refactor(instagram): update platform schemas and scraper for tagged media

This commit is contained in:
Anish Sarkar 2026-07-11 03:25:17 +05:30
parent 457be1871c
commit 5cac6612c3
2 changed files with 3 additions and 3 deletions

View file

@ -19,7 +19,7 @@ from typing import Any, Literal
from pydantic import BaseModel, ConfigDict, Field from pydantic import BaseModel, ConfigDict, Field
InstagramResultsType = Literal["posts", "details", "reels", "mentions"] InstagramResultsType = Literal["posts", "details", "reels"]
InstagramSearchType = Literal["profile", "user"] InstagramSearchType = Literal["profile", "user"]

View file

@ -16,7 +16,7 @@ Google-backed handle discovery. Login-walled surfaces (hashtag/place feeds,
comment threads, IG's native keyword search) are deliberately absent. comment threads, IG's native keyword search) are deliberately absent.
Flows are selected by ``resultsType``: Flows are selected by ``resultsType``:
- ``posts`` / ``reels`` / ``mentions`` -> media items (profile feed, or a single - ``posts`` / ``reels`` -> media items (profile feed, or a single
``/p/``/``/reel/`` page, or discovery search) ``/p/``/``/reel/`` page, or discovery search)
- ``details`` -> profile metadata (by URL or discovery search) - ``details`` -> profile metadata (by URL or discovery search)
@ -394,7 +394,7 @@ async def iter_instagram(
yield item yield item
return return
# posts / reels / mentions -> media feeds, de-duped by id across targets. # posts / reels -> media feeds, de-duped by id across targets.
jobs = [ jobs = [
_media_flow( _media_flow(
r, input_model=input_model, cutoff=cutoff, per_target=per_target r, input_model=input_model, cutoff=cutoff, per_target=per_target