-between">
<div className="flex items-center gap-3">
{job.status === 'completed' && <CheckCircle className="text-success" size={18} />}
{job.status === 'failed' && <AlertCircle className="text-error" size={18} />}
{(job.status === 'pending' || job.status === 'running') && (
<div className="animate-spin rounded-full h-[18px] w-[18px] border-t-2 border-b-2 border-secondary" />
)}
<span className="font-mono text-sm text-text-primary">{job.job_id.slice(0, 8)}</span>
<span className="text-text-secondary text-sm">
{job.total_companies} {job.total_companies === 1 ? 'company' : 'companies'}
</span>
</div>
<span
className={`text-xs font-semibold px-2.5 py-1 rounded-full ${
job.status === 'completed'
? 'bg-success/15 text-success'
: job.status === 'failed'
? 'bg-error/15 text-error'
: 'bg-secondary/15 text-secondary'
}`}
>
{job.status}
</span>
</div>
{(job.status === 'running' || job.status === 'pending') && job.total_companies > 0 && (
<div className="mt-3">
<div className="flex items-center justify-between text-xs text-text-secondary mb-1">
<span>Progress</span>
<span>{job.completed_companies}/{job.total_companies}</span>
</div>
<div className="h-1.5 bg-bg-dark rounded-full overflow-hidden">
<div
className="h-full bg-gradient-to-r from-primary to-secondary rounded-full transition-all duration-300"
style={{ width: `${(job.completed_companies / job.total_companies) * 100}%` }}
/>
</div>
</div>
)}
{job.status === 'failed' && job.error && (
<p className="mt-2 text-sm text-error/80">{job.error}</p>
)}
</div>
))}
</div>
)}
</div>
</div>
);
}
+161
View File
@@ -0,0 +1,161 @@
import { useState } from 'react';
import { useSearchParams } from 'react-router-dom';
import { useQuery } from '@tanstack/react-query';
import { analysisApi } from '../api/client';
import { GitCompareArrows, AlertCircle, FileText, Clock } from 'lucide-react';
import type { CompanyAnalysis } from '../types';
function CompanyPanel({ data, isLoading, isError }: { data?: CompanyAnalysis; isLoading: boolean; isError: boolean }) {
if (isLoading) {
return (
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6 animate-pulse">
<div className="h-6 w-32 bg-primary/20 rounded mb-4" />
<div className="space-y-3">
<div className="h-4 bg-primary/10 rounded w-full" />
<div className="h-4 bg-primary/10 rounded w-3/4" />
<div className="h-4 bg-primary/10 rounded w-5/6" />
</div>
</div>
);
}
if (isError) {
return (
<div className="bg-error/10 border border-error/20 rounded-2xl p-6">
<div className="flex items-center gap-2 text-error">
<AlertCircle size={18} />
<span>Failed to load analysis. Check the company name and try again.</span>
</div>
</div>
);
}
if (!data) return null;
return (
<div className="bg-bg-card/60 border border-primary/15 rounded-2xl p-6 space-y-4">
<h3 className="text-lg font-bold text-text-primary border-b-2 border-primary/30 pb-2">
{data.company_name.toUpperCase()}
</h3>
<div className="grid grid-cols-2 gap-3">
<div className="bg-primary/10 rounded-lg p-3 text-center">
<FileText className="mx-auto mb-1 text-primary" size={18} />
<div className="text-xl font-bold text-text-primary">{data.patent_count}</div>
<div className="text-xs text-text-secondary uppercase">Patents</div>
</div>
<div className="bg-primary/10 rounded-lg p-3 text-center">
<Clock className="mx-auto mb-1 text-primary" size={18} />
<div className="text-sm font-medium text-text-primary">
{new Date(data.timestamp).toLocaleDateString()}
</div>
<div className="text-xs text-text-secondary uppercase">Analyzed</div>
</div>
</div>
{data.success && data.analysis ? (
<div className="text-text-primary whitespace-pre-wrap leading-relaxed text-sm">
{data.analysis}
</div>
) : (
