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In this article, author Aaditya Chauhan discusses the limitations of RAG pipelines based purely on vector search and how an internal omni-search application using Reciprocal Rank Fusion (RRF) that combines BM25 and vector results, can enhance the search solution. By Aaditya Chauhan

Stuck on Meta App Review and hoping someone here has cracked it. Setup: Instagram API with Instagram Login (graph.instagram.com, v25.0), Instagram User token (IGAA...), BUSINESS account. Trying to get Advanced Access for instagram_business_manage_comments. The blocker: the "make 1 successful API call" requirement stays at "0 of 1 API call(s)" for days (past Meta's 2-day logging window), so the Request Advanced Access button stays grayed out. What I've confirmed: - The token DOES hold the scope (granted permissions list includes it). - GET /{media-id}/comments?fields=id,username,timestamp returns HTTP 200. - Rate-limit usage increases per call, so the calls are landing. - It's not the endpoint: I also tried creating a comment + replying (POST /{media-id}/comments, POST /{comment-id}/replies) — all 200, none registered. On the SAME token/path, instagram_business_manage_messages registered fine (its requirement is complete) even though ITS call (GET /me/conversations) also returns an empty array (200, "data":[]). So an empty 200 counted for manage_messages but the comments call never counts for manage_comments — looks like a tracking bug specific to the manage_comments counter. Question: has anyone gotten instagram_business_manage_comments to flip 0 -> 1 on the Instagram-Login path? What exact call/step did it, or did Meta credit it via a Platform Bug Report? Anything that worked would save me. submitted by /u/Traditional-Lake3525 [link] [留言]

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Inspiration Build a simple and modular technical documentation and blog. Build the website without using node/npm or any external frameworks(CSS, JS, icon, font). Only GoHugo normal binary + pageFind binary needed. Features [x] Responsive and adaptive layouts. [x] Support for light and dark modes. [x] Support for multiple documentation sets. [x] Support for a blog. [x] Implement a menu via Hugo configs. [x] Customizable sidebars using Hugo data templates. [x] Plug-and-play/ repeatable home page blocks using separate partials/ css/ data templates. [x] Integrate a search via Pagefind. [x] Inline SVG icons based on Google's Material Symbols GitHub Repo: https://github.com/dumindu/E25DX Example Docs: https://github.com/dumindu/E25DX/tree/gh-pages/example Example Live: https://dumindu.github.io/E25DX/ submitted by /u/dumindunuwan [link] [留言]

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I don't identify as a gamer. I occasionally participate in board games or an amateur football match,...

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Ever received a WebSocket tick stream for US stocks and wondered why your indicators behave oddly outside regular hours? The raw data doesn’t tell you which session a trade belongs to, but identifying the session is crucial for signal quality. Here’s a clean, no-dependency-heavy way to do it in Python. Quick Session Reference Session US Eastern Time Data Characteristics Pre-market 04:00-09:30 Sparse trades, choppy moves Regular hours 09:30-16:00 Dense liquidity, smooth price action After-hours 16:00-20:00 Volatility often triggered by news Method 1: Timestamp Conversion Almost every API sends a UTC timestamp. Convert it to US/Eastern and classify. from datetime import datetime import pytz # US Eastern timezone et = pytz . timezone ( ' US/Eastern ' ) def get_session ( ts ): t = datetime . fromtimestamp ( ts , et ) # Check pre-market window if t . hour < 9 or ( t . hour == 9 and t . minute < 30 ): return " pre " # Regular session if t . hour < 16 : return " regular " # After-hours return " after " Method 2: Use a Session Status Field If your provider sends a field like sessionType , you can skip the timezone math. Just make sure to test edge cases at session boundaries. Live Integration Example Using a WebSocket feed (like AllTick’s market data stream) that includes a timestamp, I label ticks on the fly. import websocket import json from datetime import datetime import pytz # US Eastern timezone et = pytz . timezone ( ' US/Eastern ' ) def session ( ts ): t = datetime . fromtimestamp ( ts , et ) if t . hour < 9 or ( t . hour == 9 and t . minute < 30 ): return " pre " elif t . hour < 16 : return " regular " else : return " after " def on_message ( ws , message ): data = json . loads ( message ) s = session ( data [ " timestamp " ]) print ( f " { data [ ' symbol ' ] } | { s } | { data [ ' price ' ] } | { data [ ' volume ' ] } " ) # Open WebSocket connection ws = websocket . WebSocketApp ( " wss://ws.alltick.co/stock " , on_message = on_message ) ws . run_forever () Effic