# Copyright (c) 2023 Baidu, Inc. 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
import prompt_toolkit
import typer
from rich.console import Console
from rich.markdown import Markdown
import qianfan
from qianfan import Messages, QfResponse, QfRole
from qianfan.common.client.utils import (
create_client,
credential_required,
list_model_option,
print_error_msg,
print_info_msg,
render_response_debug_info,
)
from qianfan.consts import DefaultLLMModel
[docs]class CompletionClient(object):
"""
Client class for completion command.
"""
def __init__(
self,
model: str,
endpoint: Optional[str],
plain: bool,
debug: bool,
**kwargs: Any
):
"""
Init the client.
"""
self.model = model
self.endpoint = endpoint
self.plain = plain
self.console = Console(no_color=self.plain)
self.debug = debug
self.inference_args = kwargs
[docs] def completion_single(self, message: str) -> None:
"""
Use Completion to complete the given message.
"""
client = create_client(qianfan.Completion, self.model, self.endpoint)
if self.plain:
res = client.do(prompt=message, **self.inference_args)
assert isinstance(res, QfResponse)
print(res["result"])
else:
with self.console.status("Generating..."):
res = client.do(prompt=message, **self.inference_args)
assert isinstance(res, QfResponse)
self.console.print(Markdown(res["result"]))
if self.debug:
self.console.print(render_response_debug_info(res))
[docs] def completion_multi(self, messages: List[str]) -> None:
"""
Use ChatCompletion to complete the given messages.
"""
msg_history = Messages()
for i, message in enumerate(messages):
if i % 2 == 0:
msg_history.append(message, role=QfRole.User)
else:
msg_history.append(message, role=QfRole.Assistant)
client = create_client(qianfan.ChatCompletion, self.model, self.endpoint)
if self.plain:
res = client.do(messages=msg_history, **self.inference_args)
assert isinstance(res, QfResponse)
print(res["result"])
else:
with self.console.status("Generating..."):
res = client.do(messages=msg_history, **self.inference_args)
assert isinstance(res, QfResponse)
self.console.print(Markdown(res["result"]))
if self.debug:
self.console.print(render_response_debug_info(res))
MODEL_ARGUMENTS_PANEL = (
"Model Arguments (Some arguments are not supported by every model)"
)
[docs]@credential_required
def completion_entry(
prompts: Optional[List[str]] = typer.Argument(None, help="Prompt List"),
model: str = typer.Option(
DefaultLLMModel.Completion,
help="Model name of the completion model.",
autocompletion=qianfan.Completion.models,
),
endpoint: Optional[str] = typer.Option(
None,
help=(
"Endpoint of the completion model. This option will override `model`"
" option."
),
),
plain: bool = typer.Option(False, help="Plain text mode won't use rich text"),
list_model: bool = list_model_option,
multi_line: bool = typer.Option(
False,
"--multi-line",
help="Multi-line mode which needs to press Esc before enter to submit message.",
),
debug: bool = typer.Option(
False,
help="Debug mode. Request information will be printed.",
),
temperature: Optional[float] = typer.Option(
None,
help=(
"Controls the randomness of the generated text. A higher temperature makes"
" the model more creative and produces more diverse, but potentially less"
" coherent."
),
rich_help_panel=MODEL_ARGUMENTS_PANEL,
),
top_p: Optional[float] = typer.Option(
None,
help=(
"Lower top_p value allows the model to focus on a narrowed set of likely"
" next tokens, making the response more conherent but less random."
),
rich_help_panel=MODEL_ARGUMENTS_PANEL,
),
penalty_score: Optional[float] = typer.Option(
None,
help="Penalty scores can be applied to discourage repetition.",
rich_help_panel=MODEL_ARGUMENTS_PANEL,
),
system: Optional[str] = typer.Option(
None,
help="Persona setting for the model.",
rich_help_panel=MODEL_ARGUMENTS_PANEL,
),
stop: Optional[str] = typer.Option(
None,
help="Stop words. Use comma to split multiple stop words.",
rich_help_panel=MODEL_ARGUMENTS_PANEL,
),
disable_search: Optional[bool] = typer.Option(
None, help="Disable search", rich_help_panel=MODEL_ARGUMENTS_PANEL
),
enable_citation: Optional[bool] = typer.Option(
None, help="Enable citation", rich_help_panel=MODEL_ARGUMENTS_PANEL
),
) -> None:
"""
Complete the provided prompt or messages.
"""
if prompts is None or len(prompts) == 0:
if multi_line:
print_info_msg(
"Multi-line mode is enabled. [green bold]Press Esc before Enter[/] to"
" submit prompt.\n"
)
while True:
print("Please enter your prompt:")
prompt = prompt_toolkit.prompt(multiline=multi_line).strip()
if len(prompt) != 0:
prompts = [prompt]
break
print_error_msg("Prompt can't be empty.\n")
if len(prompts) % 2 != 1:
print_error_msg("The number of messages must be odd.")
raise typer.Exit(code=1)
extra_args = {}
def add_if_not_none(key: str, value: Any) -> None:
if value is not None:
extra_args[key] = value
add_if_not_none("temperature", temperature)
add_if_not_none("top_p", top_p)
add_if_not_none("penalty_score", penalty_score)
add_if_not_none("system", system)
add_if_not_none("disable_search", disable_search)
add_if_not_none("enable_citation", enable_citation)
if stop is not None:
extra_args["stop"] = stop.split(",")
client = CompletionClient(model, endpoint, plain, debug, **extra_args)
if len(prompts) == 1:
client.completion_single(prompts[0])
else:
client.completion_multi(prompts)