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8 Commits
v1.0.0 ... main

Author SHA1 Message Date
Paul Harrison 0698919cb6 Incorporate custom bots into chat CLI
This commit will add the ability to create custom bots in the form of
automatically prepending additional bot-specific context to your chat
session. A new `chat` CLI argument will be added allowing users to
provide the name of an existing bot. For example:

```
llm chat -b "My Bot"
```

An additional `bot` CLI is added for creating and removing bots.

Closes #13
2024-06-27 17:07:28 +01:00
Paul Harrison 76bee1aed9 Update default history directory 2024-02-23 11:25:27 +00:00
Paul Harrison ff836e617c Get default chat paramters from settings file
In the current CLI implementation, default values for the model,
temperature, and history directory were provided as defaults to the
`typer` CLI interface. This bypassed the ability to set values via
environment variables and relied on `typer` rather than `pydantic` to
validate the history directory. This prevented the directory's creation
when it doesn't exist.

This commit sets the default values in the CLI to `None` and thus relies
on the `OpenAISettings` class for default values and parameter
validation.
2024-02-23 11:15:09 +00:00
Paul Harrison b859c8bb95 Fix failing cost calculation test
When updating the model pricing in commit 50fa0cc5ae I forgot to update
the associated test. As well as fixing this test, this commit also
updates the calculation to use `math.floor` instead of `round` to round
to six decimal places. This is because the `round` function appeared to
round incorrectly. For example, when running the test, 0.0000275 was
rounded to 0.000028 instead of the expected 0.000028.
2024-02-23 11:12:53 +00:00
Paul Harrison aade152486 Add GPT-4-turbo-preview to enabled models 2024-02-17 16:13:54 +00:00
Paul Harrison 50fa0cc5ae Update GPT-3 pricing 2024-02-17 16:02:29 +00:00
Paul Harrison 2764777c0b Add macOS files to .gitignore 2024-02-17 15:46:15 +00:00
Paul Harrison 2d10e3ff40 Update openai to v1.9
The update from openai 0.x to 1.x introduced many breaking changes. This
commit makes the required refactoring to address these changes.

Closes #9
2024-01-23 23:41:35 +01:00
16 changed files with 819 additions and 723 deletions

33
.gitignore vendored
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@ -8,6 +8,39 @@
### asdf ###
/.tool-versions
### macOS ###
# General
.DS_Store
.AppleDouble
.LSOverride
# Icon must end with two \r
Icon
# Thumbnails
._*
# Files that might appear in the root of a volume
.DocumentRevisions-V100
.fseventsd
.Spotlight-V100
.TemporaryItems
.Trashes
.VolumeIcon.icns
.com.apple.timemachine.donotpresent
# Directories potentially created on remote AFP share
.AppleDB
.AppleDesktop
Network Trash Folder
Temporary Items
.apdisk
### macOS Patch ###
# iCloud generated files
*.icloud
### Python ###
# Byte-compiled / optimized / DLL files
__pycache__/

836
poetry.lock generated
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@ -1,126 +1,4 @@
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]
[package.dependencies]
idna = ">=2.0"
multidict = ">=4.0"
[metadata]
lock-version = "2.0"
python-versions = ">=3.11,<3.12"
content-hash = "5b81fe2c2ca1756c2c446ab727fd30fd976ed7d8c82ffb8f7d3870c38755bce6"
content-hash = "8d76898eeb53fd3848f3be2f6aa1662517f9dbd80146db8dfd6f2932021ace48"

View File

@ -1,6 +1,6 @@
[tool.poetry]
name = "llm-chat"
version = "1.0.0"
version = "2.0.0"
description = "A general CLI interface for large language models."
authors = ["Paul Harrison <paul@harrison.sh>"]
readme = "README.md"
@ -8,8 +8,8 @@ packages = [{include = "llm_chat", from = "src"}]
[tool.poetry.dependencies]
python = ">=3.11,<3.12"
openai = "^0.27.8"
pydantic = "^2.1.1"
openai = "^1.9"
pydantic = "^2.5.3"
pydantic-settings = "^2.0.2"
typer = {extras = ["all"], version = "^0.9.0"}
prompt-toolkit = "^3.0.39"
@ -21,6 +21,7 @@ isort = "^5.12.0"
ruff = "^0.0.284"
mypy = "^1.5.0"
pydocstyle = "^6.3.0"
types-attrs = "^19.1.0"
[tool.poetry.scripts]
llm = "llm_chat.cli:app"

