Feature/add repo enhancement framework #54
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This commit introduces a comprehensive framework for repository enhancement, including dependency management, configuration validation, testing, and CI/CD. Key additions: - `ai_apps_manager.py`: A master script with a CLI for managing, testing, and monitoring AI applications. - CI/CD Pipeline: A GitHub Actions workflow (`.github/workflows/ai-apps-cicd.yml`) for automated testing and deployment. - Containerization: `docker-compose.yml` for local development and placeholder Dockerfiles. - Kubernetes Manifests: Basic deployment configurations for Kubernetes. - Monitoring: Configuration for Prometheus and Alertmanager. - Development Support: `Makefile`, `requirements.txt`, `requirements-dev.txt`, and `.env.example` to streamline development. - Supporting Scripts: `setup.sh` and `init_database.py` for environment setup and database initialization.
This commit introduces a comprehensive framework for repository enhancement, including dependency management, configuration validation, testing, and CI/CD. It also includes fixes for the `ai_apps_manager.py` script to make it executable and handle asynchronous operations correctly. Key additions and fixes: - `ai_apps_manager.py`: A master script with a CLI for managing, testing, and monitoring AI applications. - **Fix**: Added an async decorator to `click` commands to handle coroutines. - **Fix**: Commented out calls to unimplemented methods in the `initialize_repository` function. - CI/CD Pipeline: A GitHub Actions workflow for automated testing and deployment. - Containerization: `docker-compose.yml` for local development and placeholder Dockerfiles. - Kubernetes Manifests: Basic deployment configurations for Kubernetes. - Monitoring: Configuration for Prometheus and Alertmanager. - Development Support: `Makefile`, `requirements.txt`, `requirements-dev.txt`, and `.env.example` to streamline development. - Supporting Scripts: `setup.sh` and `init_database.py` for environment setup and database initialization.
WalkthroughAdds repository-wide tooling and deployment artifacts: CI/CD workflow, repo management CLI and health monitor, environment and app configuration, Docker Compose and placeholder Dockerfiles, Kubernetes manifests, monitoring rules, DB init and setup scripts, dev tooling (Makefile, requirements), and assorted app README/content tweaks. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
actor Dev
participant GH as GitHub Actions
participant Repo as Repository
participant QA as Quality Gate
participant Dkr as Docker
participant Stg as Staging
participant Slack as Slack
Dev->>GH: push/PR/dispatch (optional app_name)
GH->>Repo: checkout & detect-changes
alt changes detected
GH->>QA: run lint/tests/safety/black/ruff
QA-->>GH: results
GH->>Dkr: build per-app image (auto-Dockerfile if missing)
GH->>Dkr: run container & check /health
par on develop
GH->>Stg: staging deploy (simulate)
Stg->>GH: trigger follow-up task creation
GH->>Slack: send notification (via webhook)
and on main
GH->>GH: require manual approval for production
end
else no changes
GH-->>Dev: skip downstream jobs
end
sequenceDiagram
autonumber
actor User
participant CLI as ai_apps_manager CLI
participant FS as File System
participant Py as Python Tools
participant Net as Services
User->>CLI: initialize --repo-path
CLI->>FS: create structure & scan apps
CLI->>FS: write `scripts/app_registry.json`
User->>CLI: test-app --app-path
CLI->>Py: dependency checks, pytest, safety
CLI-->>User: status + recommendations
User->>CLI: monitor --config
CLI->>Net: async poll health endpoints
CLI-->>User: aggregated health + alerts
sequenceDiagram
autonumber
participant Pipeline
participant TMI as TaskManagementIntegrator
participant GHAPI as GitHub API
participant SlackAPI as Slack API
Pipeline->>TMI: create_deployment_followup_tasks(app, deployment, env)
TMI->>TMI: build task list + due dates
loop per task
TMI->>GHAPI: create issue
GHAPI-->>TMI: issue number/URL
TMI->>SlackAPI: send notification
end
TMI-->>Pipeline: return created tasks with traceability
Estimated code review effort🎯 4 (Complex) | ⏱️ ~60–90 minutes Possibly related PRs
Suggested reviewers
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Actionable comments posted: 28
🧹 Nitpick comments (37)
scripts/app_registry.json (1)
1-1: Empty registry file: clarify whether this is a generated artifact or a source-controlled seed.If
scripts/app_registry.jsonis produced by the CLI at runtime, committing it will cause churn and merge conflicts. Prefer ignoring it in VCS and generating on demand; otherwise ship a minimal schema stub to prevent consumer code from breaking on structure changes.
- If intended as a generated artifact: add it to .gitignore and have the CLI create it atomically (write to temp + rename) to avoid partial writes when using aiofiles.
- If intended as a checked-in seed: consider a versioned schema to stabilize downstream parsing.
