test_fake_chat_model.py — langchain Source File
Architecture documentation for test_fake_chat_model.py, a python file in the langchain codebase. 10 imports, 0 dependents.
Entity Profile
Dependency Diagram
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Relationship Graph
Source Code
"""Tests for verifying that testing utility code works as expected."""
import time
from itertools import cycle
from typing import Any, cast
from uuid import UUID
from typing_extensions import override
from langchain_core.callbacks.base import AsyncCallbackHandler
from langchain_core.language_models import (
FakeListChatModel,
FakeMessagesListChatModel,
GenericFakeChatModel,
ParrotFakeChatModel,
)
from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage, HumanMessage
from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
from tests.unit_tests.stubs import (
_any_id_ai_message,
_any_id_ai_message_chunk,
_any_id_human_message,
)
def test_generic_fake_chat_model_invoke() -> None:
# Will alternate between responding with hello and goodbye
infinite_cycle = cycle([AIMessage(content="hello"), AIMessage(content="goodbye")])
model = GenericFakeChatModel(messages=infinite_cycle)
response = model.invoke("meow")
assert response == _any_id_ai_message(content="hello")
response = model.invoke("kitty")
assert response == _any_id_ai_message(content="goodbye")
response = model.invoke("meow")
assert response == _any_id_ai_message(content="hello")
async def test_generic_fake_chat_model_ainvoke() -> None:
# Will alternate between responding with hello and goodbye
infinite_cycle = cycle([AIMessage(content="hello"), AIMessage(content="goodbye")])
model = GenericFakeChatModel(messages=infinite_cycle)
response = await model.ainvoke("meow")
assert response == _any_id_ai_message(content="hello")
response = await model.ainvoke("kitty")
assert response == _any_id_ai_message(content="goodbye")
response = await model.ainvoke("meow")
assert response == _any_id_ai_message(content="hello")
async def test_generic_fake_chat_model_stream() -> None:
"""Test streaming."""
infinite_cycle = cycle(
[
AIMessage(content="hello goodbye"),
]
)
model = GenericFakeChatModel(messages=infinite_cycle)
chunks = [chunk async for chunk in model.astream("meow")]
assert chunks == [
_any_id_ai_message_chunk(content="hello"),
// ... (196 more lines)Domain
Subdomains
Functions
Classes
Dependencies
- itertools
- langchain_core.callbacks.base
- langchain_core.language_models
- langchain_core.messages
- langchain_core.outputs
- tests.unit_tests.stubs
- time
- typing
- typing_extensions
- uuid
Source
Frequently Asked Questions
What does test_fake_chat_model.py do?
test_fake_chat_model.py is a source file in the langchain codebase, written in python. It belongs to the CoreAbstractions domain, MessageSchema subdomain.
What functions are defined in test_fake_chat_model.py?
test_fake_chat_model.py defines 8 function(s): test_callback_handlers, test_chat_model_inputs, test_fake_list_chat_model_batch, test_fake_messages_list_chat_model_sleep_delay, test_generic_fake_chat_model_ainvoke, test_generic_fake_chat_model_astream_log, test_generic_fake_chat_model_invoke, test_generic_fake_chat_model_stream.
What does test_fake_chat_model.py depend on?
test_fake_chat_model.py imports 10 module(s): itertools, langchain_core.callbacks.base, langchain_core.language_models, langchain_core.messages, langchain_core.outputs, tests.unit_tests.stubs, time, typing, and 2 more.
Where is test_fake_chat_model.py in the architecture?
test_fake_chat_model.py is located at libs/core/tests/unit_tests/fake/test_fake_chat_model.py (domain: CoreAbstractions, subdomain: MessageSchema, directory: libs/core/tests/unit_tests/fake).
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