162
src/llm_chat/bot.py Normal file
View File

@ -0,0 +1,162 @@
from __future__ import annotations
import json
import shutil
from pathlib import Path
from typing import Iterable
from pydantic import BaseModel
from llm_chat.models import Message, Role
from llm_chat.utils import kebab_case
class BotExists(Exception):
"""Bot already exists error."""
pass
class BotDoesNotExist(Exception):
"""Bot does not exist error."""
pass
class BotConfig(BaseModel):
"""Bot configuration class."""
bot_id: str
name: str
context_files: list[str]
def _bot_id_from_name(name: str) -> str:
"""Create bot ID from name.
Args:
name: Bot name in full prose (e.g. My Amazing Bot).
"""
return kebab_case(name)
def _load_context(config: BotConfig, bot_dir: Path) -> list[Message]:
"""Load text from context files.
Args:
config: Bot configuration.
Returns:
List of system messages to provide as context.
"""
context: list[Message] = []
for context_file in config.context_files:
path = bot_dir / config.bot_id / "context" / context_file
if not path.exists():
raise ValueError(f"{path} does not exist.")
if not path.is_file():
raise ValueError(f"{path} is not a file")
with path.open("r") as f:
content = f.read()
context.append(Message(role=Role.SYSTEM, content=content))
return context
class Bot:
"""Custom bot interface.
Args:
config: Bot configuration instance.
bot_dir: Path to directory of bot configurations.
"""
def __init__(self, config: BotConfig, bot_dir: Path) -> None:
self.config = config
self.context = _load_context(config, bot_dir)
@property
def id(self) -> str:
"""Return the bot ID."""
return self.config.bot_id
@property
def name(self) -> str:
"""Return the bot name."""
return self.config.name
@classmethod
def create(
cls,
name: str,
bot_dir: Path,
context_files: Iterable[Path] = tuple(),
) -> None:
"""Create a custom bot.
This command creates the directory structure for the custom bot and copies
the context files. The bot directory is stored within the base bot directory
(e.g. `~/.llm_chat/bots/<name>`), which is stored as the snake case version of
the name argument. the directory contains a settings file `<name>.json` and a
directory of context files.
Args:
name: Name of the custom bot.
bot_dir: Path to where custom bot contexts are stored.
context_files: Paths to context files.
Returns:
Instantiated Bot instance.
"""
bot_id = _bot_id_from_name(name)
path = bot_dir / bot_id
if path.exists():
raise BotExists(f"The bot {name} already exists.")
(path / "context").mkdir(parents=True)
config = BotConfig(
bot_id=bot_id,
name=name,
context_files=[context.name for context in context_files],
)
with (path / f"{bot_id}.json").open("w") as f:
f.write(config.model_dump_json() + "\n")
for context in context_files:
shutil.copy(context, path / "context" / context.name)
@classmethod
def load(cls, name: str, bot_dir: Path) -> Bot:
"""Load an existing bot.
Args:
name: Name of the custom bot.
bot_dir: Path to where custom bot contexts are stored.
Returns:
Instantiated Bot instance.
"""
bot_id = _bot_id_from_name(name)
bot_path = bot_dir / bot_id
if not bot_path.exists():
raise BotDoesNotExist(f"Bot {name} does not exist.")
with (bot_path / f"{bot_id}.json").open("r") as f:
config = BotConfig(**json.load(f))
return cls(config, bot_dir)
@classmethod
def remove(cls, name: str, bot_dir: Path) -> None:
"""Remove an existing bot.
Args:
name: Name of the custom bot.
bot_dir: Path to where custom bot contexts are stored.
"""
bot_id = _bot_id_from_name(name)
bot_path = bot_dir / bot_id
if not bot_path.exists():
raise BotDoesNotExist(f"Bot {name} does not exist.")
shutil.rmtree(bot_path)

