serving_responses.py 84.2 KB
Newer Older
1
2
3
4
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

import asyncio
5
import json
6
import time
7
import uuid
8
from collections import deque
9
from collections.abc import AsyncGenerator, AsyncIterator, Callable, Sequence
10
from contextlib import AsyncExitStack
11
from copy import copy
12
from http import HTTPStatus
13
from typing import Final
14
15
16

import jinja2
from fastapi import Request
17
18
19
20
21
22
from openai.types.responses import (
    ResponseCodeInterpreterCallCodeDeltaEvent,
    ResponseCodeInterpreterCallCodeDoneEvent,
    ResponseCodeInterpreterCallCompletedEvent,
    ResponseCodeInterpreterCallInProgressEvent,
    ResponseCodeInterpreterCallInterpretingEvent,
23
24
25
    ResponseCodeInterpreterToolCallParam,
    ResponseContentPartAddedEvent,
    ResponseContentPartDoneEvent,
26
27
    ResponseFunctionCallArgumentsDeltaEvent,
    ResponseFunctionCallArgumentsDoneEvent,
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
    ResponseFunctionToolCall,
    ResponseFunctionWebSearch,
    ResponseOutputItem,
    ResponseOutputItemAddedEvent,
    ResponseOutputItemDoneEvent,
    ResponseOutputMessage,
    ResponseOutputText,
    ResponseReasoningItem,
    ResponseReasoningTextDeltaEvent,
    ResponseReasoningTextDoneEvent,
    ResponseStatus,
    ResponseTextDeltaEvent,
    ResponseTextDoneEvent,
    ResponseWebSearchCallCompletedEvent,
    ResponseWebSearchCallInProgressEvent,
    ResponseWebSearchCallSearchingEvent,
    response_function_web_search,
    response_text_delta_event,
)
from openai.types.responses.response_output_text import Logprob, LogprobTopLogprob
48
from openai.types.responses.response_reasoning_item import (
49
50
    Content as ResponseReasoningTextContent,
)
51
from openai.types.responses.tool import Tool
52
from openai_harmony import Message as OpenAIHarmonyMessage
53

54
from vllm import envs
55
from vllm.engine.protocol import EngineClient
56
57
58
59
60
61
62
63
64
65
from vllm.entrypoints.chat_utils import (
    ChatCompletionMessageParam,
    ChatTemplateContentFormatOption,
)
from vllm.entrypoints.context import (
    ConversationContext,
    HarmonyContext,
    SimpleContext,
    StreamingHarmonyContext,
)
66
from vllm.entrypoints.harmony_utils import (
67
    construct_harmony_previous_input_messages,
68
69
70
71
72
73
74
75
76
77
    get_developer_message,
    get_stop_tokens_for_assistant_actions,
    get_system_message,
    get_user_message,
    has_custom_tools,
    parse_output_message,
    parse_remaining_state,
    parse_response_input,
    render_for_completion,
)
78
from vllm.entrypoints.logger import RequestLogger
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
from vllm.entrypoints.openai.protocol import (
    DeltaMessage,
    ErrorResponse,
    InputTokensDetails,
    OutputTokensDetails,
    RequestResponseMetadata,
    ResponseCompletedEvent,
    ResponseCreatedEvent,
    ResponseInProgressEvent,
    ResponseReasoningPartAddedEvent,
    ResponseReasoningPartDoneEvent,
    ResponsesRequest,
    ResponsesResponse,
    ResponseUsage,
    StreamingResponsesResponse,
)
95
96
from vllm.entrypoints.openai.serving_engine import OpenAIServing
from vllm.entrypoints.openai.serving_models import OpenAIServingModels
97
from vllm.entrypoints.tool_server import ToolServer
98
from vllm.inputs.data import TokensPrompt as EngineTokensPrompt
99
from vllm.logger import init_logger
100
101
from vllm.logprobs import Logprob as SampleLogprob
from vllm.logprobs import SampleLogprobs
102
from vllm.outputs import CompletionOutput
103
from vllm.sampling_params import SamplingParams, StructuredOutputsParams
104
105
106
107
108
109
from vllm.transformers_utils.tokenizer import AnyTokenizer
from vllm.utils import random_uuid

logger = init_logger(__name__)


110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
def extract_tool_types(tools: list[Tool]) -> set[str]:
    """
    Extracts the tool types from the given tools.
    """
    tool_types: set[str] = set()
    for tool in tools:
        if tool.type == "mcp":
            # Allow the MCP Tool type to enable built in tools if the
            # server_label is allowlisted in
            # envs.VLLM_GPT_OSS_SYSTEM_TOOL_MCP_LABELS
            if tool.server_label in envs.VLLM_GPT_OSS_SYSTEM_TOOL_MCP_LABELS:
                tool_types.add(tool.server_label)
        else:
            tool_types.add(tool.type)
    return tool_types


127
128
129
130
131
132
class OpenAIServingResponses(OpenAIServing):
    def __init__(
        self,
        engine_client: EngineClient,
        models: OpenAIServingModels,
        *,
133
134
        request_logger: RequestLogger | None,
        chat_template: str | None,
135
136
137
138
        chat_template_content_format: ChatTemplateContentFormatOption,
        return_tokens_as_token_ids: bool = False,
        reasoning_parser: str = "",
        enable_auto_tools: bool = False,
139
140
        tool_parser: str | None = None,
        tool_server: ToolServer | None = None,
141
142
        enable_prompt_tokens_details: bool = False,
        enable_force_include_usage: bool = False,
143
        enable_log_outputs: bool = False,
144
        log_error_stack: bool = False,
145
146
147
148
149
150
    ) -> None:
        super().__init__(
            engine_client=engine_client,
            models=models,
            request_logger=request_logger,
            return_tokens_as_token_ids=return_tokens_as_token_ids,
151
            log_error_stack=log_error_stack,
152
153
154
155
        )

        self.chat_template = chat_template
        self.chat_template_content_format: Final = chat_template_content_format
156
        self.enable_log_outputs = enable_log_outputs
157

158
159
        self.reasoning_parser = self._get_reasoning_parser(
            reasoning_parser_name=reasoning_parser
160
        )
161
162
        self.enable_prompt_tokens_details = enable_prompt_tokens_details
        self.enable_force_include_usage = enable_force_include_usage
163
        self.default_sampling_params = self.model_config.get_diff_sampling_param()
164
165
166
        if self.default_sampling_params:
            source = self.model_config.generation_config
            source = "model" if source == "auto" else source
167
168
169
170
171
            logger.info(
                "Using default chat sampling params from %s: %s",
                source,
                self.default_sampling_params,
            )
172

173
174
175
176
177
        # If False (default), the "store" option is (silently) ignored and the
        # response is not stored. If True, the response is stored in memory.
        # NOTE(woosuk): This may not be intuitive for users, as the default
        # behavior in OpenAI's Responses API is to store the response, but
        # vLLM's default behavior is not.
178
        self.enable_store = envs.VLLM_ENABLE_RESPONSES_API_STORE
179
180
181
182
        if self.enable_store:
            logger.warning_once(
                "`VLLM_ENABLE_RESPONSES_API_STORE` is enabled. This may "
                "cause a memory leak since we never remove responses from "
183
184
                "the store."
            )
185

186
        self.use_harmony = self.model_config.hf_config.model_type == "gpt_oss"
187
        if self.use_harmony:
188
189
190
191
            logger.warning(
                "For gpt-oss, we ignore --enable-auto-tool-choice "
                "and always enable tool use."
            )
192
193
194
195
196
            # OpenAI models have two EOS-like tokens: <|return|> and <|call|>.
            # We need to add them to the stop token ids.
            if "stop_token_ids" not in self.default_sampling_params:
                self.default_sampling_params["stop_token_ids"] = []
            self.default_sampling_params["stop_token_ids"].extend(
197
198
                get_stop_tokens_for_assistant_actions()
            )
199
200
201
202
203

        # set up tool use
        self.enable_auto_tools: bool = enable_auto_tools
        if self.enable_auto_tools:
            logger.info(
204
                '"auto" tool choice has been enabled please note that while'
205
                " the parallel_tool_calls client option is preset for "
206
207
                "compatibility reasons, it will be ignored."
            )
208

209
        # HACK(woosuk): This is a hack. We should use a better store.
210
211
        # FIXME: If enable_store=True, this may cause a memory leak since we
        # never remove responses from the store.
212
213
214
215
        self.response_store: dict[str, ResponsesResponse] = {}
        self.response_store_lock = asyncio.Lock()

        # HACK(woosuk): This is a hack. We should use a better store.
216
217
        # FIXME: If enable_store=True, this may cause a memory leak since we
        # never remove messages from the store.
218
219
        self.msg_store: dict[str, list[ChatCompletionMessageParam]] = {}

