For the HNG Internship, I built a modular text transformation chain using FastAPI microservices and fully integrated it with Telex.im’s AI coworker platform.

Workflow:

Input Agent: Receives text, coordinates calls.

Capitalizer Agent: Converts all text to uppercase.

Reverse Agent: Reverses word order.

Example: Input: “hello world again” Output: “AGAIN WORLD HELLO”

Deployment: Each microservice is deployed independently on Render, communicating via HTTP endpoints. The Input Agent orchestrates the chain and exposes a /transform-text endpoint.

Integration: On Telex.im, I registered my input agent, described its workflow, and verified with test prompts. (Side note: Still troubleshooting the category/publishing error, but setup is ready and endpoint works fine!)

Tech Used:

FastAPI

Uvicorn

httpx

Render for cloud hosting

Telex.im for agent collaboration

Challenges & Fixes: Wrestling with JSON validation for category, I switched to defining tasks directly in the Telex UI—this is more reliable and makes agent setup seamless.

How To Try:

Send a POST to my endpoint with any sentence: get back uppercase and word-reversed result instantly!

Example:

json { “text”: “hello world again” } Returns:

json { “text”: “AGAIN WORLD HELLO” } Next Steps: Once publishing is fixed, my agent will be live for anyone on Telex.im. Follow my repository [your GitHub repo link] for source, docs, and updates.

Conclusion: Microservice agent chaining is a scalable pattern for AI and automation. Happy to assist with integration tips—ping me for help.