ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter2/prompt-engineering/tau_bench/model_utils/model/outlines_completion.py

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+from typing import Any
+
+from pydantic import BaseModel
+
+from tau_bench.model_utils.api.datapoint import Datapoint
+from tau_bench.model_utils.model.vllm_completion import VLLMCompletionModel
+from tau_bench.model_utils.model.vllm_utils import generate_request
+
+
+class OutlinesCompletionModel(VLLMCompletionModel):
+    def parse_force_from_prompt(
+        self, prompt: str, typ: BaseModel, temperature: float | None = None
+    ) -> dict[str, Any]:
+        if temperature is None:
+            temperature = self.temperature
+        schema = typ.model_json_schema()
+        res = generate_request(
+            url=self.url,
+            prompt=prompt,
+            force_json=True,
+            schema=schema,
+            temperature=temperature,
+        )
+        return self.handle_parse_force_response(prompt=prompt, content=res)
+
+    def get_approx_cost(self, dp: Datapoint) -> float:
+        return super().get_approx_cost(dp)
+
+    def get_latency(self, dp: Datapoint) -> float:
+        return super().get_latency(dp)
+
+    def get_capability(self) -> float:
+        return super().get_capability()
+
+    def supports_dp(self, dp: Datapoint) -> bool:
+        return super().supports_dp(dp)