Proposed schema stub:
-[] +{ + "schema_version": 1, + "generated_at": null, + "apps": [] +}requirements.txt (1)
1-4: YAML loading safety contract.If you’re loading
ai_apps_config.yaml, ensure the code usesyaml.safe_loadand notload/full_load. Also consider constraining PyYAML to a secure baseline and documenting the loader choice.Example (in code, not here):
with open("ai_apps_config.yaml", "r", encoding="utf-8") as f: cfg = yaml.safe_load(f)requirements-dev.txt (1)
1-19: Dev toolchain looks sensible; consider pytest asyncio mode and pre-commit config.Good coverage across testing, linting, typing, and security. Two small improvements:
- With pytest-asyncio>=0.21, explicitly set
asyncio_mode=autoin pytest.ini to avoid deprecation noise.- Since
pre-commitis listed, add a.pre-commit-config.yaml(Black, Ruff, Mypy, trailing-whitespace, end-of-file-fixer), and consider enabling Safety/Bandit as pre-commit hooks.Optional adds:
- pytest-xdist for parallel tests.
- types-requests or other stubs if you interact with libraries lacking type hints.
docker_health_check.py (2)
6-8: Remove unused import.The
jsonmodule is imported but never used in the current implementation.import sys import requests -import json import os
15-15: Consider adding request headers for better compatibility.Some applications may expect specific headers (like User-Agent) in health check requests. Consider adding basic headers to improve compatibility.
- response = requests.get(f'http://localhost:{port}{health_endpoint}', timeout=5) + response = requests.get( + f'http://localhost:{port}{health_endpoint}', + timeout=5, + headers={'User-Agent': 'docker-healthcheck/1.0'} + ).env.example (1)
18-18: Use environment-specific database configuration.The hardcoded database credentials in the default value could be a security risk if accidentally used in production. Consider using more generic placeholder values.
-DATABASE_URL=postgresql://ai_apps:ai_apps_password@localhost:5432/ai_apps_tasks +DATABASE_URL=postgresql://username:password@localhost:5432/database_namescripts/init_database.py (3)
7-7: Remove unused import.The
Pathimport frompathlibis not used in the script.import asyncio import asyncpg import os -from pathlib import Path
27-27: Consider adding foreign key constraint for parent_task_id.The
parent_task_idfield references other tasks but lacks a foreign key constraint, unlike thetask_followupstable which properly defines foreign keys.parent_task_id VARCHAR(255), + FOREIGN KEY (parent_task_id) REFERENCES tasks(task_id),
24-25: Consider using ENUM types for constrained values.The
priorityandstatusfields accept arbitrary VARCHAR values. Consider using PostgreSQL ENUM types or CHECK constraints to enforce valid values.- priority VARCHAR(20), - status VARCHAR(20) DEFAULT 'open', + priority VARCHAR(20) CHECK (priority IN ('low', 'medium', 'high', 'critical')), + status VARCHAR(20) DEFAULT 'open' CHECK (status IN ('open', 'in_progress', 'completed', 'cancelled')),Makefile (1)
91-91: Parameterize the hardcoded application path in thetest-apptargetThe
test-apptarget currently invokes:python ai_apps_manager.py test-app --app-path ./starter_ai_agents/agno_starterWhile
./starter_ai_agents/agno_starterdoes exist, hardcoding this path makes future restructuring or custom runs harder. Consider introducing a Makefile variable for the app path so it can be overridden as needed.• File: Makefile (line 91)
• Suggested diff:@@ Makefile - python ai_apps_manager.py test-app --app-path ./starter_ai_agents/agno_starter + python ai_apps_manager.py test-app --app-path $(APP_PATH)• And at the top of your Makefile, add:
# Default application path (override with `make APP_PATH=…`) APP_PATH ?= ./starter_ai_agents/agno_starterThis change preserves the existing default but allows users to run, for example,
make test-app APP_PATH=./starter_ai_agents/custom_agentwithout editing the Makefile directly.
monitoring/alert_rules.yml (1)
4-38: Harden alert expressions with aggregation and label scoping.The current expressions will either alert per time series without grouping or may be noisy:
- ApplicationDown: up == 0 alerts per-target. If you have multiple targets per app, consider grouping and scoping by job/app label.
- HighResponseTime: use a histogram/summary or at least an avg/quantile over a window and group by app_name to avoid per-instance spikes.
- TaskChainBroken: increase(...) > 0 is fine, but add by(app_name) and possibly job scoping to avoid duplicate alerts across replicas.
- HighErrorRate: rate() should be summed by app_name over all instances to represent app-level error rate.
Illustrative rewrite (adjust label names to your metric schema):
- expr: up == 0 + expr: sum by (job, instance) (up == 0) --- - expr: ai_app_response_time_seconds > 2 + expr: avg_over_time(ai_app_response_time_seconds[5m]) > 2 + # or if you have histograms: histogram_quantile(0.95, sum by (le, app_name) (rate(ai_app_response_time_seconds_bucket[5m]))) > 2 --- - expr: increase(ai_app_chain_breaks_total[5m]) > 0 + expr: sum by (app_name) (increase(ai_app_chain_breaks_total[5m])) > 0 --- - expr: rate(ai_app_errors_total[5m]) > 0.05 + expr: sum by (app_name) (rate(ai_app_errors_total[5m])) > 0.05Also consider adding a runbook_url annotation for each alert to streamline remediation.
