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8 results for “retrieval” (members search the full text)

• GuideProAny assistantRAG for Engineers - Chunking, Embeddings and Evaluating RetrievalThe practical decisions in a retrieval pipeline: how to chunk, which embedding choices matter, hybrid search, and how to measure retrieval separately from answers.
• GuideStarterAny assistantRAG for Beginners - Letting AI Answer from Your Own DocumentsRetrieval-augmented generation explained without jargon: how an assistant looks things up in your files before answering, and where it still goes wrong.
• Q&AStarterAny assistantHow do I build a chatbot that answers from my own documents?The usual approach is retrieval: store your documents in a searchable form, find the relevant passages for each question, and give them to the AI with an instruction to answer only from them.
• Q&AStarterAny assistantWhat is RAG and why do people use it with AI?RAG, or retrieval-augmented generation, means searching your own documents for relevant passages and giving them to the model along with the question, so it answers from real material instead of memory.
• GuideStarterAny assistantWhy AI Gets Things Wrong, and How to Catch ItUnderstand hallucinations, outdated knowledge and false confidence, then use a practical verification routine to keep errors out of your work.
• GuideBuilderAny assistantLong Chats, Forgetting and Memory: How to Keep AI on TrackWhy assistants lose details in long conversations, and how to use summaries, fresh chats, projects and memory features to keep context sharp.
• GuideBuilderAny assistantRate Limits and Usage Caps - Why You Hit Them and How to CopeUnderstand the difference between app usage caps and API rate limits, why they exist, and how to work within them with batching, caching and retries.
• Q&AStarterAny assistantWhat does "context length exceeded" or "message too long" mean?It means the text you sent, plus any reply space reserved for the answer, is larger than the model can handle in one request.