🐦 Twitter Post Details

Viewing enriched Twitter post

@llama_index

Multi-agent workflow to Generate a Structured Financial Report 📊 In our new video we show you how to generate simple analyses containing text and tables over a bank of 10K documents. First, we use LlamaCloud to advanced retrieval endpoints allowing you to fetch chunk and document-level context from complex financial reports consisting of text, tables, and sometimes images/diagrams. We then build an agentic workflow on top of LlamaCloud, using OpenAI GPT-4o, consisting of researcher and writer steps in order to generate the final response. Video: https://t.co/njMOgcxuif Signup to LlamaCloud: https://t.co/yQGTiRSNvj For enterprise usage, come talk to us: https://t.co/ek65coieav

Media 1

📊 Media Metadata

{
  "data": [
    {
      "media_url": "https://pbs.twimg.com/media/Gcmt-7Da4AAnDWk.jpg",
      "type": "photo"
    }
  ],
  "score": 1.0,
  "scored_at": "2025-08-09T13:46:07.553747",
  "import_source": "network_archive_import",
  "media": [
    {
      "type": "photo",
      "url": "https://crmoxkoizveukayfjuyo.supabase.co/storage/v1/object/public/media/posts/1858207641732084076/media_0.jpg?",
      "filename": "media_0.jpg",
      "original_url": "https://pbs.twimg.com/media/Gcmt-7Da4AAnDWk.jpg"
    }
  ],
  "storage_migrated": true
}

🔧 Raw API Response

{
  "user": {
    "created_at": "2022-12-18T00:52:44.000Z",
    "default_profile_image": false,
    "description": "Build LLM agents over your data\n\nGithub: https://t.co/HC19j7vMwc\nDocs: https://t.co/QInqg2zksh\nDiscord: https://t.co/3ktq3zzYII",
    "fast_followers_count": 0,
    "favourites_count": 1261,
    "followers_count": 82613,
    "friends_count": 26,
    "has_custom_timelines": false,
    "is_translator": false,
    "listed_count": 1366,
    "location": "",
    "media_count": 1375,
    "name": "LlamaIndex 🦙",
    "normal_followers_count": 82613,
    "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": 2997,
    "translator_type": "none",
    "url": "https://t.co/epzefqQqZx",
    "verified": true,
    "withheld_in_countries": [],
    "id_str": "1604278358296055808"
  },
  "id": "1858207641732084076",
  "conversation_id": "1858207641732084076",
  "full_text": "Multi-agent workflow to Generate a Structured Financial Report 📊\n\nIn our new video we show you how to generate simple analyses containing text and tables over a bank of 10K documents.\n\nFirst, we use LlamaCloud to advanced retrieval endpoints allowing you to fetch chunk and document-level context from complex financial reports consisting of text, tables, and sometimes images/diagrams.\n\nWe then build an agentic workflow on top of LlamaCloud, using OpenAI GPT-4o, consisting of researcher and writer steps in order to generate the final response.\n\nVideo: https://t.co/njMOgcxuif\nSignup to LlamaCloud: https://t.co/yQGTiRSNvj\nFor enterprise usage, come talk to us: https://t.co/ek65coieav",
  "reply_count": 2,
  "retweet_count": 69,
  "favorite_count": 336,
  "hashtags": [],
  "symbols": [],
  "user_mentions": [],
  "urls": [],
  "media": [
    {
      "media_url": "https://pbs.twimg.com/media/Gcmt-7Da4AAnDWk.jpg",
      "type": "photo"
    }
  ],
  "url": "https://twitter.com/llama_index/status/1858207641732084076",
  "created_at": "2024-11-17T17:56:40.000Z",
  "#sort_index": "1858207641732084076",
  "view_count": 29704,
  "quote_count": 1,
  "is_quote_tweet": false,
  "is_retweet": false,
  "is_pinned": false,
  "is_truncated": true,
  "startUrl": "https://x.com/llama_index/status/1858207641732084076"
}