View File

@ -1,12 +1,15 @@
import math
from datetime import datetime
from enum import StrEnum, auto
from pathlib import Path
from typing import Any, Protocol, Type
from zoneinfo import ZoneInfo
from openai import ChatCompletion
from openai.openai_object import OpenAIObject
from openai import OpenAI
from openai.types.chat import ChatCompletion
from openai.types.completion_usage import CompletionUsage
from llm_chat.bot import Bot
from llm_chat.models import Conversation, Message, Role
from llm_chat.settings import Model, OpenAISettings
@ -51,6 +54,10 @@ class ChatProtocol(Protocol):
conversation: Conversation
@property
def bot(self) -> str:
"""Get the name of the bot the conversation is with."""
@property
def cost(self) -> float:
"""Get the cost of the conversation."""
@ -66,28 +73,36 @@ class ChatProtocol(Protocol):
def save(self) -> None:
"""Save the conversation to the history directory."""
def send_message(self, message: str) -> str:
def send_message(self, prompt: str) -> str:
"""Send a message to the assistant."""
class Chat:
"""Interface class for OpenAI's ChatGPT chat API.
Arguments:
settings (optional): Settings for the chat. Defaults to reading from
environment variables.
context (optional): Context for the chat. Defaults to an empty list.
Args:
settings: Settings for the chat. Defaults to reading from environment
variables.
context: Context for the chat. Defaults to an empty list.
name: Name of the chat.
bot: Name of bot to chat with.
initial_system_messages: Whether to include the standard initial system
messages.
"""
_pricing: dict[Model, dict[Token, float]] = {
Model.GPT3: {
Token.COMPLETION: 0.002,
Token.COMPLETION: 0.0005,
Token.PROMPT: 0.0015,
},
Model.GPT4: {
Token.COMPLETION: 0.06,
Token.PROMPT: 0.03,
},
Model.GPT4_TURBO: {
Token.COMPLETION: 0.03,
Token.PROMPT: 0.01,
},
}
def __init__(
@ -95,22 +110,32 @@ class Chat:
settings: OpenAISettings | None = None,
context: list[Message] = [],
name: str = "",
bot: str = "",
initial_system_messages: bool = True,
) -> None:
self._settings = settings
if bot:
context = Bot.load(bot, self.settings.bot_dir).context + context
if initial_system_messages:
context = INITIAL_SYSTEM_MESSAGES + context
self.conversation = Conversation(
messages=INITIAL_SYSTEM_MESSAGES + context
if initial_system_messages
else context,
messages=context,
model=self.settings.model,
temperature=self.settings.temperature,
name=name,
bot=bot,
)
self._start_time = datetime.now(tz=ZoneInfo("UTC"))
self._client = OpenAI(
api_key=self.settings.api_key,
)
@classmethod
def load(
cls, path: Path, api_key: str | None = None, history_dir: Path | None = None
cls, path: Path, api_key: str | None = None, base_dir: Path | None = None
) -> ChatProtocol:
"""Load a chat from a file."""
with path.open() as f:
@ -121,8 +146,8 @@ class Chat:
}
if api_key is not None:
args["api_key"] = api_key
if history_dir is not None:
args["history_dir"] = history_dir
if base_dir is not None:
args["base_dir"] = base_dir
settings = OpenAISettings(**args)
return cls(
@ -138,6 +163,11 @@ class Chat:
self._settings = OpenAISettings()
return self._settings
@property
def bot(self) -> str:
"""Get the name of the bot the conversation is with."""
return self.conversation.bot
@property
def cost(self) -> float:
"""Get the cost of the conversation."""
@ -148,7 +178,7 @@ class Chat:
"""Get the name of the conversation."""
return self.conversation.name
def _make_request(self, message: str) -> dict[str, Any]:
def _make_request(self, message: str) -> ChatCompletion:
"""Send a request to the OpenAI API.
TODO: Add error handling.
@ -156,26 +186,30 @@ class Chat:
"""
self.conversation.messages.append(Message(role=Role.USER, content=message))
response: OpenAIObject = ChatCompletion.create(
response: ChatCompletion = self._client.chat.completions.create(
model=self.settings.model,
temperature=self.settings.temperature,
api_key=self.settings.api_key,
messages=self.conversation.model_dump()["messages"],
stream=False,
)
out: dict[str, Any] = response.to_dict()
return out
return response
def _calculate_cost(self, usage: dict[str, int]) -> None:
def _calculate_cost(self, usage: CompletionUsage) -> None:
"""Calculate the cost of a request."""
self.conversation.completion_tokens += usage["completion_tokens"]
self.conversation.prompt_tokens += usage["prompt_tokens"]
self.conversation.cost = round(
self.conversation.completion_tokens += usage.completion_tokens
self.conversation.prompt_tokens += usage.prompt_tokens
self.conversation.cost = (
math.floor(
1000000
* (
(self.conversation.completion_tokens / 1000)
* self._pricing[self.settings.model][Token.COMPLETION]
+ (self.conversation.prompt_tokens / 1000)
* self._pricing[self.settings.model][Token.PROMPT],
6,
* self._pricing[self.settings.model][Token.PROMPT]
)
)
/ 1000000
)
def save(self) -> None:
@ -192,19 +226,24 @@ class Chat:
TODO: Add error handling.
"""
request_response = self._make_request(prompt)
self._calculate_cost(request_response["usage"])
response: str = request_response["choices"][0]["message"]["content"]
if request_response.usage is not None:
self._calculate_cost(request_response.usage)
response = request_response.choices[0].message.content
self.conversation.messages.append(
Message(role=Role.ASSISTANT, content=response)
Message(role=Role.ASSISTANT, content=response if response else "")
)
return response
return response if response else ""
def get_chat(
settings: OpenAISettings | None = None, context: list[Message] = [], name: str = ""
settings: OpenAISettings | None = None,
context: list[Message] = [],
name: str = "",
bot: str = "",
) -> ChatProtocol:
"""Get a chat object."""
return Chat(settings=settings, context=context, name=name)
return Chat(settings=settings, context=context, name=name, bot=bot)
def get_chat_class() -> Type[Chat]:

