FastAPI SPA & AI Integration

@ZohaibRoy

⭐⭐⭐⭐⭐ Build a FastAPI Server and Java Micro-Service with AI Integration ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and I see you are looking for a server-side setup for your single-page application. You don’t need to look any further; Zohaib is here to help you! My team has completed 50+ similar projects for server-side applications. I will create a Python FastAPI service with a clear REST API, store data in PostgreSQL, and ensure a clean architecture with tests. Additionally, I will build a lightweight Java Spring Boot micro-service for background jobs and integrate an AI component. ➡️ Why Me? I can easily create your FastAPI and Spring Boot services as I have 5 years of experience in Python, Java, and database management. My expertise includes API development, data persistence, and service integration. Moreover, I have a strong grip on Docker, unit testing, and webhooks, ensuring a smooth and efficient project delivery. ➡️ Let's have a quick chat to discuss your project in detail and I can show you samples of my previous work. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Python FastAPI ✅ Java Spring Boot ✅ PostgreSQL ✅ REST API Development ✅ Docker ✅ SQLAlchemy ✅ Alembic Migrations ✅ Unit Testing ✅ Webhook Integration ✅ AI Integration ✅ Telegram Bot Development ✅ Clean Architecture Waiting for your response! Best Regards, Zohaib

@DrSyafiq

I can take this from scope to a tested handoff without bloating the first milestone. You're building FastAPI SPA & AI Integration, where the real delivery risk is usually in the workflow details, not just the feature list. My approach would be to first define the input schema, generation rules, and output validation, then build the workflow around those controls so AI output stays consistent. Quick question: Which external integrations are absolutely required for MVP, and which can be staged after launch? Also, what real examples will define a correct AI output, and which failure cases must be blocked before launch? Best, Dr. Syafiq

@onkarkulkarni8

Hello, I can help you with "FastAPI SPA & AI Integration" as per your given project description. We can discuss more in detail during a chat conversation when you are available. I've worked on many PHP projects in recent times. So I am confident on achieving your expected Goals. Please initiate a communication thread to discuss further and start with the project. ⭐ 5.0/5 from a recent client: "A more professional version: “Excellent work! The job was completed within the committed timeline. Great quality, professionalism, and timely delivery. Highly appreciated and recommended.”" Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@corpmember29

I HAVE BUILT SIMILAR MULTI-SERVICE BACKEND SYSTEMS — I CAN CONNECT FASTAPI, SPRING BOOT, POSTGRESQL, AI AND TELEGRAM INTO ONE CLEAN, TESTABLE ARCHITECTURE. I understand you want the server side built first with FastAPI as the primary REST API, PostgreSQL persistence, a Java Spring Boot background-service foundation, an independently replaceable AI layer, and Telegram integration. I can deliver: • Python FastAPI REST API with complete OpenAPI/Swagger documentation • PostgreSQL + SQLAlchemy models and Alembic migrations • Spring Boot microservice with a sample background task • Separated AI service layer for OpenAI or another provider • Telegram bot using webhooks and shared database workflows • Docker Compose setup for all services • Automatic initial database migrations • Environment configuration and clear README • Unit tests for critical endpoints/services • Clean architecture, validation, error handling and logging I’ll structure the services so the FastAPI layer remains responsive while background processing can move to Spring Boot as the platform grows. AI logic will remain isolated so models/providers can be changed without rewriting the core application. I’ll test the complete startup and workflow using a single docker-compose up and verify every FastAPI endpoint appears correctly under /docs. Estimated timeline: 3–5 weeks depending on final workflows. I can provide complete source code, documentation and 2 years of free ongoing support post-launch.

@vladang

The key is making FastAPI, migrations, Telegram webhooks, and the worker start cleanly from one compose file. I’d build the API around SQLAlchemy, Alembic, tested service boundaries, and a separate AI adapter so model changes don’t leak into endpoint code. The Spring Boot service would get one clear background-task contract, while Telegram webhook handlers would reuse the same application services instead of duplicating business logic. My recent work at MacKenzie & MacKenzie Consulting covers Python, AI, data pipelines, and full-stack applications. I can deliver the first working milestone, FastAPI + PostgreSQL + migrations + docker-compose, in 2 days, and you release it only when docker-compose up brings it up cleanly with /docs populated. Should the Spring Boot job be fire-and-forget, or does the FastAPI side need task status back?

