I built my first RAG-based AI education chatbot using Python + MongoDB vector storage, but deployment on Render fails with “No open ports detected.” I’m trying to figure out if this is caused by slow RAG startup, embedding initialization, or a configuration issue.
Github Repository: https://github.com/NjiruWinfred/RAG-Edulearn
Additional Technical Context
I’m still learning deployment and backend architecture, so some terminology may not be perfect yet.
Stack
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Python backend
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MongoDB for chat history and vector storage
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RAG implementation for curriculum-aware responses
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Hosted on Render
I’m not fully sure whether my structure is closer to Flask or FastAPI because I followed tutorials while learning, but the backend exposes API endpoints for the chatbot.
Startup Behavior
One thing I suspect is happening is that embeddings/vector retrieval initialization may be happening during startup before the server fully opens a port.
My theory is:
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Render waits for the app to expose a port
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The RAG initialization process takes too long
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Render times out and throws:
“No open ports detected”
Render Logs
The main error shown is:
“Error: No open ports detected”
I didn’t see a clear Python crash traceback, which is why I started suspecting startup timeout issues instead of syntax errors.
Startup Command
I used the standard Render startup command based on the tutorial/documentation I followed for running the Python app.
I’m still learning how production deployment differs from local development, so I may be missing best practices around:
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lazy loading
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async initialization
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precomputed embeddings
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separating vector indexing from app startup
Would appreciate any guidance or debugging ideas from more experienced developers ![]()
Thank you so much in advance.