.github/workflows/ai-apps-cicd.yml (1)
65-70: Tooling pragmatics and reliability improvements (optional).
- setup-python: consider v5 (actions/setup-python@v5).
- safety: the new CLI favors safety scan; python -m safety check still works but can be flaky. Consider pinning safety and using --full-report to improve logs.
- mypy triggering via grep may miss annotations; running mypy unconditionally with --ignore-missing-imports is often fine for small apps.
Also applies to: 86-107, 109-164
k8s/namespace.yaml (1)
1-6: LGTM — minimal, valid namespace manifest.The namespace and label are fine. If you plan to use environment protection, align this with GitHub Environments for naming consistency (e.g., ai-apps-staging/production).
k8s/configmap.yaml (1)
7-21: ConfigMap looks consistent; verify units/metric names match your monitor.
- response_time_ms is in milliseconds, while Prometheus rule uses seconds (> 2). Ensure your health monitor converts consistently.
- The service URLs and health endpoints align; double-check that newsletter_agent/finance_agent expose those paths.
If you want, I can add a smoke-check script to curl these endpoints from a cluster Job as part of post-deploy validation.
monitoring/prometheus.yml (1)
27-33: Scrape targets reference non-existent services in this PRfinance-agent:8000 and newsletter-agent:8000 are not defined in docker-compose, and K8s samples typically name them finance-agent-service and newsletter-agent-service. These targets will stay down and can mask real issues.
- Remove this job from the “compose” variant, or
- Rename targets to the actual K8s Service names when you add them, or
- Use service discovery (kubernetes_sd_configs) with label selectors.
Example to comment them out for now:
- - job_name: 'ai-apps-applications' - static_configs: - - targets: - - 'finance-agent:8000' - - 'newsletter-agent:8000' - metrics_path: /metrics - scrape_interval: 30s + # - job_name: 'ai-apps-applications' + # static_configs: + # - targets: + # - 'finance-agent:8000' + # - 'newsletter-agent:8000' + # metrics_path: /metrics + # scrape_interval: 30sI can split this into prometheus.compose.yml and prometheus.k8s.yml and wire docker-compose/K8s manifests accordingly. Want me to draft that?
ai_apps_config.yaml (2)
31-31: Clarify the unit in health_check_intervalThe key doesn’t specify units. Elsewhere you use “_ms” for response time.
Rename to health_check_interval_seconds for consistency or document units in README.
- health_check_interval: 30 + health_check_interval_seconds: 30
8-24: Expand framework env requirements or note optional keysDepending on the framework, additional envs are commonly needed (e.g., OPENAI_BASE_URL or model routing, LangChain tracing keys, etc.). If not required now, consider documenting optional envs to prevent runtime surprises.
I can add comments in this YAML and mirror them into k8s Secret/ConfigMap templates. Want me to propose that?
k8s/monitoring-deployment.yaml (1)
31-34: ConfigMap mount is fine; ensure key structure matchesYou mount the entire ai-apps-config at /app/config. Verify the application expects files under that path (e.g., /app/config/monitoring.yaml). If it expects a specific filename, add subPath to mount only that key.
If needed, I can adjust to:
volumeMounts: - name: monitoring-config mountPath: /app/config/monitoring.yaml subPath: monitoring.yamldocker-compose.yml (1)
58-71: Add a healthcheck for the monitoring serviceThe monitoring container exposes 8002 but has no healthcheck; compose can restart it proactively on failure.
monitoring: @@ depends_on: - prometheus - grafana + healthcheck: + test: ["CMD-SHELL", "wget -qO- http://localhost:8002/health || exit 1"] + interval: 30s + timeout: 5s + retries: 3k8s/task-manager-deployment.yaml (1)
48-59: Probes look good; consider tuning initial delays to match startup timeIf the application performs DB migrations on startup, readiness might need a longer initialDelaySeconds to avoid flapping during deploys.
Confirm average startup time in your environment; I can propose tuned values based on logs.
