forked from 0xWheatyz/SPARC
Compare commits
6 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 2e6b8c7445 | |||
| 55c131cb32 | |||
| fbb72fe2a5 | |||
| e484baaf5f | |||
| 069f1c343c | |||
| b000146585 |
@@ -40,3 +40,9 @@ JWT_SECRET=your-secure-jwt-secret-change-in-production
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# When USE_CACHE=true: check database for cached responses before making API calls
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# When USE_CACHE=false: always make fresh API calls (still stores results in database)
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USE_CACHE=true
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# ---- Webhooks ----
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# Comma-separated list of webhook URLs for job completion and alert notifications
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# Supports generic HTTP POST and Slack/Discord incoming webhooks
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# WEBHOOK_URLS=https://hooks.slack.com/services/XXX,https://example.com/webhook
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@@ -9,7 +9,43 @@ on:
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workflow_dispatch:
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jobs:
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test:
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runs-on: ubuntu-latest
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steps:
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- name: Install system dependencies
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shell: sh
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run: |
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apk add --no-cache git python3 py3-pip gcc musl-dev libpq-dev python3-dev
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- name: Checkout code
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shell: sh
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run: |
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git clone http://gitea.gitea.svc.cluster.local/${{ gitea.repository }}.git .
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git checkout ${{ gitea.sha }}
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- name: Install Python dependencies
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shell: sh
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run: |
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pip3 install --break-system-packages -r requirements.txt ruff
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- name: Run ruff linter
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shell: sh
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run: |
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ruff check SPARC/ tests/
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- name: Run pytest
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shell: sh
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env:
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DATABASE_URL: "sqlite://"
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API_KEY: "test-key"
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OPENROUTER_API_KEY: "test-key"
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JWT_SECRET: "test-secret-for-ci"
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APP_ENV: "development"
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run: |
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python3 -m pytest tests/ -v --tb=short -x
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build-api:
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needs: test
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runs-on: ubuntu-latest
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steps:
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- name: Install dependencies
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@@ -81,6 +117,7 @@ jobs:
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echo "API image available at ${{ steps.tags.outputs.IMAGE_TAG }}"
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build-frontend:
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needs: test
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runs-on: ubuntu-latest
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steps:
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- name: Install dependencies
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@@ -0,0 +1,46 @@
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name: Test and Lint
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on:
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push:
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branches:
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- main
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pull_request:
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branches:
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- main
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workflow_dispatch:
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jobs:
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test:
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runs-on: ubuntu-latest
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steps:
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- name: Install system dependencies
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shell: sh
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run: |
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apk add --no-cache git python3 py3-pip gcc musl-dev libpq-dev python3-dev
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- name: Checkout code
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shell: sh
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run: |
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git clone http://gitea.gitea.svc.cluster.local/${{ gitea.repository }}.git .
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git checkout ${{ gitea.sha }}
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- name: Install Python dependencies
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shell: sh
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run: |
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pip3 install --break-system-packages -r requirements.txt ruff
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- name: Run ruff linter
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shell: sh
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run: |
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ruff check SPARC/ tests/
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- name: Run pytest
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shell: sh
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env:
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DATABASE_URL: "sqlite://"
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API_KEY: "test-key"
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OPENROUTER_API_KEY: "test-key"
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JWT_SECRET: "test-secret-for-ci"
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APP_ENV: "development"
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run: |
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python3 -m pytest tests/ -v --tb=short -x
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+3
-2
@@ -1,3 +1,4 @@
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from .types import Patents, Patent
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from .types import Patent as Patent
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from .types import Patents as Patents
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all = ["Patents", "Patent"]
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__all__ = ["Patents", "Patent"]
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+23
-18
@@ -5,14 +5,17 @@ to provide company performance estimation based on patent portfolios.
