langchain[patch]: Mask API key for ForeFrontAI LLM (#14013)

- **Description:** Mask API key for ForeFrontAI LLM and associated unit
tests
  - **Issue:** https://github.com/langchain-ai/langchain/issues/12165
  - **Dependencies:** N/A
  - **Tag maintainer:** @eyurtsev 
  - **Twitter handle:** `__mmahmad__`

I made the API key non-optional since linting required adding validation
for None, but the key is required per documentation:
https://python.langchain.com/docs/integrations/llms/forefrontai
This commit is contained in:
Mohammad Ahmad 2023-11-29 13:12:19 -08:00 committed by GitHub
parent a0e859df51
commit 1600ebe6c7
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2 changed files with 57 additions and 7 deletions

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@ -1,12 +1,12 @@
from typing import Any, Dict, List, Mapping, Optional
import requests
from langchain_core.pydantic_v1 import Extra, root_validator
from langchain_core.pydantic_v1 import Extra, SecretStr, root_validator
from langchain.callbacks.manager import CallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_stop_tokens
from langchain.utils import get_from_dict_or_env
from langchain.utils import convert_to_secret_str, get_from_dict_or_env
class ForefrontAI(LLM):
@ -41,7 +41,7 @@ class ForefrontAI(LLM):
repetition_penalty: int = 1
"""Penalizes repeated tokens according to frequency."""
forefrontai_api_key: Optional[str] = None
forefrontai_api_key: SecretStr = None
base_url: Optional[str] = None
"""Base url to use, if None decides based on model name."""
@ -54,10 +54,9 @@ class ForefrontAI(LLM):
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that api key exists in environment."""
forefrontai_api_key = get_from_dict_or_env(
values, "forefrontai_api_key", "FOREFRONTAI_API_KEY"
values["forefrontai_api_key"] = convert_to_secret_str(
get_from_dict_or_env(values, "forefrontai_api_key", "FOREFRONTAI_API_KEY")
)
values["forefrontai_api_key"] = forefrontai_api_key
return values
@property
@ -102,10 +101,11 @@ class ForefrontAI(LLM):
response = ForefrontAI("Tell me a joke.")
"""
auth_value = f"Bearer {self.forefrontai_api_key.get_secret_value()}"
response = requests.post(
url=self.endpoint_url,
headers={
"Authorization": f"Bearer {self.forefrontai_api_key}",
"Authorization": auth_value,
"Content-Type": "application/json",
},
json={"text": prompt, **self._default_params, **kwargs},

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@ -0,0 +1,50 @@
"""Test ForeFrontAI LLM"""
from typing import cast
from langchain_core.pydantic_v1 import SecretStr
from pytest import CaptureFixture, MonkeyPatch
from langchain.llms.forefrontai import ForefrontAI
def test_forefrontai_api_key_is_secret_string() -> None:
"""Test that the API key is stored as a SecretStr."""
llm = ForefrontAI(forefrontai_api_key="secret-api-key", temperature=0.2)
assert isinstance(llm.forefrontai_api_key, SecretStr)
def test_forefrontai_api_key_masked_when_passed_from_env(
monkeypatch: MonkeyPatch, capsys: CaptureFixture
) -> None:
"""Test that the API key is masked when passed from an environment variable."""
monkeypatch.setenv("FOREFRONTAI_API_KEY", "secret-api-key")
llm = ForefrontAI(temperature=0.2)
print(llm.forefrontai_api_key, end="")
captured = capsys.readouterr()
assert captured.out == "**********"
def test_forefrontai_api_key_masked_when_passed_via_constructor(
capsys: CaptureFixture,
) -> None:
"""Test that the API key is masked when passed via the constructor."""
llm = ForefrontAI(
forefrontai_api_key="secret-api-key",
temperature=0.2,
)
print(llm.forefrontai_api_key, end="")
captured = capsys.readouterr()
assert captured.out == "**********"
def test_forefrontai_uses_actual_secret_value_from_secretstr() -> None:
"""Test that the actual secret value is correctly retrieved."""
llm = ForefrontAI(
forefrontai_api_key="secret-api-key",
temperature=0.2,
)
assert (
cast(SecretStr, llm.forefrontai_api_key).get_secret_value() == "secret-api-key"
)