<div className="text-error text-sm">{data.error || 'Analysis not available'}</div>
)}
</div>
);
}
export function Compare() {
const [searchParams, setSearchParams] = useSearchParams();
const [companyA, setCompanyA] = useState(searchParams.get('a') || '');
const [companyB, setCompanyB] = useState(searchParams.get('b') || '');
const queryA = searchParams.get('a') || '';
const queryB = searchParams.get('b') || '';
const resultA = useQuery({
queryKey: ['analyze', queryA],
queryFn: () => analysisApi.analyzeCompany(queryA),
enabled: !!queryA,
});
const resultB = useQuery({
queryKey: ['analyze', queryB],
queryFn: () => analysisApi.analyzeCompany(queryB),
enabled: !!queryB,
});
const handleCompare = (e: React.FormEvent) => {
e.preventDefault();
const a = companyA.trim();
const b = companyB.trim();
if (a && b) {
setSearchParams({ a, b });
}
};
return (
<div className="space-y-6">
{/* Header */}
<div>
<h2 className="text-xl font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-2">
Portfolio Comparison
</h2>
<p className="text-text-secondary">
Compare patent portfolios of two companies side by side.
</p>
</div>
{/* Input Form */}
<form onSubmit={handleCompare} className="flex flex-col sm:flex-row gap-3 items-end">
<div className="flex-1">
<label className="block text-sm font-medium text-text-secondary mb-1">Company A</label>
<input
type="text"
value={companyA}
onChange={(e) => setCompanyA(e.target.value)}
placeholder="e.g. nvidia"
className="w-full bg-bg-card/80 border border-primary/30 rounded-xl px-4 py-2.5 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
/>
</div>
<div className="flex-1">
<label className="block text-sm font-medium text-text-secondary mb-1">Company B</label>
<input
type="text"
value={companyB}
onChange={(e) => setCompanyB(e.target.value)}
placeholder="e.g. intel"
className="w-full bg-bg-card/80 border border-primary/30 rounded-xl px-4 py-2.5 text-text-primary placeholder-text-secondary/50 focus:outline-none focus:border-primary focus:ring-2 focus:ring-primary/20 transition-all"
/>
</div>
<button
type="submit"
disabled={!companyA.trim() || !companyB.trim() || resultA.isLoading || resultB.isLoading}
className="bg-gradient-to-r from-primary to-primary-dark text-white font-semibold py-2.5 px-6 rounded-xl hover:shadow-lg hover:shadow-primary/30 transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center gap-2"
>
<GitCompareArrows size={18} />
Compare
</button>
</form>
{/* Comparison Panels */}
{(queryA || queryB) && (
<div className="grid grid-cols-1 lg:grid-cols-2 gap-6">
{queryA && (
<CompanyPanel
data={resultA.data}
isLoading={resultA.isLoading}
isError={resultA.isError}
/>
)}
{queryB && (
<CompanyPanel
data={resultB.data}
isLoading={resultB.isLoading}
isError={resultB.isError}
/>
)}
</div>
)}
</div>
);
}
+1 -1
View File
@@ -31,7 +31,7 @@ export function Login() {
};
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950 flex items-center justify-center px-4">
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-slate-100 dark:to-indigo-950 flex items-center justify-center px-4">
<div className="w-full max-w-md">
{/* Brand */}
<div className="text-center mb-8">
+1 -1
View File
@@ -40,7 +40,7 @@ export function Register() {
};
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-indigo-950 flex items-center justify-center px-4">
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-slate-100 dark:to-indigo-950 flex items-center justify-center px-4">
<div className="w-full max-w-md">
{/* Brand */}
<div className="text-center mb-8">
+28 -42
View File
@@ -1,46 +1,32 @@
export interface User {
id: number;
email: string;
role: 'admin' | 'user';
created_at: string;
}
/**
* Application types derived from the auto-generated OpenAPI schema.
