mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
480626dc99
…tch]: import models from community ran ```bash git grep -l 'from langchain\.chat_models' | xargs -L 1 sed -i '' "s/from\ langchain\.chat_models/from\ langchain_community.chat_models/g" git grep -l 'from langchain\.llms' | xargs -L 1 sed -i '' "s/from\ langchain\.llms/from\ langchain_community.llms/g" git grep -l 'from langchain\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.embeddings/from\ langchain_community.embeddings/g" git checkout master libs/langchain/tests/unit_tests/llms git checkout master libs/langchain/tests/unit_tests/chat_models git checkout master libs/langchain/tests/unit_tests/embeddings/test_imports.py make format cd libs/langchain; make format cd ../experimental; make format cd ../core; make format ```
63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
"""Fake LLM wrapper for testing purposes."""
|
|
from typing import Any, Dict, List, Mapping, Optional, cast
|
|
|
|
from langchain.callbacks.manager import CallbackManagerForLLMRun
|
|
from langchain_core.language_models import LLM
|
|
|
|
from langchain_experimental.pydantic_v1 import validator
|
|
|
|
|
|
class FakeLLM(LLM):
|
|
"""Fake LLM wrapper for testing purposes."""
|
|
|
|
queries: Optional[Mapping] = None
|
|
sequential_responses: Optional[bool] = False
|
|
response_index: int = 0
|
|
|
|
@validator("queries", always=True)
|
|
def check_queries_required(
|
|
cls, queries: Optional[Mapping], values: Mapping[str, Any]
|
|
) -> Optional[Mapping]:
|
|
if values.get("sequential_response") and not queries:
|
|
raise ValueError(
|
|
"queries is required when sequential_response is set to True"
|
|
)
|
|
return queries
|
|
|
|
def get_num_tokens(self, text: str) -> int:
|
|
"""Return number of tokens."""
|
|
return len(text.split())
|
|
|
|
@property
|
|
def _llm_type(self) -> str:
|
|
"""Return type of llm."""
|
|
return "fake"
|
|
|
|
def _call(
|
|
self,
|
|
prompt: str,
|
|
stop: Optional[List[str]] = None,
|
|
run_manager: Optional[CallbackManagerForLLMRun] = None,
|
|
**kwargs: Any,
|
|
) -> str:
|
|
if self.sequential_responses:
|
|
return self._get_next_response_in_sequence
|
|
|
|
if self.queries is not None:
|
|
return self.queries[prompt]
|
|
if stop is None:
|
|
return "foo"
|
|
else:
|
|
return "bar"
|
|
|
|
@property
|
|
def _identifying_params(self) -> Dict[str, Any]:
|
|
return {}
|
|
|
|
@property
|
|
def _get_next_response_in_sequence(self) -> str:
|
|
queries = cast(Mapping, self.queries)
|
|
response = queries[list(queries.keys())[self.response_index]]
|
|
self.response_index = self.response_index + 1
|
|
return response
|