Store conversation history on session end
At the end of each sesssion the conversation is stored to a directory (defaulting to `.history` in the currrent working directory) as a JSON object. Note, the session must be ended by sending the quit message (/q) for the conversation to be saved. Ctrl+C will not work.
This commit is contained in:
parent
1670383fee
commit
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@ -1,5 +1,6 @@
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.idea
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.idea
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.vscode
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.vscode
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.history
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# Created by https://www.toptal.com/developers/gitignore/api/python,vim,asdf
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# Created by https://www.toptal.com/developers/gitignore/api/python,vim,asdf
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# Edit at https://www.toptal.com/developers/gitignore?templates=python,vim,asdf
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# Edit at https://www.toptal.com/developers/gitignore?templates=python,vim,asdf
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@ -1,6 +1,6 @@
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[tool.poetry]
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[tool.poetry]
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name = "llm-chat"
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name = "llm-chat"
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version = "0.3.0"
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version = "0.4.0"
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description = "A general CLI interface for large language models."
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description = "A general CLI interface for large language models."
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authors = ["Paul Harrison <paul@harrison.sh>"]
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authors = ["Paul Harrison <paul@harrison.sh>"]
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readme = "README.md"
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readme = "README.md"
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@ -1,5 +1,8 @@
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from datetime import datetime
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from enum import StrEnum, auto
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from enum import StrEnum, auto
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from pathlib import Path
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from typing import Any, Protocol
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from typing import Any, Protocol
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from zoneinfo import ZoneInfo
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from openai import ChatCompletion
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from openai import ChatCompletion
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from openai.openai_object import OpenAIObject
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from openai.openai_object import OpenAIObject
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@ -18,6 +21,20 @@ INITIAL_SYSTEM_MESSAGES = [
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]
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]
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def save_conversation(
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conversation: Conversation, history_dir: Path, dt: datetime
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) -> None:
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"""Store a conversation in the history directory."""
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if conversation.prompt_tokens == 0:
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return
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history_dir.mkdir(parents=True, exist_ok=True)
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path = history_dir / f"{dt.strftime('%Y%m%d%H%M%S')}.json"
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with path.open(mode="w") as f:
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f.write(conversation.model_dump_json(indent=2))
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class Token(StrEnum):
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class Token(StrEnum):
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"""Token type for the OpenAI chat."""
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"""Token type for the OpenAI chat."""
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@ -32,6 +49,9 @@ class ChatProtocol(Protocol):
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def cost(self) -> float:
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def cost(self) -> float:
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"""Get the cost of the conversation."""
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"""Get the cost of the conversation."""
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def save(self) -> None:
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"""Save the conversation to the history directory."""
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def send_message(self, message: str) -> str:
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def send_message(self, message: str) -> str:
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"""Send a message to the assistant."""
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"""Send a message to the assistant."""
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}
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}
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def __init__(
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def __init__(
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self, settings: OpenAISettings | None = None, context: list[Message] = []
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self,
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settings: OpenAISettings | None = None,
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context: list[Message] = [],
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) -> None:
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) -> None:
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self._settings = settings
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self._settings = settings
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self.conversation = Conversation(
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self.conversation = Conversation(
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messages=INITIAL_SYSTEM_MESSAGES + context,
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messages=INITIAL_SYSTEM_MESSAGES + context,
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model=self.settings.model,
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temperature=self.settings.temperature,
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)
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)
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self._start_time = datetime.now(tz=ZoneInfo("UTC"))
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@property
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@property
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def settings(self) -> OpenAISettings:
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def settings(self) -> OpenAISettings:
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6,
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6,
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)
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)
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def save(self) -> None:
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"""Save the conversation to the history directory."""
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save_conversation(
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conversation=self.conversation,
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history_dir=self.settings.history_dir,
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dt=self._start_time,
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)
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def send_message(self, prompt: str) -> str:
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def send_message(self, prompt: str) -> str:
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"""Send a message to the assistant.
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"""Send a message to the assistant.
