aboutsummaryrefslogtreecommitdiff
path: root/.venv/lib/python3.12/site-packages/openai/cli/_api/completions.py
diff options
context:
space:
mode:
Diffstat (limited to '.venv/lib/python3.12/site-packages/openai/cli/_api/completions.py')
-rw-r--r--.venv/lib/python3.12/site-packages/openai/cli/_api/completions.py173
1 files changed, 173 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/openai/cli/_api/completions.py b/.venv/lib/python3.12/site-packages/openai/cli/_api/completions.py
new file mode 100644
index 00000000..cbdb35bf
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/openai/cli/_api/completions.py
@@ -0,0 +1,173 @@
+from __future__ import annotations
+
+import sys
+from typing import TYPE_CHECKING, Optional, cast
+from argparse import ArgumentParser
+from functools import partial
+
+from openai.types.completion import Completion
+
+from .._utils import get_client
+from ..._types import NOT_GIVEN, NotGivenOr
+from ..._utils import is_given
+from .._errors import CLIError
+from .._models import BaseModel
+from ..._streaming import Stream
+
+if TYPE_CHECKING:
+ from argparse import _SubParsersAction
+
+
+def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
+ sub = subparser.add_parser("completions.create")
+
+ # Required
+ sub.add_argument(
+ "-m",
+ "--model",
+ help="The model to use",
+ required=True,
+ )
+
+ # Optional
+ sub.add_argument("-p", "--prompt", help="An optional prompt to complete from")
+ sub.add_argument("--stream", help="Stream tokens as they're ready.", action="store_true")
+ sub.add_argument("-M", "--max-tokens", help="The maximum number of tokens to generate", type=int)
+ sub.add_argument(
+ "-t",
+ "--temperature",
+ help="""What sampling temperature to use. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.
+
+Mutually exclusive with `top_p`.""",
+ type=float,
+ )
+ sub.add_argument(
+ "-P",
+ "--top_p",
+ help="""An alternative to sampling with temperature, called nucleus sampling, where the considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10%% probability mass are considered.
+
+ Mutually exclusive with `temperature`.""",
+ type=float,
+ )
+ sub.add_argument(
+ "-n",
+ "--n",
+ help="How many sub-completions to generate for each prompt.",
+ type=int,
+ )
+ sub.add_argument(
+ "--logprobs",
+ help="Include the log probabilities on the `logprobs` most likely tokens, as well the chosen tokens. So for example, if `logprobs` is 10, the API will return a list of the 10 most likely tokens. If `logprobs` is 0, only the chosen tokens will have logprobs returned.",
+ type=int,
+ )
+ sub.add_argument(
+ "--best_of",
+ help="Generates `best_of` completions server-side and returns the 'best' (the one with the highest log probability per token). Results cannot be streamed.",
+ type=int,
+ )
+ sub.add_argument(
+ "--echo",
+ help="Echo back the prompt in addition to the completion",
+ action="store_true",
+ )
+ sub.add_argument(
+ "--frequency_penalty",
+ help="Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.",
+ type=float,
+ )
+ sub.add_argument(
+ "--presence_penalty",
+ help="Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.",
+ type=float,
+ )
+ sub.add_argument("--suffix", help="The suffix that comes after a completion of inserted text.")
+ sub.add_argument("--stop", help="A stop sequence at which to stop generating tokens.")
+ sub.add_argument(
+ "--user",
+ help="A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.",
+ )
+ # TODO: add support for logit_bias
+ sub.set_defaults(func=CLICompletions.create, args_model=CLICompletionCreateArgs)
+
+
+class CLICompletionCreateArgs(BaseModel):
+ model: str
+ stream: bool = False
+
+ prompt: Optional[str] = None
+ n: NotGivenOr[int] = NOT_GIVEN
+ stop: NotGivenOr[str] = NOT_GIVEN
+ user: NotGivenOr[str] = NOT_GIVEN
+ echo: NotGivenOr[bool] = NOT_GIVEN
+ suffix: NotGivenOr[str] = NOT_GIVEN
+ best_of: NotGivenOr[int] = NOT_GIVEN
+ top_p: NotGivenOr[float] = NOT_GIVEN
+ logprobs: NotGivenOr[int] = NOT_GIVEN
+ max_tokens: NotGivenOr[int] = NOT_GIVEN
+ temperature: NotGivenOr[float] = NOT_GIVEN
+ presence_penalty: NotGivenOr[float] = NOT_GIVEN
+ frequency_penalty: NotGivenOr[float] = NOT_GIVEN
+
+
+class CLICompletions:
+ @staticmethod
+ def create(args: CLICompletionCreateArgs) -> None:
+ if is_given(args.n) and args.n > 1 and args.stream:
+ raise CLIError("Can't stream completions with n>1 with the current CLI")
+
+ make_request = partial(
+ get_client().completions.create,
+ n=args.n,
+ echo=args.echo,
+ stop=args.stop,
+ user=args.user,
+ model=args.model,
+ top_p=args.top_p,
+ prompt=args.prompt,
+ suffix=args.suffix,
+ best_of=args.best_of,
+ logprobs=args.logprobs,
+ max_tokens=args.max_tokens,
+ temperature=args.temperature,
+ presence_penalty=args.presence_penalty,
+ frequency_penalty=args.frequency_penalty,
+ )
+
+ if args.stream:
+ return CLICompletions._stream_create(
+ # mypy doesn't understand the `partial` function but pyright does
+ cast(Stream[Completion], make_request(stream=True)) # pyright: ignore[reportUnnecessaryCast]
+ )
+
+ return CLICompletions._create(make_request())
+
+ @staticmethod
+ def _create(completion: Completion) -> None:
+ should_print_header = len(completion.choices) > 1
+ for choice in completion.choices:
+ if should_print_header:
+ sys.stdout.write("===== Completion {} =====\n".format(choice.index))
+
+ sys.stdout.write(choice.text)
+
+ if should_print_header or not choice.text.endswith("\n"):
+ sys.stdout.write("\n")
+
+ sys.stdout.flush()
+
+ @staticmethod
+ def _stream_create(stream: Stream[Completion]) -> None:
+ for completion in stream:
+ should_print_header = len(completion.choices) > 1
+ for choice in sorted(completion.choices, key=lambda c: c.index):
+ if should_print_header:
+ sys.stdout.write("===== Chat Completion {} =====\n".format(choice.index))
+
+ sys.stdout.write(choice.text)
+
+ if should_print_header:
+ sys.stdout.write("\n")
+
+ sys.stdout.flush()
+
+ sys.stdout.write("\n")