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Author SHA1 Message Date
agent-company c317632edb ci: add pytest and ruff linting to CI, fix all lint errors
- Add test job to build.yaml that runs pytest and ruff before building images
- Add standalone test.yaml workflow for PRs
- Add ruff.toml with E/F/I rules configured
- Fix all ruff lint errors: sort imports, remove unused imports, fix re-exports
- Build jobs now depend on test job passing (needs: test)

Closes leeworks-agents/SPARC#18
Closes leeworks-agents/SPARC#19

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-26 06:04:24 +00:00
31 changed files with 267 additions and 1472 deletions
-18
View File
@@ -35,26 +35,8 @@ 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
# ---- 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
# ---- 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
-11
View File
@@ -34,17 +34,6 @@ jobs:
run: |
ruff check SPARC/ tests/
- name: Install Node.js and frontend dependencies
shell: sh
run: |
apk add --no-cache nodejs npm
cd frontend && npm ci
- name: Run TypeScript type check
shell: sh
run: |
cd frontend && npx tsc --noEmit
- name: Run pytest
shell: sh
env:
+25 -40
View File
@@ -5,13 +5,10 @@ to provide company performance estimation based on patent portfolios.
"""
import hashlib
import logging
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
@@ -55,13 +52,13 @@ class CompanyAnalyzer:
query_hash = hashlib.sha256(company_name.lower().encode()).hexdigest()
cached_ids = self.db.get_cached_serp_query(query_hash)
if cached_ids is not None:
logger.info("Using cached SERP results for %s (%d patents)", company_name, len(cached_ids))
print(f"Using cached SERP results for {company_name} ({len(cached_ids)} patents)")
patents = Patents(patents=[
Patent(patent_id=pid, pdf_link="")
for pid in cached_ids
])
else:
logger.info("Retrieving patents for %s...", company_name)
print(f"Retrieving patents for {company_name}...")
patents = SERP.query(company_name)
# Cache the SERP results
if patents.patents:
@@ -69,13 +66,12 @@ class CompanyAnalyzer:
company_name=company_name,
query_hash=query_hash,
patent_ids=[p.patent_id for p in patents.patents],
ttl_hours=config.serp_cache_ttl_hours,
)
if not patents.patents:
return f"No patents found for {company_name}"
logger.info("Found %d patents. Processing...", len(patents.patents))
print(f"Found {len(patents.patents)} patents. Processing...")
# Download, parse, and minimize patents in parallel
processed_patents = []
@@ -91,12 +87,12 @@ class CompanyAnalyzer:
if result:
processed_patents.append(result)
except Exception as e:
logger.warning("Failed to process %s: %s", patent.patent_id, e)
print(f"Warning: Failed to process {patent.patent_id}: {e}")
if not processed_patents:
return f"Failed to process any patents for {company_name}"
logger.info("Analyzing portfolio with LLM...")
print("Analyzing portfolio with LLM...")
# Analyze the full portfolio with LLM
analysis = self.llm_analyzer.analyze_patent_portfolio(
@@ -108,10 +104,12 @@ class CompanyAnalyzer:
def analyze_single_patent(self, patent_id: str, company_name: str) -> str:
"""Analyze a single patent by ID.
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.
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.
Args:
patent_id: Publication ID of the patent (e.g. "US-11234567-B2")
@@ -121,29 +119,16 @@ class CompanyAnalyzer:
Analysis of the specific patent's innovation quality
Raises:
FileNotFoundError: If the patent PDF cannot be found or downloaded.
FileNotFoundError: If the patent PDF is not found at the expected path.
"""
import os
logger.info("Analyzing patent %s for %s...", patent_id, company_name)
patent_path = f"patents/{patent_id}.pdf"
if not os.path.exists(patent_path):
# 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."
f"Patent PDF not found at '{patent_path}'. "
f"Download the PDF first using SERP.save_patents() or the batch analysis pipeline."