View File

@ -0,0 +1,3 @@
from llm_chat.cli.main import app
__all__ = ["app"]

79
src/llm_chat/cli/bot.py Normal file
View File

@ -0,0 +1,79 @@
from pathlib import Path
from typing import Annotated, Any, Optional
import typer
from llm_chat.bot import Bot
from llm_chat.settings import OpenAISettings
app = typer.Typer()
@app.command("create")
def create(
name: Annotated[
str,
typer.Argument(help="Name of bot to create."),
],
base_dir: Annotated[
Optional[Path],
typer.Option(
...,
"--base-dir",
"-d",
help=(
"Path to the base directory in which conversation "
"configuration and history will be saved."
),
),
] = None,
context_files: Annotated[
list[Path],
typer.Option(
...,
"--context",
"-c",
help=(
"Path to a file containing context text. "
"Can provide multiple times for multiple files."
),
exists=True,
file_okay=True,
dir_okay=False,
readable=True,
),
] = [],
) -> None:
"""Create a new bot."""
args: dict[str, Any] = {}
if base_dir is not None:
args |= {"base_dir": base_dir}
settings = OpenAISettings(**args)
Bot.create(name, settings.bot_dir, context_files=context_files)
@app.command("remove")
def remove(
name: Annotated[
str,
typer.Argument(help="Name of bot to remove."),
],
base_dir: Annotated[
Optional[Path],
typer.Option(
...,
"--base-dir",
"-d",
help=(
"Path to the base directory in which conversation "
"configuration and history will be saved."
),
),
] = None,
) -> None:
"""Remove an existing bot."""
args: dict[str, Any] = {}
if base_dir is not None:
args |= {"base_dir": base_dir}
settings = OpenAISettings(**args)
Bot.remove(name, settings.bot_dir)

