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langchain-gpt4free/langchain_g4f/G4FLLM.py

83 lines
2.9 KiB
Python

from typing import Any, List, Mapping, Optional, Union
from functools import partial
from g4f import ChatCompletion
from g4f.models import Model
from g4f.Provider.base_provider import BaseProvider
from langchain.callbacks.manager import CallbackManagerForLLMRun, AsyncCallbackManagerForLLMRun
from langchain.llms.base import LLM
from langchain.llms.utils import enforce_stop_tokens
MAX_TRIES = 5
class G4FLLM(LLM):
model: Union[Model, str]
provider: Optional[type[BaseProvider]] = None
auth: Optional[Union[str, bool]] = None
create_kwargs: Optional[dict[str, Any]] = None
@property
def _llm_type(self) -> str:
return "custom"
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
create_kwargs = {} if self.create_kwargs is None else self.create_kwargs.copy()
create_kwargs["model"] = self.model
if self.provider is not None:
create_kwargs["provider"] = self.provider
if self.auth is not None:
create_kwargs["auth"] = self.auth
for i in range(MAX_TRIES):
try:
text = ChatCompletion.create(
messages=[{"role": "user", "content": prompt}],
**create_kwargs,
)
# Generator -> str
text = text if type(text) is str else "".join(text)
if stop is not None:
text = enforce_stop_tokens(text, stop)
if text:
return text
print(f"Empty response, trying {i+1} of {MAX_TRIES}")
except Exception as e:
print(f"Error in G4FLLM._call: {e}, trying {i+1} of {MAX_TRIES}")
return ""
async def _acall(self, prompt: str, stop: Optional[List[str]] = None, run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, **kwargs: Any) -> str:
create_kwargs = {} if self.create_kwargs is None else self.create_kwargs.copy()
create_kwargs["model"] = self.model
if self.provider is not None:
create_kwargs["provider"] = self.provider
if self.auth is not None:
create_kwargs["auth"] = self.auth
text_callback = None
if run_manager:
text_callback = partial(run_manager.on_llm_new_token)
text = ""
for token in ChatCompletion.create(messages=[{"role": "user", "content": prompt}], stream=True, **create_kwargs):
if text_callback:
await text_callback(token)
text += token
return text
@property
def _identifying_params(self) -> Mapping[str, Any]:
"""Get the identifying parameters."""
return {
"model": self.model,
"provider": self.provider,
"auth": self.auth,
"create_kwargs": self.create_kwargs,
}