Files
GenAIExamples/CodeTrans/code_translation.py
lkk bde285dfce move examples gateway (#992)
Co-authored-by: root <root@idc708073.jf.intel.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Sihan Chen <39623753+Spycsh@users.noreply.github.com>
2024-12-06 14:40:25 +08:00

94 lines
3.1 KiB
Python

# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import asyncio
import os
from comps import Gateway, MegaServiceEndpoint, MicroService, ServiceOrchestrator, ServiceType
from comps.cores.proto.api_protocol import (
ChatCompletionRequest,
ChatCompletionResponse,
ChatCompletionResponseChoice,
ChatMessage,
UsageInfo,
)
from fastapi import Request
from fastapi.responses import StreamingResponse
MEGA_SERVICE_PORT = int(os.getenv("MEGA_SERVICE_PORT", 7777))
LLM_SERVICE_HOST_IP = os.getenv("LLM_SERVICE_HOST_IP", "0.0.0.0")
LLM_SERVICE_PORT = int(os.getenv("LLM_SERVICE_PORT", 9000))
class CodeTransService(Gateway):
def __init__(self, host="0.0.0.0", port=8000):
self.host = host
self.port = port
self.megaservice = ServiceOrchestrator()
def add_remote_service(self):
llm = MicroService(
name="llm",
host=LLM_SERVICE_HOST_IP,
port=LLM_SERVICE_PORT,
endpoint="/v1/chat/completions",
use_remote_service=True,
)
self.megaservice.add(llm)
async def handle_request(self, request: Request):
data = await request.json()
language_from = data["language_from"]
language_to = data["language_to"]
source_code = data["source_code"]
prompt_template = """
### System: Please translate the following {language_from} codes into {language_to} codes.
### Original codes:
'''{language_from}
{source_code}
'''
### Translated codes:
"""
prompt = prompt_template.format(language_from=language_from, language_to=language_to, source_code=source_code)
result_dict, runtime_graph = await self.megaservice.schedule(initial_inputs={"query": prompt})
for node, response in result_dict.items():
# Here it suppose the last microservice in the megaservice is LLM.
if (
isinstance(response, StreamingResponse)
and node == list(self.megaservice.services.keys())[-1]
and self.megaservice.services[node].service_type == ServiceType.LLM
):
return response
last_node = runtime_graph.all_leaves()[-1]
response = result_dict[last_node]["text"]
choices = []
usage = UsageInfo()
choices.append(
ChatCompletionResponseChoice(
index=0,
message=ChatMessage(role="assistant", content=response),
finish_reason="stop",
)
)
return ChatCompletionResponse(model="codetrans", choices=choices, usage=usage)
def start(self):
super().__init__(
megaservice=self.megaservice,
host=self.host,
port=self.port,
endpoint=str(MegaServiceEndpoint.CODE_TRANS),
input_datatype=ChatCompletionRequest,
output_datatype=ChatCompletionResponse,
)
if __name__ == "__main__":
service_ochestrator = CodeTransService(port=MEGA_SERVICE_PORT)
service_ochestrator.add_remote_service()
service_ochestrator.start()