View File

@ -7,16 +7,12 @@ from rich.console import Console
from rich.markdown import Markdown
from llm_chat.chat import ChatProtocol, get_chat, get_chat_class
from llm_chat.cli import bot
from llm_chat.models import Message, Role
from llm_chat.settings import (
DEFAULT_HISTORY_DIR,
DEFAULT_MODEL,
DEFAULT_TEMPERATURE,
Model,
OpenAISettings,
)
from llm_chat.settings import Model, OpenAISettings
app = typer.Typer()
app.add_typer(bot.app, name="bot", help="Manage custom bots.")
def prompt_continuation(width: int, *args: Any) -> str:
@ -79,6 +75,8 @@ def run_conversation(current_chat: ChatProtocol) -> None:
)
if current_chat.name:
console.print(f"[bold green]Name:[/bold green] {current_chat.name}")
if current_chat.bot:
console.print(f"[bold green]Bot:[/bold green] {current_chat.bot}")
while not finished:
prompt = read_user_input(session)
@ -106,15 +104,15 @@ def chat(
),
] = None,
model: Annotated[
Model,
Optional[Model],
typer.Option(..., "--model", "-m", help="Model to use.", show_choices=True),
] = DEFAULT_MODEL,
] = None,
temperature: Annotated[
float,
Optional[float],
typer.Option(
..., "--temperature", "-t", help="Model temperature (i.e. creativeness)."
),
] = DEFAULT_TEMPERATURE,
] = None,
context: Annotated[
list[Path],
typer.Option(
@ -123,7 +121,7 @@ def chat(
"-c",
help=(
"Path to a file containing context text. "
"Can provide multiple time for multiple files."
"Can provide multiple times for multiple files."
),
exists=True,
file_okay=True,
@ -131,18 +129,18 @@ def chat(
readable=True,
),
] = [],
history_dir: Annotated[
Path,
base_dir: Annotated[
Optional[Path],
typer.Option(
...,
"--history-dir",
"--base-dir",
"-d",
help="Path to the directory where conversation history will be saved.",
exists=True,
dir_okay=True,
file_okay=False,
help=(
"Path to the base directory in which conversation "
"configuration and history will be saved."
),
] = DEFAULT_HISTORY_DIR,
),
] = None,
name: Annotated[
str,
typer.Option(
@ -152,24 +150,31 @@ def chat(
help="Name of the chat.",
),
] = "",
bot: Annotated[
str,
typer.Option(
..., "--bot", "-b", help="Name of bot with whom you want to chat."
),
] = "",
) -> None:
"""Start a chat session."""
# TODO: Add option to provide context string as an argument.
args: dict[str, Any] = {}
if api_key is not None:
settings = OpenAISettings(
api_key=api_key,
model=model,
temperature=temperature,
history_dir=history_dir,
)
else:
settings = OpenAISettings(
model=model, temperature=temperature, history_dir=history_dir
)
args |= {"api_key": api_key}
if model is not None:
args |= {"model": model}
if temperature is not None:
args |= {"temperature": temperature}
if base_dir is not None:
args |= {"base_dir": base_dir}
settings = OpenAISettings(**args)
context_messages = [load_context(path) for path in context]
current_chat = get_chat(settings=settings, context=context_messages, name=name)
current_chat = get_chat(
settings=settings, context=context_messages, name=name, bot=bot
)
run_conversation(current_chat)

View File

@ -32,6 +32,7 @@ class Conversation(BaseModel):
model: Model
temperature: float = DEFAULT_TEMPERATURE
name: str = ""
bot: str = ""
completion_tokens: int = 0
prompt_tokens: int = 0
cost: float = 0.0

