mirror of
https://github.com/hwchase17/langchain
synced 2024-11-11 19:11:02 +00:00
a0c2281540
```python
"""python scripts/update_mypy_ruff.py"""
import glob
import tomllib
from pathlib import Path
import toml
import subprocess
import re
ROOT_DIR = Path(__file__).parents[1]
def main():
for path in glob.glob(str(ROOT_DIR / "libs/**/pyproject.toml"), recursive=True):
print(path)
with open(path, "rb") as f:
pyproject = tomllib.load(f)
try:
pyproject["tool"]["poetry"]["group"]["typing"]["dependencies"]["mypy"] = (
"^1.10"
)
pyproject["tool"]["poetry"]["group"]["lint"]["dependencies"]["ruff"] = (
"^0.5"
)
except KeyError:
continue
with open(path, "w") as f:
toml.dump(pyproject, f)
cwd = "/".join(path.split("/")[:-1])
completed = subprocess.run(
"poetry lock --no-update; poetry install --with typing; poetry run mypy . --no-color",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
logs = completed.stdout.split("\n")
to_ignore = {}
for l in logs:
if re.match("^(.*)\:(\d+)\: error:.*\[(.*)\]", l):
path, line_no, error_type = re.match(
"^(.*)\:(\d+)\: error:.*\[(.*)\]", l
).groups()
if (path, line_no) in to_ignore:
to_ignore[(path, line_no)].append(error_type)
else:
to_ignore[(path, line_no)] = [error_type]
print(len(to_ignore))
for (error_path, line_no), error_types in to_ignore.items():
all_errors = ", ".join(error_types)
full_path = f"{cwd}/{error_path}"
try:
with open(full_path, "r") as f:
file_lines = f.readlines()
except FileNotFoundError:
continue
file_lines[int(line_no) - 1] = (
file_lines[int(line_no) - 1][:-1] + f" # type: ignore[{all_errors}]\n"
)
with open(full_path, "w") as f:
f.write("".join(file_lines))
subprocess.run(
"poetry run ruff format .; poetry run ruff --select I --fix .",
cwd=cwd,
shell=True,
capture_output=True,
text=True,
)
if __name__ == "__main__":
main()
```
408 lines
14 KiB
Python
408 lines
14 KiB
Python
"""Test ChatGroq chat model."""
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import json
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from typing import Any, Optional
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import pytest
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from langchain_core.messages import (
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AIMessage,
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AIMessageChunk,
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BaseMessage,
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BaseMessageChunk,
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HumanMessage,
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SystemMessage,
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)
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from langchain_core.outputs import ChatGeneration, LLMResult
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from langchain_core.pydantic_v1 import BaseModel, Field
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from langchain_groq import ChatGroq
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from tests.unit_tests.fake.callbacks import (
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FakeCallbackHandler,
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FakeCallbackHandlerWithChatStart,
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)
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#
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# Smoke test Runnable interface
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#
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@pytest.mark.scheduled
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def test_invoke() -> None:
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"""Test Chat wrapper."""
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chat = ChatGroq( # type: ignore[call-arg]
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temperature=0.7,
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base_url=None,
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groq_proxy=None,
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timeout=10.0,
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max_retries=3,
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http_client=None,
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n=1,
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max_tokens=10,
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default_headers=None,
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default_query=None,
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)
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message = HumanMessage(content="Welcome to the Groqetship")
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response = chat.invoke([message])
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assert isinstance(response, BaseMessage)
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assert isinstance(response.content, str)
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@pytest.mark.scheduled
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async def test_ainvoke() -> None:
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"""Test ainvoke tokens from ChatGroq."""
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chat = ChatGroq(max_tokens=10) # type: ignore[call-arg]
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result = await chat.ainvoke("Welcome to the Groqetship!", config={"tags": ["foo"]})
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assert isinstance(result, BaseMessage)
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assert isinstance(result.content, str)
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@pytest.mark.scheduled
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def test_batch() -> None:
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"""Test batch tokens from ChatGroq."""
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chat = ChatGroq(max_tokens=10) # type: ignore[call-arg]
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result = chat.batch(["Hello!", "Welcome to the Groqetship!"])
