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
144 lines
4.5 KiB
Python
144 lines
4.5 KiB
Python
from __future__ import annotations
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from typing import TYPE_CHECKING, Iterable, List, Optional, Sequence
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseLoader
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if TYPE_CHECKING:
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import praw
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def _dependable_praw_import() -> praw:
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try:
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import praw
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except ImportError:
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raise ImportError(
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"praw package not found, please install it with `pip install praw`"
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)
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return praw
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class RedditPostsLoader(BaseLoader):
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"""Load `Reddit` posts.
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Read posts on a subreddit.
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First, you need to go to
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https://www.reddit.com/prefs/apps/
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and create your application
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"""
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def __init__(
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self,
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client_id: str,
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client_secret: str,
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user_agent: str,
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search_queries: Sequence[str],
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mode: str,
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categories: Sequence[str] = ["new"],
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number_posts: Optional[int] = 10,
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):
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"""
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Initialize with client_id, client_secret, user_agent, search_queries, mode,
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categories, number_posts.
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Example: https://www.reddit.com/r/learnpython/
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Args:
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client_id: Reddit client id.
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client_secret: Reddit client secret.
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user_agent: Reddit user agent.
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search_queries: The search queries.
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mode: The mode.
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categories: The categories. Default: ["new"]
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number_posts: The number of posts. Default: 10
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"""
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self.client_id = client_id
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self.client_secret = client_secret
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self.user_agent = user_agent
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self.search_queries = search_queries
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self.mode = mode
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self.categories = categories
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self.number_posts = number_posts
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def load(self) -> List[Document]:
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"""Load reddits."""
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praw = _dependable_praw_import()
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reddit = praw.Reddit(
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client_id=self.client_id,
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client_secret=self.client_secret,
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user_agent=self.user_agent,
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)
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results: List[Document] = []
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if self.mode == "subreddit":
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for search_query in self.search_queries:
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for category in self.categories:
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docs = self._subreddit_posts_loader(
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search_query=search_query, category=category, reddit=reddit
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)
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results.extend(docs)
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elif self.mode == "username":
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for search_query in self.search_queries:
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for category in self.categories:
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docs = self._user_posts_loader(
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search_query=search_query, category=category, reddit=reddit
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)
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results.extend(docs)
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else:
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raise ValueError(
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"mode not correct, please enter 'username' or 'subreddit' as mode"
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)
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return results
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def _subreddit_posts_loader(
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self, search_query: str, category: str, reddit: praw.reddit.Reddit
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) -> Iterable[Document]:
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subreddit = reddit.subreddit(search_query)
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method = getattr(subreddit, category)
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cat_posts = method(limit=self.number_posts)
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"""Format reddit posts into a string."""
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for post in cat_posts:
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metadata = {
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"post_subreddit": post.subreddit_name_prefixed,
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"post_category": category,
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"post_title": post.title,
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"post_score": post.score,
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"post_id": post.id,
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"post_url": post.url,
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"post_author": post.author,
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}
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yield Document(
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page_content=post.selftext,
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metadata=metadata,
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)
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def _user_posts_loader(
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self, search_query: str, category: str, reddit: praw.reddit.Reddit
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) -> Iterable[Document]:
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user = reddit.redditor(search_query)
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method = getattr(user.submissions, category)
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cat_posts = method(limit=self.number_posts)
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"""Format reddit posts into a string."""
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for post in cat_posts:
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metadata = {
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"post_subreddit": post.subreddit_name_prefixed,
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"post_category": category,
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"post_title": post.title,
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"post_score": post.score,
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"post_id": post.id,
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"post_url": post.url,
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"post_author": post.author,
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}
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yield Document(
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page_content=post.selftext,
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metadata=metadata,
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)
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