View File

@ -10,11 +10,14 @@ class Model(StrEnum):
GPT3 = "gpt-3.5-turbo"
GPT4 = "gpt-4"
GPT4_TURBO = "gpt-4-turbo-preview"
DEFAULT_MODEL = Model.GPT3
DEFAULT_TEMPERATURE = 0.7
DEFAULT_HISTORY_DIR = Path.home() / ".llm_chat"
DEFAULT_BASE_DIR = Path.home() / ".llm-chat"
DEFAULT_BOT_PATH = "bots"
DEFAULT_HISTORY_PATH = "history"
class OpenAISettings(BaseSettings):
@ -23,7 +26,9 @@ class OpenAISettings(BaseSettings):
api_key: str = ""
model: Model = DEFAULT_MODEL
temperature: float = DEFAULT_TEMPERATURE
history_dir: Path = DEFAULT_HISTORY_DIR
base_dir: Path = DEFAULT_BASE_DIR
bot_path: str = DEFAULT_BOT_PATH
history_path: str = DEFAULT_HISTORY_PATH
model_config: SettingsConfigDict = SettingsConfigDict( # type: ignore[misc]
env_file=".env",
@ -33,9 +38,25 @@ class OpenAISettings(BaseSettings):
use_enum_values=True,
)
@field_validator("history_dir")
def history_dir_must_exist(cls, history_dir: Path) -> Path:
"""Ensure that the history directory exists."""
if not history_dir.exists():
history_dir.mkdir(parents=True)
return history_dir
@field_validator("base_dir")
def base_dir_must_exist(cls, base_dir: Path) -> Path:
"""Ensure that the base directory exists."""
if not base_dir.exists():
base_dir.mkdir(parents=True)
return base_dir
@property
def bot_dir(self) -> Path:
"""Return bot directory Path object, creating if required."""
path = self.base_dir / self.bot_path
if not path.exists():
path.mkdir()
return path
@property
def history_dir(self) -> Path:
"""Return history directory Path object, creating if required."""
path = self.base_dir / self.history_path
if not path.exists():
path.mkdir()
return path

9
src/llm_chat/utils.py Normal file
View File

@ -0,0 +1,9 @@
import re
def kebab_case(string: str) -> str:
"""Convert a string to kebab case."""
string = string.replace("-", " ")
string = re.sub("([A-Z][a-z]+)", r" \1", string)
string = re.sub("([A-Z]+)", r" \1", string)
return "-".join(string.split()).lower()

View File

@ -11,6 +11,6 @@ def mock_openai_api_key() -> None:
@pytest.fixture(autouse=True)
def mock_history_dir(tmp_path: Path) -> None:
def mock_base_dir(tmp_path: Path) -> None:
"""Set a fake history directory."""
os.environ["OPENAI_HISTORY_DIR"] = str(tmp_path / ".llm_chat")
os.environ["OPENAI_BASE_DIR"] = str(tmp_path / ".llm_chat")

64
tests/test_bot.py Normal file
View File

@ -0,0 +1,64 @@
from pathlib import Path
import pytest
from llm_chat.bot import Bot, BotConfig, BotDoesNotExist, BotExists
def test_create_load_remove_bot(tmp_path: Path) -> None:
bot_name = "Test Bot"
bot_id = "test-bot"
with (tmp_path / "context.md").open("w") as f:
f.write("Hello, world!")
assert not (tmp_path / bot_id).exists()
Bot.create(
name=bot_name,
bot_dir=tmp_path,
context_files=[tmp_path / "context.md"],
)
assert (tmp_path / bot_id).exists()
assert (tmp_path / bot_id / "context").exists()
assert (tmp_path / bot_id / "context" / "context.md").exists()
assert (tmp_path / bot_id / f"{bot_id}.json").exists()
with (tmp_path / bot_id / f"{bot_id}.json").open() as f:
config = BotConfig.model_validate_json(f.read(), strict=True)
assert config.name == bot_name
assert config.bot_id == bot_id
assert config.context_files == ["context.md"]
with (tmp_path / bot_id / "context" / "context.md").open() as f:
assert f.read() == "Hello, world!"
bot = Bot.load(name=bot_name, bot_dir=tmp_path)
assert bot.config == config
assert bot.id == bot_id
assert bot.name == bot_name
Bot.remove(name=bot_name, bot_dir=tmp_path)
assert not (tmp_path / bot_id).exists()
def test_bot_does_not_exist(tmp_path: Path) -> None:
with pytest.raises(BotDoesNotExist):
Bot.load(name="Test Bot", bot_dir=tmp_path)
def test_bot_already_exists(tmp_path: Path) -> None:
bot_name = "Test Bot"
Bot.create(
name=bot_name,
bot_dir=tmp_path,
)
with pytest.raises(BotExists):
Bot.create(
name="Test Bot",
bot_dir=tmp_path,
)