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for token in result:
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assert isinstance(token, BaseMessage)
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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async def test_abatch() -> None:
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"""Test abatch tokens from ChatGroq."""
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chat = ChatGroq(max_tokens=10) # type: ignore[call-arg]
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result = await chat.abatch(["Hello!", "Welcome to the Groqetship!"])
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for token in result:
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assert isinstance(token, BaseMessage)
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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async def test_stream() -> None:
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"""Test streaming tokens from Groq."""
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chat = ChatGroq(max_tokens=10) # type: ignore[call-arg]
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for token in chat.stream("Welcome to the Groqetship!"):
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assert isinstance(token, BaseMessageChunk)
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assert isinstance(token.content, str)
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@pytest.mark.scheduled
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async def test_astream() -> None:
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"""Test streaming tokens from Groq."""
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chat = ChatGroq(max_tokens=10) # type: ignore[call-arg]
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full: Optional[BaseMessageChunk] = None
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chunks_with_token_counts = 0
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async for token in chat.astream("Welcome to the Groqetship!"):
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assert isinstance(token, AIMessageChunk)
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assert isinstance(token.content, str)
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full = token if full is None else full + token
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if token.usage_metadata is not None:
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chunks_with_token_counts += 1
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if chunks_with_token_counts != 1:
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raise AssertionError(
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"Expected exactly one chunk with token counts. "
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"AIMessageChunk aggregation adds counts. Check that "
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"this is behaving properly."
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)
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assert isinstance(full, AIMessageChunk)
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assert full.usage_metadata is not None
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assert full.usage_metadata["input_tokens"] > 0
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assert full.usage_metadata["output_tokens"] > 0
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assert (
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full.usage_metadata["input_tokens"] + full.usage_metadata["output_tokens"]
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== full.usage_metadata["total_tokens"]
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)
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#
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# Test Legacy generate methods
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#
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@pytest.mark.scheduled
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def test_generate() -> None:
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"""Test sync generate."""
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n = 1
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chat = ChatGroq(max_tokens=10) # type: ignore[call-arg]
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message = HumanMessage(content="Hello", n=1)
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response = chat.generate([[message], [message]])
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assert isinstance(response, LLMResult)
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assert len(response.generations) == 2
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assert response.llm_output
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assert response.llm_output["model_name"] == chat.model_name
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for generations in response.generations:
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assert len(generations) == n
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for generation in generations:
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assert isinstance(generation, ChatGeneration)
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assert isinstance(generation.text, str)
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assert generation.text == generation.message.content
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@pytest.mark.scheduled
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async def test_agenerate() -> None:
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"""Test async generation."""
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n = 1
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chat = ChatGroq(max_tokens=10, n=1) # type: ignore[call-arg]
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message = HumanMessage(content="Hello")
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response = await chat.agenerate([[message], [message]])
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assert isinstance(response, LLMResult)
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assert len(response.generations) == 2
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assert response.llm_output
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assert response.llm_output["model_name"] == chat.model_name
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for generations in response.generations:
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assert len(generations) == n
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for generation in generations:
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assert isinstance(generation, ChatGeneration)
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assert isinstance(generation.text, str)
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assert generation.text == generation.message.content
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#
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# Test streaming flags in invoke and generate
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#
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@pytest.mark.scheduled
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def test_invoke_streaming() -> None:
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"""Test that streaming correctly invokes on_llm_new_token callback."""
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callback_handler = FakeCallbackHandler()
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chat = ChatGroq( # type: ignore[call-arg]
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max_tokens=2,
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streaming=True,
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temperature=0,
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callbacks=[callback_handler],
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)
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message = HumanMessage(content="Welcome to the Groqetship")
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response = chat.invoke([message])
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assert callback_handler.llm_streams > 0
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assert isinstance(response, BaseMessage)
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@pytest.mark.scheduled
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async def test_agenerate_streaming() -> None:
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"""Test that streaming correctly invokes on_llm_new_token callback."""