220
221
222
        # HACK(wuhang): This is a hack. We should use a better store.
        # FIXME: If enable_store=True, this may cause a memory leak since we
        # never remove events from the store.
223
224
225
        self.event_store: dict[
            str, tuple[deque[StreamingResponsesResponse], asyncio.Event]
        ] = {}
226

227
228
        self.background_tasks: dict[str, asyncio.Task] = {}

229
230
        self.tool_server = tool_server

231
    def _validate_generator_input(
232
        self, engine_prompt: EngineTokensPrompt
233
    ) -> ErrorResponse | None:
234
235
236
237
238
239
        """Add validations to the input to the generator here."""
        if self.max_model_len <= len(engine_prompt["prompt_token_ids"]):
            error_message = (
                "The engine prompt length"
                f" {len(engine_prompt['prompt_token_ids'])} "
                f"exceeds the max_model_len {self.max_model_len}. "
240
241
                "Please reduce prompt."
            )
242
243
244
245
246
247
248
            return self.create_error_response(
                err_type="invalid_request_error",
                message=error_message,
                status_code=HTTPStatus.BAD_REQUEST,
            )
        return None

249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
    def _validate_create_responses_input(
        self, request: ResponsesRequest
    ) -> ErrorResponse | None:
        if self.use_harmony and request.is_include_output_logprobs():
            return self.create_error_response(
                err_type="invalid_request_error",
                message="logprobs are not supported with gpt-oss models",
                status_code=HTTPStatus.BAD_REQUEST,
            )
        if request.store and not self.enable_store and request.background:
            return self.create_error_response(
                err_type="invalid_request_error",
                message=(
                    "This vLLM engine does not support `store=True` and "
                    "therefore does not support the background mode. To "
                    "enable these features, set the environment variable "
                    "`VLLM_ENABLE_RESPONSES_API_STORE=1` when launching "
                    "the vLLM server."
                ),
                status_code=HTTPStatus.BAD_REQUEST,
            )
270
271
272
273
274
275
276
        if request.previous_input_messages and request.previous_response_id:
            return self.create_error_response(
                err_type="invalid_request_error",
                message="Only one of `previous_input_messages` and "
                "`previous_response_id` can be set.",
                status_code=HTTPStatus.BAD_REQUEST,
            )
277
278
        return None

279
280
281
    async def create_responses(
        self,
        request: ResponsesRequest,
282
283
284
285
286
287
        raw_request: Request | None = None,
    ) -> (
        AsyncGenerator[StreamingResponsesResponse, None]
        | ResponsesResponse
        | ErrorResponse
    ):
288
289
290
291
        error_check_ret = await self._check_model(request)
        if error_check_ret is not None:
            logger.error("Error with model %s", error_check_ret)
            return error_check_ret
292
293
294
        maybe_validation_error = self._validate_create_responses_input(request)
        if maybe_validation_error is not None:
            return maybe_validation_error
295
296
297
298
299
300
301

        # If the engine is dead, raise the engine's DEAD_ERROR.
        # This is required for the streaming case, where we return a
        # success status before we actually start generating text :).
        if self.engine_client.errored:
            raise self.engine_client.dead_error

302
        if request.store and not self.enable_store:
303
304
305
306
307
308
309
            # Disable the store option.
            # NOTE(woosuk): Although returning an error is possible, we opted
            # to implicitly disable store and process the request anyway, as
            # we assume most users do not intend to actually store the response
            # (i.e., their request's `store=True` just because it's the default
            # value).
            request.store = False
310

311
312
313
314
315
316
317
318
319
320
321
        # Handle the previous response ID.
        prev_response_id = request.previous_response_id
        if prev_response_id is not None:
            async with self.response_store_lock:
                prev_response = self.response_store.get(prev_response_id)
            if prev_response is None:
                return self._make_not_found_error(prev_response_id)
        else:
            prev_response = None

        try:
322
            lora_request = self._maybe_get_adapters(request)
323
            model_name = self.models.model_name(lora_request)
324
            tokenizer = await self.engine_client.get_tokenizer()
325

326
327
            if self.use_harmony:
                messages, request_prompts, engine_prompts = (
328
329
                    self._make_request_with_harmony(request, prev_response)
                )
330
            else:
331
332
333
                messages, request_prompts, engine_prompts = await self._make_request(
                    request, prev_response, tokenizer
                )
334

335
336
337
338
339
340
341
        except (
            ValueError,
            TypeError,
            RuntimeError,
            jinja2.TemplateError,
            NotImplementedError,
        ) as e:
342
343
344
            logger.exception("Error in preprocessing prompt inputs")
            return self.create_error_response(f"{e} {e.__cause__}")

345
        request_metadata = RequestResponseMetadata(request_id=request.request_id)
346
347
348
349
        if raw_request:
            raw_request.state.request_metadata = request_metadata

        # Schedule the request and get the result generator.
350
        generators: list[AsyncGenerator[ConversationContext, None]] = []
351
352
353
354
355
356
357

        builtin_tool_list: list[str] = []
        if self.use_harmony and self.tool_server is not None:
            if self.tool_server.has_tool("browser"):
                builtin_tool_list.append("browser")
            if self.tool_server.has_tool("python"):
                builtin_tool_list.append("python")
358
359
            if self.tool_server.has_tool("container"):
                builtin_tool_list.append("container")
360

361
362
363
364
365
366
367
        if self.tool_server is not None:
            available_tools = builtin_tool_list
        else:
            assert len(builtin_tool_list) == 0
            available_tools = []
        try:
            for i, engine_prompt in enumerate(engine_prompts):
368
369
370
371
                maybe_error = self._validate_generator_input(engine_prompt)
                if maybe_error is not None:
                    return maybe_error

372
                default_max_tokens = self.max_model_len - len(
373
374
                    engine_prompt["prompt_token_ids"]
                )
375

376
                sampling_params = request.to_sampling_params(
377
378
                    default_max_tokens, self.default_sampling_params
                )
379

380
381
382
383
384
                trace_headers = (
                    None
                    if raw_request is None
                    else await self._get_trace_headers(raw_request.headers)
                )
385
386
387
388

                context: ConversationContext
                if self.use_harmony:
                    if request.stream:
389
                        context = StreamingHarmonyContext(messages, available_tools)
390
391
392
393
                    else:
                        context = HarmonyContext(messages, available_tools)
                else:
                    context = SimpleContext()
394
395
396
397
398
399
400
401
402
403
404
405
406

                if self.reasoning_parser is not None:
                    reasoning_parser = self.reasoning_parser(tokenizer)
                    if sampling_params.structured_outputs is None:
                        sampling_params.structured_outputs = StructuredOutputsParams()
                    struct_out = sampling_params.structured_outputs
                    if struct_out.all_non_structural_tag_constraints_none():
                        sampling_params.structured_outputs.structural_tag = (
                            reasoning_parser.prepare_structured_tag(
                                sampling_params.structured_outputs.structural_tag,
                                self.tool_server,
                            )
                        )
407
408
409
410
411
412
413
414
415
                generator = self._generate_with_builtin_tools(
                    request_id=request.request_id,
                    request_prompt=request_prompts[i],
                    engine_prompt=engine_prompt,
                    sampling_params=sampling_params,
                    context=context,
                    lora_request=lora_request,
                    priority=request.priority,
                    trace_headers=trace_headers,
416
                )
417
418
419
420
                generators.append(generator)
        except ValueError as e:
            # TODO: Use a vllm-specific Validation Error
            return self.create_error_response(str(e))
421

422
        assert len(generators) == 1
423
        (result_generator,) = generators
424
425
426
427

        # Store the input messages.
        if request.store:
            self.msg_store[request.request_id] = messages
428

429
430
431
432
433
434
435
436
437
438
439
440
441
        if request.background:
            created_time = int(time.time())
            response = ResponsesResponse.from_request(
                request,
                sampling_params,
                model_name=model_name,
                created_time=created_time,
                output=[],
                status="queued",
                usage=None,
            )
            async with self.response_store_lock:
                self.response_store[response.id] = response
442

443
            # Run the request in the background.
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
            if request.stream:
                task = asyncio.create_task(
                    self._run_background_request_stream(
                        request,
                        sampling_params,
                        result_generator,
                        context,
                        model_name,
                        tokenizer,
                        request_metadata,
                        created_time,
                    ),
                    name=f"create_{request.request_id}",
                )
            else:
                task = asyncio.create_task(
                    self._run_background_request(
                        request,
                        sampling_params,
                        result_generator,
                        context,
                        model_name,
                        tokenizer,
                        request_metadata,
                        created_time,
                    ),
                    name=f"create_{response.id}",
                )
472