ai_apps_manager.py (17)
195-210: Requirements parsing is too naive; handle comments, extras, VCS/URLs, and specifier setsOnly supports
==/>=and will misparse lines likefoo~=1.2,bar[all]==3,-e .,git+https://…, or inline comments. Usepackagingfor robust parsing; fall back to current logic if unavailable.Apply this diff:
def _parse_requirements(self, requirements: str) -> Dict: """Parse requirements.txt content""" - deps = {} - for line in requirements.splitlines(): - line = line.strip() - if line and not line.startswith('#'): - if '==' in line: - name, version = line.split('==', 1) - deps[name.strip()] = version.strip() - elif '>=' in line: - name, version = line.split('>=', 1) - deps[name.strip()] = f">={version.strip()}" - else: - deps[line] = "unpinned" - return deps + deps: Dict[str, str] = {} + try: + from packaging.requirements import Requirement # type: ignore + except Exception: + # Fallback parser + for raw in requirements.splitlines(): + line = raw.split("#", 1)[0].strip() + if not line or line.startswith(("-", "git+", "http://", "https://")): + continue + if "==" in line: + name, version = line.split("==", 1) + deps[name.strip()] = version.strip() + elif ">=" in line: + name, version = line.split(">=", 1) + deps[name.strip()] = f">={version.strip()}" + else: + deps[line] = "unpinned" + return deps + + for raw in requirements.splitlines(): + line = raw.split("#", 1)[0].strip() + if not line or line.startswith(("-", "git+", "http://", "https://")): + continue + try: + req = Requirement(line) + deps[req.name] = str(req.specifier) if req.specifier else "unpinned" + except Exception: + # best-effort fallback if a line is still unparsable + deps[line] = "unpinned" + return deps
354-387: Gracefully fall back to unittest when pytest isn’t available; make timeout configurableRunning pytest will fail hard if it isn’t installed. Provide a lightweight fallback to
unittest discoverand allow timeout override.Apply this diff:
try: # Run pytest - result = subprocess.run([ - sys.executable, "-m", "pytest", str(test_dir), "-v", "--tb=short" - ], cwd=self.app_path, capture_output=True, text=True, timeout=300) - - if result.returncode == 0: - return {"status": "passed", "output": result.stdout} - else: - return {"status": "failed", "error": result.stderr} + timeout = int(os.environ.get("AI_APPS_TEST_TIMEOUT_SEC", "300")) + result = subprocess.run( + [sys.executable, "-m", "pytest", str(test_dir), "-v", "--tb=short"], + cwd=self.app_path, capture_output=True, text=True, timeout=timeout + ) + if result.returncode == 0: + return {"status": "passed", "output": result.stdout} + # Fallback to unittest if pytest not found + if "No module named pytest" in (result.stderr or ""): + uni = subprocess.run( + [sys.executable, "-m", "unittest", "discover", "-s", str(test_dir)], + cwd=self.app_path, capture_output=True, text=True, timeout=timeout + ) + if uni.returncode == 0: + return {"status": "passed", "output": uni.stdout} + return {"status": "failed", "error": uni.stderr or uni.stdout} + return {"status": "failed", "error": result.stderr or result.stdout} except subprocess.TimeoutExpired: return {"status": "failed", "error": "Unit tests timeout"} except Exception as e: return {"status": "failed", "error": str(e)}
434-453: Avoid green “pass” when no AI frameworks are presentIf no AI framework is detected, returning
passedis misleading. Mark asskippedwith guidance; still return detected frameworks if any.Apply this diff:
- return { - "status": "passed", - "frameworks_detected": frameworks_detected, - "recommendation": "Implement AI model response testing with mocks" - } + if frameworks_detected: + return { + "status": "passed", + "frameworks_detected": frameworks_detected, + "recommendation": "Implement AI model response testing with mocks" + } + return { + "status": "skipped", + "frameworks_detected": [], + "recommendation": "No AI frameworks detected; skip model tests" + }
704-741: Use monitoring thresholds from config to classify health, not just success ratesYou already define thresholds (
response_time_ms,error_rate) in config but they aren’t applied. Consider marking an app “degraded” when average latency exceeds threshold even if all endpoints return 200, and include threshold values in the result.I can add a small check after computing
health_results["response_time_ms"], e.g.:thresholds = self.config.get("monitoring", {}).get("alert_thresholds", {}) rt_thresh = thresholds.get("response_time_ms", 5000) if health_results["response_time_ms"] > rt_thresh and health_results["status"] == "healthy": health_results["status"] = "degraded" health_results["message"] = f"Avg latency {health_results['response_time_ms']:.0f}ms exceeds {rt_thresh}ms"
825-851: Infinite monitoring loop; add configurable interval and bounded iterations with graceful shutdownCurrent command runs forever with a hard-coded 30s sleep. Make it CI-friendly with
--iterationsand allow overriding interval via CLI or config.Apply this diff:
-@cli.command() -@click.option('--config-file', default='monitoring_config.json', help='Monitoring configuration file') -@coro -async def monitor(config_file): +@cli.command() +@click.option('--config-file', default='monitoring_config.json', help='Monitoring configuration file') +@click.option('--interval', type=int, default=None, help='Polling interval in seconds (overrides config)') +@click.option('--iterations', type=int, default=0, help='Number of iterations to run (0 = infinite)') +@coro +async def monitor(config_file, interval, iterations): """Start health monitoring""" with open(config_file) as f: config = json.load(f) async with HealthMonitor(config) as monitor: - while True: - results = await monitor.monitor_all_applications() + poll = interval or config.get("interval") or config.get("monitoring", {}).get("health_check_interval", 30) + count = 0 + try: + while iterations == 0 or count < iterations: + results = await monitor.monitor_all_applications() - click.echo(f"🏥 Health Check - {results['timestamp']}") - click.echo(f"Overall Status: {results['overall_status']}") + click.echo(f"🏥 Health Check - {results['timestamp']}") + click.echo(f"Overall Status: {results['overall_status']}") - for app_name, app_health in results['applications'].items(): - status = app_health['status'] - emoji = "🟢" if status == "healthy" else "🟡" if status == "degraded" else "🔴" - click.echo(f"{emoji} {app_name}: {status}") + for app_name, app_health in results['applications'].items(): + status = app_health['status'] + emoji = "🟢" if status == "healthy" else "🟡" if status == "degraded" else "🔴" + click.echo(f"{emoji} {app_name}: {status}") - if results['alerts']: - click.echo("\n🚨 Alerts:") - for alert in results['alerts']: - click.echo(f" {alert['app']}: {alert['message']}") + if results['alerts']: + click.echo("\n🚨 Alerts:") + for alert in results['alerts']: + click.echo(f" {alert['app']}: {alert['message']}") - await asyncio.sleep(30) + count += 1 + await asyncio.sleep(poll) + except KeyboardInterrupt: + click.echo("\n👋 Monitor stopped by user")
920-925: Don’t unconditionally rewrite docker_health_check.py on every runAvoid side-effects on module invocation. Only create the script if it’s missing (or move behind a dedicated CLI command).
