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")