)
try:
@@ -198,7 +183,7 @@ class CompanyAnalyzer:
return {"patent_id": patent.patent_id, "content": minimized_content}
except Exception as e:
logger.warning("Failed to process %s: %s", patent.patent_id, e)
print(f"Warning: Failed to process {patent.patent_id}: {e}")
return None
def _analyze_company_safe(self, company_name: str) -> CompanyAnalysisResult:
@@ -269,7 +254,7 @@ class CompanyAnalyzer:
results: list[CompanyAnalysisResult] = []
total = len(companies)
logger.info("Starting batch analysis of %d companies...", total)
print(f"Starting batch analysis of {total} companies...")
with ThreadPoolExecutor(max_workers=max_workers) as executor:
future_to_company = {
@@ -286,8 +271,8 @@ class CompanyAnalyzer:
result = future.result()
results.append(result)
status = "OK" if result.success else "FAIL"
logger.info("[%d/%d] %s %s", completed, total, status, company)
status = "" if result.success else ""
print(f"[{completed}/{total}] {status} {company}")
if progress_callback:
progress_callback(company, completed, total)
@@ -302,12 +287,12 @@ class CompanyAnalyzer:
error=str(e),
)
)
logger.error("[%d/%d] FAIL %s: %s", completed, total, company, e)
print(f"[{completed}/{total}] ✗ {company}: {e}")
successful = sum(1 for r in results if r.success)
failed = total - successful
logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
print(f"\nBatch complete: {successful} succeeded, {failed} failed")
return BatchAnalysisResult(
results=results,
@@ -333,20 +318,20 @@ class CompanyAnalyzer:
results: list[CompanyAnalysisResult] = []
total = len(companies)
logger.info("Starting sequential analysis of %d companies...", total)
print(f"Starting sequential analysis of {total} companies...")
for idx, company in enumerate(companies, 1):
logger.info("[%d/%d] Analyzing %s...", idx, total, company)
print(f"\n[{idx}/{total}] Analyzing {company}...")
result = self._analyze_company_safe(company)
results.append(result)
status = "OK" if result.success else "FAIL"
logger.info("[%d/%d] %s %s", idx, total, status, company)
status = "" if result.success else ""
print(f"[{idx}/{total}] {status} {company}")
successful = sum(1 for r in results if r.success)
failed = total - successful
logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
print(f"\nBatch complete: {successful} succeeded, {failed} failed")
return BatchAnalysisResult(
results=results,
+7 -206
View File
@@ -9,7 +9,7 @@ from typing import Annotated, List
from fastapi import BackgroundTasks, Depends, FastAPI, HTTPException, Query, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import JSONResponse, StreamingResponse
from fastapi.responses import JSONResponse
from pydantic import BaseModel, EmailStr, Field
from slowapi import Limiter
from slowapi.errors import RateLimitExceeded
@@ -21,13 +21,11 @@ from SPARC.auth import (
TokenResponse,
UserResponse,
check_jwt_secret,
close_db_client,
create_tokens,
decode_token,
get_current_admin,
get_current_user,
get_db_client,
init_db_client,
)
from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult
@@ -77,13 +75,6 @@ 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."""
@@ -164,7 +155,6 @@ async def lifespan(app: FastAPI):
"""Initialize resources on startup, clean up on shutdown."""
global _analyzer
check_jwt_secret()
init_db_client()
_analyzer = CompanyAnalyzer()
# Mark any jobs that were running/pending before the restart as failed
from SPARC.database import DatabaseClient
@@ -176,13 +166,9 @@ 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
# Cleanup if needed
_analyzer = None
close_db_client()
app = FastAPI(
@@ -379,60 +365,6 @@ 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 ==============
@@ -453,61 +385,6 @@ async def get_analytics(
)
# ============== 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"'},
)
# ============== System Endpoints ==============
@@ -548,38 +425,6 @@ async def analyze_company(
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,
@@ -670,25 +515,8 @@ 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"])
@@ -745,51 +573,24 @@ async def get_job_status(
return _job_row_to_status(job_row)
@app.get("/jobs", response_model=PaginatedJobsResponse, tags=["Jobs"])
@app.get("/jobs", response_model=list[JobStatus], 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 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.