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"""
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import hashlib
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import logging
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from typing import Callable
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from SPARC import config
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logger = logging.getLogger(__name__)
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from SPARC.database import DatabaseClient
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from SPARC.serp_api import SERP
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from SPARC.llm import LLMAnalyzer
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from SPARC.types import Patent, Patents, CompanyAnalysisResult, BatchAnalysisResult
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from SPARC.serp_api import SERP
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from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult, Patent, Patents
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class CompanyAnalyzer:
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@@ -52,13 +55,13 @@ class CompanyAnalyzer:
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query_hash = hashlib.sha256(company_name.lower().encode()).hexdigest()
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cached_ids = self.db.get_cached_serp_query(query_hash)
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if cached_ids is not None:
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print(f"Using cached SERP results for {company_name} ({len(cached_ids)} patents)")
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logger.info("Using cached SERP results for %s (%d patents)", company_name, len(cached_ids))
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patents = Patents(patents=[
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Patent(patent_id=pid, pdf_link="")
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for pid in cached_ids
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])
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else:
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print(f"Retrieving patents for {company_name}...")
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logger.info("Retrieving patents for %s...", company_name)
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patents = SERP.query(company_name)
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# Cache the SERP results
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if patents.patents:
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@@ -66,12 +69,13 @@ class CompanyAnalyzer:
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company_name=company_name,
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query_hash=query_hash,
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patent_ids=[p.patent_id for p in patents.patents],
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ttl_hours=config.serp_cache_ttl_hours,
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)
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if not patents.patents:
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return f"No patents found for {company_name}"
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print(f"Found {len(patents.patents)} patents. Processing...")
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logger.info("Found %d patents. Processing...", len(patents.patents))
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# Download, parse, and minimize patents in parallel
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processed_patents = []
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@@ -87,12 +91,12 @@ class CompanyAnalyzer:
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if result:
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processed_patents.append(result)
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except Exception as e:
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print(f"Warning: Failed to process {patent.patent_id}: {e}")
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logger.warning("Failed to process %s: %s", patent.patent_id, e)
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if not processed_patents:
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return f"Failed to process any patents for {company_name}"
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print(f"Analyzing portfolio with LLM...")
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logger.info("Analyzing portfolio with LLM...")
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# Analyze the full portfolio with LLM
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analysis = self.llm_analyzer.analyze_patent_portfolio(
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@@ -122,6 +126,7 @@ class CompanyAnalyzer:
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FileNotFoundError: If the patent PDF is not found at the expected path.
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"""
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import os
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logger.info("Analyzing patent %s for %s...", patent_id, company_name)
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patent_path = f"patents/{patent_id}.pdf"
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@@ -183,7 +188,7 @@ class CompanyAnalyzer:
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return {"patent_id": patent.patent_id, "content": minimized_content}
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except Exception as e:
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print(f"Warning: Failed to process {patent.patent_id}: {e}")
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logger.warning("Failed to process %s: %s", patent.patent_id, e)
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return None
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def _analyze_company_safe(self, company_name: str) -> CompanyAnalysisResult:
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@@ -254,7 +259,7 @@ class CompanyAnalyzer:
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results: list[CompanyAnalysisResult] = []
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total = len(companies)
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print(f"Starting batch analysis of {total} companies...")
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logger.info("Starting batch analysis of %d companies...", total)
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with ThreadPoolExecutor(max_workers=max_workers) as executor:
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future_to_company = {
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@@ -271,8 +276,8 @@ class CompanyAnalyzer:
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result = future.result()
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results.append(result)
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status = "✓" if result.success else "✗"
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print(f"[{completed}/{total}] {status} {company}")
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status = "OK" if result.success else "FAIL"
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logger.info("[%d/%d] %s %s", completed, total, status, company)
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if progress_callback:
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progress_callback(company, completed, total)
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@@ -287,12 +292,12 @@ class CompanyAnalyzer:
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error=str(e),
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)
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)
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print(f"[{completed}/{total}] ✗ {company}: {e}")
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logger.error("[%d/%d] FAIL %s: %s", completed, total, company, e)
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successful = sum(1 for r in results if r.success)
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failed = total - successful
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print(f"\nBatch complete: {successful} succeeded, {failed} failed")
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logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
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return BatchAnalysisResult(
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results=results,
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@@ -318,20 +323,20 @@ class CompanyAnalyzer:
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results: list[CompanyAnalysisResult] = []
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total = len(companies)
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print(f"Starting sequential analysis of {total} companies...")