473
474
475
476
            # For cleanup.
            response_id = response.id
            self.background_tasks[response_id] = task
            task.add_done_callback(
477
478
                lambda _: self.background_tasks.pop(response_id, None)
            )
479
480

            if request.stream:
481
                return self.responses_background_stream_generator(request.request_id)
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
            return response

        if request.stream:
            return self.responses_stream_generator(
                request,
                sampling_params,
                result_generator,
                context,
                model_name,
                tokenizer,
                request_metadata,
            )

        try:
            return await self.responses_full_generator(
                request,
                sampling_params,
                result_generator,
                context,
                model_name,
                tokenizer,
                request_metadata,
            )
        except Exception as e:
            return self.create_error_response(str(e))
507

508
509
510
    async def _make_request(
        self,
        request: ResponsesRequest,
511
        prev_response: ResponsesResponse | None,
512
513
        tokenizer: AnyTokenizer,
    ):
514
515
        if len(request.tools) > 0:
            raise NotImplementedError(
516
517
                "Tool use is not supported in Responses API without Harmony"
            )
518
519
520
521
522
523
524
525
526
527
528
529
530
531
        # Construct the input messages.
        messages = self._construct_input_messages(request, prev_response)
        _, request_prompts, engine_prompts = await self._preprocess_chat(
            request,
            tokenizer,
            messages,
            chat_template=self.chat_template,
            chat_template_content_format=self.chat_template_content_format,
        )
        return messages, request_prompts, engine_prompts

    def _make_request_with_harmony(
        self,
        request: ResponsesRequest,
532
        prev_response: ResponsesResponse | None,
533
534
535
    ):
        if request.tool_choice != "auto":
            raise NotImplementedError(
536
537
538
                "Only 'auto' tool_choice is supported in response API with Harmony"
            )
        messages = self._construct_input_messages_with_harmony(request, prev_response)
539
540
        prompt_token_ids = render_for_completion(messages)
        engine_prompt = EngineTokensPrompt(prompt_token_ids=prompt_token_ids)
541
542
543
544
545

        # Add cache_salt if provided in the request
        if request.cache_salt is not None:
            engine_prompt["cache_salt"] = request.cache_salt

546
547
        return messages, [prompt_token_ids], [engine_prompt]

548
549
550
551
552
553
    async def _initialize_tool_sessions(
        self,
        request: ResponsesRequest,
        context: ConversationContext,
        exit_stack: AsyncExitStack,
    ):
554
555
556
557
        # we should only initialize the tool session if the request needs tools
        if len(request.tools) == 0:
            return
        mcp_tools = {
558
            tool.server_label: tool for tool in request.tools if tool.type == "mcp"
559
        }
560
561
562
        await context.init_tool_sessions(
            self.tool_server, exit_stack, request.request_id, mcp_tools
        )
563

564
565
566
567
    async def responses_full_generator(
        self,
        request: ResponsesRequest,
        sampling_params: SamplingParams,
568
        result_generator: AsyncIterator[ConversationContext],
569
        context: ConversationContext,
570
571
572
        model_name: str,
        tokenizer: AnyTokenizer,
        request_metadata: RequestResponseMetadata,
573
574
        created_time: int | None = None,
    ) -> ErrorResponse | ResponsesResponse:
575
576
577
        if created_time is None:
            created_time = int(time.time())

578
579
        async with AsyncExitStack() as exit_stack:
            try:
580
                await self._initialize_tool_sessions(request, context, exit_stack)
581
582
583
584
585
586
587
                async for _ in result_generator:
                    pass
            except asyncio.CancelledError:
                return self.create_error_response("Client disconnected")
            except ValueError as e:
                # TODO: Use a vllm-specific Validation Error
                return self.create_error_response(str(e))
588

589
590
591
592
593
        # NOTE: Implementation of stauts is still WIP, but for now
        # we guarantee that if the status is not "completed", it is accurate.
        # "completed" is implemented as the "catch-all" for now.
        status: ResponseStatus = "completed"

594
595
        input_messages = None
        output_messages = None
596
597
598
        if self.use_harmony:
            assert isinstance(context, HarmonyContext)
            output = self._make_response_output_items_with_harmony(context)
599
            if request.enable_response_messages:
600
601
                input_messages = context.messages[: context.num_init_messages]
                output_messages = context.messages[context.num_init_messages :]
602
            num_tool_output_tokens = context.num_tool_output_tokens
603
604
605
606
607
608
609
            if len(output) > 0:
                if context.finish_reason == "length":
                    status = "incomplete"
                elif context.finish_reason == "abort":
                    status = "cancelled"
            else:
                status = "incomplete"
610
        else:
611
612
613
614
615
616
            assert isinstance(context, SimpleContext)
            final_res = context.last_output
            assert final_res is not None
            assert len(final_res.outputs) == 1
            final_output = final_res.outputs[0]

617
            output = self._make_response_output_items(request, final_output, tokenizer)
618

619
620
621
622
            # TODO: context for non-gptoss models doesn't use messages
            # so we can't get them out yet
            if request.enable_response_messages:
                raise NotImplementedError(
623
624
                    "enable_response_messages is currently only supported for gpt-oss"
                )
625
626
            # Calculate usage.
            assert final_res.prompt_token_ids is not None
627
628
            num_tool_output_tokens = 0

629
630
631
632
633
        assert isinstance(context, (SimpleContext, HarmonyContext))
        num_prompt_tokens = context.num_prompt_tokens
        num_generated_tokens = context.num_output_tokens
        num_cached_tokens = context.num_cached_tokens
        num_reasoning_tokens = context.num_reasoning_tokens
634
635
636
637

        usage = ResponseUsage(
            input_tokens=num_prompt_tokens,
            output_tokens=num_generated_tokens,
638
            total_tokens=num_prompt_tokens + num_generated_tokens,
639
640
641
642
643
644
645
646
647
            input_tokens_details=InputTokensDetails(
                cached_tokens=num_cached_tokens,
                input_tokens_per_turn=[
                    turn.input_tokens for turn in context.all_turn_metrics
                ],
                cached_tokens_per_turn=[
                    turn.cached_input_tokens for turn in context.all_turn_metrics
                ],
            ),
648
            output_tokens_details=OutputTokensDetails(
649
                reasoning_tokens=num_reasoning_tokens,
650
                tool_output_tokens=num_tool_output_tokens,
651
652
653
654
655
656
                output_tokens_per_turn=[
                    turn.output_tokens for turn in context.all_turn_metrics
                ],
                tool_output_tokens_per_turn=[
                    turn.tool_output_tokens for turn in context.all_turn_metrics
                ],
657
            ),
658
659
660
661
        )
        response = ResponsesResponse.from_request(
            request,
            sampling_params,
662
663
            input_messages=input_messages,
            output_messages=output_messages,
664
665
666
            model_name=model_name,
            created_time=created_time,
            output=output,
667
            status=status,
668
669
670
671
672
673
674
            usage=usage,
        )

        if request.store:
            async with self.response_store_lock:
                stored_response = self.response_store.get(response.id)
                # If the response is already cancelled, don't update it.
675
                if stored_response is None or stored_response.status != "cancelled":
676
677
678
                    self.response_store[response.id] = response
        return response

679
680
681
682
683
684
    def _topk_logprobs(
        self,
        logprobs: dict[int, SampleLogprob],
        top_logprobs: int,
        tokenizer: AnyTokenizer,
    ) -> list[LogprobTopLogprob]:
685
686
687
688
689
        """Returns the top-k logprobs from the logprobs dictionary."""
        out = []
        for i, (token_id, _logprob) in enumerate(logprobs.items()):
            if i >= top_logprobs:
                break
690
691
692
693
694
            text = (
                _logprob.decoded_token
                if _logprob.decoded_token is not None
                else tokenizer.decode([token_id])
            )
695
696
697
698
699
            out.append(
                LogprobTopLogprob(
                    token=text,
                    logprob=max(_logprob.logprob, -9999.0),
                    bytes=list(text.encode("utf-8", errors="replace")),
700
701
                )
            )
702
703
704
        return out

    def _create_response_logprobs(
705
706
        self,
        token_ids: Sequence[int],
707
        logprobs: SampleLogprobs | None,
708
        tokenizer: AnyTokenizer,
709
        top_logprobs: int | None = None,
710
    ) -> list[Logprob]:
711
712
        assert logprobs is not None, "logprobs must be provided"
        assert len(token_ids) == len(logprobs), (
713
714
            "token_ids and logprobs.token_ids must have the same length"
        )
715
716
717
718
        out = []
        for i, token_id in enumerate(token_ids):
            logprob = logprobs[i]
            token_logprob = logprob[token_id]
719
720
721
722
723
            text = (
                token_logprob.decoded_token
                if token_logprob.decoded_token is not None
                else tokenizer.decode([token_id])
            )
724
725
726
727
728
            out.append(
                Logprob(
                    token=text,
                    logprob=max(token_logprob.logprob, -9999.0),
                    bytes=list(text.encode("utf-8", errors="replace")),
729
730
731
732
733
734
735
                    top_logprobs=(
                        self._topk_logprobs(
                            logprob, top_logprobs=top_logprobs, tokenizer=tokenizer
                        )
                        if top_logprobs
                        else []
                    ),
736
737
                )
            )
738
739
        return out

