refactor: 推理协议层重构为策略/建造者模式

- ProtocolHandler 改为具体类，格式化委托给 ResponseBuilder
- 新增 api/protocols/ 目录，含 OpenAIResponseBuilder、AnthropicResponseBuilder
- GenContext、StopInfo 参数对象替代 StreamContext
- 消除 Builder 的实例可变状态（accumulated、_yielded）
- SSE 工具和停止检测收归 ProtocolHandler 统一管理
- prepare() 方法合并原来的 build_prompt、create_response_id
- 参数校验去重：仅 GenerationRequest.init 负责校验
- Prefill 阶段提前短路完全命中的缓存任务

astrai/inference/api/openai.py

@@ -0,0 +1,111 @@
+"""OpenAI chat completion response builder."""
+
+import uuid
+from typing import Any, Dict, List, Optional, Tuple
+
+from pydantic import BaseModel
+
+from astrai.inference.api.protocol import (
+    GenContext,
+    ResponseBuilder,
+    StopInfo,
+    sse_event,
+)
+from astrai.inference.engine import InferenceEngine
+
+
+class OpenAIResponseBuilder(ResponseBuilder):
+    def prepare(
+        self, request: BaseModel, engine: InferenceEngine
+    ) -> Tuple[str, GenContext, List[str]]:
+        messages = [{"role": m.role, "content": m.content} for m in request.messages]
+        prompt = engine.tokenizer.apply_chat_template(messages, tokenize=False)
+
+        self._resp_id = f"chatcmpl-{uuid.uuid4().hex[:12]}"
+        self._model = request.model
+
+        ctx = GenContext(
+            resp_id=self._resp_id,
+            created=0,
+            model=self._model,
+            prompt_tokens=0,
+        )
+        stop = request.stop
+        stop_sequences = (
+            [] if stop is None else [stop] if isinstance(stop, str) else stop
+        )
+        return prompt, ctx, stop_sequences
+
+    def format_stream_start(self, ctx: GenContext) -> List[str]:
+        return [
+            sse_event(
+                {
+                    "id": self._resp_id,
+                    "object": "chat.completion.chunk",
+                    "created": ctx.created,
+                    "model": self._model,
+                    "choices": [
+                        {
+                            "index": 0,
+                            "delta": {"role": "assistant"},
+                            "finish_reason": None,
+                        }
+                    ],
+                }
+            )
+        ]
+
+    def format_chunk(self, token: str) -> str:
+        return sse_event(
+            {
+                "id": self._resp_id,
+                "object": "chat.completion.chunk",
+                "created": 0,
+                "model": self._model,
+                "choices": [
+                    {"index": 0, "delta": {"content": token}, "finish_reason": None}
+                ],
+            }
+        )
+
+    def format_stream_end(self, ctx: GenContext, stop: StopInfo) -> List[str]:
+        return [
+            sse_event(
+                {
+                    "id": self._resp_id,
+                    "object": "chat.completion.chunk",
+                    "created": ctx.created,
+                    "model": self._model,
+                    "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
+                }
+            ),
+            sse_event(
+                {
+                    "prompt_tokens": ctx.prompt_tokens,
+                    "completion_tokens": ctx.completion_tokens,
+                    "total_tokens": ctx.prompt_tokens + ctx.completion_tokens,
+                }
+            ),
+        ]
+
+    def format_response(
+        self, ctx: GenContext, content: str, stop: StopInfo
+    ) -> Dict[str, Any]:
+        return {
+            "id": self._resp_id,
+            "object": "chat.completion",
+            "created": ctx.created,
+            "model": self._model,
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {"role": "assistant", "content": content},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {
+                "prompt_tokens": ctx.prompt_tokens,
+                "completion_tokens": ctx.completion_tokens,
+                "total_tokens": ctx.prompt_tokens + ctx.completion_tokens,
+            },
+        }