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callback_handler = FakeCallbackHandlerWithChatStart()
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chat = ChatGroq( # type: ignore[call-arg]
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max_tokens=10,
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streaming=True,
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temperature=0,
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callbacks=[callback_handler],
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)
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message = HumanMessage(content="Welcome to the Groqetship")
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response = await chat.agenerate([[message], [message]])
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assert callback_handler.llm_streams > 0
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assert isinstance(response, LLMResult)
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assert len(response.generations) == 2
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assert response.llm_output is not None
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assert response.llm_output["model_name"] == chat.model_name
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for generations in response.generations:
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assert len(generations) == 1
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for generation in generations:
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assert isinstance(generation, ChatGeneration)
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assert isinstance(generation.text, str)
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assert generation.text == generation.message.content
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#
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# Misc tests
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#
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def test_streaming_generation_info() -> None:
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"""Test that generation info is preserved when streaming."""
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class _FakeCallback(FakeCallbackHandler):
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saved_things: dict = {}
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def on_llm_end(
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self,
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*args: Any,
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**kwargs: Any,
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) -> Any:
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# Save the generation
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self.saved_things["generation"] = args[0]
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callback = _FakeCallback()
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chat = ChatGroq( # type: ignore[call-arg]
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max_tokens=2,
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temperature=0,
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callbacks=[callback],
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)
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list(chat.stream("Respond with the single word Hello", stop=["o"]))
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generation = callback.saved_things["generation"]
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# `Hello!` is two tokens, assert that that is what is returned
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assert isinstance(generation, LLMResult)
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assert generation.generations[0][0].text == "Hell"
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def test_system_message() -> None:
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"""Test ChatGroq wrapper with system message."""
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chat = ChatGroq(max_tokens=10) # type: ignore[call-arg]
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system_message = SystemMessage(content="You are to chat with the user.")
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human_message = HumanMessage(content="Hello")
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response = chat.invoke([system_message, human_message])
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assert isinstance(response, BaseMessage)
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assert isinstance(response.content, str)
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@pytest.mark.xfail(reason="Groq tool_choice doesn't currently force a tool call")
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def test_tool_choice() -> None:
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"""Test that tool choice is respected."""
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llm = ChatGroq() # type: ignore[call-arg]
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class MyTool(BaseModel):
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name: str
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age: int
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with_tool = llm.bind_tools([MyTool], tool_choice="MyTool")
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resp = with_tool.invoke("Who was the 27 year old named Erick?")
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assert isinstance(resp, AIMessage)
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assert resp.content == "" # should just be tool call
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tool_calls = resp.additional_kwargs["tool_calls"]
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assert len(tool_calls) == 1
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tool_call = tool_calls[0]
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assert tool_call["function"]["name"] == "MyTool"
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assert json.loads(tool_call["function"]["arguments"]) == {
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"age": 27,
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"name": "Erick",
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}
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assert tool_call["type"] == "function"
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assert isinstance(resp.tool_calls, list)
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assert len(resp.tool_calls) == 1
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tool_call = resp.tool_calls[0]
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assert tool_call["name"] == "MyTool"
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assert tool_call["args"] == {"name": "Erick", "age": 27}
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@pytest.mark.xfail(reason="Groq tool_choice doesn't currently force a tool call")
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def test_tool_choice_bool() -> None:
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"""Test that tool choice is respected just passing in True."""
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llm = ChatGroq() # type: ignore[call-arg]
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class MyTool(BaseModel):
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name: str
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age: int
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with_tool = llm.bind_tools([MyTool], tool_choice=True)
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resp = with_tool.invoke("Who was the 27 year old named Erick?")
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assert isinstance(resp, AIMessage)
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assert resp.content == "" # should just be tool call
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tool_calls = resp.additional_kwargs["tool_calls"]
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assert len(tool_calls) == 1
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tool_call = tool_calls[0]
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assert tool_call["function"]["name"] == "MyTool"
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assert json.loads(tool_call["function"]["arguments"]) == {
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"age": 27,
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"name": "Erick",
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}
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assert tool_call["type"] == "function"
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@pytest.mark.xfail(reason="Groq tool_choice doesn't currently force a tool call")
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def test_streaming_tool_call() -> None:
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"""Test that tool choice is respected."""