740
741
742
    def _create_stream_response_logprobs(
        self,
        token_ids: Sequence[int],
743
        logprobs: SampleLogprobs | None,
744
        tokenizer: AnyTokenizer,
745
        top_logprobs: int | None = None,
746
    ) -> list[response_text_delta_event.Logprob]:
747
748
749
750
751
752
        lgs = self._create_response_logprobs(
            token_ids=token_ids,
            logprobs=logprobs,
            tokenizer=tokenizer,
            top_logprobs=top_logprobs,
        )
753
754
755
756
757
758
        return [
            response_text_delta_event.Logprob(
                token=lg.token,
                logprob=lg.logprob,
                top_logprobs=[
                    response_text_delta_event.LogprobTopLogprob(
759
760
                        token=tl.token, logprob=tl.logprob
                    )
761
                    for tl in lg.top_logprobs
762
763
764
                ],
            )
            for lg in lgs
765
766
        ]

767
768
769
770
771
772
773
774
775
776
777
778
779
    def _make_response_output_items(
        self,
        request: ResponsesRequest,
        final_output: CompletionOutput,
        tokenizer: AnyTokenizer,
    ) -> list[ResponseOutputItem]:
        if self.reasoning_parser:
            try:
                reasoning_parser = self.reasoning_parser(tokenizer)
            except RuntimeError as e:
                logger.exception("Error in reasoning parser creation.")
                raise e

780
781
782
            reasoning_content, content = reasoning_parser.extract_reasoning_content(
                final_output.text, request=request
            )
783
784
785
786
        else:
            reasoning_content = None
            content = final_output.text

787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
        # Log complete response if output logging is enabled
        if self.enable_log_outputs and self.request_logger:
            output_text = ""
            if content:
                output_text = content
            elif reasoning_content:
                output_text = f"[reasoning: {reasoning_content}]"

            if output_text:
                self.request_logger.log_outputs(
                    request_id=request.request_id,
                    outputs=output_text,
                    output_token_ids=final_output.token_ids,
                    finish_reason=final_output.finish_reason,
                    is_streaming=False,
                    delta=False,
                )

805
806
807
808
809
810
811
        output = []
        if reasoning_content:
            reasoning_item = ResponseReasoningItem(
                id=f"rs_{random_uuid()}",
                summary=[],
                type="reasoning",
                content=[
812
813
814
                    ResponseReasoningTextContent(
                        text=reasoning_content, type="reasoning_text"
                    )
815
816
817
818
819
820
821
822
823
                ],
                status=None,  # NOTE: Only the last output item has status.
            )
            output.append(reasoning_item)
        if content:
            output_text = ResponseOutputText(
                text=content,
                annotations=[],  # TODO
                type="output_text",
824
825
826
827
828
829
830
831
832
833
                logprobs=(
                    self._create_response_logprobs(
                        token_ids=final_output.token_ids,
                        logprobs=final_output.logprobs,
                        tokenizer=tokenizer,
                        top_logprobs=request.top_logprobs,
                    )
                    if request.is_include_output_logprobs()
                    else None
                ),
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
            )
            message = ResponseOutputMessage(
                id=f"msg_{random_uuid()}",
                content=[output_text],
                role="assistant",
                status="completed",
                type="message",
            )
            output.append(message)
        return output

    def _make_response_output_items_with_harmony(
        self,
        context: HarmonyContext,
    ) -> list[ResponseOutputItem]:
849
        output_items: list[ResponseOutputItem] = []
850
851
852
853
854
855
856
857
858
        num_init_messages = context.num_init_messages
        for msg in context.messages[num_init_messages:]:
            output_items.extend(parse_output_message(msg))
        # Handle the generation stopped in the middle (if any).
        last_items = parse_remaining_state(context.parser)
        if last_items:
            output_items.extend(last_items)
        return output_items

859
860
861
    def _construct_input_messages(
        self,
        request: ResponsesRequest,
862
        prev_response: ResponsesResponse | None = None,
863
864
865
    ) -> list[ChatCompletionMessageParam]:
        messages: list[ChatCompletionMessageParam] = []
        if request.instructions:
866
867
868
869
870
871
            messages.append(
                {
                    "role": "system",
                    "content": request.instructions,
                }
            )
872
873
874
875
876
877
878
879
880
881
882
883

        # Prepend the conversation history.
        if prev_response is not None:
            # Add the previous messages.
            prev_msg = self.msg_store[prev_response.id]
            messages.extend(prev_msg)

            # Add the previous output.
            for output_item in prev_response.output:
                # NOTE: We skip the reasoning output.
                if isinstance(output_item, ResponseOutputMessage):
                    for content in output_item.content:
884
885
886
887
888
889
                        messages.append(
                            {
                                "role": "assistant",
                                "content": content.text,
                            }
                        )
890
891

        # Append the new input.
892
        # Responses API supports simple text inputs without chat format.
893
894
895
896
897
898
        if isinstance(request.input, str):
            messages.append({"role": "user", "content": request.input})
        else:
            messages.extend(request.input)  # type: ignore
        return messages

899
    def _construct_harmony_system_input_message(
900
        self, request: ResponsesRequest, with_custom_tools: bool, tool_types: set[str]
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
    ) -> OpenAIHarmonyMessage:
        reasoning_effort = request.reasoning.effort if request.reasoning else None
        enable_browser = (
            "web_search_preview" in tool_types
            and self.tool_server is not None
            and self.tool_server.has_tool("browser")
        )
        enable_code_interpreter = (
            "code_interpreter" in tool_types
            and self.tool_server is not None
            and self.tool_server.has_tool("python")
        )
        enable_container = (
            "container" in tool_types
            and self.tool_server is not None
            and self.tool_server.has_tool("container")
        )
        sys_msg = get_system_message(
            reasoning_effort=reasoning_effort,
            browser_description=(
                self.tool_server.get_tool_description("browser")
                if enable_browser and self.tool_server is not None
                else None
            ),
            python_description=(
                self.tool_server.get_tool_description("python")
                if enable_code_interpreter and self.tool_server is not None
                else None
            ),
            container_description=(
                self.tool_server.get_tool_description("container")
                if enable_container and self.tool_server is not None
                else None
            ),
            instructions=request.instructions,
            with_custom_tools=with_custom_tools,
        )
        return sys_msg

940
941
942
    def _construct_input_messages_with_harmony(
        self,
        request: ResponsesRequest,
943
        prev_response: ResponsesResponse | None,
944
945
946
947
    ) -> list[OpenAIHarmonyMessage]:
        messages: list[OpenAIHarmonyMessage] = []
        if prev_response is None:
            # New conversation.
948
            tool_types = extract_tool_types(request.tools)
949
            with_custom_tools = has_custom_tools(tool_types)
950
951
952

            sys_msg = self._construct_harmony_system_input_message(
                request, with_custom_tools, tool_types
953
954
            )
            messages.append(sys_msg)
955
956
            if with_custom_tools:
                dev_msg = get_developer_message(
957
958
                    instructions=request.instructions, tools=request.tools
                )
959
                messages.append(dev_msg)
960
961
            messages += construct_harmony_previous_input_messages(request)

962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
        else:
            # Continue the previous conversation.
            # FIXME(woosuk): Currently, request params like reasoning and
            # instructions are ignored.
            prev_msgs = self.msg_store[prev_response.id]
            # Remove the previous chain-of-thoughts if there is a new "final"
            # message. Note that this also removes these messages from the
            # msg_store.
            if len(prev_msgs) > 0:
                last_msg = prev_msgs[-1]
                assert isinstance(last_msg, OpenAIHarmonyMessage)
                if last_msg.channel == "final":
                    prev_final_msg_idx = -1
                    for i in range(len(prev_msgs) - 2, -1, -1):
                        prev_msg_i = prev_msgs[i]
                        assert isinstance(prev_msg_i, OpenAIHarmonyMessage)
                        if prev_msg_i.channel == "final":
                            prev_final_msg_idx = i
                            break
981
982
                    recent_turn_msgs = prev_msgs[prev_final_msg_idx + 1 :]
                    del prev_msgs[prev_final_msg_idx + 1 :]
983
984
985
986
987
988
                    for msg in recent_turn_msgs:
                        assert isinstance(msg, OpenAIHarmonyMessage)
                        if msg.channel != "analysis":
                            prev_msgs.append(msg)
            messages.extend(prev_msgs)
        # Append the new input.
co63oc's avatar
co63oc committed
989
        # Responses API supports simple text inputs without chat format.
990
991
992
993
994
995
996
997
        if isinstance(request.input, str):
            messages.append(get_user_message(request.input))
        else:
            if prev_response is not None:
                prev_outputs = copy(prev_response.output)
            else:
                prev_outputs = []
            for response_msg in request.input:
998
                messages.append(parse_response_input(response_msg, prev_outputs))
999
                # User passes in a tool call request and its output. We need
1000
1001
1002
                # to add the tool call request to prev_outputs so that the
                # parse_response_input can find the tool call request when
                # parsing the tool call output.
1003
1004
1005
1006
1007
                if (
                    isinstance(response_msg, dict)
                    and response_msg.get("type") == "function_call"
                ):
                    response_msg = ResponseFunctionToolCall.model_validate(response_msg)
1008
1009
1010
1011
                if isinstance(response_msg, ResponseFunctionToolCall):
                    prev_outputs.append(response_msg)
        return messages

