{"id":45615685,"url":"https://github.com/xerox563/agents-with-python","last_synced_at":"2026-02-23T18:01:26.794Z","repository":{"id":337283628,"uuid":"1152894492","full_name":"Xerox563/Agents-with-Python","owner":"Xerox563","description":"This repository contains a complete, structured learning path designed to take me build solid Python skills for becoming a Backend + AI Agent Engineer.","archived":false,"fork":false,"pushed_at":"2026-02-22T11:25:40.000Z","size":9237,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2026-02-22T15:36:45.220Z","etag":null,"topics":["fastapi","langchain","langgraph","postgresql","python"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Xerox563.png","metadata":{"files":{"readme":"Readme.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-02-08T15:49:31.000Z","updated_at":"2026-02-22T11:25:49.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/Xerox563/Agents-with-Python","commit_stats":null,"previous_names":["xerox563/agents-with-python"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Xerox563/Agents-with-Python","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xerox563%2FAgents-with-Python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xerox563%2FAgents-with-Python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xerox563%2FAgents-with-Python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xerox563%2FAgents-with-Python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Xerox563","download_url":"https://codeload.github.com/Xerox563/Agents-with-Python/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Xerox563%2FAgents-with-Python/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29749928,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-23T07:44:07.782Z","status":"ssl_error","status_checked_at":"2026-02-23T07:44:07.432Z","response_time":90,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["fastapi","langchain","langgraph","postgresql","python"],"created_at":"2026-02-23T18:00:51.067Z","updated_at":"2026-02-23T18:01:26.787Z","avatar_url":"https://github.com/Xerox563.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Backend + AI Agent Engineering Roadmap\n\n### _FastAPI • PostgreSQL • Auth • Deployment • LLMs • LangChain • AI Agents_\n\nThis repository contains a complete, structured learning path designed to take me build solid Python skills for becoming a **Backend + AI Agent Engineer**.\n\n---\n\n## 📌 What This Repository Covers\n\n### 🔷 **1. FastAPI Fundamentals**\n\n- Setting up FastAPI and project structure\n- GET/POST endpoints\n- Path \u0026 query parameters\n- Request/response models\n- Pydantic deep dive\n- Error handling\n- Dependency Injection\n- Middleware \u0026 Background tasks\n- CRUD Notes API project\n\n---\n\n### 🔷 **2. PostgreSQL + SQLAlchemy**\n\n- SQL fundamentals\n- Connecting FastAPI with PostgreSQL\n- SQLAlchemy ORM models\n- CRUD operations\n- Relationships (1-many, many-many)\n- Alembic migrations\n- User + Tasks database project\n\n---\n\n### 🔷 **3. Authentication, Authorization \u0026 Performance**\n\n- Password hashing (bcrypt)\n- JWT authentication (access \u0026 refresh tokens)\n- OAuth2PasswordBearer\n- Role-based access\n- Redis caching\n- Rate limiting\n- Background jobs (Celery / RQ)\n- Full authentication system project\n\n---\n\n### 🔷 **4. Deployment \u0026 Best Practices**\n\n- Docker fundamentals\n- Containerizing FastAPI + PostgreSQL\n- Docker Compose setup\n- Deploying to Railway / Render\n- Environment variables \u0026 secrets\n- Logging \u0026 monitoring\n- Production-ready backend API\n\n---\n\n### 🔷 **5. LLM Foundations**\n\n- What LLMs can and cannot do\n- Prompt engineering\n- Embeddings \u0026 vector similarity\n- Vector databases (FAISS, Chroma)\n- RAG (Retrieval Augmented Generation)\n- Mini Q\u0026A RAG system project\n\n---\n\n### 🔷 **6. LangChain Core Concepts**\n\n- Document loaders\n- Text splitters\n- Embeddings + VectorStore\n- LLMChain \u0026 SequentialChain\n- Conversational memory\n- Tools \u0026 Agents\n- AI chatbot with memory\n\n---\n\n### 🔷 **7. AI Agent Systems**\n\n- Tool-enabled agents\n- Creating custom Python tools\n- Connecting FastAPI endpoints as tools\n- Multi-agent orchestration\n- RAG-enhanced agents\n- Web-based agents\n- Tool-using automation agent project\n\n---\n\n## 🧩 **Final Goal**\n\nBy the end of this repo, I will have:  \n✔ A fully deployed backend (FastAPI + PostgreSQL + Auth)  \n✔ A RAG-powered AI system  \n✔ LangChain-based agents using custom tools  \n✔ A multi-agent automation system  \n✔ A strong portfolio demonstrating backend + AI integration\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxerox563%2Fagents-with-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxerox563%2Fagents-with-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxerox563%2Fagents-with-python/lists"}