I ordered a thin crust pizza from @dominos on @zomato . The pizza was burnt amd they offered me half of the price as coupon which I am not able to use at other outlet.
I order pizza from outlet that location I visited for 1 day. How is this a solution?
@CJP_for_India Why cjp only demanded resign from Dharmendra Pradhan. As multiple peaperleaked happened across India why not others who are also responsible.
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8 RAG architectures for AI Engineers:
(explained with usage)
1) Naive RAG
- Retrieves documents purely based on vector similarity between the query embedding and stored embeddings.
- Works best for simple, fact-based queries where direct semantic matching suffices.
2) Multimodal RAG
- Handles multiple data types (text, images, audio, etc.) by embedding and retrieving across modalities.
- Ideal for cross-modal retrieval tasks like answering a text query with both text and image context.
3) HyDE (Hypothetical Document Embeddings)
- Queries are not semantically similar to documents.
- This technique generates a hypothetical answer document from the query before retrieval.
- Uses this generated document’s embedding to find more relevant real documents.
4) Corrective RAG
- Validates retrieved results by comparing them against trusted sources (e.g., web search).
- Ensures up-to-date and accurate information, filtering or correcting retrieved content before passing to the LLM.
5) Graph RAG
- Converts retrieved content into a knowledge graph to capture relationships and entities.
- Enhances reasoning by providing structured context alongside raw text to the LLM.
6) Hybrid RAG
- Combines dense vector retrieval with graph-based retrieval in a single pipeline.
- Useful when the task requires both unstructured text and structured relational data for richer answers.
7) Adaptive RAG
- Dynamically decides if a query requires a simple direct retrieval or a multi-step reasoning chain.
- Breaks complex queries into smaller sub-queries for better coverage and accuracy.
8) Agentic RAG
- Uses AI agents with planning, reasoning (ReAct, CoT), and memory to orchestrate retrieval from multiple sources.
- Best suited for complex workflows that require tool use, external APIs, or combining multiple RAG techniques.
👉 Over to you: Which RAG architecture do you use the most?
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Ordered wax powder on @amazonIN and got damaged packaging as shown in the below image. And don't have return or replace option for such product. Damaged packaging on both sides.
I noticed another customer raising a similar concern at the billing counter for pears soap, which prompted me to double-check my own bill. @jagograhakjago@ConsumerReports
I bought a pack of dates from @AvenueDmart. The shelf price was listed as ₹155, but when I checked my bill, it showed ₹199.
This kind of discrepancy is how customers get misled.
@GujaratGasLtd
I have applied for gas connection.
I have my own house of g+2. I live with my family and I want connection on both 1st and 2nd floor. I have submitted application form, but the staff says I have to get 1 extra meter for 2nd floor
I have raised a return request but gets canceled each time on @flipkartsupport . This the the agent didn't even came at my place and the return order got cancelled.
WAQF BOARD has send a NOTICE to ‘Indian Army Cantonment Authorities’ in Kannur, Kerala stating that the ground occupied by Indian Army belongs to WAQF.
We need ANTI-DOTE of this VIRUS otherwise we will next SOMALIA.
Shut Down WAQF BOARD in India🔥