*
* Run `npm run generate:local` (or `npm run generate` with the API running)
* to regenerate `src/api/schema.d.ts` from the backend OpenAPI spec.
*
* These aliases keep the rest of the codebase stable while the source of
* truth lives in the generated file.
*/
export interface TokenResponse {
access_token: string;
refresh_token: string;
token_type: string;
}
import type { components } from '../api/schema';
export interface CompanyAnalysis {
company_name: string;
analysis: string;
patent_count: number;
success: boolean;
error: string | null;
timestamp: string;
}
export interface BatchAnalysisResult {
results: CompanyAnalysis[];
total_companies: number;
successful: number;
failed: number;
timestamp: string;
}
export interface JobStatus {
job_id: string;
status: 'pending' | 'running' | 'completed' | 'failed';
progress: number;
total_companies: number;
completed_companies: number;
result: BatchAnalysisResult | null;
error: string | null;
}
export interface Analytics {
total_messages: number;
// Re-export schema types under the names the rest of the app expects.
export type User = components['schemas']['UserResponse'];
export type TokenResponse = components['schemas']['TokenResponse'];
export type CompanyAnalysis = components['schemas']['CompanyAnalysisResponse'];
export type BatchAnalysisResult = components['schemas']['BatchAnalysisResponse'];
export type JobStatus = components['schemas']['JobStatus'];
export type Analytics = Omit<components['schemas']['AnalyticsResponse'], 'by_company' | 'by_type'> & {
by_company: Array<{ company_name: string; count: number }>;
by_type: Array<{ analysis_type: string; count: number }>;
period_days: number;
}
};
// Additional generated types that may be useful elsewhere.
export type RegisterRequest = components['schemas']['RegisterRequest'];
export type LoginRequest = components['schemas']['LoginRequest'];
export type RefreshRequest = components['schemas']['RefreshRequest'];
export type UpdateRoleRequest = components['schemas']['UpdateRoleRequest'];
export type HealthResponse = components['schemas']['HealthResponse'];
export type BatchAnalysisRequest = components['schemas']['BatchAnalysisRequest'];
export type ValidationError = components['schemas']['ValidationError'];
export type HTTPValidationError = components['schemas']['HTTPValidationError'];
+7 -6
View File
@@ -4,6 +4,7 @@ export default {
"./index.html",
"./src/**/*.{js,ts,jsx,tsx}",
],
darkMode: 'class',
theme: {
extend: {
colors: {
@@ -16,15 +17,15 @@ export default {
warning: '#f59e0b',
error: '#ef4444',
bg: {
dark: '#0f172a',
card: '#1e293b',
'card-hover': '#334155',
dark: 'var(--color-bg-dark)',
card: 'var(--color-bg-card)',
'card-hover': 'var(--color-bg-card-hover)',
},
text: {
primary: '#f8fafc',
secondary: '#94a3b8',
primary: 'var(--color-text-primary)',
secondary: 'var(--color-text-secondary)',
},
border: '#334155',
border: 'var(--color-border)',
},
},
},
+3
View File
@@ -15,3 +15,6 @@ pandas
bcrypt
PyJWT
slowapi
apscheduler
boto3
reportlab
+44
View File
@@ -182,3 +182,47 @@ class TestJobEndpoints:
"""Test listing jobs with status filter."""
response = client.get("/jobs?status=completed")
assert response.status_code == 200
class TestModelValidation:
"""Test that unsupported model identifiers are rejected."""
def test_analyze_rejects_unsupported_model(self, client, mock_analyzer):
"""GET /analyze/{company} with unsupported model returns 400."""
response = client.get("/analyze/nvidia?model=fake/nonexistent-model")
assert response.status_code == 400
assert "Unsupported model" in response.json()["detail"]
def test_analyze_accepts_supported_model(self, client, mock_analyzer):
"""GET /analyze/{company} with a supported model succeeds."""
