What this error means
Error: pull model manifest: Get https://registry.ollama.ai/v2/library/<model>/manifests/latest: net/http: TLS handshake timeout is a Ollama failure pattern reported for developers trying to running ollama inside docker container behind restricted network/firewall/proxy cannot pull models from registry due to tls handshake timeout; needs proxy configuration or dns fix workaround. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
forums.docker.com thread confirms TLS handshake timeout during ollama pull from Docker container. Root causes include DNS resolution failure (lookup registry.ollama.ai times out), corporate firewall blocking outbound HTTPS, or missing HTTPS_PROXY env var. Hugging Face community thread shows 429 quota errors during model pulls too. Proxy config workaround involves systemd Environment=HTTPS_PROXY setup. Category: Ollama per mapping.
Common causes
- forums.docker.com thread confirms TLS handshake timeout during ollama pull from Docker container. Root causes include DNS resolution failure (lookup registry.ollama.ai times out), corporate firewall blocking outbound HTTPS, or missing HTTPS_PROXY env var. Hugging Face community thread shows 429 quota errors during model pulls too. Proxy config workaround involves systemd Environment=HTTPS_PROXY setup. Category: Ollama per mapping.
Quick fixes
- Confirm the exact error signature matches
Error: pull model manifest: Get https://registry.ollama.ai/v2/library/<model>/manifests/latest: net/http: TLS handshake timeout. - Check the Ollama account, local tool state, and provider configuration involved in the failing workflow.
- Verify the model name, local service connectivity, and network access before retrying the model pull.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.