1012
1013
1014
1015
1016
1017
    async def _run_background_request_stream(
        self,
        request: ResponsesRequest,
        *args,
        **kwargs,
    ):
1018
        event_deque: deque[StreamingResponsesResponse] = deque()
1019
1020
1021
1022
        new_event_signal = asyncio.Event()
        self.event_store[request.request_id] = (event_deque, new_event_signal)
        response = None
        try:
1023
            generator = self.responses_stream_generator(request, *args, **kwargs)
1024
1025
1026
1027
            async for event in generator:
                event_deque.append(event)
                new_event_signal.set()  # Signal new event available
        except Exception as e:
1028
            logger.exception("Background request failed for %s", request.request_id)
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
            response = self.create_error_response(str(e))
        finally:
            new_event_signal.set()

        if response is not None and isinstance(response, ErrorResponse):
            # If the request has failed, update the status to "failed".
            response_id = request.request_id
            async with self.response_store_lock:
                stored_response = self.response_store.get(response_id)
                assert stored_response is not None
                if stored_response.status not in ("completed", "cancelled"):
                    stored_response.status = "failed"

1042
1043
1044
1045
1046
1047
1048
    async def _run_background_request(
        self,
        request: ResponsesRequest,
        *args,
        **kwargs,
    ):
        try:
1049
            response = await self.responses_full_generator(request, *args, **kwargs)
1050
        except Exception as e:
1051
            logger.exception("Background request failed for %s", request.request_id)
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
            response = self.create_error_response(str(e))

        if isinstance(response, ErrorResponse):
            # If the request has failed, update the status to "failed".
            response_id = request.request_id
            async with self.response_store_lock:
                stored_response = self.response_store.get(response_id)
                assert stored_response is not None
                if stored_response.status not in ("completed", "cancelled"):
                    stored_response.status = "failed"

1063
1064
1065
    async def responses_background_stream_generator(
        self,
        response_id: str,
1066
        starting_after: int | None = None,
1067
    ) -> AsyncGenerator[StreamingResponsesResponse, None]:
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
        if response_id not in self.event_store:
            raise ValueError(f"Unknown response_id: {response_id}")

        event_deque, new_event_signal = self.event_store[response_id]
        start_index = 0 if starting_after is None else starting_after + 1
        current_index = start_index

        while True:
            new_event_signal.clear()

            # Yield existing events from start_index
            while current_index < len(event_deque):
                event = event_deque[current_index]
                yield event
1082
                if getattr(event, "type", "unknown") == "response.completed":
1083
                    return
1084
1085
1086
1087
                current_index += 1

            await new_event_signal.wait()

1088
1089
1090
    async def retrieve_responses(
        self,
        response_id: str,
1091
1092
1093
1094
1095
1096
1097
        starting_after: int | None,
        stream: bool | None,
    ) -> (
        ErrorResponse
        | ResponsesResponse
        | AsyncGenerator[StreamingResponsesResponse, None]
    ):
1098
1099
1100
1101
1102
        async with self.response_store_lock:
            response = self.response_store.get(response_id)

        if response is None:
            return self._make_not_found_error(response_id)
1103
1104
1105
1106
1107
1108

        if stream:
            return self.responses_background_stream_generator(
                response_id,
                starting_after,
            )
1109
1110
1111
1112
1113
        return response

    async def cancel_responses(
        self,
        response_id: str,
1114
    ) -> ErrorResponse | ResponsesResponse:
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
        async with self.response_store_lock:
            response = self.response_store.get(response_id)
            if response is None:
                return self._make_not_found_error(response_id)

            prev_status = response.status
            if prev_status not in ("queued", "in_progress"):
                return self.create_error_response(
                    err_type="invalid_request_error",
                    message="Cannot cancel a synchronous response.",
                )

            # Update the status to "cancelled".
            response.status = "cancelled"

        # Abort the request.
1131
        if task := self.background_tasks.get(response_id):
1132
1133
1134
1135
            task.cancel()
            try:
                await task
            except asyncio.CancelledError:
1136
                logger.exception("Background task for %s was cancelled", response_id)
1137
1138
1139
1140
1141
1142
1143
1144
        return response

    def _make_not_found_error(self, response_id: str) -> ErrorResponse:
        return self.create_error_response(
            err_type="invalid_request_error",
            message=f"Response with id '{response_id}' not found.",
            status_code=HTTPStatus.NOT_FOUND,
        )
1145
1146
1147
1148

    def _make_store_not_supported_error(self) -> ErrorResponse:
        return self.create_error_response(
            err_type="invalid_request_error",
1149
1150
1151
1152
1153
1154
            message=(
                "`store=True` (default) is not supported. Please set "
                "`store=False` in Responses API or set "
                "`VLLM_ENABLE_RESPONSES_API_STORE=1` in the env var when "
                "starting the vLLM server."
            ),
1155
1156
            status_code=HTTPStatus.BAD_REQUEST,
        )
1157

1158
    async def _process_simple_streaming_events(
1159
1160
1161
        self,
        request: ResponsesRequest,
        sampling_params: SamplingParams,
1162
        result_generator: AsyncIterator[ConversationContext | None],
1163
1164
1165
1166
        context: ConversationContext,
        model_name: str,
        tokenizer: AnyTokenizer,
        request_metadata: RequestResponseMetadata,
1167
        created_time: int,
1168
        _increment_sequence_number_and_return: Callable[
1169
1170
            [StreamingResponsesResponse], StreamingResponsesResponse
        ],
1171
    ) -> AsyncGenerator[StreamingResponsesResponse, None]:
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
        current_content_index = 0
        current_output_index = 0
        current_item_id = ""
        reasoning_parser = None
        if self.reasoning_parser:
            reasoning_parser = self.reasoning_parser(tokenizer)
        previous_text = ""
        previous_token_ids: list[int] = []
        first_delta_sent = False
        previous_delta_messages: list[DeltaMessage] = []
        async for ctx in result_generator:
            assert isinstance(ctx, SimpleContext)
            if ctx.last_output is None:
                continue
            if ctx.last_output.outputs:
                output = ctx.last_output.outputs[0]
                if reasoning_parser:
1189
                    delta_message = (
1190
                        reasoning_parser.extract_reasoning_content_streaming(
1191
1192
1193
1194
1195
1196
1197
                            previous_text=previous_text,
                            current_text=previous_text + output.text,
                            delta_text=output.text,
                            previous_token_ids=previous_token_ids,
                            current_token_ids=previous_token_ids + output.token_ids,
                            delta_token_ids=output.token_ids,
                        )
1198
1199
                    )
                else:
1200
1201
1202
                    delta_message = DeltaMessage(
                        content=output.text,
                    )
1203
1204
1205
1206
1207
1208
1209
                previous_text += output.text
                previous_token_ids += output.token_ids
                if not delta_message:
                    continue
                if not first_delta_sent:
                    current_item_id = str(uuid.uuid4())
                    if delta_message.reasoning_content:
1210
                        yield _increment_sequence_number_and_return(
1211
1212
1213
1214
                            ResponseOutputItemAddedEvent(
                                type="response.output_item.added",
                                sequence_number=-1,
                                output_index=current_output_index,
1215
                                item=ResponseReasoningItem(
1216
1217
1218
1219
1220
                                    type="reasoning",
                                    id=current_item_id,
                                    summary=[],
                                    status="in_progress",
                                ),
1221
1222
                            )
                        )
1223
                    else:
1224
                        yield _increment_sequence_number_and_return(
1225
1226
1227
1228
                            ResponseOutputItemAddedEvent(
                                type="response.output_item.added",
                                sequence_number=-1,
                                output_index=current_output_index,
1229
                                item=ResponseOutputMessage(
1230
1231
1232
1233
1234
1235
                                    id=current_item_id,
                                    type="message",
                                    role="assistant",
                                    content=[],
                                    status="in_progress",
                                ),
1236
1237
                            )
                        )
1238
                    yield _increment_sequence_number_and_return(
1239
                        ResponseContentPartAddedEvent(
1240
1241
1242
1243
1244
                            type="response.content_part.added",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
                            content_index=current_content_index,
1245
                            part=ResponseOutputText(
1246
1247
1248
1249
1250
                                type="output_text",
                                text="",
                                annotations=[],
                                logprobs=[],
                            ),
1251
1252
                        )
                    )
1253
1254
1255
1256
1257
1258
                    current_content_index += 1
                    first_delta_sent = True
                # todo(kebe7jun) tool call support