View File

@ -4,7 +4,11 @@ from unittest.mock import patch
from zoneinfo import ZoneInfo
import pytest
from openai.types.chat import ChatCompletion, ChatCompletionMessage
from openai.types.chat.chat_completion import Choice
from openai.types.completion_usage import CompletionUsage
from llm_chat.bot import Bot
from llm_chat.chat import Chat, save_conversation
from llm_chat.models import Conversation, Message, Role
from llm_chat.settings import Model, OpenAISettings
@ -67,19 +71,21 @@ def test_load(tmp_path: Path) -> None:
)
# Save the conversation to a file
file_path = tmp_path / "conversation.json"
history_dir = tmp_path / "history"
history_dir.mkdir()
file_path = history_dir / "conversation.json"
with file_path.open("w") as f:
f.write(conversation.model_dump_json())
# Load the conversation from the file
loaded_chat = Chat.load(file_path, api_key="foo", history_dir=tmp_path)
loaded_chat = Chat.load(file_path, api_key="foo", base_dir=tmp_path)
# Check that the loaded conversation matches the original conversation
assert loaded_chat.settings.model == conversation.model
assert loaded_chat.settings.temperature == conversation.temperature
assert loaded_chat.conversation.messages == conversation.messages
assert loaded_chat.settings.api_key == "foo"
assert loaded_chat.settings.history_dir == tmp_path
assert loaded_chat.settings.base_dir == tmp_path
# We don't want to load the tokens or cost from the previous session
assert loaded_chat.conversation.completion_tokens == 0
@ -89,24 +95,70 @@ def test_load(tmp_path: Path) -> None:
def test_send_message() -> None:
with patch("llm_chat.chat.Chat._make_request") as mock_make_request:
mock_make_request.return_value = {
"choices": [{"message": {"content": "Hello!"}}],
"usage": {"completion_tokens": 1, "prompt_tokens": 1},
}
mock_make_request.return_value = ChatCompletion(
choices=[
Choice(
message=ChatCompletionMessage(content="Hello!", role="assistant"),
finish_reason="stop",
index=0,
),
],
id="foo",
created=0,
model="gpt-3.5-turbo-0613",
object="chat.completion",
usage=CompletionUsage(
completion_tokens=1,
prompt_tokens=1,
total_tokens=2,
),
)
conversation = Chat()
response = conversation.send_message("Hello")
assert isinstance(response, str)
assert response == "Hello!"
@pytest.mark.parametrize("model,cost", [(Model.GPT3, 0.000043), (Model.GPT4, 0.00105)])
@pytest.mark.parametrize(
"model,cost", [(Model.GPT3, round(0.000027, 6)), (Model.GPT4, 0.00105)]
)
def test_calculate_cost(model: Model, cost: float) -> None:
with patch("llm_chat.chat.Chat._make_request") as mock_make_request:
mock_make_request.return_value = {
"choices": [{"message": {"content": "Hello!"}}],
"usage": {"completion_tokens": 10, "prompt_tokens": 15},
}
mock_make_request.return_value = ChatCompletion(
choices=[
Choice(
message=ChatCompletionMessage(content="Hello!", role="assistant"),
finish_reason="stop",
index=0,
),
],
id="foo",
created=0,
model="gpt-3.5-turbo-0613",
object="chat.completion",
usage=CompletionUsage(
completion_tokens=10,
prompt_tokens=15,
total_tokens=25,
),
)
settings = OpenAISettings(model=model)
conversation = Chat(settings=settings)
_ = conversation.send_message("Hello")
assert conversation.cost == cost
def test_chat_with_bot(tmp_path: Path) -> None:
settings = OpenAISettings()
bot_name = "Test Bot"
context = "Hello, world!"
with (tmp_path / "context.md").open("w") as f:
f.write(context)
Bot.create(
name=bot_name, bot_dir=settings.bot_dir, context_files=[tmp_path / "context.md"]
)
chat = Chat(settings=settings, bot=bot_name)
assert chat.conversation.messages[-1].content == context

