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Connect OpenHands to local/self-hosted inference through Ollama or vLLM while planning model choice, endpoint reachability, context and GPU capacity.
Before running commands in production, validate versions, backups, firewall rules and the rollback plan on your own infrastructure.
The agent layer calls a local provider endpoint; the runtime must be able to reach it over the network. For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.
Beyond install commands, this guide covers architecture, capacity, security, troubleshooting and production operations as one workflow.
The agent layer calls a local provider endpoint; the runtime must be able to reach it over the network.
Do not approve the OpenHands + Ollama / vLLM Local Model Setup design merely because every service starts. Keep the inference endpoint private and restrict access with API keys, firewall rules and runtime egress policy. Validate the real network and data path against OpenHands Local LLMs documentation before production.
For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.
Failure to reach host-side Ollama via localhost from a container is a common network-namespace issue. Capacity testing should therefore use representative data and concurrent work on OpenHands + Ollama / vLLM Local Model Setup; idle RAM alone is not a sizing decision.
For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together. For GPU-accelerated workloads, benchmarks are not comparable unless model/data, concurrency and measurement window remain identical.
Keep the model/data, concurrency and measurement window identical across comparisons. Failure to reach host-side Ollama via localhost from a container is a common network-namespace issue. Record failure rate and peak resource usage next to throughput.
Keep the inference endpoint private and restrict access with API keys, firewall rules and runtime egress policy.
Access control for OpenHands + Ollama / vLLM Local Model Setup is an architectural input rather than a post-deployment add-on. The agent layer calls a local provider endpoint; the runtime must be able to reach it over the network. Database, worker, runtime or admin ports that do not need public exposure should remain private.
Compare success rate, latency and token usage on the same task set; a single-prompt benchmark is not enough.
Use this operation as one release verification point: curl http://127.0.0.1:11434/api/tags. Failure to reach host-side Ollama via localhost from a container is a common network-namespace issue. If it fails, validate the rollback point before proceeding.
Failure to reach host-side Ollama via localhost from a container is a common network-namespace issue.
To separate symptoms from root cause in OpenHands + Ollama / vLLM Local Model Setup, record the last change first. For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together. Then correlate service logs, dependency health and network reachability on the same timeline.
The agent layer calls a local provider endpoint; the runtime must be able to reach it over the network. For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.
| Symptom / problem | Likely layer | First verification |
|---|---|---|
| Sandbox starts but workspace is not writable | Failure to reach host-side Ollama via localhost from a container is a common network-namespace issue. | Correlate the relevant service log, dependency health and the last change on one timeline. |
| Agent cannot reach the local model endpoint | For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together. | Measure peak resources, concurrency and disk/network pressure in the same test window. |
| Tool calls produce malformed JSON or timeouts | Keep the inference endpoint private and restrict access with API keys, firewall rules and runtime egress policy. | Verify public/private ports, authentication, TLS and secret scope from outside in. |
| GPU is available but task success remains low | Compare success rate, latency and token usage on the same task set; a single-prompt benchmark is not enough. | Check version, config diff, persistent data and the rollback point together. |
Beyond install commands, this guide covers architecture, capacity, security, troubleshooting and production operations as one workflow.
Connect OpenHands to local/self-hosted inference through Ollama or vLLM while planning model choice, endpoint reachability, context and GPU capacity.
The agent layer calls a local provider endpoint; the runtime must be able to reach it over the network.
For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.
Keep the inference endpoint private and restrict access with API keys, firewall rules and runtime egress policy.
Compare success rate, latency and token usage on the same task set; a single-prompt benchmark is not enough.
Failure to reach host-side Ollama via localhost from a container is a common network-namespace issue.
Beyond install commands, this guide covers architecture, capacity, security, troubleshooting and production operations as one workflow.
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ollama listcurl http://127.0.0.1:11434/api/tagscurl http://127.0.0.1:8000/v1/modelsnvidia-smiApproximate VRAM planner for model weights
Beyond install commands, this guide covers architecture, capacity, security, troubleshooting and production operations as one workflow. For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.
Beyond install commands, this guide covers architecture, capacity, security, troubleshooting and production operations as one workflow.
Beyond install commands, this guide covers architecture, capacity, security, troubleshooting and production operations as one workflow.
The agent layer calls a local provider endpoint; the runtime must be able to reach it over the network. For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.
The agent layer calls a local provider endpoint; the runtime must be able to reach it over the network.
Keep the inference endpoint private and restrict access with API keys, firewall rules and runtime egress policy.
For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.
Compare success rate, latency and token usage on the same task set; a single-prompt benchmark is not enough.
Failure to reach host-side Ollama via localhost from a container is a common network-namespace issue.
No. It is an initial planning estimate. For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together. Validate the final decision against the real workload.
Beyond install commands, this guide covers architecture, capacity, security, troubleshooting and production operations as one workflow. For coding agents, context and tool-use quality matter alongside model quality; measure VRAM and token throughput together.