feat: add psagentai agent with deployment and configuration
Initial project setup including the main agent script, configuration files, profile JSON state, systemd service unit, startup script, deployment documentation, and Python dependencies. Includes .env, venv/, and __pycache__/ which should likely be excluded via .gitignore to avoid committing secrets and artifacts.
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from argparse import ArgumentParser
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from . import completions
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if TYPE_CHECKING:
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from argparse import _SubParsersAction
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def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
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completions.register(subparser)
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from __future__ import annotations
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import sys
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from typing import TYPE_CHECKING, List, Optional, cast
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from argparse import ArgumentParser
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from typing_extensions import Literal, NamedTuple
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from ..._utils import get_client
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from ..._models import BaseModel
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from ...._streaming import Stream
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from ....types.chat import (
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ChatCompletionRole,
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ChatCompletionChunk,
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CompletionCreateParams,
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)
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from ....types.chat.completion_create_params import (
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CompletionCreateParamsStreaming,
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CompletionCreateParamsNonStreaming,
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)
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if TYPE_CHECKING:
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from argparse import _SubParsersAction
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def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
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sub = subparser.add_parser("chat.completions.create")
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sub._action_groups.pop()
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req = sub.add_argument_group("required arguments")
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opt = sub.add_argument_group("optional arguments")
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req.add_argument(
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"-g",
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"--message",
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action="append",
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nargs=2,
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metavar=("ROLE", "CONTENT"),
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help="A message in `{role} {content}` format. Use this argument multiple times to add multiple messages.",
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required=True,
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)
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req.add_argument(
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"-m",
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"--model",
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help="The model to use.",
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required=True,
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)
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opt.add_argument(
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"-n",
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"--n",
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help="How many completions to generate for the conversation.",
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type=int,
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)
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opt.add_argument("-M", "--max-tokens", help="The maximum number of tokens to generate.", type=int)
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opt.add_argument(
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"-t",
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"--temperature",
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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.
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Mutually exclusive with `top_p`.""",
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type=float,
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)
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opt.add_argument(
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"-P",
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"--top_p",
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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.
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Mutually exclusive with `temperature`.""",
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type=float,
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)
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opt.add_argument(
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"--stop",
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help="A stop sequence at which to stop generating tokens for the message.",
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)
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opt.add_argument("--stream", help="Stream messages as they're ready.", action="store_true")
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sub.set_defaults(func=CLIChatCompletion.create, args_model=CLIChatCompletionCreateArgs)
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class CLIMessage(NamedTuple):
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role: ChatCompletionRole
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content: str
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class CLIChatCompletionCreateArgs(BaseModel):
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message: List[CLIMessage]
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model: str
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n: Optional[int] = None
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max_tokens: Optional[int] = None
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temperature: Optional[float] = None
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top_p: Optional[float] = None
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stop: Optional[str] = None
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stream: bool = False
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class CLIChatCompletion:
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@staticmethod
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def create(args: CLIChatCompletionCreateArgs) -> None:
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params: CompletionCreateParams = {
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"model": args.model,
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"messages": [
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{"role": cast(Literal["user"], message.role), "content": message.content} for message in args.message
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],
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"n": args.n,
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"temperature": args.temperature,
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"top_p": args.top_p,
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"stop": args.stop,
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# type checkers are not good at inferring union types so we have to set stream afterwards
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"stream": False,
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}
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if args.stream:
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params["stream"] = args.stream # type: ignore
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if args.max_tokens is not None:
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params["max_tokens"] = args.max_tokens
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if args.stream:
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return CLIChatCompletion._stream_create(cast(CompletionCreateParamsStreaming, params))
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return CLIChatCompletion._create(cast(CompletionCreateParamsNonStreaming, params))
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@staticmethod
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def _create(params: CompletionCreateParamsNonStreaming) -> None:
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completion = get_client().chat.completions.create(**params)
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should_print_header = len(completion.choices) > 1
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for choice in completion.choices:
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if should_print_header:
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sys.stdout.write("===== Chat Completion {} =====\n".format(choice.index))
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content = choice.message.content if choice.message.content is not None else "None"
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sys.stdout.write(content)
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if should_print_header or not content.endswith("\n"):
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sys.stdout.write("\n")
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sys.stdout.flush()
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@staticmethod
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def _stream_create(params: CompletionCreateParamsStreaming) -> None:
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# cast is required for mypy
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stream = cast( # pyright: ignore[reportUnnecessaryCast]
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Stream[ChatCompletionChunk], get_client().chat.completions.create(**params)
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)
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for chunk in stream:
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should_print_header = len(chunk.choices) > 1
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for choice in chunk.choices:
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if should_print_header:
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sys.stdout.write("===== Chat Completion {} =====\n".format(choice.index))
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content = choice.delta.content or ""
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sys.stdout.write(content)
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if should_print_header:
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sys.stdout.write("\n")
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sys.stdout.flush()
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sys.stdout.write("\n")
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