mock_result = CompanyAnalysisResult(
company_name="nvidia",
analysis="test",
patent_count=1,
success=True,
timestamp=datetime.now(),
model="anthropic/claude-3.5-sonnet",
)
mock_analyzer._analyze_company_safe.return_value = mock_result
response = client.get("/analyze/nvidia?model=anthropic/claude-3.5-sonnet")
assert response.status_code == 200
def test_batch_rejects_unsupported_model(self, client, mock_analyzer):
"""POST /analyze/batch with unsupported model returns 400."""
response = client.post(
"/analyze/batch",
json={"companies": ["nvidia"], "model": "fake/nonexistent-model"},
)
assert response.status_code == 400
assert "Unsupported model" in response.json()["detail"]
def test_list_models_returns_supported(self, client):
"""GET /models returns the allow-list."""
response = client.get("/models")
assert response.status_code == 200
data = response.json()
assert "models" in data
assert "default" in data
assert len(data["models"]) > 0
assert all("id" in m and "name" in m and "provider" in m for m in data["models"])
+209 -9
View File
@@ -1,13 +1,29 @@
"""Tests for JWT authentication flow: register, login, protected routes, refresh, admin access."""
"""Tests for JWT authentication flow: register, login, protected routes, refresh, admin access.
from datetime import datetime, timezone
Covers all five scenarios required by issue #1624:
1. Registration (POST /auth/register)
2. Login (POST /auth/login)
3. Protected route access (GET /auth/me) -- valid, missing, expired, wrong-type tokens
4. Token refresh (POST /auth/refresh)
5. Admin-only endpoints (GET /admin/users, PATCH role, DELETE user)
All tests use mocked DB fixtures and require no live database.
"""
from datetime import datetime, timedelta, timezone
from unittest.mock import MagicMock, patch
import jwt as pyjwt
import pytest
from fastapi.testclient import TestClient
from SPARC.api import app
from SPARC.auth import create_access_token, create_refresh_token
from SPARC.auth import (
JWT_ALGORITHM,
JWT_SECRET,
create_access_token,
create_refresh_token,
)
@pytest.fixture
@@ -171,12 +187,6 @@ class TestGetMe:
def test_expired_token_returns_401(self, client, mock_db):
"""An expired token should return 401."""
# Create a token that has already expired
from datetime import timedelta
import jwt as pyjwt
from SPARC.auth import JWT_ALGORITHM, JWT_SECRET
payload = {
"sub": "1",
"email": "user@test.com",
@@ -300,3 +310,193 @@ class TestAdminUsers:
assert response.status_code == 400
assert "own role" in response.json()["detail"].lower()
def test_role_change_nonexistent_user_returns_404(self, client, mock_db):
"""Changing role for a user that does not exist should return 404."""
admin = _make_admin_user()
mock_db.get_user_by_id.return_value = admin
mock_db.update_user_role.return_value = None
response = client.patch(
"/admin/users/999/role",
json={"role": "admin"},
headers=_auth_header(admin),
)
assert response.status_code == 404
assert "not found" in response.json()["detail"].lower()
def test_regular_user_cannot_change_role(self, client, mock_db):
"""Non-admin user should receive 403 when trying to change roles."""
user = _make_regular_user()
mock_db.get_user_by_id.return_value = user
response = client.patch(
"/admin/users/1/role",
json={"role": "admin"},
headers=_auth_header(user),
)
assert response.status_code == 403
class TestAdminDeleteUser:
"""DELETE /admin/users/{user_id}"""
def test_admin_can_delete_user(self, client, mock_db):
"""Admin should be able to delete another user."""
admin = _make_admin_user()
mock_db.get_user_by_id.return_value = admin
mock_db.delete_user.return_value = True
response = client.delete(
"/admin/users/2",
headers=_auth_header(admin),
)
assert response.status_code == 200
assert "deleted" in response.json()["message"].lower()
mock_db.delete_user.assert_called_once_with(2)
def test_admin_cannot_delete_self(self, client, mock_db):
"""Admin should not be able to delete themselves."""