                # check delta message and previous delta message are
                # same as content or reasoning content
1259
1260
1261
1262
1263
                if (
                    previous_delta_messages
                    and previous_delta_messages[-1].reasoning_content is not None
                    and delta_message.content is not None
                ):
1264
1265
                    # from reasoning to normal content, send done
                    # event for reasoning
1266
1267
1268
1269
1270
                    reason_content = "".join(
                        pm.reasoning_content
                        for pm in previous_delta_messages
                        if pm.reasoning_content is not None
                    )
1271
                    yield _increment_sequence_number_and_return(
1272
1273
1274
1275
1276
1277
1278
                        ResponseReasoningTextDoneEvent(
                            type="response.reasoning_text.done",
                            item_id=current_item_id,
                            sequence_number=-1,
                            output_index=current_output_index,
                            content_index=current_content_index,
                            text=reason_content,
1279
1280
                        )
                    )
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
                    current_content_index = 0
                    reasoning_item = ResponseReasoningItem(
                        type="reasoning",
                        content=[
                            ResponseReasoningTextContent(
                                text=reason_content,
                                type="reasoning_text",
                            ),
                        ],
                        status="completed",
                        id=current_item_id,
                        summary=[],
                    )
1294
                    yield _increment_sequence_number_and_return(
1295
1296
1297
1298
1299
                        ResponseOutputItemDoneEvent(
                            type="response.output_item.done",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item=reasoning_item,
1300
1301
                        )
                    )
1302
                    yield _increment_sequence_number_and_return(
1303
                        ResponseOutputItemAddedEvent(
1304
1305
1306
                            type="response.output_item.added",
                            sequence_number=-1,
                            output_index=current_output_index,
1307
                            item=ResponseOutputMessage(
1308
1309
1310
1311
1312
1313
                                id=current_item_id,
                                type="message",
                                role="assistant",
                                content=[],
                                status="in_progress",
                            ),
1314
1315
                        )
                    )
1316
1317
                    current_output_index += 1
                    current_item_id = str(uuid.uuid4())
1318
                    yield _increment_sequence_number_and_return(
1319
                        ResponseContentPartAddedEvent(
1320
1321
1322
1323
1324
                            type="response.content_part.added",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
                            content_index=current_content_index,
1325
                            part=ResponseOutputText(
1326
1327
1328
1329
1330
                                type="output_text",
                                text="",
                                annotations=[],
                                logprobs=[],
                            ),
1331
1332
                        )
                    )
1333
1334
1335
                    current_content_index += 1
                    # reset previous delta messages
                    previous_delta_messages = []
1336

1337
                if delta_message.reasoning_content is not None:
1338
                    yield _increment_sequence_number_and_return(
1339
1340
1341
1342
1343
1344
1345
                        ResponseReasoningTextDeltaEvent(
                            type="response.reasoning_text.delta",
                            sequence_number=-1,
                            content_index=current_content_index,
                            output_index=current_output_index,
                            item_id=current_item_id,
                            delta=delta_message.reasoning_content,
1346
1347
                        )
                    )
1348
                elif delta_message.content is not None:
1349
                    yield _increment_sequence_number_and_return(
1350
                        ResponseTextDeltaEvent(
1351
1352
1353
1354
1355
1356
                            type="response.output_text.delta",
                            sequence_number=-1,
                            content_index=current_content_index,
                            output_index=current_output_index,
                            item_id=current_item_id,
                            delta=delta_message.content,
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
                            logprobs=(
                                self._create_stream_response_logprobs(
                                    token_ids=output.token_ids,
                                    logprobs=output.logprobs,
                                    tokenizer=tokenizer,
                                    top_logprobs=request.top_logprobs,
                                )
                                if request.is_include_output_logprobs()
                                else []
                            ),
1367
1368
                        )
                    )
1369
1370
1371
1372
1373
                current_content_index += 1

                previous_delta_messages.append(delta_message)
        if previous_delta_messages:
            if previous_delta_messages[-1].reasoning_content is not None:
1374
1375
1376
1377
1378
                reason_content = "".join(
                    pm.reasoning_content
                    for pm in previous_delta_messages
                    if pm.reasoning_content is not None
                )
1379
                yield _increment_sequence_number_and_return(
1380
1381
1382
1383
1384
1385
1386
                    ResponseReasoningTextDoneEvent(
                        type="response.reasoning_text.done",
                        item_id=current_item_id,
                        sequence_number=-1,
                        output_index=current_output_index,
                        content_index=current_content_index,
                        text=reason_content,
1387
1388
                    )
                )
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
                current_content_index += 1
                reasoning_item = ResponseReasoningItem(
                    type="reasoning",
                    content=[
                        ResponseReasoningTextContent(
                            text=reason_content,
                            type="reasoning_text",
                        ),
                    ],
                    status="completed",
                    id=current_item_id,
                    summary=[],
                )
1402
                yield _increment_sequence_number_and_return(
1403
1404
1405
1406
1407
                    ResponseOutputItemDoneEvent(
                        type="response.output_item.done",
                        sequence_number=-1,
                        output_index=current_output_index,
                        item=reasoning_item,
1408
1409
                    )
                )
1410
            elif previous_delta_messages[-1].content is not None:
1411
1412
1413
1414
1415
                final_content = "".join(
                    pm.content
                    for pm in previous_delta_messages
                    if pm.content is not None
                )
1416
                yield _increment_sequence_number_and_return(
1417
                    ResponseTextDoneEvent(
1418
1419
1420
1421
1422
1423
1424
                        type="response.output_text.done",
                        sequence_number=-1,
                        output_index=current_output_index,
                        content_index=current_content_index,
                        text=final_content,
                        logprobs=[],
                        item_id=current_item_id,
1425
1426
                    )
                )
1427
1428
1429
1430
1431
1432
                current_content_index += 1
                part = ResponseOutputText(
                    text=final_content,
                    type="output_text",
                    annotations=[],
                )
1433
                yield _increment_sequence_number_and_return(
1434
                    ResponseContentPartDoneEvent(
1435
1436
1437
1438
1439
1440
                        type="response.content_part.done",
                        sequence_number=-1,
                        item_id=current_item_id,
                        output_index=current_output_index,
                        content_index=current_content_index,
                        part=part,
1441
1442
                    )
                )
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
                current_content_index += 1
                item = ResponseOutputMessage(
                    type="message",
                    role="assistant",
                    content=[
                        part,
                    ],
                    status="completed",
                    id=current_item_id,
                    summary=[],
                )
1454
                yield _increment_sequence_number_and_return(
1455
1456
1457
1458
1459
                    ResponseOutputItemDoneEvent(
                        type="response.output_item.done",
                        sequence_number=-1,
                        output_index=current_output_index,
                        item=item,
1460
1461
                    )
                )
1462
1463
1464
1465
1466

    async def _process_harmony_streaming_events(
        self,
        request: ResponsesRequest,
        sampling_params: SamplingParams,
1467
        result_generator: AsyncIterator[ConversationContext | None],
1468
1469
1470
1471
1472
        context: ConversationContext,
        model_name: str,
        tokenizer: AnyTokenizer,
        request_metadata: RequestResponseMetadata,
        created_time: int,
1473
        _increment_sequence_number_and_return: Callable[
1474
1475
            [StreamingResponsesResponse], StreamingResponsesResponse
        ],
1476
    ) -> AsyncGenerator[StreamingResponsesResponse, None]:
1477
        current_content_index = -1
1478
        current_output_index = 0
1479
        current_item_id: str = ""
1480
        sent_output_item_added = False
1481
        is_first_function_call_delta = False
1482
1483
1484
1485
1486
1487
        async for ctx in result_generator:
            assert isinstance(ctx, StreamingHarmonyContext)