"""List all analysis jobs.
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:
Paginated list of job statuses
List of job statuses
"""
db = _get_job_db()
# 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)
job_rows = db.list_jobs(status=status, limit=limit)
return [_job_row_to_status(row) for row in job_rows]
+4 -29
View File
@@ -146,36 +146,11 @@ def decode_token(token: str) -> Optional[TokenPayload]:
return None
# Shared database client singleton, initialized at startup via init_db_client()
_db_client: DatabaseClient | None = None
def init_db_client() -> None:
"""Initialize the shared database client. Call once at app startup."""
global _db_client
_db_client = DatabaseClient(config.database_url)
_db_client.connect()
def close_db_client() -> None:
"""Close the shared database client. Call at app shutdown."""
global _db_client
if _db_client:
_db_client.close()
_db_client = None
def get_db_client() -> DatabaseClient:
"""Get the shared pooled database client for auth operations.
Returns the module-level singleton DatabaseClient. If not yet initialized
(e.g., during tests), creates a new instance as a fallback.
"""
global _db_client
if _db_client is None:
_db_client = DatabaseClient(config.database_url)
_db_client.connect()
return _db_client
"""Get database client for auth operations."""
client = DatabaseClient(config.database_url)
client.connect()
return client
async def get_current_user(
-21
View File
@@ -2,20 +2,12 @@
Loads environment variables from .env file for API keys and other secrets.
"""
import logging
import os
from dotenv import load_dotenv
load_dotenv()
# Logging configuration
log_level = os.getenv("LOG_LEVEL", "INFO").upper()
logging.basicConfig(
level=getattr(logging, log_level, logging.INFO),
format="%(asctime)s %(levelname)s %(name)s %(message)s",
)
# SerpAPI key for patent search
api_key = os.getenv("API_KEY")
@@ -39,12 +31,6 @@ use_database = os.getenv("USE_DATABASE", "false").lower() in ("true", "1", "yes"
patent_search_days = int(os.getenv("PATENT_SEARCH_DAYS", "90"))
patent_thread_workers = int(os.getenv("PATENT_THREAD_WORKERS", "5"))
# LLM model to use via OpenRouter (e.g. "anthropic/claude-3.5-sonnet", "openai/gpt-4o")
model = os.getenv("MODEL", "anthropic/claude-3.5-sonnet")
# SERP cache TTL in hours (how long cached search results are considered fresh)
serp_cache_ttl_hours = int(os.getenv("SERP_CACHE_TTL_HOURS", "24"))
# Root path for running behind a reverse proxy (e.g., "/api" when served at /api/)
# This ensures OpenAPI docs work correctly when accessed via the proxy
root_path = os.getenv("ROOT_PATH", "")
@@ -53,13 +39,6 @@ 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", "")
+50 -169
View File
@@ -192,35 +192,6 @@ 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
@@ -251,6 +222,8 @@ class DatabaseClient:
Returns:
Cached message dict if found, None otherwise
"""
self.connect()
prompt_hash = self.hash_prompt(prompt)
query = """
@@ -273,8 +246,7 @@ class DatabaseClient:
query += " ORDER BY timestamp DESC LIMIT 1"
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(query, params)
result = cursor.fetchone()
return dict(result) if result else None
@@ -305,10 +277,11 @@ class DatabaseClient:
Returns:
The ID of the inserted record
"""
self.connect()
prompt_hash = self.hash_prompt(prompt)
with self.get_conn() as conn:
with conn.cursor() as cursor:
with self.conn.cursor() as cursor:
cursor.execute(
"""
INSERT INTO llm_messages
@@ -330,7 +303,7 @@ class DatabaseClient:
)
message_id = cursor.fetchone()[0]
conn.commit()
self.conn.commit()
return message_id
@@ -352,6 +325,8 @@ class DatabaseClient:
Returns:
List of message dictionaries
"""
self.connect()
query = "SELECT * FROM llm_messages WHERE 1=1"
params = []
@@ -366,8 +341,7 @@ class DatabaseClient:
query += " ORDER BY timestamp DESC LIMIT %s OFFSET %s"
params.extend([limit, offset])
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(query, params)
return [dict(row) for row in cursor.fetchall()]
@@ -380,8 +354,9 @@ class DatabaseClient:
Returns:
Dictionary with analytics data
"""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
# Total messages
cursor.execute(
"""
@@ -597,45 +572,20 @@ class DatabaseClient:
self,
status: Optional[str] = None,
limit: int = 10,
cursor: Optional[str] = None,
) -> List[Dict]:
"""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:
conditions.append("status = %s")
params.append(status)
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
"""List jobs, optionally filtered by status."""
