ပင်မအကြောင်းအရာသို့ ကျော်သွားရန်

နည်းပညာနှင့် စီမံကိန်းနယ်ပယ်

pgvector

ဤနည်းပညာသည် မည်သည့်လုပ်ငန်းအတွက် သင့်တော်သည်၊ ဘာလိုအပ်သည်နှင့် မည်သူက လည်ပတ်ထိန်းသိမ်းမည်ကို သုံးသပ်ပါ။

အောက်ပါအသေးစိတ်လမ်းညွှန်နှင့် ရှင်းလင်းဖော်ပြသည့်ဥပမာများသည် အင်္ဂလိပ်ဘာသာဖြင့် ဖြစ်သည်။ ဥပမာရှိ လုပ်ငန်းမှတ်တမ်းအားလုံးသည် စိတ်ကူးယဉ်ဖြစ်သည်။

Where pgvector fits

Searching approved documents within a PostgreSQL-backed application.

When to choose another approach

Similarity search does not prove a statement is correct, current or authorized for a reader.

Worked example and evidence

Fictional support portal: approved documents → versioned chunks → permission-filtered retrieval → answer with citations. Withdrawn content is removed from retrieval.

What you need to supply

Document owners, customer boundaries, permissions, update policy, embedding provider and evaluation questions.

What acceptance should demonstrate

Verify cross-customer access rejection, citation accuracy, document withdrawal and answers to unsupported questions.

Running costs and responsibilities

Assign embedding costs, index maintenance, document freshness, model evaluation and access reviews.

Technical scope to confirm

Filtering and approximate-index behaviour must be measured together for the real query pattern.

A proposal should identify the systems and data, direction of sync, access feasibility, failure handling, named owners and included deliverables. Listing this technology does not imply a prebuilt connector, vendor partnership or included feature.

How do we prevent answers from another customer’s documents?

Enforce tenant and document permissions before context reaches the model, then verify with deliberately forbidden cross-customer requests. A prompt alone is insufficient.