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@ -124,6 +124,7 @@ def chat(
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prompt = read_user_input(session)
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prompt = read_user_input(session)
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if prompt.strip() == "/q":
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if prompt.strip() == "/q":
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finished = True
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finished = True
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current_chat.save()
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else:
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else:
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response = current_chat.send_message(prompt.strip())
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response = current_chat.send_message(prompt.strip())
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console.print(Markdown(response))
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console.print(Markdown(response))
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@ -2,6 +2,8 @@ from enum import StrEnum, auto
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from pydantic import BaseModel, ConfigDict
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from pydantic import BaseModel, ConfigDict
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from llm_chat.settings import DEFAULT_TEMPERATURE, Model
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class Role(StrEnum):
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class Role(StrEnum):
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"""Role of a user in the chat."""
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"""Role of a user in the chat."""
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"""Conversation in the chat."""
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"""Conversation in the chat."""
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messages: list[Message]
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messages: list[Message]
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model: Model
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temperature: float = DEFAULT_TEMPERATURE
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completion_tokens: int = 0
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completion_tokens: int = 0
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prompt_tokens: int = 0
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prompt_tokens: int = 0
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cost: float = 0.0
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cost: float = 0.0
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from enum import StrEnum
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from enum import StrEnum
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from pathlib import Path
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from pydantic_settings import BaseSettings, SettingsConfigDict
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from pydantic_settings import BaseSettings, SettingsConfigDict
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api_key: str = ""
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api_key: str = ""
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model: Model = DEFAULT_MODEL
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model: Model = DEFAULT_MODEL
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temperature: float = DEFAULT_TEMPERATURE
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temperature: float = DEFAULT_TEMPERATURE
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history_dir: Path = Path().absolute() / ".history"
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model_config: SettingsConfigDict = SettingsConfigDict( # type: ignore[misc]
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model_config: SettingsConfigDict = SettingsConfigDict( # type: ignore[misc]
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env_file=".env",
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env_file=".env",
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from datetime import datetime
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from pathlib import Path
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from unittest.mock import patch
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from unittest.mock import patch
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from zoneinfo import ZoneInfo
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import pytest
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import pytest
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from llm_chat.chat import Chat
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from llm_chat.chat import Chat, save_conversation
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from llm_chat.models import Conversation, Message, Role
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from llm_chat.settings import Model, OpenAISettings
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from llm_chat.settings import Model, OpenAISettings
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def test_save_conversation(tmp_path: Path) -> None:
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conversation = Conversation(
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messages=[
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Message(role=Role.SYSTEM, content="Hello!"),
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Message(role=Role.USER, content="Hi!"),
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Message(role=Role.ASSISTANT, content="How are you?"),
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],
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model=Model.GPT3,
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temperature=0.5,
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completion_tokens=10,
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prompt_tokens=15,
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cost=0.000043,
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)
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path = tmp_path / ".history"
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expected_file_path = path / "20210101120000.json"
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dt = datetime(2021, 1, 1, 12, 0, 0, tzinfo=ZoneInfo("UTC"))
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assert not path.exists()
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save_conversation(
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conversation=conversation,
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history_dir=path,
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dt=dt,
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)
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assert path.exists()
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assert path.is_dir()
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assert expected_file_path in path.iterdir()
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with expected_file_path.open() as f:
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conversation_from_file = Conversation.model_validate_json(f.read())
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assert conversation == conversation_from_file
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def test_send_message() -> None:
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def test_send_message() -> None:
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with patch("llm_chat.chat.Chat._make_request") as mock_make_request:
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with patch("llm_chat.chat.Chat._make_request") as mock_make_request:
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mock_make_request.return_value = {
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mock_make_request.return_value = {
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"""Get the cost of the conversation."""
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"""Get the cost of the conversation."""
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return 0.0
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return 0.0
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def save(self) -> None:
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"""Dummy save method."""
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pass
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def send_message(self, message: str) -> str:
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def send_message(self, message: str) -> str:
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"""Echo the received message."""
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"""Echo the received message."""
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self.received_messages.append(message)
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self.received_messages.append(message)
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Loading…
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