View File

@ -9,9 +9,9 @@ from pytest import MonkeyPatch
from rich.console import Console
from typer.testing import CliRunner
import llm_chat
import llm_chat.cli
from llm_chat.chat import ChatProtocol
from llm_chat.cli import app
from llm_chat.cli.main import app
from llm_chat.models import Conversation, Message, Role
from llm_chat.settings import Model, OpenAISettings
@ -37,6 +37,11 @@ class ChatFake:
def _set_args(self, **kwargs: Any) -> None:
self.args = kwargs
@property
def bot(self) -> str:
"""Get the name of the bot the conversation is with."""
return self.args.get("bot", "")
@property
def cost(self) -> float:
"""Get the cost of the conversation."""
@ -77,9 +82,9 @@ def test_chat(monkeypatch: MonkeyPatch) -> None:
mock_read_user_input = MagicMock(side_effect=["Hello", "/q"])
monkeypatch.setattr(llm_chat.cli, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli, "read_user_input", mock_read_user_input)
monkeypatch.setattr(llm_chat.cli.main, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli.main, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli.main, "read_user_input", mock_read_user_input)
result = runner.invoke(app, ["chat"])
assert result.exit_code == 0
@ -107,9 +112,9 @@ def test_chat_with_context(
mock_read_user_input = MagicMock(side_effect=["Hello", "/q"])
monkeypatch.setattr(llm_chat.cli, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli, "read_user_input", mock_read_user_input)
monkeypatch.setattr(llm_chat.cli.main, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli.main, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli.main, "read_user_input", mock_read_user_input)
result = runner.invoke(app, ["chat", argument, str(tmp_file)])
assert result.exit_code == 0
@ -139,9 +144,9 @@ def test_chat_with_name(
mock_read_user_input = MagicMock(side_effect=["Hello", "/q"])
monkeypatch.setattr(llm_chat.cli, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli, "read_user_input", mock_read_user_input)
monkeypatch.setattr(llm_chat.cli.main, "get_chat", mock_get_chat)
monkeypatch.setattr(llm_chat.cli.main, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli.main, "read_user_input", mock_read_user_input)
result = runner.invoke(app, ["chat", argument, name])
assert result.exit_code == 0
@ -179,9 +184,9 @@ def test_load(monkeypatch: MonkeyPatch, tmp_path: Path) -> None:
mock_read_user_input = MagicMock(side_effect=["Hello", "/q"])
monkeypatch.setattr(llm_chat.cli, "get_chat_class", mock_get_chat)
monkeypatch.setattr(llm_chat.cli, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli, "read_user_input", mock_read_user_input)
monkeypatch.setattr(llm_chat.cli.main, "get_chat_class", mock_get_chat)
monkeypatch.setattr(llm_chat.cli.main, "get_console", mock_get_console)
monkeypatch.setattr(llm_chat.cli.main, "read_user_input", mock_read_user_input)
# Load the conversation from the file
result = runner.invoke(app, ["load", str(file_path)])

22
tests/test_utils.py Normal file
View File

@ -0,0 +1,22 @@
import pytest
from llm_chat.utils import kebab_case
@pytest.mark.parametrize(
"string,expected",
[
("fooBar", "foo-bar"),
("FooBar", "foo-bar"),
("Foo Bar", "foo-bar"),
("1Foo2Bar3", "1-foo2-bar3"),
],
ids=[
"fooBar",
"FooBar",
"Foo Bar",
"1Foo2Bar3",
],
)
def test_kebab_case(string: str, expected: str) -> None:
assert kebab_case(string) == expected