admin = _make_admin_user()
mock_db.get_user_by_id.return_value = admin
response = client.delete(
"/admin/users/1",
headers=_auth_header(admin),
)
assert response.status_code == 400
assert "yourself" in response.json()["detail"].lower()
def test_delete_nonexistent_user_returns_404(self, client, mock_db):
"""Deleting a user that does not exist should return 404."""
admin = _make_admin_user()
mock_db.get_user_by_id.return_value = admin
mock_db.delete_user.return_value = False
response = client.delete(
"/admin/users/999",
headers=_auth_header(admin),
)
assert response.status_code == 404
assert "not found" in response.json()["detail"].lower()
def test_regular_user_cannot_delete_user(self, client, mock_db):
"""Non-admin user should receive 403 when trying to delete users."""
user = _make_regular_user()
mock_db.get_user_by_id.return_value = user
response = client.delete(
"/admin/users/1",
headers=_auth_header(user),
)
assert response.status_code == 403
def test_no_token_cannot_delete_user(self, client):
"""Missing token should be rejected for delete endpoint."""
response = client.delete("/admin/users/1")
assert response.status_code in (401, 403)
class TestEdgeCases:
"""Additional edge-case tests for auth robustness."""
def test_register_invalid_email_returns_422(self, client, mock_db):
"""Registration with an invalid email format should return 422."""
response = client.post(
"/auth/register",
json={"email": "not-an-email", "password": "securepass123"},
)
assert response.status_code == 422
def test_register_short_password_returns_422(self, client, mock_db):
"""Registration with a password shorter than 8 chars should return 422."""
response = client.post(
"/auth/register",
json={"email": "user@test.com", "password": "short"},
)
assert response.status_code == 422
def test_register_missing_fields_returns_422(self, client, mock_db):
"""Registration with missing fields should return 422."""
response = client.post("/auth/register", json={})
assert response.status_code == 422
def test_login_missing_fields_returns_422(self, client, mock_db):
"""Login with missing fields should return 422."""
response = client.post("/auth/login", json={"email": "user@test.com"})
assert response.status_code == 422
def test_malformed_token_returns_401(self, client, mock_db):
"""A completely malformed token string should return 401."""
response = client.get(
"/auth/me",
headers={"Authorization": "Bearer not.a.valid.jwt.token"},
)
assert response.status_code == 401
def test_token_with_wrong_secret_returns_401(self, client, mock_db):
"""A token signed with a different secret should return 401."""
payload = {
"sub": "1",
"email": "user@test.com",
"role": "user",
"exp": datetime.now(timezone.utc) + timedelta(hours=1),
"type": "access",
}
wrong_secret_token = pyjwt.encode(payload, "wrong-secret", algorithm=JWT_ALGORITHM)
response = client.get(
"/auth/me",
headers={"Authorization": f"Bearer {wrong_secret_token}"},
)
assert response.status_code == 401
def test_token_for_deleted_user_returns_401(self, client, mock_db):
"""A valid token for a user no longer in the DB should return 401."""
user = _make_regular_user()
mock_db.get_user_by_id.return_value = None # user was deleted
response = client.get("/auth/me", headers=_auth_header(user))
assert response.status_code == 401
def test_refresh_for_deleted_user_returns_401(self, client, mock_db):
"""Refreshing a token for a deleted user should return 401."""
user = _make_regular_user()
mock_db.get_user_by_id.return_value = None
refresh = create_refresh_token(user["id"], user["email"], user["role"])
response = client.post(
"/auth/refresh", json={"refresh_token": refresh}
)
assert response.status_code == 401
def test_login_returns_decodable_tokens(self, client, mock_db):
"""Tokens returned by login should be decodable and contain expected claims."""