query = "SELECT * FROM jobs"
if conditions:
query += " WHERE " + " AND ".join(conditions)
query += " ORDER BY created_at DESC, job_id DESC LIMIT %s"
params: list = []
if status:
query += " WHERE status = %s"
params.append(status)
query += " ORDER BY created_at DESC LIMIT %s"
params.append(limit)
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cur:
cur.execute(query, params)
return [dict(row) for row in cur.fetchall()]
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(query, params)
return [dict(row) for row in cursor.fetchall()]
def mark_stale_jobs_failed(self) -> int:
"""Mark any jobs in 'running' or 'pending' state as 'failed'.
@@ -701,11 +651,12 @@ class DatabaseClient:
Returns:
Created user dict or None if email exists
"""
self.connect()
password_hash = self.hash_password(password)
try:
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"""
INSERT INTO users (email, password_hash, role)
@@ -715,9 +666,10 @@ class DatabaseClient:
(email, password_hash, role),
)
user = cursor.fetchone()
conn.commit()
self.conn.commit()
return dict(user) if user else None
except psycopg2.errors.UniqueViolation:
self.conn.rollback()
return None
def authenticate_user(self, email: str, password: str) -> Optional[Dict]:
@@ -730,8 +682,9 @@ class DatabaseClient:
Returns:
User dict if authenticated, None otherwise
"""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"SELECT * FROM users WHERE email = %s",
(email,),
@@ -756,8 +709,9 @@ class DatabaseClient:
Returns:
User dict or None
"""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"SELECT id, email, role, created_at FROM users WHERE id = %s",
(user_id,),
@@ -774,8 +728,9 @@ class DatabaseClient:
Returns:
User dict or None
"""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"SELECT id, email, role, created_at FROM users WHERE email = %s",
(email,),
@@ -793,8 +748,9 @@ class DatabaseClient:
Returns:
List of user dicts
"""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"""
SELECT id, email, role, created_at
@@ -816,8 +772,9 @@ class DatabaseClient:
Returns:
Updated user dict or None
"""
with self.get_conn() as conn:
with conn.cursor(cursor_factory=RealDictCursor) as cursor:
self.connect()
with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
cursor.execute(
"""
UPDATE users
@@ -828,7 +785,7 @@ class DatabaseClient:
(role, user_id),
)
user = cursor.fetchone()
conn.commit()
self.conn.commit()
return dict(user) if user else None
def delete_user(self, user_id: int) -> bool:
@@ -840,11 +797,12 @@ class DatabaseClient:
Returns:
True if deleted
"""
with self.get_conn() as conn:
with conn.cursor() as cursor:
self.connect()
with self.conn.cursor() as cursor:
cursor.execute("DELETE FROM users WHERE id = %s", (user_id,))
deleted = cursor.rowcount > 0
conn.commit()
self.conn.commit()
return deleted
def get_user_count(self) -> int:
@@ -853,85 +811,8 @@ class DatabaseClient:
Returns:
Number of users
"""
with self.get_conn() as conn:
with conn.cursor() as cursor:
self.connect()
with self.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()]
+7 -6
View File
@@ -1,6 +1,5 @@
"""LLM integration for patent analysis using OpenRouter."""
import logging
from typing import Dict
from openai import OpenAI
@@ -8,8 +7,6 @@ from openai import OpenAI
from SPARC import config
from SPARC.database import DatabaseClient
logger = logging.getLogger(__name__)
class LLMAnalyzer:
"""Handles LLM-based analysis of patent content."""