Apply this diff:
if __name__ == "__main__": - # Create Docker health check script - create_docker_health_check() + # Create Docker health check script if missing + if not Path('docker_health_check.py').exists(): + create_docker_health_check() # Run CLI cli()
168-174: Broaden Dockerized app detectionOnly checking for
Dockerfilemight miss multi-service setups where Compose is used without a per-app Dockerfile. Consider also checking fordocker-compose.yml/compose.yaml.Example tweak (outside this hunk):
app_info["has_docker"] = any((app_path / name).exists() for name in ("Dockerfile", "docker-compose.yml", "compose.yaml"))
214-233: Framework detection can be expanded with common providers and runtimesOptional: include indicators for Anthropic, Groq, OpenRouter, Mistral, vLLM, Ollama, and common vector DBs. This helps tests tailor recommendations.
Example additions (outside this hunk):
framework_indicators.update({ "anthropic": ["anthropic"], "groq": ["groq", "groq-sdk"], "mistral": ["mistralai"], "openrouter": ["openrouter"], "ollama": ["ollama"], "vllm": ["vllm"], "faiss": ["faiss-cpu", "faiss-gpu"], "chromadb": ["chromadb"], "pinecone": ["pinecone-client", "pinecone"], })
7-22: Add missing stdlib imports used by proposed changes
osis required for chmod;tempfileis used in dependency fallback.Apply this diff:
import asyncio import aiohttp import aiofiles import json import yaml import subprocess import sys import time import logging +import os from pathlib import Path from typing import Dict, List, Optional, Any from dataclasses import dataclass, asdict from datetime import datetime import hashlib import re
661-703: Parallelize per-app health checks for scale (optional)
monitor_all_applicationsruns checks serially. For many apps/endpoints, you canasyncio.gathertasks to cut wall-clock time, keepingaiohttpsession reuse.I can provide a drop-in parallel version if you want to adopt it.
795-803: Initialize command is a good start—consider enabling optional steps via flagsYou’ve scaffolded commented steps (CI/CD templates, monitoring, task mgmt). Expose flags like
--setup-cicd/--no-setup-cicdto selectively run them without editing the file.
321-353: Config validation could extract env var names from .env.exampleTo improve the signal, parse keys from
.env.exampleand assert they’re mentioned in README. This avoids false positives on generic “environment” mentions.
299-320: Guard against environment mutation during dependency checksEven with a dry-run or download, make it explicit that no install occurs into the runner environment. Emit a note in the result message for transparency.
571-605: Slack payload uses legacy attachments/actionsModern Slack apps prefer Block Kit. Not urgent since this is a mock, but when you wire the real call, switch to blocks for long-term compatibility.
50-79: Default config aligns with the PR template—consider adding discovery/monitor knobsAdd:
app_roots(list) for category folders,discovery_excludes(list) to tweak excludes without code changes,monitoring.health_check_intervalreuse in CLImonitor(now addressed in suggested diff).
879-915: One more thing: write to repo root intentionallyConsider placing the generated
docker_health_check.pyunderscripts/to keep repo root tidy, and adjust DockerfileHEALTHCHECKaccordingly.
299-320: Isolation: consider running checks in a temp venvFor stricter isolation (especially in CI), create a temp venv and run
pip download/pip install --dry-runthere. This keeps the runner Python environment untouched.