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logger.info("Starting sequential analysis of %d companies...", total)
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for idx, company in enumerate(companies, 1):
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print(f"\n[{idx}/{total}] Analyzing {company}...")
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logger.info("[%d/%d] Analyzing %s...", idx, total, company)
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result = self._analyze_company_safe(company)
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results.append(result)
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status = "✓" if result.success else "✗"
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print(f"[{idx}/{total}] {status} {company}")
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status = "OK" if result.success else "FAIL"
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logger.info("[%d/%d] %s %s", idx, total, status, company)
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successful = sum(1 for r in results if r.success)
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failed = total - successful
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print(f"\nBatch complete: {successful} succeeded, {failed} failed")
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logger.info("Batch complete: %d succeeded, %d failed", successful, failed)
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return BatchAnalysisResult(
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results=results,
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@@ -519,8 +519,25 @@ def _run_batch_job(job_id: str, companies: list[str], max_workers: int):
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progress=100,
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result_json=_json.dumps(batch_response.model_dump(), default=str),
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)
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# Fire webhook notification
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from SPARC.webhooks import notify_job_completed
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notify_job_completed(
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job_id=job_id,
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status="completed",
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total_companies=result.total_companies,
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successful=result.successful,
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failed=result.failed,
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)
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except Exception as e:
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db.update_job(job_id, status="failed", error=str(e))
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from SPARC.webhooks import notify_job_completed
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notify_job_completed(
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job_id=job_id,
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status="failed",
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total_companies=len(companies),
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successful=0,
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failed=len(companies),
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)
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@app.post("/analyze/batch/async", response_model=JobStatus, tags=["Analysis"])
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+16
-1
@@ -2,11 +2,20 @@
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Loads environment variables from .env file for API keys and other secrets.
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"""
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from dotenv import load_dotenv
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import logging
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import os
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from dotenv import load_dotenv
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load_dotenv()
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# Logging configuration
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log_level = os.getenv("LOG_LEVEL", "INFO").upper()
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logging.basicConfig(
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level=getattr(logging, log_level, logging.INFO),
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format="%(asctime)s %(levelname)s %(name)s %(message)s",
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)
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# SerpAPI key for patent search
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api_key = os.getenv("API_KEY")
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@@ -30,6 +39,12 @@ use_database = os.getenv("USE_DATABASE", "false").lower() in ("true", "1", "yes"
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patent_search_days = int(os.getenv("PATENT_SEARCH_DAYS", "90"))
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patent_thread_workers = int(os.getenv("PATENT_THREAD_WORKERS", "5"))
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# LLM model to use via OpenRouter (e.g. "anthropic/claude-3.5-sonnet", "openai/gpt-4o")
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model = os.getenv("MODEL", "anthropic/claude-3.5-sonnet")
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# SERP cache TTL in hours (how long cached search results are considered fresh)
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serp_cache_ttl_hours = int(os.getenv("SERP_CACHE_TTL_HOURS", "24"))
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|
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# Root path for running behind a reverse proxy (e.g., "/api" when served at /api/)
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# This ensures OpenAPI docs work correctly when accessed via the proxy
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root_path = os.getenv("ROOT_PATH", "")
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|
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+7
-6
@@ -1,14 +1,15 @@
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"""Database client for storing and retrieving LLM messages and user authentication."""
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import contextlib
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import psycopg2
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from psycopg2.pool import ThreadedConnectionPool
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from psycopg2.extras import RealDictCursor
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from typing import Dict, List, Optional
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from datetime import datetime, timedelta
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import json
|
||||
import hashlib
|
||||
import json
|
||||
from datetime import datetime, timedelta
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from typing import Dict, List, Optional
|
||||
|
||||
import bcrypt
|
||||
import psycopg2
|
||||
from psycopg2.extras import RealDictCursor
|
||||
from psycopg2.pool import ThreadedConnectionPool
|
||||
|
||||
|
||||
class DatabaseClient:
|
||||
|
||||
+9
-8
@@ -1,9 +1,14 @@
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"""LLM integration for patent analysis using OpenRouter."""
