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>

.env.example

@@ -40,3 +40,9 @@ JWT_SECRET=your-secure-jwt-secret-change-in-production
 # 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

SPARC/analyzer.py

@@ -5,10 +5,13 @@ 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
@@ -52,13 +55,13 @@ 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:
-                print(f"Using cached SERP results for {company_name} ({len(cached_ids)} patents)")
+                logger.info("Using cached SERP results for %s (%d patents)", company_name, len(cached_ids))
                 patents = Patents(patents=[
                     Patent(patent_id=pid, pdf_link="")
                     for pid in cached_ids
                 ])
             else:
-                print(f"Retrieving patents for {company_name}...")
+                logger.info("Retrieving patents for %s...", company_name)
                 patents = SERP.query(company_name)
                 # Cache the SERP results
                 if patents.patents:
@@ -66,12 +69,13 @@ 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}"
 
-        print(f"Found {len(patents.patents)} patents. Processing...")
+        logger.info("Found %d patents. Processing...", len(patents.patents))
 
         # Download, parse, and minimize patents in parallel
         processed_patents = []
@@ -87,12 +91,12 @@ class CompanyAnalyzer:
                     if result:
                         processed_patents.append(result)
                 except Exception as e:
-                    print(f"Warning: Failed to process {patent.patent_id}: {e}")
+                    logger.warning("Failed to process %s: %s", patent.patent_id, e)
 
         if not processed_patents:
             return f"Failed to process any patents for {company_name}"
 
-        print("Analyzing portfolio with LLM...")
+        logger.info("Analyzing portfolio with LLM...")
 
         # Analyze the full portfolio with LLM
         analysis = self.llm_analyzer.analyze_patent_portfolio(
@@ -122,6 +126,7 @@ class CompanyAnalyzer:
           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"
 
@@ -183,7 +188,7 @@ class CompanyAnalyzer:
 
             return {"patent_id": patent.patent_id, "content": minimized_content}
         except Exception as e:
-            print(f"Warning: Failed to process {patent.patent_id}: {e}")
+            logger.warning("Failed to process %s: %s", patent.patent_id, e)
             return None
 
     def _analyze_company_safe(self, company_name: str) -> CompanyAnalysisResult:
@@ -254,7 +259,7 @@ class CompanyAnalyzer:
         results: list[CompanyAnalysisResult] = []
         total = len(companies)
 
-        print(f"Starting batch analysis of {total} companies...")
+        logger.info("Starting batch analysis of %d companies...", total)
 
         with ThreadPoolExecutor(max_workers=max_workers) as executor:
             future_to_company = {
@@ -271,8 +276,8 @@ class CompanyAnalyzer:
                     result = future.result()
                     results.append(result)
 
-                    status = "✓" if result.success else "✗"
-                    print(f"[{completed}/{total}] {status} {company}")
+                    status = "OK" if result.success else "FAIL"
+                    logger.info("[%d/%d] %s %s", completed, total, status, company)
 
                     if progress_callback:
                         progress_callback(company, completed, total)
@@ -287,12 +292,12 @@ class CompanyAnalyzer:
                             error=str(e),
                         )
                     )
-                    print(f"[{completed}/{total}] ✗ {company}: {e}")
+                    logger.error("[%d/%d] FAIL %s: %s", completed, total, company, e)
 
         successful = sum(1 for r in results if r.success)
         failed = total - successful
 
-        print(f"\nBatch complete: {successful} succeeded, {failed} failed")
+        logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
 
         return BatchAnalysisResult(
             results=results,
@@ -318,20 +323,20 @@ class CompanyAnalyzer:
         results: list[CompanyAnalysisResult] = []
         total = len(companies)
 
-        print(f"Starting sequential analysis of {total} companies...")
+        logger.info("Starting sequential analysis of %d companies...", total)
 
         for idx, company in enumerate(companies, 1):
-            print(f"\n[{idx}/{total}] Analyzing {company}...")
+            logger.info("[%d/%d] Analyzing %s...", idx, total, company)
             result = self._analyze_company_safe(company)
             results.append(result)
 
-            status = "✓" if result.success else "✗"
-            print(f"[{idx}/{total}] {status} {company}")
+            status = "OK" if result.success else "FAIL"
+            logger.info("[%d/%d] %s %s", idx, total, status, company)
 
         successful = sum(1 for r in results if r.success)
         failed = total - successful
 
-        print(f"\nBatch complete: {successful} succeeded, {failed} failed")
+        logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
 
         return BatchAnalysisResult(
             results=results,

SPARC/api.py

@@ -21,11 +21,13 @@ 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
 
@@ -155,6 +157,7 @@ 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
@@ -167,8 +170,9 @@ async def lifespan(app: FastAPI):
         logging.getLogger(__name__).warning("Marked %d stale jobs as failed on startup", stale)
     _db.close()
     yield
-    # Cleanup if needed
+    # Cleanup
     _analyzer = None
+    close_db_client()
 
 
 app = FastAPI(
@@ -515,8 +519,25 @@ 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"])

SPARC/auth.py

@@ -146,11 +146,36 @@ 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 database client for auth operations."""
-    client = DatabaseClient(config.database_url)
-    client.connect()
-    return client
+    """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
 
 
 async def get_current_user(

SPARC/config.py

@@ -2,12 +2,20 @@
 
 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")
 
@@ -31,6 +39,12 @@ 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", "")

SPARC/database.py

@@ -222,8 +222,6 @@ class DatabaseClient:
         Returns:
             Cached message dict if found, None otherwise
         """
-        self.connect()
-
         prompt_hash = self.hash_prompt(prompt)
 
         query = """
@@ -246,7 +244,8 @@ class DatabaseClient:
 
         query += " ORDER BY timestamp DESC LIMIT 1"
 
