NVIDIA / NVIDIA/TensorRT-Edge-LLM
parallel agentic calls not supported by server
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 563
- Forks
- 135
- Avg merge
- 14h 13m
- Merged PRs (30d)
- 1
Description
Thanks for landing this in 0.7.0. I tested it on Jetson AGX Thor with nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-NVFP4 and single-stream throughput was excellent (~1.8× than same model in vllm), plus load times are much faster after first run.
Two observations from the quick tests I ran:
The server handles one request at a time. Sending two concurrently triggers an error, and the process needs a restart to recover.
Responses seem to return text only. The OpenAI-standard tool_calls field doesn't seem to be populated yet, I rely on that for agentic workflows.
Let me know if there's something I might be missing that could cause these problems if they are known and to be solved.
I can provide my setup if useful
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the two reported behaviors on the server: send two requests concurrently and inspect an agentic response for the OpenAI-standard tool_calls field. Done means concurrent requests do not require a restart and supported responses populate tool_calls; the reporter can provide setup details if needed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- api, backend
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 55/100