93 lines
3.6 KiB
Python
93 lines
3.6 KiB
Python
# Copyright (C) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import os
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from comps import MicroService, ServiceOrchestrator, ServiceType
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MEGA_SERVICE_PORT = int(os.getenv("MEGA_SERVICE_PORT", 16011))
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PIPELINE_SERVICE_HOST_IP = os.getenv("PIPELINE_SERVICE_HOST_IP", "127.0.0.1")
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PIPELINE_SERVICE_PORT = int(os.getenv("PIPELINE_SERVICE_PORT", 16010))
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from comps import MegaServiceEndpoint, ServiceRoleType
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from comps.cores.proto.api_protocol import (
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ChatCompletionRequest,
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ChatCompletionResponse,
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ChatCompletionResponseChoice,
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ChatMessage,
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UsageInfo,
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)
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from comps.cores.proto.docarray import LLMParams
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from fastapi import Request
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from fastapi.responses import StreamingResponse
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class EdgeCraftRagService:
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def __init__(self, host="0.0.0.0", port=16010):
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self.host = host
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self.port = port
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self.megaservice = ServiceOrchestrator()
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self.endpoint = str(MegaServiceEndpoint.CHAT_QNA)
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def add_remote_service(self):
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edgecraftrag = MicroService(
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name="pipeline",
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host=PIPELINE_SERVICE_HOST_IP,
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port=PIPELINE_SERVICE_PORT,
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endpoint="/v1/chatqna",
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use_remote_service=True,
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service_type=ServiceType.LLM,
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)
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self.megaservice.add(edgecraftrag)
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async def handle_request(self, request: Request):
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input = await request.json()
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stream_opt = input.get("stream", False)
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chat_request = ChatCompletionRequest.parse_obj(input)
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parameters = LLMParams(
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max_tokens=chat_request.max_tokens if chat_request.max_tokens else 1024,
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top_k=chat_request.top_k if chat_request.top_k else 10,
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top_p=chat_request.top_p if chat_request.top_p else 0.95,
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temperature=chat_request.temperature if chat_request.temperature else 0.01,
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frequency_penalty=chat_request.frequency_penalty if chat_request.frequency_penalty else 0.0,
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presence_penalty=chat_request.presence_penalty if chat_request.presence_penalty else 0.0,
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repetition_penalty=chat_request.repetition_penalty if chat_request.repetition_penalty else 1.03,
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stream=stream_opt,
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chat_template=chat_request.chat_template if chat_request.chat_template else None,
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)
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result_dict, runtime_graph = await self.megaservice.schedule(initial_inputs=input, llm_parameters=parameters)
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for node, response in result_dict.items():
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if isinstance(response, StreamingResponse):
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return response
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last_node = runtime_graph.all_leaves()[-1]
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response = result_dict[last_node]
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choices = []
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usage = UsageInfo()
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choices.append(
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ChatCompletionResponseChoice(
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index=0,
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message=ChatMessage(role="assistant", content=response),
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finish_reason="stop",
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)
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)
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return ChatCompletionResponse(model="edgecraftrag", choices=choices, usage=usage)
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def start(self):
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self.service = MicroService(
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self.__class__.__name__,
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service_role=ServiceRoleType.MEGASERVICE,
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host=self.host,
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port=self.port,
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endpoint=self.endpoint,
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input_datatype=ChatCompletionRequest,
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output_datatype=ChatCompletionResponse,
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)
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self.service.add_route(self.endpoint, self.handle_request, methods=["POST"])
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self.service.start()
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if __name__ == "__main__":
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edgecraftrag = EdgeCraftRagService(port=MEGA_SERVICE_PORT)
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edgecraftrag.add_remote_service()
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edgecraftrag.start()
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