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                 cursor.execute(query, params)
                 result = cursor.fetchone()
                 return dict(result) if result else None
@@ -277,11 +276,10 @@ class DatabaseClient:
         Returns:
             The ID of the inserted record
         """
-        self.connect()
-
         prompt_hash = self.hash_prompt(prompt)
 
-        with self.conn.cursor() as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
                 cursor.execute(
                     """
                     INSERT INTO llm_messages
@@ -303,7 +301,7 @@ class DatabaseClient:
                 )
 
                 message_id = cursor.fetchone()[0]
-            self.conn.commit()
+            conn.commit()
 
             return message_id
 
@@ -325,8 +323,6 @@ class DatabaseClient:
         Returns:
             List of message dictionaries
         """
-        self.connect()
-
         query = "SELECT * FROM llm_messages WHERE 1=1"
         params = []
 
@@ -341,7 +337,8 @@ class DatabaseClient:
         query += " ORDER BY timestamp DESC LIMIT %s OFFSET %s"
         params.extend([limit, offset])
 
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        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()]
 
@@ -354,9 +351,8 @@ class DatabaseClient:
         Returns:
             Dictionary with analytics data
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                 # Total messages
                 cursor.execute(
                     """
@@ -651,12 +647,11 @@ class DatabaseClient:
         Returns:
             Created user dict or None if email exists
         """
-        self.connect()
-
         password_hash = self.hash_password(password)
 
         try:
-            with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+            with self.get_conn() as conn:
+                with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                     cursor.execute(
                         """
                         INSERT INTO users (email, password_hash, role)
@@ -666,10 +661,9 @@ class DatabaseClient:
                         (email, password_hash, role),
                     )
                     user = cursor.fetchone()
-                self.conn.commit()
+                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]:
@@ -682,9 +676,8 @@ class DatabaseClient:
         Returns:
             User dict if authenticated, None otherwise
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                 cursor.execute(
                     "SELECT * FROM users WHERE email = %s",
                     (email,),
@@ -709,9 +702,8 @@ class DatabaseClient:
         Returns:
             User dict or None
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                 cursor.execute(
                     "SELECT id, email, role, created_at FROM users WHERE id = %s",
                     (user_id,),
@@ -728,9 +720,8 @@ class DatabaseClient:
         Returns:
             User dict or None
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                 cursor.execute(
                     "SELECT id, email, role, created_at FROM users WHERE email = %s",
                     (email,),
@@ -748,9 +739,8 @@ class DatabaseClient:
         Returns:
             List of user dicts
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                 cursor.execute(
                     """
                     SELECT id, email, role, created_at
@@ -772,9 +762,8 @@ class DatabaseClient:
         Returns:
             Updated user dict or None
         """
-        self.connect()
-
-        with self.conn.cursor(cursor_factory=RealDictCursor) as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor(cursor_factory=RealDictCursor) as cursor:
                 cursor.execute(
                     """
                     UPDATE users
@@ -785,7 +774,7 @@ class DatabaseClient:
                     (role, user_id),
                 )
                 user = cursor.fetchone()
-            self.conn.commit()
+            conn.commit()
             return dict(user) if user else None
 
     def delete_user(self, user_id: int) -> bool:
@@ -797,12 +786,11 @@ class DatabaseClient:
         Returns:
             True if deleted
         """
-        self.connect()
-
-        with self.conn.cursor() as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
                 cursor.execute("DELETE FROM users WHERE id = %s", (user_id,))
                 deleted = cursor.rowcount > 0
-            self.conn.commit()
+            conn.commit()
             return deleted
 
     def get_user_count(self) -> int:
@@ -811,8 +799,7 @@ class DatabaseClient:
         Returns:
             Number of users
         """
-        self.connect()
-
-        with self.conn.cursor() as cursor:
+        with self.get_conn() as conn:
+            with conn.cursor() as cursor:
                 cursor.execute("SELECT COUNT(*) FROM users")
                 return cursor.fetchone()[0]

SPARC/llm.py

@@ -1,5 +1,6 @@
 """LLM integration for patent analysis using OpenRouter."""
 
+import logging
 from typing import Dict
 
 from openai import OpenAI
@@ -7,6 +8,8 @@ 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."""
@@ -22,7 +25,7 @@ class LLMAnalyzer:
         """
         self.test_mode = test_mode
         self.use_cache = use_cache if use_cache is not None else config.use_cache
-        self.model = "anthropic/claude-3.5-sonnet"
+        self.model = config.model
 
         # Always initialize database client for storage and caching
         self.db_client = DatabaseClient(config.database_url)
@@ -61,11 +64,7 @@ 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:
-            print("=" * 80)
-            print("TEST MODE - Prompt that would be sent to LLM:")
-            print("=" * 80)
-            print(prompt)
-            print("=" * 80)
+            logger.debug("TEST MODE - Prompt that would be sent to LLM:\n%s", prompt)
             return "[TEST MODE - No API call made]"
 
         # Check cache first
@@ -167,7 +166,7 @@ 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:
-            print(prompt)
+            logger.debug("TEST MODE - Portfolio prompt:\n%s", prompt)
             return "[TEST MODE]"
 
         metadata = {

SPARC/types.py

@@ -4,7 +4,7 @@ from datetime import datetime
 
 @dataclass
 class Patent:
-    patent_id: int
+    patent_id: str
     pdf_link: str
     pdf_path: str | None = None
     summary: dict | None = None

SPARC/webhooks.py

@@ -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,
+    })