🐦 Twitter Post Details

Viewing enriched Twitter post

@llama_index

The quality of your embeddings can have a huge impact on the effectiveness of your retrieval, which is critical to the quality of your RAG system. @Shahules786 looks at how to pick the best embeddings for your specific data. https://t.co/f6Q9XZfSkt https://t.co/pGS355hy9J

Media 1

📊 Media Metadata

{
  "media": [
    {
      "id": "",
      "type": "photo",
      "url": "https://pbs.twimg.com/media/F8QSLp4XkAA2EaH.jpg",
      "media_url": "https://pbs.twimg.com/media/F8QSLp4XkAA2EaH.jpg",
      "filename": "media_0.jpg"
    }
  ],
  "nlp": {
    "sentiment": "positive",
    "processed_at": "2025-08-06T12:45:32.198278"
  },
  "score": 1.0,
  "scored_at": "2025-08-09T13:46:07.542910",
  "import_source": "manual_curation_2023",
  "score_components": {
    "author": 0.264,
    "engagement": 0.11087419721069532,
    "quality": 0.13999999999999999,
    "source": 0.15,
    "nlp": 0.1,
    "recency": 0.010000000000000002
  },
  "source_tagged_at": "2025-08-09T13:42:55.094561",
  "enriched": true,
  "enriched_at": "2025-08-09T13:42:55.094563",
  "links_checked": true,
  "checked_at": "2025-08-10T10:32:29.928467",
  "original_structure": "had_media_only",
  "enhanced_from_raw_response": true,
  "enhanced_at": "2025-08-13T17:10:00Z"
}

🔧 Raw API Response

{
  "user": {
    "created_at": "2022-12-18T00:52:44.000Z",
    "default_profile_image": false,
    "description": "The way to connect LLMs to your data.\n\nGithub: https://t.co/HC19j7vMwc\nDocs: https://t.co/QInqg2zksh\nDiscord: https://t.co/3ktq3zzYII\nhttps://t.co/UXeIlwvvbA",
    "fast_followers_count": 0,
    "favourites_count": 633,
    "followers_count": 33457,
    "friends_count": 20,
    "has_custom_timelines": false,
    "is_translator": false,
    "listed_count": 667,
    "location": "",
    "media_count": 412,
    "name": "LlamaIndex 🦙",
    "normal_followers_count": 33457,
    "possibly_sensitive": false,
    "profile_banner_url": "https://pbs.twimg.com/profile_banners/1604278358296055808/1696908553",
    "profile_image_url_https": "https://pbs.twimg.com/profile_images/1623505166996742144/n-PNQGgd_normal.jpg",
    "screen_name": "llama_index",
    "statuses_count": 1325,
    "translator_type": "none",
    "url": "https://t.co/epzefqQqZx",
    "verified": false,
    "withheld_in_countries": [],
    "id_str": "1604278358296055808"
  },
  "id": "1712513752333996322",
  "conversation_id": "1712513752333996322",
  "full_text": "The quality of your embeddings can have a huge impact on the effectiveness of your retrieval, which is critical to the quality of your RAG system. @Shahules786 looks at how to pick the best embeddings for your specific data. https://t.co/f6Q9XZfSkt https://t.co/pGS355hy9J",
  "reply_count": 1,
  "retweet_count": 21,
  "favorite_count": 122,
  "hashtags": [],
  "symbols": [],
  "user_mentions": [
    {
      "id_str": "826039247392088064",
      "name": "Shahul Es",
      "screen_name": "Shahules786",
      "profile": "https://twitter.com/Shahules786"
    }
  ],
  "urls": [
    {
      "url": "https://t.co/f6Q9XZfSkt",
      "expanded_url": "https://buff.ly/3rMmECS",
      "display_url": "buff.ly/3rMmECS"
    }
  ],
  "media": [
    {
      "media_url": "https://pbs.twimg.com/media/F8QSLp4XkAA2EaH.jpg",
      "type": "photo"
    }
  ],
  "url": "https://twitter.com/llama_index/status/1712513752333996322",
  "created_at": "2023-10-12T17:01:10.000Z",
  "#sort_index": "1712513752333996322",
  "view_count": 51743,
  "quote_count": 3,
  "is_quote_tweet": false,
  "is_retweet": false,
  "is_pinned": false,
  "is_truncated": false,
  "startUrl": "https://twitter.com/llama_index/status/1712513752333996322"
}