            if ctx.is_expecting_start():
                current_output_index += 1
                sent_output_item_added = False
1488
                is_first_function_call_delta = False
1489
1490
1491
                if len(ctx.parser.messages) > 0:
                    previous_item = ctx.parser.messages[-1]
                    if previous_item.recipient is not None:
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
                        # Deal with tool call
                        if previous_item.recipient.startswith("functions."):
                            function_name = previous_item.recipient[len("functions.") :]
                            yield _increment_sequence_number_and_return(
                                ResponseFunctionCallArgumentsDoneEvent(
                                    type="response.function_call_arguments.done",
                                    arguments=previous_item.content[0].text,
                                    name=function_name,
                                    item_id=current_item_id,
                                    output_index=current_output_index,
                                    sequence_number=-1,
                                )
                            )
                            function_call_item = ResponseFunctionToolCall(
                                type="function_call",
                                arguments=previous_item.content[0].text,
                                name=function_name,
                                item_id=current_item_id,
                                output_index=current_output_index,
                                sequence_number=-1,
                                call_id=f"fc_{random_uuid()}",
                                status="completed",
                            )
                            yield _increment_sequence_number_and_return(
                                ResponseOutputItemDoneEvent(
                                    type="response.output_item.done",
                                    sequence_number=-1,
                                    output_index=current_output_index,
                                    item=function_call_item,
                                )
                            )
1523
                    elif previous_item.channel == "analysis":
1524
1525
1526
1527
                        content = ResponseReasoningTextContent(
                            text=previous_item.content[0].text,
                            type="reasoning_text",
                        )
1528
1529
                        reasoning_item = ResponseReasoningItem(
                            type="reasoning",
1530
                            content=[content],
1531
                            status="completed",
1532
1533
                            id=current_item_id,
                            summary=[],
1534
                        )
1535
                        yield _increment_sequence_number_and_return(
1536
1537
1538
1539
1540
1541
1542
                            ResponseReasoningTextDoneEvent(
                                type="response.reasoning_text.done",
                                item_id=current_item_id,
                                sequence_number=-1,
                                output_index=current_output_index,
                                content_index=current_content_index,
                                text=previous_item.content[0].text,
1543
1544
                            )
                        )
1545
1546
1547
1548
1549
1550
1551
1552
                        yield _increment_sequence_number_and_return(
                            ResponseReasoningPartDoneEvent(
                                type="response.reasoning_part.done",
                                sequence_number=-1,
                                item_id=current_item_id,
                                output_index=current_output_index,
                                content_index=current_content_index,
                                part=content,
1553
1554
                            )
                        )
1555
                        yield _increment_sequence_number_and_return(
1556
1557
1558
1559
1560
                            ResponseOutputItemDoneEvent(
                                type="response.output_item.done",
                                sequence_number=-1,
                                output_index=current_output_index,
                                item=reasoning_item,
1561
1562
                            )
                        )
1563
1564
1565
1566
1567
1568
                    elif previous_item.channel == "final":
                        text_content = ResponseOutputText(
                            type="output_text",
                            text=previous_item.content[0].text,
                            annotations=[],
                        )
1569
                        yield _increment_sequence_number_and_return(
1570
                            ResponseTextDoneEvent(
1571
1572
1573
1574
1575
1576
1577
                                type="response.output_text.done",
                                sequence_number=-1,
                                output_index=current_output_index,
                                content_index=current_content_index,
                                text=previous_item.content[0].text,
                                logprobs=[],
                                item_id=current_item_id,
1578
1579
                            )
                        )
1580
                        yield _increment_sequence_number_and_return(
1581
1582
1583
1584
1585
1586
1587
                            ResponseContentPartDoneEvent(
                                type="response.content_part.done",
                                sequence_number=-1,
                                item_id=current_item_id,
                                output_index=current_output_index,
                                content_index=current_content_index,
                                part=text_content,
1588
1589
                            )
                        )
1590
                        yield _increment_sequence_number_and_return(
1591
                            ResponseOutputItemDoneEvent(
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
                                type="response.output_item.done",
                                sequence_number=-1,
                                output_index=current_output_index,
                                item=ResponseOutputMessage(
                                    id=current_item_id,
                                    type="message",
                                    role="assistant",
                                    content=[text_content],
                                    status="completed",
                                ),
1602
1603
                            )
                        )
1604

1605
            # stream the output of a harmony message
1606
            if ctx.parser.last_content_delta:
1607
1608
1609
1610
                if (
                    ctx.parser.current_channel == "final"
                    and ctx.parser.current_recipient is None
                ):
1611
1612
                    if not sent_output_item_added:
                        sent_output_item_added = True
1613
                        current_item_id = f"msg_{random_uuid()}"
1614
                        yield _increment_sequence_number_and_return(
1615
1616
1617
1618
                            ResponseOutputItemAddedEvent(
                                type="response.output_item.added",
                                sequence_number=-1,
                                output_index=current_output_index,
1619
                                item=ResponseOutputMessage(
1620
1621
1622
1623
1624
1625
                                    id=current_item_id,
                                    type="message",
                                    role="assistant",
                                    content=[],
                                    status="in_progress",
                                ),
1626
1627
                            )
                        )
1628
                        current_content_index += 1
1629
                        yield _increment_sequence_number_and_return(
1630
1631
1632
1633
1634
1635
                            ResponseContentPartAddedEvent(
                                type="response.content_part.added",
                                sequence_number=-1,
                                output_index=current_output_index,
                                item_id=current_item_id,
                                content_index=current_content_index,
1636
                                part=ResponseOutputText(
1637
1638
1639
1640
1641
                                    type="output_text",
                                    text="",
                                    annotations=[],
                                    logprobs=[],
                                ),
1642
1643
                            )
                        )
1644
                    yield _increment_sequence_number_and_return(
1645
                        ResponseTextDeltaEvent(
1646
1647
1648
1649
1650
1651
1652
1653
                            type="response.output_text.delta",
                            sequence_number=-1,
                            content_index=current_content_index,
                            output_index=current_output_index,
                            item_id=current_item_id,
                            delta=ctx.parser.last_content_delta,
                            # TODO, use logprobs from ctx.last_request_output
                            logprobs=[],
1654
1655
1656
1657
1658
1659
                        )
                    )
                elif (
                    ctx.parser.current_channel == "analysis"
                    and ctx.parser.current_recipient is None
                ):
1660
1661
                    if not sent_output_item_added:
                        sent_output_item_added = True
1662
                        current_item_id = f"msg_{random_uuid()}"
1663
                        yield _increment_sequence_number_and_return(
1664
1665
1666
1667
                            ResponseOutputItemAddedEvent(
                                type="response.output_item.added",
                                sequence_number=-1,
                                output_index=current_output_index,
1668
                                item=ResponseReasoningItem(
1669
1670
1671
1672
1673
                                    type="reasoning",
                                    id=current_item_id,
                                    summary=[],
                                    status="in_progress",
                                ),
1674
1675
                            )
                        )
1676
                        current_content_index += 1
1677
                        yield _increment_sequence_number_and_return(
1678
1679
                            ResponseReasoningPartAddedEvent(
                                type="response.reasoning_part.added",
1680
1681
1682
1683
                                sequence_number=-1,
                                output_index=current_output_index,
                                item_id=current_item_id,
                                content_index=current_content_index,
1684
                                part=ResponseReasoningTextContent(
1685
                                    text="",
1686
                                    type="reasoning_text",
1687
                                ),
1688
1689
                            )
                        )
1690
                    yield _increment_sequence_number_and_return(
1691
1692
1693
1694
1695
1696
1697
                        ResponseReasoningTextDeltaEvent(
                            type="response.reasoning_text.delta",
                            item_id=current_item_id,
                            output_index=current_output_index,
                            content_index=current_content_index,
                            delta=ctx.parser.last_content_delta,
                            sequence_number=-1,
1698
1699
                        )
                    )
1700
1701
1702
                # built-in tools will be triggered on the analysis channel
                # However, occasionally built-in tools will
                # still be output to commentary.
1703
1704
1705
1706
                elif (
                    ctx.parser.current_channel == "commentary"
                    or ctx.parser.current_channel == "analysis"
                ) and ctx.parser.current_recipient == "python":
1707
1708
                    if not sent_output_item_added:
                        sent_output_item_added = True
1709
                        current_item_id = f"tool_{random_uuid()}"
1710
                        yield _increment_sequence_number_and_return(
1711
1712
1713
1714
                            ResponseOutputItemAddedEvent(
                                type="response.output_item.added",
                                sequence_number=-1,
                                output_index=current_output_index,
1715
                                item=ResponseCodeInterpreterToolCallParam(
1716
1717
1718
1719
1720
1721
1722
                                    type="code_interpreter_call",
                                    id=current_item_id,
                                    code=None,
                                    container_id="auto",
                                    outputs=None,
                                    status="in_progress",
                                ),
1723
1724
                            )
                        )
1725
                        yield _increment_sequence_number_and_return(
1726
                            ResponseCodeInterpreterCallInProgressEvent(
1727
                                type="response.code_interpreter_call.in_progress",
1728
1729
1730
                                sequence_number=-1,
                                output_index=current_output_index,
                                item_id=current_item_id,
1731
1732
                            )
                        )
1733
                    yield _increment_sequence_number_and_return(
1734
1735
1736
1737
1738
1739
                        ResponseCodeInterpreterCallCodeDeltaEvent(
                            type="response.code_interpreter_call_code.delta",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
                            delta=ctx.parser.last_content_delta,
1740
1741
                        )
                    )
1742
1743