@koolvishruth

Hi there, This is squarely in my range — FastAPI/PostgreSQL, an AI service layer, and a Telegram bot are all things I build regularly, and the Spring Boot piece is a small enough skeleton that it's not a stretch alongside the rest. I'd structure it as: FastAPI core with SQLAlchemy models and Alembic migrations, AI logic isolated behind its own service interface so swapping providers later doesn't touch the API layer, and the Telegram bot reading/writing to the same database via webhook rather than polling, so notifications stay real-time. Spring Boot gets a minimal skeleton with one working sample task on a queue, structured so you can drop in real background jobs later without re-architecting. Everything wired through docker-compose so it comes up in one command with migrations running automatically, and /docs showing the full FastAPI surface out of the box. I have worked here with more than 130+ clients, including Telegram bot and webhook integration work. One question: for the AI component, do you have a specific use case in mind yet (e.g., content generation, classification), or is this phase just the scaffolding with a placeholder call?

@devendrathakur12

Hi, I’m a Senior Full-Stack Engineer with 20+ years of experience, focused on Python backends and service architecture. I have gone through your specific requirement for a multi-service backend. I would keep FastAPI as the main API and use PostgreSQL transactions for shared data, rather than split ownership across separate databases that could leave the bot and API out of sync. I will build the FastAPI codebase with SQLAlchemy and Alembic migrations, plus a Spring Boot worker with one sample job. The Telegram webhook will call the same backend workflows, while the AI logic stays behind its own service layer. Docker Compose will bring up the services and run migrations, with tests and setup notes included. At least that is where I would start. I can send project details and relevant code samples. What are the first core data models and API actions you want included? Which Telegram commands and notifications should the initial bot support? Do you already have an OpenAI key and a preferred model, or should I keep the provider configurable? Free for a quick call this week? Or answer these here and I will map out the first version. Dev Singh

@Hrolgar

Does the AI service layer sit behind FastAPI as an internal call, or does it need its own route and auth so the Telegram bot can hit it directly without going through the main API? Either way the shape is the same underneath. FastAPI owns the domain and Postgres, with Alembic running migrations on container start so the schema is never a manual step, and Swagger comes free off the route definitions rather than being written separately. Spring Boot sits next to it as its own service for the background jobs, reading and writing the same Postgres instance so there's one source of truth instead of two systems syncing state. The Telegram bot is a thin client against the FastAPI routes, meaning any action a user can do through the API they can also do through the bot, and neither one drifts out of sync with the other because they're not two separate implementations of the same logic. The whole point of your acceptance criteria is docker-compose up and it just works, so that's where I'd start, not where I'd end up. Compose file with fastapi, postgres, spring-boot, bot and a migration step that runs before the API container is marked healthy, so nothing races against an empty schema on first boot. M1: FastAPI + Postgres + Alembic migrations + Swagger docs, all running through docker-compose. $215, 2 days. M2: Spring Boot skeleton service wired to the same Postgres, plus the AI service layer. $215, 2 days. M3: Telegram bot mirroring the API actions, full docker-compose up verified end to end. $220, 2 days. Happy to start on M1 first so you've got the core stack running and reviewable before the rest gets built on top of it.

