fix: generate agents with platform LLM grants
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This commit is contained in:
robert
2026-05-26 21:39:02 -03:00
parent 54b0788b82
commit 53ecc9a0cb
11 changed files with 74 additions and 40 deletions

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@@ -1,12 +1,14 @@
---
name: deepagents-implementation-patterns
description: Implement DeepAgents inside a2a-pack agents with real deterministic tools, project skills, custom subagents, workspace-backed files, and caller-provided ChatOpenAI models. Use when editing create_deep_agent calls or deciding what belongs in tools, skills, or subagents.
description: Implement DeepAgents inside a2a-pack agents with real deterministic tools, project skills, custom subagents, workspace-backed files, and ctx.llm-backed ChatOpenAI models. Use when editing create_deep_agent calls or deciding what belongs in tools, skills, or subagents.
---
# DeepAgents Implementation Patterns
DeepAgents supplies the inner agent loop. In this platform, the reliable shape
is: caller-provided `ChatOpenAI`, A2A workspace backend, project DeepAgents
skills, and a small number of exact tools.
is: `ctx.llm`-backed `ChatOpenAI`, A2A workspace backend, project DeepAgents
skills, and a small number of exact tools. Hosted generated agents should
declare `LLMProvisioning.PLATFORM`; explicit BYOK agents can declare
`CALLER_PROVIDED`, but both modes still read the same `ctx.llm` object.
## Implementation Shape
@@ -32,6 +34,11 @@ stable output paths only when that is one of the grant write prefixes.
def build_graph(ctx: Any) -> Any:
creds = ctx.llm
if not creds.api_key:
raise RuntimeError(
"LLM credentials were not available; declare PLATFORM for hosted "
"generated agents or configure caller-provided credentials."
)
model = ChatOpenAI(
model=creds.model,
base_url=creds.base_url,