likang/cdsl-cad
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

wip: preserve local engine and agent workflow changes before ganjihong refactor integration

Browse Source
This commit is contained in:
李康
2026-09-09 17:08:24 +08:00
parent a5c3ec1f36
commit 387b99e255
112 changed files with 3543 additions and 12177 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/app/cad_agent/adapters/structured_llm.py
+5 -32
View File
@@ -1,4 +1,4 @@
"""The sole OpenAI-compatible structured-output adapter for protocol v3.
"""The sole OpenAI-compatible structured-output adapter for Authoring CDSL.
Raw tool arguments are intentionally preserved. Callers must run their
Pydantic/JSON-Schema canonical validator before causing any state transition.
@@ -170,39 +170,12 @@ class StructuredModelGateway:
@staticmethod
def _conformance_messages(tool: dict[str, Any]) -> list[dict[str, Any]]:
"""Give capability probes the same selector fact production exposes.
A required opaque selector is not inferable from a generic request for
a minimal example. Production fragment turns expose a topology token
before the fragment tool, so the probe must do the same while still
letting the provider generate every other schema field itself.
"""
"""Probe the two standalone structured documents used by this protocol."""
function = tool.get("function") if isinstance(tool.get("function"), dict) else {}
name = str(function.get("name") or "")
parameters = function.get("parameters") if isinstance(function.get("parameters"), dict) else {}
feature = parameters.get("properties", {}).get("feature") if isinstance(parameters.get("properties"), dict) else None
feature_properties = feature.get("properties") if isinstance(feature, dict) and isinstance(feature.get("properties"), dict) else {}
feature_required = feature.get("required") if isinstance(feature, dict) and isinstance(feature.get("required"), list) else []
selector_required = "selector_tokens" in feature_required and isinstance(feature_properties.get("selector_tokens"), dict)
instruction = "Return exactly the required function call with a minimal valid example. The active JSON Schema is authoritative."
if selector_required:
atomic_id = feature_properties.get("atomic_id", {}).get("const") if isinstance(feature_properties.get("atomic_id"), dict) else "..."
instruction += (
" The current topology exposes opaque selector token `sel_conformance`. "
f"Use root shape {{\"feature\":{{\"atomic_id\":{json.dumps(atomic_id)},"
"\"selector_tokens\":[\"sel_conformance\"],\"params\":{...}}}}. "
"Because feature.selector_tokens is required, it is author input and must not be moved into params."
)
if name == "review_candidate":
instruction += (
" This is a candidate-review probe: include every required top-level and nested field; "
"in particular provide a verdict and claim_coverage. Use accept and pass only where the schema permits them."
)
elif name == "review_final":
instruction += (
" This is a final-review probe: include every required top-level and nested field; "
"in particular provide a verdict and claim_coverage. Use pass only where the schema permits it."
)
if name == "write_authoring_cdsl":
instruction += " Return cad.author.v1 with document-local names only; do not include runtime IDs, stable selectors, snapshots, or selector tokens."
return [{"role": "system", "content": instruction}]
def _provider_model(self, provider_id: str, model_id: str) -> tuple[ProviderConfig, ProviderModel]:
@@ -256,7 +229,7 @@ class StructuredModelGateway:
force_tool_name: bool = True,
) -> dict[str, Any]:
if len(tools) != 1 or not required_tool_name:
raise StructuredModelError("The v3 protocol requires exactly one named tool per provider call.")
raise StructuredModelError("The Authoring protocol requires exactly one named tool per provider call.")
request_options = provider.request_options if include_reasoning else {}
if provider.api_style == "responses":
payload: dict[str, Any] = {