mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 11:56:44 +08:00
f36a388ffe
* fix response processsors * fix ci * fix ut --------- Co-authored-by: YuBaoku <49938469+EmmonsCurse@users.noreply.github.com>
150 lines
7.1 KiB
Python
150 lines
7.1 KiB
Python
"""
|
|
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License"
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
"""
|
|
|
|
from typing import Any, List, Optional
|
|
|
|
from fastdeploy.input.tokenzier_client import AsyncTokenizerClient, ImageDecodeRequest
|
|
from fastdeploy.utils import api_server_logger
|
|
|
|
|
|
class ChatResponseProcessor:
|
|
"""
|
|
A decoder class to build multimodal content (text/image) from token_ids.
|
|
|
|
Attributes:
|
|
eoi_token_id: Token ID indicating the end of an image (<eoi>).
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
data_processor,
|
|
enable_mm_output: Optional[bool] = False,
|
|
eoi_token_id: Optional[int] = 101032,
|
|
eos_token_id: Optional[int] = 2,
|
|
decoder_base_url: Optional[str] = None,
|
|
):
|
|
self.data_processor = data_processor
|
|
self.enable_mm_output = enable_mm_output
|
|
self.eoi_token_id = eoi_token_id
|
|
self.eos_token_id = eos_token_id
|
|
if decoder_base_url is not None:
|
|
self.decoder_client = AsyncTokenizerClient(base_url=decoder_base_url)
|
|
else:
|
|
self.decoder_client = None
|
|
self._mm_buffer: List[Any] = [] # Buffer for accumulating image token_ids
|
|
self._end_image_code_request_output: Optional[Any] = None
|
|
self._multipart_buffer = []
|
|
|
|
def enable_multimodal_content(self):
|
|
return self.enable_mm_output
|
|
|
|
def accumulate_token_ids(self, request_output):
|
|
decode_type = request_output["outputs"].get("decode_type", 0)
|
|
|
|
if not self._multipart_buffer:
|
|
self._multipart_buffer.append({"decode_type": decode_type, "request_output": request_output})
|
|
else:
|
|
last_part = self._multipart_buffer[-1]
|
|
|
|
if last_part["decode_type"] == decode_type:
|
|
last_token_ids = last_part["request_output"]["outputs"]["token_ids"]
|
|
last_token_ids.extend(request_output["outputs"]["token_ids"])
|
|
request_output["outputs"]["token_ids"] = last_token_ids
|
|
last_part["request_output"] = request_output
|
|
else:
|
|
self._multipart_buffer.append({"decode_type": decode_type, "request_output": request_output})
|
|
|
|
async def process_response_chat(self, request_outputs, stream, enable_thinking, include_stop_str_in_output):
|
|
"""
|
|
Process a list of responses into a generator that yields each processed response as it's generated.
|
|
Args:
|
|
request_outputs: The list of outputs to be processed.
|
|
stream: Whether or not to stream the output.
|
|
enable_thinking: Whether or not to show thinking messages.
|
|
include_stop_str_in_output: Whether or not to include stop strings in the output.
|
|
"""
|
|
for request_output in request_outputs:
|
|
api_server_logger.debug(f"request_output {request_output}")
|
|
if not self.enable_mm_output:
|
|
yield self.data_processor.process_response_dict(
|
|
response_dict=request_output,
|
|
stream=stream,
|
|
enable_thinking=enable_thinking,
|
|
include_stop_str_in_output=include_stop_str_in_output,
|
|
)
|
|
elif stream:
|
|
decode_type = request_output["outputs"].get("decode_type", 0)
|
|
token_ids = request_output["outputs"]["token_ids"]
|
|
if decode_type == 0:
|
|
if self.eoi_token_id and self.eoi_token_id in token_ids:
|
|
if self._mm_buffer:
|
|
all_tokens = self._mm_buffer
|
|
self._mm_buffer = []
|
|
image = {"type": "image"}
|
|
if self.decoder_client:
|
|
req_id = request_output["request_id"]
|
|
image_ret = await self.decoder_client.decode_image(
|
|
request=ImageDecodeRequest(req_id=req_id, data=all_tokens)
|
|
)
|
|
image["url"] = image_ret["http_url"]
|
|
image_output = self._end_image_code_request_output
|
|
image_output["outputs"]["multipart"] = [image]
|
|
image_output["outputs"]["token_ids"] = all_tokens
|
|
yield image_output
|
|
|
|
self.data_processor.process_response_dict(
|
|
response_dict=request_output,
|
|
stream=stream,
|
|
enable_thinking=enable_thinking,
|
|
include_stop_str_in_output=include_stop_str_in_output,
|
|
)
|
|
text = {"type": "text", "text": request_output["outputs"]["text"]}
|
|
request_output["outputs"]["multipart"] = [text]
|
|
yield request_output
|
|
|
|
elif decode_type == 1:
|
|
self._mm_buffer.append(token_ids)
|
|
self._end_image_code_request_output = request_output
|
|
else:
|
|
self.accumulate_token_ids(request_output)
|
|
token_ids = request_output["outputs"]["token_ids"]
|
|
if token_ids[-1] == self.eos_token_id:
|
|
multipart = []
|
|
for part in self._multipart_buffer:
|
|
if part["decode_type"] == 0:
|
|
self.data_processor.process_response_dict(
|
|
response_dict=part["request_output"],
|
|
stream=False,
|
|
enable_thinking=enable_thinking,
|
|
include_stop_str_in_output=include_stop_str_in_output,
|
|
)
|
|
text = {"type": "text", "text": part["request_output"]["outputs"]["text"]}
|
|
multipart.append(text)
|
|
elif part["decode_type"] == 1:
|
|
image = {"type": "image"}
|
|
if self.decoder_client:
|
|
req_id = part["request_output"]["request_id"]
|
|
all_tokens = part["request_output"]["outputs"]["token_ids"]
|
|
image_ret = await self.decoder_client.decode_image(
|
|
request=ImageDecodeRequest(req_id=req_id, data=all_tokens)
|
|
)
|
|
image["url"] = image_ret["http_url"]
|
|
multipart.append(image)
|
|
|
|
lasrt_request_output = self._multipart_buffer[-1]["request_output"]
|
|
lasrt_request_output["outputs"]["multipart"] = multipart
|
|
yield lasrt_request_output
|