user = _make_regular_user()
mock_db.authenticate_user.return_value = user
response = client.post(
"/auth/login",
json={"email": "user@test.com", "password": "correctpassword"},
)
data = response.json()
access_payload = pyjwt.decode(
data["access_token"], JWT_SECRET, algorithms=[JWT_ALGORITHM]
)
assert access_payload["sub"] == str(user["id"])
assert access_payload["email"] == user["email"]
assert access_payload["type"] == "access"
refresh_payload = pyjwt.decode(
data["refresh_token"], JWT_SECRET, algorithms=[JWT_ALGORITHM]
)
assert refresh_payload["type"] == "refresh"
+2 -1
View File
@@ -1,7 +1,8 @@
"""Tests for rate limiting on auth endpoints."""
from unittest.mock import MagicMock, patch
import pytest
from unittest.mock import Mock, patch, MagicMock
from fastapi.testclient import TestClient
from SPARC.api import app
+7
View File
@@ -14,6 +14,7 @@ class TestJWTSecretStartupCheck:
with patch.dict(os.environ, {"APP_ENV": "production"}):
# Reload config to pick up the new APP_ENV
import importlib
import SPARC.config
importlib.reload(SPARC.config)
@@ -31,6 +32,7 @@ class TestJWTSecretStartupCheck:
"""Starting with default secret and APP_ENV=development must not raise."""
with patch.dict(os.environ, {"APP_ENV": "development"}):
import importlib
import SPARC.config
importlib.reload(SPARC.config)
@@ -46,6 +48,7 @@ class TestJWTSecretStartupCheck:
"""Starting with a custom secret in production must not raise."""
with patch.dict(os.environ, {"APP_ENV": "production"}):
import importlib
import SPARC.config
importlib.reload(SPARC.config)
@@ -65,6 +68,7 @@ class TestJWTSecretStartupCheck:
env.pop("APP_ENV", None)
with patch.dict(os.environ, env, clear=True):
import importlib
import SPARC.config
importlib.reload(SPARC.config)
@@ -84,6 +88,7 @@ class TestCORSConfig:
"""When CORS_ORIGINS is unset, defaults to localhost origins."""
with patch.dict(os.environ, {"CORS_ORIGINS": ""}):
import importlib
import SPARC.config
importlib.reload(SPARC.config)
assert SPARC.config.cors_origins == [
@@ -95,6 +100,7 @@ class TestCORSConfig:
"""Setting CORS_ORIGINS configures allowed origins."""
with patch.dict(os.environ, {"CORS_ORIGINS": "https://sparc.example.com,https://app.example.com"}):
import importlib
import SPARC.config
importlib.reload(SPARC.config)
assert SPARC.config.cors_origins == [
@@ -109,6 +115,7 @@ class TestCORSConfig:
"""A single origin without comma works correctly."""
with patch.dict(os.environ, {"CORS_ORIGINS": "https://sparc.example.com"}):
import importlib
import SPARC.config
importlib.reload(SPARC.config)
assert SPARC.config.cors_origins == ["https://sparc.example.com"]
+280
View File
@@ -0,0 +1,280 @@
"""Tests for webhook notification system: retry logic and Slack/Discord payload format.
Covers issue #1657:
- Retry logic with exponential backoff in _send_with_retry
- Slack/Discord payload formatting in _build_payload
- Generic HTTP POST payload formatting
- notify() dispatching to multiple URLs
- notify_job_completed() and notify_alert() convenience helpers
"""
from datetime import datetime
from unittest.mock import MagicMock, patch, call
import pytest
import requests
from SPARC.webhooks import (
MAX_RETRIES,
_build_payload,
_is_slack_url,
_send_with_retry,
notify,
notify_alert,
notify_job_completed,
)
class TestIsSlackUrl:
"""Tests for Slack/Discord URL detection."""
