refactor(tool): flatten request body parameters for model exposure
- Refactor the extraction logic in tool service to flatten request body parameters into independent arguments exposed to the model.
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@@ -73,6 +73,7 @@ class CustomTool(BaseTool):
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# 添加通用参数(基于第一个操作的参数)
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if self._parsed_operations:
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first_operation = next(iter(self._parsed_operations.values()))
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# path/query 参数
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for param_name, param_info in first_operation.get("parameters", {}).items():
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params.append(ToolParameter(
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name=param_name,
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@@ -85,6 +86,23 @@ class CustomTool(BaseTool):
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maximum=param_info.get("maximum"),
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pattern=param_info.get("pattern")
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))
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# requestBody 参数 — 将 body 字段平铺为独立参数暴露给模型
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request_body = first_operation.get("request_body")
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if request_body:
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body_schema = request_body.get("properties", {})
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required_fields = request_body.get("required", [])
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for prop_name, prop_schema in body_schema.items():
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params.append(ToolParameter(
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name=prop_name,
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type=self._convert_openapi_type(prop_schema.get("type", "string")),
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description=prop_schema.get("description", ""),
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required=prop_name in required_fields,
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default=prop_schema.get("default"),
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enum=prop_schema.get("enum"),
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minimum=prop_schema.get("minimum"),
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maximum=prop_schema.get("maximum"),
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pattern=prop_schema.get("pattern")
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))
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return params
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@@ -815,11 +815,12 @@ class ToolService:
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"default": param_info.get("default")
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})
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# 请求体参数
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# 请求体参数 — _extract_request_body 返回 {"schema": {...}, "required": bool, ...}
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request_body = operation.get("request_body")
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if request_body:
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schema_props = request_body.get("schema", {}).get("properties", {})
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required_props = request_body.get("schema", {}).get("required", [])
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body_schema = request_body.get("schema", {})
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schema_props = body_schema.get("properties", {})
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required_props = body_schema.get("required", [])
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for prop_name, prop_schema in schema_props.items():
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parameters.append({
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