langchain/libs/community/langchain_community/tools/reddit_search/tool.py

65 lines
1.9 KiB
Python
Raw Normal View History

community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
2023-12-11 21:53:30 +00:00
"""Tool for the Reddit search API."""
from typing import Optional, Type
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.tools import BaseTool
from langchain_community.utilities.reddit_search import RedditSearchAPIWrapper
class RedditSearchSchema(BaseModel):
"""Input for Reddit search."""
query: str = Field(
description="should be query string that post title should \
contain, or '*' if anything is allowed."
)
sort: str = Field(
description='should be sort method, which is one of: "relevance" \
, "hot", "top", "new", or "comments".'
)
time_filter: str = Field(
description='should be time period to filter by, which is \
one of "all", "day", "hour", "month", "week", or "year"'
)
subreddit: str = Field(
description='should be name of subreddit, like "all" for \
r/all'
)
limit: str = Field(
description="a positive integer indicating the maximum number \
of results to return"
)
class RedditSearchRun(BaseTool):
"""Tool that queries for posts on a subreddit."""
name: str = "reddit_search"
description: str = (
"A tool that searches for posts on Reddit."
"Useful when you need to know post information on a subreddit."
)
api_wrapper: RedditSearchAPIWrapper = Field(default_factory=RedditSearchAPIWrapper)
args_schema: Type[BaseModel] = RedditSearchSchema
def _run(
self,
query: str,
sort: str,
time_filter: str,
subreddit: str,
limit: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> str:
"""Use the tool."""
return self.api_wrapper.run(
query=query,
sort=sort,
time_filter=time_filter,
subreddit=subreddit,
limit=int(limit),
)