def test_slack_webhook_url(self):
assert _is_slack_url("https://hooks.slack.com/services/T00/B00/xxx") is True
def test_discord_webhook_url(self):
assert _is_slack_url("https://discord.com/api/webhooks/123/abc") is True
def test_generic_url(self):
assert _is_slack_url("https://example.com/webhook") is False
def test_empty_url(self):
assert _is_slack_url("") is False
class TestBuildPayload:
"""Tests for payload construction."""
def test_generic_payload_structure(self):
"""Generic payload includes event type, timestamp, and data."""
payload = _build_payload("job_completed", {"job_id": "abc123"})
assert payload["event"] == "job_completed"
assert payload["job_id"] == "abc123"
assert "timestamp" in payload
# Timestamp should be ISO format ending with Z
assert payload["timestamp"].endswith("Z")
def test_slack_payload_wraps_in_text(self):
"""Slack payload wraps content in a 'text' field."""
payload = _build_payload("patent_alert", {"company_name": "NVIDIA"}, slack=True)
assert "text" in payload
assert "patent_alert" in payload["text"]
assert "NVIDIA" in payload["text"]
# Slack payload should NOT have the event/timestamp at top level
assert "event" not in payload
assert "timestamp" not in payload
def test_generic_payload_does_not_have_text_field(self):
"""Non-Slack payload does not wrap in text."""
payload = _build_payload("job_completed", {"status": "done"})
assert "text" not in payload
assert payload["status"] == "done"
def test_slack_payload_contains_bold_header(self):
"""Slack payload starts with bold event header using Slack markdown."""
payload = _build_payload("job_completed", {"count": 5}, slack=True)
assert payload["text"].startswith("*[SPARC] job_completed*")
def test_payload_merges_all_data_keys(self):
"""All data keys are included in the generic payload."""
data = {"key1": "val1", "key2": 42, "key3": True}
payload = _build_payload("test_event", data)
assert payload["key1"] == "val1"
assert payload["key2"] == 42
assert payload["key3"] is True
class TestSendWithRetry:
"""Tests for retry logic in _send_with_retry."""
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_success_on_first_attempt(self, mock_post, mock_sleep):
"""Successful delivery on first attempt, no retries."""
mock_post.return_value = MagicMock(status_code=200)
result = _send_with_retry("https://example.com/hook", {"event": "test"})
assert result is True
mock_post.assert_called_once()
mock_sleep.assert_not_called()
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_success_on_second_attempt(self, mock_post, mock_sleep):
"""Fails first, succeeds on retry."""
mock_post.side_effect = [
MagicMock(status_code=500),
MagicMock(status_code=200),
]
result = _send_with_retry("https://example.com/hook", {"event": "test"})
assert result is True
assert mock_post.call_count == 2
mock_sleep.assert_called_once()
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_all_retries_exhausted(self, mock_post, mock_sleep):
"""Returns False after all retries fail."""
mock_post.return_value = MagicMock(status_code=500)
result = _send_with_retry("https://example.com/hook", {"event": "test"})
assert result is False
assert mock_post.call_count == MAX_RETRIES
assert mock_sleep.call_count == MAX_RETRIES - 1
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_exponential_backoff_timing(self, mock_post, mock_sleep):
"""Backoff wait times follow exponential pattern (2^attempt)."""
mock_post.return_value = MagicMock(status_code=500)
_send_with_retry("https://example.com/hook", {"event": "test"})
# With BACKOFF_BASE=2: attempt 1 -> sleep(2), attempt 2 -> sleep(4)
expected_waits = [call(2 ** i) for i in range(1, MAX_RETRIES)]
assert mock_sleep.call_args_list == expected_waits
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_network_error_triggers_retry(self, mock_post, mock_sleep):
"""Network exceptions trigger retry, not immediate failure."""