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📒 Files selected for processing (21)
.env.example(1 hunks).github/workflows/ai-apps-cicd.yml(1 hunks)Makefile(1 hunks)ai_apps_config.yaml(1 hunks)ai_apps_manager.py(1 hunks)docker-compose.yml(1 hunks)docker/Dockerfile.monitoring(1 hunks)docker/Dockerfile.task-manager(1 hunks)docker_health_check.py(1 hunks)k8s/configmap.yaml(1 hunks)k8s/monitoring-deployment.yaml(1 hunks)k8s/namespace.yaml(1 hunks)k8s/secret.yaml(1 hunks)k8s/task-manager-deployment.yaml(1 hunks)monitoring/alert_rules.yml(1 hunks)monitoring/prometheus.yml(1 hunks)requirements-dev.txt(1 hunks)requirements.txt(1 hunks)scripts/app_registry.json(1 hunks)scripts/init_database.py(1 hunks)scripts/setup.sh(1 hunks)
🧰 Additional context used
🧬 Code graph analysis (1)
docker_health_check.py (2)
advance_ai_agents/finance_service_agent/scripts/ping.js (1)
response(12-12)advance_ai_agents/finance_service_agent/routes/agentRoutes.py (1)
health_check(21-89)
🪛 LanguageTool
requirements-dev.txt
[grammar] ~1-~1: There might be a mistake here.
Context: # Development and testing dependencies pytest>=7.0.0 pytest-asyncio>=0.21.0 pyt...
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🪛 Checkov (3.2.334)
k8s/task-manager-deployment.yaml
[MEDIUM] 1-66: Containers should not run with allowPrivilegeEscalation
(CKV_K8S_20)
[MEDIUM] 1-66: Minimize the admission of root containers
(CKV_K8S_23)
[MEDIUM] 23-24: Basic Auth Credentials
(CKV_SECRET_4)
k8s/monitoring-deployment.yaml
[MEDIUM] 1-34: Containers should not run with allowPrivilegeEscalation
(CKV_K8S_20)
[MEDIUM] 1-34: Minimize the admission of root containers
(CKV_K8S_23)
docker-compose.yml
[MEDIUM] 40-41: Basic Auth Credentials
(CKV_SECRET_4)
🪛 checkmake (0.2.2)
Makefile
[warning] 4-4: Target body for "setup" exceeds allowed length of 5 (6).
(maxbodylength)
[warning] 40-40: Target body for "clean" exceeds allowed length of 5 (6).
(maxbodylength)
[warning] 1-1: Missing required phony target "all"
(minphony)
🪛 dotenv-linter (3.3.0)
.env.example
[warning] 3-3: [UnorderedKey] The GITHUB_REPOSITORY key should go before the GITHUB_TOKEN key
(UnorderedKey)
[warning] 8-8: [UnorderedKey] The SLACK_CHANNEL key should go before the SLACK_TOKEN key
(UnorderedKey)
[warning] 12-12: [UnorderedKey] The NEBIUS_API_KEY key should go before the OPENAI_API_KEY key
(UnorderedKey)
[warning] 13-13: [UnorderedKey] The NEBIUS_PROJECT_ID key should go before the OPENAI_API_KEY key
(UnorderedKey)
[warning] 14-14: [UnorderedKey] The LANGCHAIN_API_KEY key should go before the NEBIUS_API_KEY key
(UnorderedKey)
[warning] 15-15: [UnorderedKey] The CREWAI_API_KEY key should go before the LANGCHAIN_API_KEY key
(UnorderedKey)
[warning] 23-23: [UnorderedKey] The GRAFANA_URL key should go before the PROMETHEUS_URL key
(UnorderedKey)
[warning] 24-24: [UnorderedKey] The GRAFANA_API_KEY key should go before the GRAFANA_URL key
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[warning] 28-28: [UnorderedKey] The ENVIRONMENT key should go before the LOG_LEVEL key
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[warning] 33-33: [UnorderedKey] The AUTOMATIC_TASK_CREATION key should go before the FOLLOWUP_GENERATION_ENABLED key
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[warning] 35-35: [UnorderedKey] The DAILY_REPORT_TIME key should go before the FOLLOWUP_GENERATION_ENABLED key
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[warning] 39-39: [UnorderedKey] The API_SECRET_KEY key should go before the JWT_SECRET_KEY key
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🪛 actionlint (1.7.7)
.github/workflows/ai-apps-cicd.yml
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🪛 YAMLlint (1.37.1)
.github/workflows/ai-apps-cicd.yml
[error] 333-333: syntax error: expected alphabetic or numeric character, but found '*'
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🔇 Additional comments (15)
docker_health_check.py (1)
10-26: LGTM! Well-implemented health check script.The health check implementation is robust with proper timeout handling, clear exit codes, and informative output messages. The use of environment variables for configuration makes it flexible for different deployment scenarios.
.env.example (1)
1-40: Comprehensive environment configuration template.The environment variables are well-organized by category and cover all the necessary integration points for the AI apps system including GitHub, Slack, AI services, databases, monitoring, and security configuration.
scripts/init_database.py (1)
9-76: Well-structured database initialization with proper error handling.The database schema is comprehensive and well-designed with appropriate foreign key relationships, default values, and timestamp tracking. The error handling and connection management are implemented correctly.
scripts/setup.sh (1)
1-61: Well-structured setup script with clear progression.The script follows a logical setup sequence and provides clear user feedback. The final instructions help users understand next steps for completing the setup.