@@ -25,7 +22,7 @@ class LLMAnalyzer:
"""
self.test_mode = test_mode
self.use_cache = use_cache if use_cache is not None else config.use_cache
self.model = config.model
self.model = "anthropic/claude-3.5-sonnet"
# Always initialize database client for storage and caching
self.db_client = DatabaseClient(config.database_url)
@@ -64,7 +61,11 @@ Patent Content:
Provide a concise analysis (2-3 paragraphs) focusing on what this patent reveals about the company's technical direction and competitive advantage."""
if self.test_mode:
logger.debug("TEST MODE - Prompt that would be sent to LLM:\n%s", prompt)
print("=" * 80)
print("TEST MODE - Prompt that would be sent to LLM:")
print("=" * 80)
print(prompt)
print("=" * 80)
return "[TEST MODE - No API call made]"
# Check cache first
@@ -166,7 +167,7 @@ Patent Portfolio:
Provide a comprehensive analysis (4-5 paragraphs) with a final verdict on the company's innovation strength and performance outlook."""
if self.test_mode:
logger.debug("TEST MODE - Portfolio prompt:\n%s", prompt)
print(prompt)
return "[TEST MODE]"
metadata = {
-109
View File
@@ -1,109 +0,0 @@
"""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,
)
+13 -47
View File
@@ -1,5 +1,4 @@
import io
import logging
import os
import re
from datetime import datetime, timedelta
from typing import Dict
@@ -9,21 +8,8 @@ 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:
@@ -58,7 +44,6 @@ class SERP:
"tbs": date_filter,
"api_key": config.api_key,
}
logger.info("Querying Google Patents for '%s' (last %d days)", company, days_back)
search = serpapi.search(params)
# Convert results to Patent objects, skipping any without PDF links
patent_ids = []
@@ -67,16 +52,13 @@ class SERP:
pdf_link = patent.get("pdf")
if pdf_link:
patent_ids.append(Patent(patent_id=patent["publication_number"], pdf_link=pdf_link, summary=None))
else:
logger.debug("Skipping patent %s (no PDF link)", patent.get("publication_number", "unknown"))
# Patents without PDF links are skipped (see docstring for details)
logger.info("Found %d patents with PDF links for '%s'", len(patent_ids), company)
return Patents(patents=patent_ids)
def save_patents(patent: Patent) -> Patent:
"""Save the patent PDF to storage, skipping download if already cached.
Uses the configured storage backend (local filesystem or S3).
"""
Save the patent PDF to the patents folder, skipping download if already cached.
Args:
patent: Patent object
@@ -84,51 +66,35 @@ class SERP:
Returns:
Patent object with updated PDF path
"""
storage = _get_storage()
key = f"{patent.patent_id}.pdf"
pdf_path = f"patents/{patent.patent_id}.pdf"
os.makedirs("patents", exist_ok=True)
if not storage.exists(key):
logger.info("Downloading PDF for %s", patent.patent_id)
if not (os.path.exists(pdf_path) and os.path.getsize(pdf_path) > 0):
response = requests.get(patent.pdf_link)
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", patent.patent_id)
with open(pdf_path, "wb") as f:
f.write(response.content)
patent.pdf_path = storage.path_for(key)
patent.pdf_path = pdf_path
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. Supports both local file
paths and S3 URIs (s3://bucket/key).
claims, summary, and detailed description.
