Immutable solution version
IBM watsonx.ai: deployment fails but inference works - project vs space scope
Complete solution
IBM watsonx.ai: deployment fails but inference works - project vs space scope. Deployments live in a space, not a project. Use when hitting this exact issue with IBM watsonx.ai. Not for unrelated errors or different features.
TL;DR
Deployments live in a space, not a project.
The error
deployment fails but inference works - project vs space scopeFix
Deployments live in a space, not a project. Expected: you can confirm this matches your situation.
Re-run the original operation and confirm the error is gone. Expected: no error, normal output.
When to use
- You hit this exact error with IBM watsonx.ai.
- The symptom matches: deployment fails but inference works - project vs space scope.
When NOT to use
- A different error message from IBM watsonx.ai; the cause here is specific to this error.
- Unrelated IBM watsonx.ai issues (different feature, different failure).
- You need general documentation for the tool; check the official docs instead.
Compatibility
Reported against IBM watsonx.ai.
Variant phrasings
deployment fails but inference works - project vs space scope
Why it happens
In watsonx.ai, model inference works but creating a deployment or scoring endpoint fails with scope errors like No project or space id provided. This is a classic project vs space mix-up.
Edge cases
- If your error message differs even slightly, this is probably a different issue; search the exact text.
- If the fix does not help, capture the full error output and check the source link for updates.
Evidence
Source: In watsonx.ai, model inference works but creating a deployment or scoring endpoint fails with scope errors like No project or space id provided. This is a classic project vs space mix-up.
Verified resolution: [field debugging playbook]: Deployments live in a space, not a project. Call client.set.defaultspace with the space ID (or pass spaceid to the foundation model object) and re-run. Related scope errors: a 401/Unauthorized usually means a bad or expired token, or the raw API key used where a Bearer token is required on REST; 403 means the key lacks access to that project/space or the region URL is wrong; REST 400 version errors mean the version query param is missing or invalid.
Source URL: https://github.com/gangwuca-art/bob-llmwiki-knowledge-manager/blob/HEAD/.bob/skills/ibm-watsonx.ai/SKILL.md
By @issueatlas · Version 2 · Exact version
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