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llm = ChatGroq() # type: ignore[call-arg]
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class MyTool(BaseModel):
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name: str
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age: int
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with_tool = llm.bind_tools([MyTool], tool_choice="MyTool")
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resp = with_tool.stream("Who was the 27 year old named Erick?")
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additional_kwargs = None
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for chunk in resp:
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assert isinstance(chunk, AIMessageChunk)
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assert chunk.content == "" # should just be tool call
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additional_kwargs = chunk.additional_kwargs
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assert additional_kwargs is not None
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tool_calls = additional_kwargs["tool_calls"]
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assert len(tool_calls) == 1
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tool_call = tool_calls[0]
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assert tool_call["function"]["name"] == "MyTool"
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assert json.loads(tool_call["function"]["arguments"]) == {
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"age": 27,
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"name": "Erick",
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}
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assert tool_call["type"] == "function"
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assert isinstance(chunk, AIMessageChunk)
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assert isinstance(chunk.tool_call_chunks, list)
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assert len(chunk.tool_call_chunks) == 1
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tool_call_chunk = chunk.tool_call_chunks[0]
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assert tool_call_chunk["name"] == "MyTool"
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assert isinstance(tool_call_chunk["args"], str)
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assert json.loads(tool_call_chunk["args"]) == {"name": "Erick", "age": 27}
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@pytest.mark.xfail(reason="Groq tool_choice doesn't currently force a tool call")
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async def test_astreaming_tool_call() -> None:
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"""Test that tool choice is respected."""
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llm = ChatGroq() # type: ignore[call-arg]
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class MyTool(BaseModel):
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name: str
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age: int
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with_tool = llm.bind_tools([MyTool], tool_choice="MyTool")
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resp = with_tool.astream("Who was the 27 year old named Erick?")
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additional_kwargs = None
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async for chunk in resp:
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assert isinstance(chunk, AIMessageChunk)
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assert chunk.content == "" # should just be tool call
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additional_kwargs = chunk.additional_kwargs
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assert additional_kwargs is not None
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tool_calls = additional_kwargs["tool_calls"]
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assert len(tool_calls) == 1
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tool_call = tool_calls[0]
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assert tool_call["function"]["name"] == "MyTool"
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assert json.loads(tool_call["function"]["arguments"]) == {
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"age": 27,
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"name": "Erick",
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}
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assert tool_call["type"] == "function"
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assert isinstance(chunk, AIMessageChunk)
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assert isinstance(chunk.tool_call_chunks, list)
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assert len(chunk.tool_call_chunks) == 1
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tool_call_chunk = chunk.tool_call_chunks[0]
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assert tool_call_chunk["name"] == "MyTool"
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assert isinstance(tool_call_chunk["args"], str)
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assert json.loads(tool_call_chunk["args"]) == {"name": "Erick", "age": 27}
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@pytest.mark.scheduled
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def test_json_mode_structured_output() -> None:
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"""Test with_structured_output with json"""
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class Joke(BaseModel):
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"""Joke to tell user."""
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setup: str = Field(description="question to set up a joke")
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punchline: str = Field(description="answer to resolve the joke")
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chat = ChatGroq().with_structured_output(Joke, method="json_mode") # type: ignore[call-arg]
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result = chat.invoke(
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"Tell me a joke about cats, respond in JSON with `setup` and `punchline` keys"
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)
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assert type(result) == Joke
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assert len(result.setup) != 0
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assert len(result.punchline) != 0
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# Groq does not currently support N > 1
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# @pytest.mark.scheduled
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# def test_chat_multiple_completions() -> None:
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# """Test ChatGroq wrapper with multiple completions."""
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# chat = ChatGroq(max_tokens=10, n=5)
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# message = HumanMessage(content="Hello")
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# response = chat._generate([message])
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# assert isinstance(response, ChatResult)
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# assert len(response.generations) == 5
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# for generation in response.generations:
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# assert isinstance(generation.message, BaseMessage)
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# assert isinstance(generation.message.content, str)
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