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.
This commit is contained in:
2026-10-25 17:05:13 -03:00
commit 6b3b6541a7
3792 changed files with 805563 additions and 0 deletions
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from __future__ import annotations
from typing import TYPE_CHECKING
from argparse import ArgumentParser
from . import completions
if TYPE_CHECKING:
from argparse import _SubParsersAction
def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
completions.register(subparser)
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from __future__ import annotations
import sys
from typing import TYPE_CHECKING, List, Optional, cast
from argparse import ArgumentParser
from typing_extensions import Literal, NamedTuple
from ..._utils import get_client
from ..._models import BaseModel
from ...._streaming import Stream
from ....types.chat import (
ChatCompletionRole,
ChatCompletionChunk,
CompletionCreateParams,
)
from ....types.chat.completion_create_params import (
CompletionCreateParamsStreaming,
CompletionCreateParamsNonStreaming,
)
if TYPE_CHECKING:
from argparse import _SubParsersAction
def register(subparser: _SubParsersAction[ArgumentParser]) -> None:
sub = subparser.add_parser("chat.completions.create")
sub._action_groups.pop()
req = sub.add_argument_group("required arguments")
opt = sub.add_argument_group("optional arguments")
req.add_argument(
"-g",
"--message",
action="append",
nargs=2,
metavar=("ROLE", "CONTENT"),
help="A message in `{role} {content}` format. Use this argument multiple times to add multiple messages.",
required=True,
)
req.add_argument(
"-m",
"--model",
help="The model to use.",
required=True,
)
opt.add_argument(
"-n",
"--n",
help="How many completions to generate for the conversation.",
type=int,
)
opt.add_argument("-M", "--max-tokens", help="The maximum number of tokens to generate.", type=int)
opt.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,
)
opt.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,
)
opt.add_argument(
"--stop",
help="A stop sequence at which to stop generating tokens for the message.",
)
opt.add_argument("--stream", help="Stream messages as they're ready.", action="store_true")
sub.set_defaults(func=CLIChatCompletion.create, args_model=CLIChatCompletionCreateArgs)
class CLIMessage(NamedTuple):
role: ChatCompletionRole
content: str
class CLIChatCompletionCreateArgs(BaseModel):
message: List[CLIMessage]
model: str
n: Optional[int] = None
max_tokens: Optional[int] = None
temperature: Optional[float] = None
top_p: Optional[float] = None
stop: Optional[str] = None
stream: bool = False
class CLIChatCompletion:
@staticmethod
def create(args: CLIChatCompletionCreateArgs) -> None:
params: CompletionCreateParams = {
"model": args.model,
"messages": [
{"role": cast(Literal["user"], message.role), "content": message.content} for message in args.message
],
"n": args.n,
"temperature": args.temperature,
"top_p": args.top_p,
"stop": args.stop,
# type checkers are not good at inferring union types so we have to set stream afterwards
"stream": False,
}
if args.stream:
params["stream"] = args.stream # type: ignore
if args.max_tokens is not None:
params["max_tokens"] = args.max_tokens
if args.stream:
return CLIChatCompletion._stream_create(cast(CompletionCreateParamsStreaming, params))
return CLIChatCompletion._create(cast(CompletionCreateParamsNonStreaming, params))
@staticmethod
def _create(params: CompletionCreateParamsNonStreaming) -> None:
completion = get_client().chat.completions.create(**params)
should_print_header = len(completion.choices) > 1
for choice in completion.choices:
if should_print_header:
sys.stdout.write("===== Chat Completion {} =====\n".format(choice.index))
content = choice.message.content if choice.message.content is not None else "None"
sys.stdout.write(content)
if should_print_header or not content.endswith("\n"):
sys.stdout.write("\n")
sys.stdout.flush()
@staticmethod
def _stream_create(params: CompletionCreateParamsStreaming) -> None:
# cast is required for mypy
stream = cast( # pyright: ignore[reportUnnecessaryCast]
Stream[ChatCompletionChunk], get_client().chat.completions.create(**params)
)
for chunk in stream:
should_print_header = len(chunk.choices) > 1
for choice in chunk.choices:
if should_print_header:
sys.stdout.write("===== Chat Completion {} =====\n".format(choice.index))
content = choice.delta.content or ""
sys.stdout.write(content)
if should_print_header:
sys.stdout.write("\n")
sys.stdout.flush()
sys.stdout.write("\n")