langchain/libs/community/langchain_community/llms/solar.py
Leonid Ganeline 4cb5f4c353
community[patch]: import flattening fix (#20110)
This PR should make it easier for linters to do type checking and for IDEs to jump to definition of code.

See #20050 as a template for this PR.
- As a byproduct: Added 3 missed `test_imports`.
- Added missed `SolarChat` in to __init___.py Added it into test_import
ut.
- Added `# type: ignore` to fix linting. It is not clear, why linting
errors appear after ^ changes.

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2024-04-10 13:01:19 -04:00

123 lines
4.0 KiB
Python

from typing import Any, Dict, List, Optional
import requests
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models import LLM
from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
from langchain_community.llms.utils import enforce_stop_tokens
SOLAR_SERVICE_URL_BASE = "https://api.upstage.ai/v1/solar"
SOLAR_SERVICE = "https://api.upstage.ai"
class _SolarClient(BaseModel):
"""An API client that talks to the Solar server."""
api_key: SecretStr
"""The API key to use for authentication."""
base_url: str = SOLAR_SERVICE_URL_BASE
def completion(self, request: Any) -> Any:
headers = {"Authorization": f"Bearer {self.api_key.get_secret_value()}"}
response = requests.post(
f"{self.base_url}/chat/completions",
headers=headers,
json=request,
)
if not response.ok:
raise ValueError(f"HTTP {response.status_code} error: {response.text}")
return response.json()["choices"][0]["message"]["content"]
class SolarCommon(BaseModel):
"""Common configuration for Solar LLMs."""
_client: _SolarClient
base_url: str = SOLAR_SERVICE_URL_BASE
solar_api_key: Optional[SecretStr] = Field(default=None, alias="api_key")
"""Solar API key. Get it here: https://console.upstage.ai/services/solar"""
model_name: str = Field(default="solar-1-mini-chat", alias="model")
"""Model name. Available models listed here: https://console.upstage.ai/services/solar"""
max_tokens: int = Field(default=1024, alias="max context")
temperature = 0.3
class Config:
allow_population_by_field_name = True
arbitrary_types_allowed = True
extra = "ignore"
@property
def lc_secrets(self) -> dict:
return {"solar_api_key": "SOLAR_API_KEY"}
@property
def _default_params(self) -> Dict[str, Any]:
return {
"model": self.model_name,
"max_tokens": self.max_tokens,
"temperature": self.temperature,
}
@property
def _invocation_params(self) -> Dict[str, Any]:
return {**{"model": self.model_name}, **self._default_params}
@root_validator(pre=True)
def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
return values
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
api_key = get_from_dict_or_env(values, "solar_api_key", "SOLAR_API_KEY")
if api_key is None or len(api_key) == 0:
raise ValueError("SOLAR_API_KEY must be configured")
values["solar_api_key"] = convert_to_secret_str(api_key)
if "base_url" not in values:
values["base_url"] = SOLAR_SERVICE_URL_BASE
if "base_url" in values and not values["base_url"].startswith(SOLAR_SERVICE):
raise ValueError("base_url must match with: " + SOLAR_SERVICE)
values["_client"] = _SolarClient(
api_key=values["solar_api_key"], base_url=values["base_url"]
)
return values
@property
def _llm_type(self) -> str:
return "solar"
class Solar(SolarCommon, LLM):
"""Solar large language models.
To use, you should have the environment variable
``SOLAR_API_KEY`` set with your API key.
Referenced from https://console.upstage.ai/services/solar
"""
class Config:
allow_population_by_field_name = True
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
request = self._invocation_params
request["messages"] = [{"role": "user", "content": prompt}]
request.update(kwargs)
text = self._client.completion(request)
if stop is not None:
# This is required since the stop tokens
# are not enforced by the model parameters
text = enforce_stop_tokens(text, stop)
return text