Makefile (2)
96-101: Robust application directory traversal.The loop properly handles multiple application directories and includes a check for
requirements.txtbefore attempting to test each application. This prevents errors when encountering directories that aren't proper applications.
104-109: Efficient workflow composition.The
devandprod-preptargets effectively compose multiple related tasks into logical workflows, making development and deployment preparation more efficient.monitoring/alert_rules.yml (1)
1-3: Fix YAML indentation for rules key (current file won’t load).In a Prometheus rule file, each group item’s keys must align. Here, rules is indented deeper than name, making the YAML invalid. Align rules with name.
Apply:
groups: - - name: ai_apps_alerts - rules: + - name: ai_apps_alerts + rules:Likely an incorrect or invalid review comment.
ai_apps_config.yaml (1)
26-31: Clarify separation between CI quality gates and runtime monitoring thresholdsThe
quality_gatessection defines CI/blocking criteria (e.g.max_error_rate: 0.01,max_response_time_ms: 2000), whereas themonitoring.alert_thresholdsare runtime alert triggers (e.g.error_rate: 0.05,response_time_ms: 5000). The higher alert thresholds are intentional—to surface production issues without failing CI—and should remain distinct.To avoid confusion, consider adding a comment in
ai_apps_config.yamlto document this distinction:• ai_apps_config.yaml L26–31
monitoring: # Runtime alert thresholds (production warnings); not CI pass/fail gates alert_thresholds: cpu_usage: 0.8 error_rate: 0.05 memory_usage: 0.7 response_time_ms: 5000 health_check_interval: 30• ai_apps_config.yaml L32–36:
quality_gates(CI limits)
• ai_apps_manager.py L62–69: default definitions of both sectionsNo changes to existing threshold values are required.
Likely an incorrect or invalid review comment.
k8s/monitoring-deployment.yaml (1)
16-31: Harden deployment security and pin imagePlease update k8s/monitoring-deployment.yaml (lines 16–31) as follows:
- Pin the container image to an explicit version or digest instead of using
:latest.- Enforce a non-root user, drop all capabilities, disable privilege escalation, and enable a read-only root filesystem at the container level.
- Set a pod-level
fsGroupso that any mounted volumes remain accessible.spec: containers: - name: health-monitor - image: ghcr.io/techfluent-au/ai-apps-monitor:latest + image: ghcr.io/techfluent-au/ai-apps-monitor:v1.0.0 # ← replace with the current semver or digest + securityContext: + runAsNonRoot: true + runAsUser: 1000 + allowPrivilegeEscalation: false + readOnlyRootFilesystem: true + capabilities: + drop: ["ALL"] ports: - containerPort: 8002 volumeMounts: - name: monitoring-config mountPath: /app/config resources: @@ spec: + securityContext: + fsGroup: 1000 volumes: - name: monitoring-config # existing config volume (e.g., ConfigMap or emptyDir)• Verification needed: Confirm that this service writes only under
/app/config(or other explicitly mounted volumes). If the process needs a writable directory for temp files or logs (e.g.,/tmp), add a dedicatedemptyDirvolume mount for that path before enablingreadOnlyRootFilesystem.k8s/task-manager-deployment.yaml (1)
21-25: Ensure Service Manifests Named “postgres” and “redis” ExistThe previous searches didn’t return any
kind: Serviceobjects withname: postgresorname: redisin thek8s/directory. Without those Services, theDATABASE_URLandREDIS_URLhosts will be unreachable.• No Kubernetes Service resources named “postgres” or “redis” were found under
k8s/**/*.yaml|yml.
• If these Services live outside this directory (another repo or namespace), confirm they are created before deploying this manifest.
• Otherwise, add Service definitions for PostgreSQL and Redis in the same namespace, or update the hostnames in yourtask-manager-deployment.yamlto match the actual Service names.ai_apps_manager.py (5)
247-298: Overall testing workflow looks cohesiveGood composition of checks with clear statuses and recommendation aggregation. The success-rate grading tiers are sensible for a repo bootstrapper.
482-570: Task workflow and follow-up taxonomy are well structuredThe categories, priorities, due-date helper, and mock integrations make the flow easy to wire to real providers later.
870-873: Nice UX on CLI outputConcise summary and emoji readouts make results easy to scan in CI logs and terminals.
812-819: CLI status glyphs are clearReadable mapping of statuses to emojis—good touch.
299-320: Dependency check--dry-runsupport confirmedWe’ve verified on pip 23.0.1 (Python 3.11) that
pip install --dry-runis supported, so the new fallback logic will simply never trigger in this environment but remains a safe, optional guard for older pip versions. No further changes are needed here—feel free to merge as is.
This commit adds a `requirements.txt` file to the `rag_apps/agentic_rag` application. The missing requirements file was causing the dependency check to fail in the newly added testing framework. This change resolves the issue by specifying the application's dependencies.