@denisSolution

Hello, I'm Denis, a full-stack developer experienced in building multi-service platforms with Python backends, Java microservices, and external integrations. I understand your architecture: FastAPI handling the primary API layer with PostgreSQL persistence, Spring Boot managing background processing, an isolated AI service layer for easy model upgrades, and a Telegram bot as a multi-channel interface. This is a solid, scalable approach. My approach: First, I'll establish FastAPI with SQLAlchemy models, Alembic migrations, and a clean service layer. Then I'll add the AI abstraction as an isolated, testable service class for OpenAI calls. Spring Boot gets a basic job queue with a working example. I'll integrate the Telegram bot via webhooks to the same database and run everything through docker-compose with auto-migrations. Finally, I'll add unit tests for critical paths and a clear README for local setup. One important consideration: the AI service layer needs robust handling of rate limits and errors. If OpenAI requests fail, the main API must stay responsive. I'll build in retry logic and fallback handling at the service layer so it's transparent to the rest of the application. To prevent database conflicts, I'll ensure Spring Boot and the Telegram bot only read from tables they don't own, while FastAPI handles all writes to core tables. I can start immediately. Let's discuss the details. Thanks, Denis.

@sumitsthakur

I can build your single-page application backend and supporting services exactly as specified. My background includes developing Python and AI-based applications, building robust REST APIs and backend systems, and integrating AI and LLM systems into software. To deliver this, I will set up the FastAPI core with automatic OpenAPI documentation and SQLAlchemy models alongside Alembic migrations connected to PostgreSQL. I will structure the AI component through a clearly separated service layer for your OpenAI integration. For the background jobs, I will create the lightweight Java Spring Boot service skeleton with a sample task. I will also build the Telegram bot integrated via webhooks to the database and ensure all critical endpoints and services include unit tests. Everything will be wrapped in a docker-compose setup where services start together and migrations run automatically. Let's discuss the details so we can get started on your architecture.

@maxscender

I’d treat this as a contract-first backend build: FastAPI owns the OpenAPI surface and clean service boundaries, SQLAlchemy and Alembic define PostgreSQL as the source of truth, and Docker Compose starts FastAPI, Postgres, the Spring Boot worker, and Telegram webhook wiring with migrations running automatically. The AI layer would sit behind a replaceable adapter so OpenAI logic can evolve without touching API or persistence code. The Spring Boot service would begin as a minimal background worker with one idempotent sample task and a clear database boundary for future heavy processing. The Telegram bot would reuse the same internal services and database rather than duplicating logic, covering selected commands and user notifications. Tests would focus on critical endpoints, service-layer behavior, and startup/migration reliability so /docs exposes the full API and every service comes up cleanly together.

@PINESCRIPTERR

Hi, I can build the server-side foundation with FastAPI, PostgreSQL, SQLAlchemy/Alembic, and a clean testable architecture, while keeping the AI integration behind a dedicated service interface. I’ll add the Spring Boot worker with a sample background task, Telegram webhook integration, Docker Compose orchestration, automatic migrations, OpenAPI documentation, environment configuration, and focused unit tests so the full stack starts consistently with a single command. 1. Should the Spring Boot worker consume jobs through a queue such as Redis/RabbitMQ, or is the initial skeleton expected to expose an internal task API? 2. Which Telegram actions should be included in the initial webhook flow, and should bot users map directly to PostgreSQL application users? 3. Do you already have the AI provider/model and expected workflows defined, or should the service layer remain provider-agnostic with an initial OpenAI-compatible implementation? Regards, Houssame

@ASSAMWEB

Greetings, I have reviewed your project description and recently worked on a similar project: ”FastAPI backend”. I believe I can help you deliver this successfully. Let’s open a chat to discuss your requirements in detail and determine the best approach for your project. Regards

@fullstack0407

As a seasoned full-stack developer with extensive experience and proficiency in both Python and Java respectively, I am confident in my ability to create exactly what you need. My skills align perfectly with your project requirements as I am well-versed in FastAPI, MySQL, PostgreSQL, Python and the overall software architecture involved. In fact, I have successfully deployed scalable apps comparable to what you are envisioning and more. Moreover, apart from my expertise in AI (Artificial Intelligence) bots and CRMs, I have an excellent command over GoHighLevel which I know you cherish. Funnels or not–whatever the requirement arises minds alike my team at [Your Agency/Company Name] can take on this challenge headfirst. To top it off my broad experience with various APIs including messaging APIs like Twilio and SendGrid make integrating the telegram bot requirement a piece of cake. Imagine working with someone who has every single integration you need under their belt - the project flows smoothly without any hitches or glitches. Let's build together!

