mirror of
https://github.com/hwchase17/langchain
synced 2024-11-18 09:25:54 +00:00
ed58eeb9c5
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
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
"""Tool for the Reddit search API."""
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from typing import Optional, Type
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from langchain_core.callbacks import CallbackManagerForToolRun
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from langchain_core.pydantic_v1 import BaseModel, Field
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from langchain_core.tools import BaseTool
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from langchain_community.utilities.reddit_search import RedditSearchAPIWrapper
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class RedditSearchSchema(BaseModel):
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"""Input for Reddit search."""
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query: str = Field(
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description="should be query string that post title should \
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contain, or '*' if anything is allowed."
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)
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sort: str = Field(
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description='should be sort method, which is one of: "relevance" \
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, "hot", "top", "new", or "comments".'
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)
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time_filter: str = Field(
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description='should be time period to filter by, which is \
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one of "all", "day", "hour", "month", "week", or "year"'
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)
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subreddit: str = Field(
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description='should be name of subreddit, like "all" for \
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r/all'
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)
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limit: str = Field(
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description="a positive integer indicating the maximum number \
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of results to return"
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)
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class RedditSearchRun(BaseTool):
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"""Tool that queries for posts on a subreddit."""
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name: str = "reddit_search"
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description: str = (
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"A tool that searches for posts on Reddit."
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"Useful when you need to know post information on a subreddit."
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)
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api_wrapper: RedditSearchAPIWrapper = Field(default_factory=RedditSearchAPIWrapper)
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args_schema: Type[BaseModel] = RedditSearchSchema
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def _run(
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self,
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query: str,
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sort: str,
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time_filter: str,
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subreddit: str,
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limit: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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"""Use the tool."""
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return self.api_wrapper.run(
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query=query,
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sort=sort,
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time_filter=time_filter,
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subreddit=subreddit,
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limit=int(limit),
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)
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