mirror of
https://github.com/MODSetter/SurfSense.git
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ff2e5f390f
- Added a new `reddit` subagent to scrape structured data from Reddit posts, comments, and users. - Introduced `reddit.scrape` capability for fetching data using URLs and search queries. - Implemented tools for scraping and parsing Reddit data, including handling pagination and rate limits. - Created input/output models for the Reddit scraper to define request and response structures. - Added documentation for the new Reddit scraping functionality and its usage. - Integrated the Reddit subagent into the existing multi-agent chat framework.
102 lines
3.4 KiB
Python
102 lines
3.4 KiB
Python
"""``reddit.scrape`` I/O contracts.
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A lean, agent-friendly surface over ``RedditScrapeInput``
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(``app/proprietary/platforms/reddit``). The executor maps this to the full
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scraper input; the scraper's ``RedditItem`` is reused verbatim as the output
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element.
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"""
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from __future__ import annotations
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from pydantic import BaseModel, Field, model_validator
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from app.proprietary.platforms.reddit import RedditItem
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from app.proprietary.platforms.reddit.schemas import RedditSort, RedditTime
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MAX_REDDIT_SOURCES = 20
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"""Per-call cap on urls + search_queries: bounds a synchronous request's fan-out."""
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MAX_REDDIT_ITEMS = 100
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"""Hard ceiling on items returned per call, regardless of the per-target caps."""
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class ScrapeInput(BaseModel):
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urls: list[str] = Field(
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default_factory=list,
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max_length=MAX_REDDIT_SOURCES,
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description=(
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"Reddit URLs to scrape: a post, a subreddit (/r/<name>), a user "
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"(/user/<name>), or a search URL. Provide these OR search_queries/"
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"community (at least one source is required)."
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),
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)
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search_queries: list[str] = Field(
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default_factory=list,
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max_length=MAX_REDDIT_SOURCES,
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description=(
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"Search terms to run on Reddit; each returns up to max_items results. "
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"Scope to one subreddit with community."
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),
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)
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community: str | None = Field(
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default=None,
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description=(
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"Subreddit name (without 'r/') to scope search_queries to, e.g. "
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"'python'. With no search_queries, its listing is scraped."
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),
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)
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sort: RedditSort = Field(
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default="new",
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description="Result ordering: relevance, hot, top, new, rising, or comments.",
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)
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time_filter: RedditTime | None = Field(
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default=None,
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description="Time window for 'top'/'controversial' sorts: hour, day, week, month, year, all.",
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)
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include_nsfw: bool = Field(
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default=True,
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description="Include posts flagged over-18 (NSFW) in the results.",
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)
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skip_comments: bool = Field(
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default=False,
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description="Skip fetching comment trees (faster; posts/listings only).",
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)
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max_items: int = Field(
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default=10,
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ge=1,
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le=MAX_REDDIT_ITEMS,
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description="Max total items to return across all sources.",
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)
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max_posts: int = Field(
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default=10,
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ge=0,
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description="Max posts to pull per subreddit/user/search target.",
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)
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max_comments: int = Field(
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default=10,
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ge=0,
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description="Max comments to pull per post (0 = none).",
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)
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post_date_limit: str | None = Field(
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default=None,
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description="ISO date; only return posts newer than this (incremental scrape).",
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)
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comment_date_limit: str | None = Field(
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default=None,
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description="ISO date; only return comments newer than this (incremental scrape).",
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)
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@model_validator(mode="after")
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def _require_a_source(self) -> ScrapeInput:
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if not self.urls and not self.search_queries and not self.community:
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raise ValueError(
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"Provide at least one of 'urls', 'search_queries', or 'community'."
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)
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return self
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class ScrapeOutput(BaseModel):
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items: list[RedditItem] = Field(
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default_factory=list,
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description="One item per result (post/comment/community/user), in emission order.",
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)
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