Args:
pdf_path: Local path or S3 URI to the patent PDF file
pdf_path: Path to the patent PDF file
Returns:
Dictionary containing all extracted sections
"""
logger.debug("Parsing patent PDF: %s", pdf_path)
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:
with pdfplumber.open(pdf_path) as pdf:
# Extract all text
full_text = ""
for page in pdf.pages:
full_text += page.extract_text() + "\n"
logger.debug("Extracted text from %d pages (%d chars)", len(pdf.pages), len(full_text))
# Define section patterns (common in patents)
sections = {
-171
View File
@@ -1,171 +0,0 @@
"""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 -1
View File
@@ -4,7 +4,7 @@ from datetime import datetime
@dataclass
class Patent:
patent_id: str
patent_id: int
pdf_link: str
pdf_path: str | None = None
summary: dict | None = None
-139
View File
@@ -1,139 +0,0 @@
"""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,
})
-24
View File
@@ -52,29 +52,6 @@ services:
- ./patents:/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:
build: ./frontend
container_name: sparc-dashboard
@@ -86,4 +63,3 @@ services:
volumes:
postgres_data:
minio_data:
-9
View File
@@ -7,15 +7,6 @@
<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>
+4 -4
View File
@@ -10,7 +10,7 @@
"dependencies": {
"@tanstack/react-query": "^5.51.0",
"axios": "^1.7.2",
"lucide-react": "^1.7.0",
"lucide-react": "^0.400.0",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-router-dom": "^6.24.0",
@@ -3452,9 +3452,9 @@
}
},
"node_modules/lucide-react": {
"version": "1.7.0",
"resolved": "https://registry.npmjs.org/lucide-react/-/lucide-react-1.7.0.tgz",
"integrity": "sha512-yI7BeItCLZJTXikmK4KNUGCKoGzSvbKlfCvw44bU4fXAL6v3gYS4uHD1jzsLkfwODYwI6Drw5Tu9Z5ulDe0TSg==",
"version": "0.400.0",
"resolved": "https://registry.npmjs.org/lucide-react/-/lucide-react-0.400.0.tgz",
"integrity": "sha512-rpp7pFHh3Xd93KHixNgB0SqThMHpYNzsGUu69UaQbSZ75Q/J3m5t6EhKyMT3m4w2WOxmJ2mY0tD3vebnXqQryQ==",
"license": "ISC",
"peerDependencies": {
"react": "^16.5.1 || ^17.0.0 || ^18.0.0 || ^19.0.0"
+1 -2
View File
@@ -7,13 +7,12 @@
"dev": "vite",
"build": "tsc -b && vite build",
"lint": "eslint .",
"typecheck": "tsc --noEmit",
"preview": "vite preview"
},
"dependencies": {
"@tanstack/react-query": "^5.51.0",
"axios": "^1.7.2",
"lucide-react": "^1.7.0",
"lucide-react": "^0.400.0",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-router-dom": "^6.24.0",
-5
View File
@@ -1,7 +1,6 @@
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';
@@ -11,7 +10,6 @@ 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: {
@@ -24,7 +22,6 @@ const queryClient = new QueryClient({
function App() {
return (
<ThemeProvider>
<QueryClientProvider client={queryClient}>
<AuthProvider>
<BrowserRouter>
@@ -44,7 +41,6 @@ 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 */}
@@ -65,7 +61,6 @@ function App() {
</BrowserRouter>
</AuthProvider>
</QueryClientProvider>
</ThemeProvider>
);
}
-17
View File
@@ -126,23 +126,6 @@ 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);
},
};
// Analytics API
export const analyticsApi = {
getAnalytics: async (days = 30): Promise<Analytics> => {
+2 -12
View File
@@ -1,11 +1,9 @@
import { Outlet, NavLink, useNavigate } from 'react-router-dom';
import { useAuth } from '../context/AuthContext';
import { useTheme } from '../context/ThemeContext';
import { Search, Layers, BarChart3, Info, Users, LogOut, GitCompareArrows, Sun, Moon } from 'lucide-react';
import { Search, Layers, BarChart3, Info, Users, LogOut } from 'lucide-react';
export function Layout() {
const { user, isAdmin, logout } = useAuth();
const { theme, toggleTheme } = useTheme();
const navigate = useNavigate();
const handleLogout = () => {
@@ -17,7 +15,6 @@ 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' },
];
@@ -26,7 +23,7 @@ export function Layout() {
}
return (
<div className="min-h-screen bg-gradient-to-br from-bg-dark to-slate-100 dark:to-indigo-950">
<div className="min-h-screen bg-gradient-to-br from-bg-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">
@@ -66,13 +63,6 @@ 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-slate-100 dark:to-indigo-950 flex items-center justify-center">
