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https://github.com/PaddlePaddle/FastDeploy.git
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[Feature] add cli command chat,complete (#4037)
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memoryCoderC
226
fastdeploy/entrypoints/cli/openai.py
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226
fastdeploy/entrypoints/cli/openai.py
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"""
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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# This file is modified from https://github.com/vllm-project/vllm/blob/main/vllm/entrypoints/cli/openai.py
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from __future__ import annotations
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import argparse
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import os
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import signal
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import sys
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from typing import TYPE_CHECKING
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from openai import OpenAI
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from openai.types.chat import ChatCompletionMessageParam
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from fastdeploy.entrypoints.cli.types import CLISubcommand
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if TYPE_CHECKING:
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from fastdeploy.utils import FlexibleArgumentParser
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def _register_signal_handlers():
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def signal_handler(sig, frame):
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sys.exit(0)
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signal.signal(signal.SIGINT, signal_handler)
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signal.signal(signal.SIGTSTP, signal_handler)
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def _interactive_cli(args: argparse.Namespace) -> tuple[str, OpenAI]:
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_register_signal_handlers()
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base_url = args.url
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api_key = args.api_key or os.environ.get("OPENAI_API_KEY", "EMPTY")
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openai_client = OpenAI(api_key=api_key, base_url=base_url)
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if args.model_name:
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model_name = args.model_name
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else:
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available_models = openai_client.models.list()
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model_name = available_models.data[0].id
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print(f"Using model: {model_name}")
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return model_name, openai_client
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def chat(system_prompt: str | None, model_name: str, client: OpenAI) -> None:
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conversation: list[ChatCompletionMessageParam] = []
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if system_prompt is not None:
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conversation.append({"role": "system", "content": system_prompt})
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print("Please enter a message for the chat model:")
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while True:
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try:
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input_message = input("> ")
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except EOFError:
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break
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conversation.append({"role": "user", "content": input_message})
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chat_completion = client.chat.completions.create(model=model_name, messages=conversation)
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response_message = chat_completion.choices[0].message
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output = response_message.content
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conversation.append(response_message) # type: ignore
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print(output)
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def _add_query_options(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
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parser.add_argument(
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"--url",
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type=str,
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default="http://localhost:9904/v1",
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help="url of the running OpenAI-Compatible RESTful API server",
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)
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parser.add_argument(
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"--model-name",
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type=str,
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default=None,
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help=("The model name used in prompt completion, default to " "the first model in list models API call."),
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)
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parser.add_argument(
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"--api-key",
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type=str,
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default=None,
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help=(
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"API key for OpenAI services. If provided, this api key "
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"will overwrite the api key obtained through environment variables."
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),
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)
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return parser
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class ChatCommand(CLISubcommand):
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"""The `chat` subcommand for the fastdeploy CLI."""
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name = "chat"
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@staticmethod
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def cmd(args: argparse.Namespace) -> None:
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model_name, client = _interactive_cli(args)
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system_prompt = args.system_prompt
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conversation: list[ChatCompletionMessageParam] = []
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if system_prompt is not None:
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conversation.append({"role": "system", "content": system_prompt})
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if args.quick:
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conversation.append({"role": "user", "content": args.quick})
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chat_completion = client.chat.completions.create(model=model_name, messages=conversation)
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print(chat_completion.choices[0].message.content)
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return
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print("Please enter a message for the chat model:")
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while True:
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try:
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input_message = input("> ")
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except EOFError:
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break
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conversation.append({"role": "user", "content": input_message})
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chat_completion = client.chat.completions.create(model=model_name, messages=conversation)
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response_message = chat_completion.choices[0].message
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output = response_message.content
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conversation.append(response_message) # type: ignore
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print(output)
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@staticmethod
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def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
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"""Add CLI arguments for the chat command."""
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_add_query_options(parser)
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parser.add_argument(
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"--system-prompt",
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type=str,
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default=None,
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help=(
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"The system prompt to be added to the chat template, " "used for models that support system prompts."
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),
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)
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parser.add_argument(
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"-q",
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"--quick",
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type=str,
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metavar="MESSAGE",
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help=("Send a single prompt as MESSAGE " "and print the response, then exit."),
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)
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return parser
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def subparser_init(self, subparsers: argparse._SubParsersAction) -> FlexibleArgumentParser:
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parser = subparsers.add_parser(
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"chat",
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help="Generate chat completions via the running API server.",
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description="Generate chat completions via the running API server.",
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usage="fastdeploy chat [options]",
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)
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return ChatCommand.add_cli_args(parser)
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class CompleteCommand(CLISubcommand):
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"""The `complete` subcommand for the fastdeloy CLI."""
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name = "complete"
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@staticmethod
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def cmd(args: argparse.Namespace) -> None:
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model_name, client = _interactive_cli(args)
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if args.quick:
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completion = client.completions.create(model=model_name, prompt=args.quick)
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print(completion.choices[0].text)
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return
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print("Please enter prompt to complete:")
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while True:
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try:
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input_prompt = input("> ")
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except EOFError:
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break
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completion = client.completions.create(model=model_name, prompt=input_prompt)
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output = completion.choices[0].text
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print(output)
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@staticmethod
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def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
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"""Add CLI arguments for the complete command."""
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_add_query_options(parser)
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parser.add_argument(
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"-q",
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"--quick",
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type=str,
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metavar="PROMPT",
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help="Send a single prompt and print the completion output, then exit.",
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)
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return parser
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def subparser_init(self, subparsers: argparse._SubParsersAction) -> FlexibleArgumentParser:
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parser = subparsers.add_parser(
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"complete",
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help=("Generate text completions based on the given prompt " "via the running API server."),
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description=("Generate text completions based on the given prompt " "via the running API server."),
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usage="fastdeploy complete [options]",
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)
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return CompleteCommand.add_cli_args(parser)
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def cmd_init() -> list[CLISubcommand]:
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return [ChatCommand(), CompleteCommand()]
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