|
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|
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import logging
|
||||
from typing import Dict
|
||||
|
||||
from openai import OpenAI
|
||||
|
||||
from SPARC import config
|
||||
from SPARC.database import DatabaseClient
|
||||
from typing import Dict
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class LLMAnalyzer:
|
||||
@@ -20,7 +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)
|
||||
@@ -59,11 +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
|
||||
@@ -165,7 +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 = {
|
||||
|
||||
+8
-5
@@ -1,12 +1,15 @@
|
||||
import os
|
||||
import serpapi
|
||||
from SPARC import config
|
||||
import re
|
||||
import pdfplumber # pip install pdfplumber
|
||||
import requests
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Dict
|
||||
from SPARC.types import Patents, Patent
|
||||
|
||||
import pdfplumber # pip install pdfplumber
|
||||
import requests
|
||||
import serpapi
|
||||
|
||||
from SPARC import config
|
||||
from SPARC.types import Patent, Patents
|
||||
|
||||
|
||||
class SERP:
|
||||
def query(company: str, days_back: int = None) -> Patents:
|
||||
|
||||
+1
-1
@@ -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
|
||||
|
||||
@@ -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,
|
||||
})
|
||||
@@ -0,0 +1,8 @@
|
||||
[lint]
|
||||
select = ["E", "F", "I"]
|
||||
ignore = [
|
||||
"E501", # line too long (handled by formatter)
|
||||
]
|
||||
|
||||
[lint.per-file-ignores]
|
||||
"tests/*" = ["E402", "F841"] # allow import not at top of file, unused vars (mocks) in tests
|
||||
@@ -1,9 +1,11 @@
|
||||
"""Tests for the high-level company analyzer orchestration."""
|
||||
|
||||
from unittest.mock import MagicMock, Mock
|
||||
|
||||
import pytest
|
||||
from unittest.mock import Mock, patch, call, MagicMock
|
||||
|
||||
from SPARC.analyzer import CompanyAnalyzer
|
||||
from SPARC.types import Patent, Patents, CompanyAnalysisResult, BatchAnalysisResult
|
||||
from SPARC.types import BatchAnalysisResult, Patent, Patents
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
@@ -24,7 +26,7 @@ class TestCompanyAnalyzer:
|
||||
"""Test analyzer initialization with API key."""
|
||||
mock_llm = mocker.patch("SPARC.analyzer.LLMAnalyzer")
|
||||
|
||||
analyzer = CompanyAnalyzer(openrouter_api_key="test-key")
|
||||
_analyzer = CompanyAnalyzer(openrouter_api_key="test-key") # noqa: F841
|
||||
|
||||
mock_llm.assert_called_once_with(api_key="test-key")
|
||||
|
||||
|
||||
+4
-3
@@ -1,12 +1,13 @@
|
||||
"""Tests for FastAPI web service endpoints."""
|
||||
|
||||
import pytest
|
||||
from datetime import datetime
|
||||
from unittest.mock import Mock, patch
|
||||
from unittest.mock import Mock
|
||||
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from SPARC.api import app
|
||||
from SPARC.types import CompanyAnalysisResult, BatchAnalysisResult
|
||||
from SPARC.types import BatchAnalysisResult, CompanyAnalysisResult
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
|
||||
+3
-1
@@ -1,7 +1,9 @@
|
||||
"""Tests for LLM analysis functionality."""
|
||||
|
||||
from unittest.mock import Mock
|
||||
|
||||
import pytest
|
||||
from unittest.mock import Mock, MagicMock, patch
|
||||
|
||||
from SPARC.llm import LLMAnalyzer
|
||||
|
||||
|
||||
|
||||
@@ -1,9 +1,8 @@
|
||||
"""Tests for SERP API patent retrieval and parsing functionality."""
|
||||
|
||||
import os
|
||||
import pytest
|
||||
from unittest.mock import patch, Mock
|
||||
from datetime import datetime, timedelta
|
||||
from unittest.mock import Mock
|
||||
|
||||
from SPARC.serp_api import SERP
|
||||
from SPARC.types import Patent
|
||||
|
||||
|
||||
Reference in New Issue
Block a user