            # stream tool call outputs
1744
1745
            if ctx.is_assistant_action_turn() and len(ctx.parser.messages) > 0:
                previous_item = ctx.parser.messages[-1]
1746
1747
1748
1749
1750
1751
1752
                if (
                    self.tool_server is not None
                    and self.tool_server.has_tool("browser")
                    and previous_item.recipient is not None
                    and previous_item.recipient.startswith("browser.")
                ):
                    function_name = previous_item.recipient[len("browser.") :]
1753
1754
1755
                    action = None
                    parsed_args = json.loads(previous_item.content[0].text)
                    if function_name == "search":
1756
                        action = response_function_web_search.ActionSearch(
1757
1758
                            type="search",
                            query=parsed_args["query"],
1759
                        )
1760
                    elif function_name == "open":
1761
1762
1763
1764
1765
                        action = response_function_web_search.ActionOpenPage(
                            type="open_page",
                            # TODO: translate to url
                            url=f"cursor:{parsed_args.get('cursor', '')}",
                        )
1766
                    elif function_name == "find":
1767
1768
1769
1770
1771
1772
                        action = response_function_web_search.ActionFind(
                            type="find",
                            pattern=parsed_args["pattern"],
                            # TODO: translate to url
                            url=f"cursor:{parsed_args.get('cursor', '')}",
                        )
1773
                    else:
1774
                        raise ValueError(f"Unknown function name: {function_name}")
1775

1776
                    current_item_id = f"tool_{random_uuid()}"
1777
                    yield _increment_sequence_number_and_return(
1778
                        ResponseOutputItemAddedEvent(
1779
1780
1781
                            type="response.output_item.added",
                            sequence_number=-1,
                            output_index=current_output_index,
1782
                            item=response_function_web_search.ResponseFunctionWebSearch(
1783
1784
1785
1786
1787
1788
                                # TODO: generate a unique id for web search call
                                type="web_search_call",
                                id=current_item_id,
                                action=action,
                                status="in_progress",
                            ),
1789
1790
                        )
                    )
1791
                    yield _increment_sequence_number_and_return(
1792
1793
1794
1795
1796
                        ResponseWebSearchCallInProgressEvent(
                            type="response.web_search_call.in_progress",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
1797
1798
                        )
                    )
1799
                    yield _increment_sequence_number_and_return(
1800
1801
1802
1803
1804
                        ResponseWebSearchCallSearchingEvent(
                            type="response.web_search_call.searching",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
1805
1806
                        )
                    )
1807
1808

                    # enqueue
1809
                    yield _increment_sequence_number_and_return(
1810
1811
1812
1813
1814
                        ResponseWebSearchCallCompletedEvent(
                            type="response.web_search_call.completed",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
1815
1816
                        )
                    )
1817
                    yield _increment_sequence_number_and_return(
1818
                        ResponseOutputItemDoneEvent(
1819
1820
1821
                            type="response.output_item.done",
                            sequence_number=-1,
                            output_index=current_output_index,
1822
                            item=ResponseFunctionWebSearch(
1823
1824
1825
1826
1827
                                type="web_search_call",
                                id=current_item_id,
                                action=action,
                                status="completed",
                            ),
1828
1829
                        )
                    )
1830

1831
1832
1833
1834
1835
1836
                if (
                    self.tool_server is not None
                    and self.tool_server.has_tool("python")
                    and previous_item.recipient is not None
                    and previous_item.recipient.startswith("python")
                ):
1837
                    yield _increment_sequence_number_and_return(
1838
1839
1840
1841
1842
                        ResponseCodeInterpreterCallCodeDoneEvent(
                            type="response.code_interpreter_call_code.done",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
1843
                            code=previous_item.content[0].text,
1844
1845
                        )
                    )
1846
                    yield _increment_sequence_number_and_return(
1847
1848
1849
1850
1851
                        ResponseCodeInterpreterCallInterpretingEvent(
                            type="response.code_interpreter_call.interpreting",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
1852
1853
                        )
                    )
1854
                    yield _increment_sequence_number_and_return(
1855
1856
1857
1858
1859
                        ResponseCodeInterpreterCallCompletedEvent(
                            type="response.code_interpreter_call.completed",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item_id=current_item_id,
1860
1861
                        )
                    )
1862
                    yield _increment_sequence_number_and_return(
1863
                        ResponseOutputItemDoneEvent(
1864
1865
1866
                            type="response.output_item.done",
                            sequence_number=-1,
                            output_index=current_output_index,
1867
                            item=ResponseCodeInterpreterToolCallParam(
1868
1869
1870
1871
1872
1873
1874
1875
                                type="code_interpreter_call",
                                id=current_item_id,
                                code=previous_item.content[0].text,
                                container_id="auto",
                                # TODO: add outputs here
                                outputs=[],
                                status="completed",
                            ),
1876
1877
                        )
                    )
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
1888
1889
1890
1891
1892
1893
1894
1895
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
            # developer tools will be triggered on the commentary channel
            # and recipient starts with "functions.TOOL_NAME"
            if (
                ctx.parser.current_channel == "commentary"
                and ctx.parser.current_recipient
                and ctx.parser.current_recipient.startswith("functions.")
            ):
                if is_first_function_call_delta is False:
                    is_first_function_call_delta = True
                    fc_name = ctx.parser.current_recipient[len("functions.") :]
                    tool_call_item = ResponseFunctionToolCall(
                        name=fc_name,
                        type="function_call",
                        id=current_item_id,
                        call_id=f"call_{random_uuid()}",
                        arguments="",
                        status="in_progress",
                    )
                    current_item_id = f"fc_{random_uuid()}"
                    yield _increment_sequence_number_and_return(
                        ResponseOutputItemAddedEvent(
                            type="response.output_item.added",
                            sequence_number=-1,
                            output_index=current_output_index,
                            item=tool_call_item,
                        )
                    )
                else:
                    yield _increment_sequence_number_and_return(
                        ResponseFunctionCallArgumentsDeltaEvent(
                            item_id=current_item_id,
                            delta=ctx.parser.last_content_delta,
                            output_index=current_output_index,
                            sequence_number=-1,
                            type="response.function_call_arguments.delta",
                        )
                    )
1915

1916
1917
1918
1919
    async def responses_stream_generator(
        self,
        request: ResponsesRequest,
        sampling_params: SamplingParams,
1920
        result_generator: AsyncIterator[ConversationContext | None],
1921
1922
1923
1924
        context: ConversationContext,
        model_name: str,
        tokenizer: AnyTokenizer,
        request_metadata: RequestResponseMetadata,
1925
        created_time: int | None = None,
1926
    ) -> AsyncGenerator[StreamingResponsesResponse, None]:
1927
1928
1929
1930
1931
        # TODO:
        # 1. Handle disconnect

        created_time = created_time or int(time.time())

1932
1933
        sequence_number = 0

1934
        def _increment_sequence_number_and_return(
1935
            event: StreamingResponsesResponse,
1936
        ) -> StreamingResponsesResponse:
1937
1938
            nonlocal sequence_number
            # Set sequence_number if the event has this attribute
1939
            if hasattr(event, "sequence_number"):
1940
1941
                event.sequence_number = sequence_number
            sequence_number += 1
1942
            return event
1943

1944
        async with AsyncExitStack() as exit_stack:
1945
1946
            processer = None
            if self.use_harmony:
1947
1948
                # TODO: in streaming, we noticed this bug:
                # https://github.com/vllm-project/vllm/issues/25697
1949
                await self._initialize_tool_sessions(request, context, exit_stack)
1950
1951
1952
                processer = self._process_harmony_streaming_events
            else:
                processer = self._process_simple_streaming_events
1953
            # TODO Hanchen make sampling params to include the structural tag
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963

            initial_response = ResponsesResponse.from_request(
                request,
                sampling_params,
                model_name=model_name,
                created_time=created_time,
                output=[],
                status="in_progress",
                usage=None,
            ).model_dump()
1964
            yield _increment_sequence_number_and_return(
1965
1966
1967
1968
                ResponseCreatedEvent(
                    type="response.created",
                    sequence_number=-1,
                    response=initial_response,
1969
1970
                )
            )
1971
            yield _increment_sequence_number_and_return(
1972
1973
1974
1975
                ResponseInProgressEvent(
                    type="response.in_progress",
                    sequence_number=-1,
                    response=initial_response,
1976
1977
                )
            )
1978

1979
            async for event_data in processer(
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
                request,
                sampling_params,
                result_generator,
                context,
                model_name,
                tokenizer,
                request_metadata,
                created_time,
                _increment_sequence_number_and_return,
            ):
1990
                yield event_data
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007

            async def empty_async_generator():
                # A hack to trick Python to think this is a generator but
                # in fact it immediately returns.
                if False:
                    yield

            final_response = await self.responses_full_generator(
                request,
                sampling_params,
                empty_async_generator(),
                context,
                model_name,
                tokenizer,
                request_metadata,
                created_time=created_time,
            )
2008
            yield _increment_sequence_number_and_return(
2009
                ResponseCompletedEvent(
2010
2011
                    type="response.completed",
                    sequence_number=-1,
2012
                    response=final_response,
2013
2014
                )
            )