@jayantkumar314

With over 5 years of experience in full-stack web development, proficient in Python and Java, I assure you that the delivery of a robust FastAPI server powered by PostgreSQL will be handled seamlessly. My expertise extends to frameworks such as NestJs and Laravel, which will be advantageous for this project. Furthermore, my ability to use AJAX, JSON and SQL contributes to ensuring smooth interactions between the different parts of your projects. As an added value, I'm experienced with AI integration through my work with Facebook API. This exposure puts me in good stead to incorporate an OpenAI model or similar into your application as required. Lastly, I have familiarity with Telegram bot development, enabling me to build a robust multi-channel interaction platform for you. Looking forward to being part of your project!

@KarthikTechCon

Hello, I’m Karthik, a seasoned developer with over 15 years of experience in building scalable applications. I’m excited about your FastAPI SPA project and believe my skills align perfectly with your requirements. I will develop a robust FastAPI service with a well-documented REST API, ensuring clean architecture and extensive test coverage. I will implement PostgreSQL for data persistence, utilizing SQLAlchemy for ORM and Alembic for migrations. The integration of a lightweight Java Spring Boot micro-service for background jobs will help ensure efficient processing. Additionally, I will incorporate an AI component, allowing for flexible and independent evolution of its logic. The Telegram bot will be developed to mirror API actions, enhancing multi-channel interaction seamlessly. Deliverables include: - FastAPI codebase with OpenAPI/Swagger docs - Spring Boot service skeleton with a sample task - SQLAlchemy models and a ready-to-run PostgreSQL Docker setup - Integrated Telegram bot code - Comprehensive README for setup - Basic unit tests for critical endpoints I’m ready to start immediately and ensure all services run smoothly with a single `docker-compose up`. Let’s create something great together! Best, Karthik

@AndrewJSMAN

I've built FastAPI services with PostgreSQL and AI integrations before, so this is right in my wheelhouse. I'll set up the FastAPI core with SQLAlchemy models, Alembic migrations, and Dockerized PostgreSQL, then add OpenAPI docs and unit tests. The Spring Boot microservice will handle background jobs with a sample task, and I'll wire in OpenAI via a clean service layer. The Telegram bot will use webhooks to mirror API actions, sharing the same database. All services will start with docker-compose up, with migrations running automatically. I'll document setup in a README and validate /docs. I can start immediately. Thanks, Andrii.

@letsUnlockAI

Hi, I can build this backend architecture with FastAPI, PostgreSQL, SQLAlchemy, Alembic, Docker, and the required AI integration. I have strong experience with Python APIs, backend systems, databases, authentication, AI/LLM workflows, and automation. I’ll create a clean FastAPI REST API with complete Swagger/OpenAPI documentation, migrations, PostgreSQL Docker setup, and unit tests. I can also provide the Spring Boot microservice with a sample background task and integrate the Telegram bot through webhooks using the same database. The AI logic will be isolated behind a service layer so you can replace or extend the model later without changing the core API. Everything will be configured so the full stack can be started with a single `docker-compose up`. I can start immediately and deliver a clean, maintainable codebase with setup documentation.

@letscms

Hi, I’m an experienced backend developer specializing in FastAPI, Python, PostgreSQL, Docker, REST APIs, and AI integrations, with additional experience in Node.js/NestJS and microservice architecture. I can build the FastAPI service with SQLAlchemy, Alembic, OpenAPI/Swagger, clean service/repository architecture, authentication if required, and proper unit tests. I’ll also create the Spring Boot background-service skeleton with a sample job and a separated AI service layer for future model changes. I can integrate the Telegram bot using webhooks with the same PostgreSQL database and provide a complete Docker Compose setup where all services and migrations start cleanly with a single command. You’ll receive the complete source code, migrations, tests, README, environment configuration, and documented /docs API. I can start with the backend architecture and database design immediately. Best Regards, Jitendra Sharma