<div className="min-h-screen bg-gradient-to-br from-bg-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
@@ -1,48 +0,0 @@
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;
}
+2 -22
View File
@@ -2,26 +2,6 @@
@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;
@@ -35,7 +15,7 @@ body {
}
::-webkit-scrollbar-track {
background: var(--color-bg-card);
background: #1e293b;
}
::-webkit-scrollbar-thumb {
@@ -50,5 +30,5 @@ body {
/* Selection */
::selection {
background: rgba(99, 102, 241, 0.3);
color: var(--color-text-primary);
color: #f8fafc;
}
+3 -12
View File
@@ -1,7 +1,7 @@
import { useState } from 'react';
import { useMutation } from '@tanstack/react-query';
import { analysisApi, exportApi } from '../api/client';
import { Search, CheckCircle, AlertCircle, Clock, FileText, Download } from 'lucide-react';
import { analysisApi } from '../api/client';
import { Search, CheckCircle, AlertCircle, Clock, FileText } from 'lucide-react';
import type { CompanyAnalysis } from '../types';
export function Analysis() {
@@ -106,18 +106,9 @@ 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">
<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">
<h3 className="text-lg font-semibold text-text-primary border-b-2 border-primary/30 pb-2 mb-4">
AI Analysis Results
</h3>
<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>
</div>
<div className="prose prose-invert max-w-none">
<div className="text-text-primary whitespace-pre-wrap leading-relaxed">
{result.analysis}
+9 -35
View File
@@ -9,38 +9,15 @@ const COLORS = ['#6366f1', '#0ea5e9', '#10b981', '#f59e0b', '#ef4444', '#8b5cf6'
export function AnalyticsPage() {
const [days, setDays] = useState(30);
const { data, isLoading, isError, refetch } = useQuery({
const { data, isLoading, isError } = useQuery({
queryKey: ['analytics', days],
queryFn: () => analyticsApi.getAnalytics(days),
});
if (isLoading) {
return (
<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 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>
);
}
@@ -56,18 +33,15 @@ 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">Unable to Load Analytics</span>
<span className="font-semibold">Database Not Connected</span>
</div>
<p className="text-text-secondary">
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.
Set <code className="bg-bg-card px-2 py-1 rounded">USE_DATABASE=true</code> in your .env file to enable analytics tracking.
</p>
<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 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>
</div>
</div>
);
+2 -14
View File
@@ -114,21 +114,9 @@ export function Batch() {
{/* Error */}
{mutation.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">
<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 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>
<button
onClick={() => mutation.reset()}
className="ml-7 mt-2 text-sm text-primary hover:text-primary-dark underline"
>
Dismiss
</button>
<span>Batch analysis failed. Please try again.</span>
</div>
)}
-161
View File
@@ -1,161 +0,0 @@
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-slate-100 dark:to-indigo-950 flex items-center justify-center px-4">
<div className="min-h-screen bg-gradient-to-br from-bg-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-slate-100 dark:to-indigo-950 flex items-center justify-center px-4">
<div className="min-h-screen bg-gradient-to-br from-bg-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">
+6 -7
View File
@@ -4,7 +4,6 @@ export default {
"./index.html",
"./src/**/*.{js,ts,jsx,tsx}",
],
darkMode: 'class',
theme: {
extend: {
colors: {
@@ -17,15 +16,15 @@ export default {
warning: '#f59e0b',
error: '#ef4444',
bg: {
dark: 'var(--color-bg-dark)',
card: 'var(--color-bg-card)',
'card-hover': 'var(--color-bg-card-hover)',
dark: '#0f172a',
card: '#1e293b',
'card-hover': '#334155',
},
text: {
primary: 'var(--color-text-primary)',
secondary: 'var(--color-text-secondary)',
primary: '#f8fafc',
secondary: '#94a3b8',
},
border: 'var(--color-border)',
border: '#334155',
},
},
},
-2
View File
@@ -15,5 +15,3 @@ pandas
bcrypt
PyJWT
slowapi
apscheduler
boto3