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⚠️ Outside diff range comments (1)
rag_apps/gemma_ocr/app.py (1)
202-209: Don’t block OCR when the user provides an API key via UI.The code errors out if NEBIUS_API_KEY is not set in the environment even when the user has entered a valid key in the sidebar. This makes OCR unusable in common cases.
Define and check a single effective key at the start of the upload block, and use it in the OCR call:
@@ - if uploaded_file is not None: - if uploaded_file != st.session_state.current_pdf: + if uploaded_file is not None: + # Determine the effective API key from UI or env + effective_key = nebius_api_key or os.getenv("NEBIUS_API_KEY") + if not effective_key: + st.error("Missing Nebius API key") + st.stop() + + if uploaded_file != st.session_state.current_pdf: @@ - if st.button("🔍 Extract Text (OCR)"): - extracted_text = ocr(uploaded_file, nebius_api_key) + if st.button("🔍 Extract Text (OCR)"): + extracted_text = ocr(uploaded_file, effective_key)Also applies to: 233-233
🧹 Nitpick comments (6)
rag_apps/gemma_ocr/app.py (6)
170-171: Unify the OCR instruction and make the output strictly tabular for consistency.The PDF path uses “Extract the Details in a Table” while the image path still uses “Extract the Details and use Tables where applicable”. This can lead to inconsistent outputs across file types and downstream parsers. Recommend a single, deterministic instruction that returns only a GitHub-flavored markdown table.
Apply this diff in both places:
@@ - "text": "Extract the Details and use Tables where applicable", + "text": "Extract the details as a single GitHub-flavored Markdown table. Output only the table, with a header row and no extra prose.", @@ - "text": "Extract the Details in a Table", + "text": "Extract the details as a single GitHub-flavored Markdown table. Output only the table, with a header row and no extra prose.",Also applies to: 118-121
189-196: Close the PDF document and delete the temp file to avoid resource leaks.Currently the opened PDF and temporary file persist after return. This can leak file descriptors and fill up /tmp on repeated runs.
Apply this minimal diff at the end of PDF processing before returning:
- progress.empty() - return "\n\n".join(results) + progress.empty() + joined = "\n\n".join(results) + try: + doc.close() + except Exception: + pass + try: + os.unlink(tmp_pdf.name) + except Exception: + pass + return joined
49-56: Clear button should also clear extracted_text to avoid stale results.Clicking “Clear Chat” leaves the previous OCR output visible after rerun.
if st.session_state.temp_dir: shutil.rmtree(st.session_state.temp_dir) st.session_state.temp_dir = None st.session_state.current_pdf = None + if "extracted_text" in st.session_state: + del st.session_state["extracted_text"] st.rerun()
1-18: Prune duplicate/unused imports for cleanliness and faster cold starts.There are duplicates (os, base64, tempfile, OpenAI) and unused imports (io, re, mimetypes, PIL.Image). Streamline the header.
-import os -from openai import OpenAI -import streamlit as st -import os -from dotenv import load_dotenv -import tempfile -import shutil -import base64 -import io -import re -import mimetypes -from openai import OpenAI -import base64 -import os -import tempfile -from PIL import Image -import fitz # PyMuPDF for PDF to image +import os +import base64 +import shutil +import tempfile + +import streamlit as st +from dotenv import load_dotenv +from openai import OpenAI +import fitz # PyMuPDF for PDF to image +# from PIL import Image # unused; remove if not needed +# import io, re, mimetypes # unused
153-156: Increase render resolution for better OCR accuracy (optional).The default pixmap resolution can be low for small-font PDFs. Upscaling improves OCR but adds latency. Consider a modest 2x zoom.
- pix = page.get_pixmap() + zoom = fitz.Matrix(2, 2) # ~2x DPI for clearer text + pix = page.get_pixmap(matrix=zoom)If latency becomes an issue on large PDFs, gate this behind a sidebar “High quality OCR” checkbox.
159-164: Restore an explicit max_tokens to control output size/cost.The PDF path has max_tokens commented out; large pages can produce very long outputs and higher costs. Align with the image path or make it configurable.
- # max_tokens=512, + max_tokens=1024,Optional: expose this via a sidebar slider to let users trade off completeness vs. speed/cost.
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⛔ Files ignored due to path filters (2)
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📒 Files selected for processing (6)
mcp_ai_agents/hotel_finder_agent/main.py(4 hunks)rag_apps/agentic_rag/README.md(1 hunks)rag_apps/agentic_rag/requirements.txt(1 hunks)rag_apps/gemma_ocr/README.md(1 hunks)rag_apps/gemma_ocr/app.py(2 hunks)starter_ai_agents/camel_ai_starter/README.md(0 hunks)
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✅ Files skipped from review due to trivial changes (4)
- mcp_ai_agents/hotel_finder_agent/main.py
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- rag_apps/gemma_ocr/README.md
- rag_apps/agentic_rag/README.md
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