mock_post.side_effect = [
requests.ConnectionError("Connection refused"),
MagicMock(status_code=200),
]
result = _send_with_retry("https://example.com/hook", {"event": "test"})
assert result is True
assert mock_post.call_count == 2
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_timeout_error_triggers_retry(self, mock_post, mock_sleep):
"""Timeout exceptions trigger retry."""
mock_post.side_effect = [
requests.Timeout("Request timed out"),
MagicMock(status_code=200),
]
result = _send_with_retry("https://example.com/hook", {"event": "test"})
assert result is True
assert mock_post.call_count == 2
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_2xx_status_codes_accepted(self, mock_post, mock_sleep):
"""Any 2xx status code is treated as success."""
mock_post.return_value = MagicMock(status_code=204)
result = _send_with_retry("https://example.com/hook", {"event": "test"})
assert result is True
mock_post.assert_called_once()
@patch("SPARC.webhooks.time.sleep")
@patch("SPARC.webhooks.requests.post")
def test_posts_json_payload(self, mock_post, mock_sleep):
"""Payload is sent as JSON with correct timeout."""
mock_post.return_value = MagicMock(status_code=200)
payload = {"event": "test", "data": "value"}
_send_with_retry("https://example.com/hook", payload)
mock_post.assert_called_once_with(
"https://example.com/hook", json=payload, timeout=10
)
class TestNotify:
"""Tests for the notify() dispatcher."""
@patch("SPARC.webhooks._send_with_retry")
@patch("SPARC.webhooks.WEBHOOK_URLS", ["https://example.com/hook1", "https://example.com/hook2"])
def test_dispatches_to_all_urls(self, mock_send):
"""notify() sends to every configured webhook URL."""
mock_send.return_value = True
notify("job_completed", {"job_id": "test123"})
assert mock_send.call_count == 2
@patch("SPARC.webhooks._send_with_retry")
@patch("SPARC.webhooks.WEBHOOK_URLS", [])
def test_no_urls_configured_returns_immediately(self, mock_send):
"""No-op when no webhook URLs are configured."""
notify("job_completed", {"job_id": "test123"})
mock_send.assert_not_called()
@patch("SPARC.webhooks._send_with_retry")
@patch("SPARC.webhooks.WEBHOOK_URLS", [
"https://hooks.slack.com/services/T00/B00/xxx",
"https://example.com/generic",
])
def test_slack_url_gets_slack_payload(self, mock_send):
"""Slack URLs receive Slack-formatted payloads, others get generic."""
mock_send.return_value = True
notify("test_event", {"key": "val"})
# First call (Slack URL) should have "text" key
slack_payload = mock_send.call_args_list[0][0][1]
assert "text" in slack_payload
# Second call (generic URL) should have "event" key
generic_payload = mock_send.call_args_list[1][0][1]
assert "event" in generic_payload
assert generic_payload["event"] == "test_event"
class TestNotifyJobCompleted:
"""Tests for notify_job_completed() convenience function."""
@patch("SPARC.webhooks.notify")
def test_sends_correct_event_and_data(self, mock_notify):
"""Job completion sends proper event type and summary."""
notify_job_completed(
job_id="batch-001",
status="completed",
total_companies=10,
successful=8,
failed=2,
)
mock_notify.assert_called_once()
event, data = mock_notify.call_args[0]
assert event == "job_completed"
assert data["job_id"] == "batch-001"
assert data["successful"] == 8
assert data["failed"] == 2
assert "8/10" in data["summary"]
class TestNotifyAlert:
"""Tests for notify_alert() convenience function."""
@patch("SPARC.webhooks.notify")
def test_sends_correct_event_and_data(self, mock_notify):
"""Alert notification sends patent_alert event type."""
notify_alert(
company_name="NVIDIA",
alert_type="patent_count_change",
message="Patent count increased by 30%",
)
mock_notify.assert_called_once()
event, data = mock_notify.call_args[0]
assert event == "patent_alert"
assert data["company_name"] == "NVIDIA"
assert data["alert_type"] == "patent_count_change"
assert "30%" in data["message"]