What the documents look like
For product questions in Convenience fresh-food orders, this page examines FastGPT document chunking. Preserve product rows, separate footnotes and missing observations with their subjects. The examples are hypothetical.
Constraints at the document chunking step
A proposed fresh-food table labels a plain wrap as a whole portion and a sauce packet as separately packed. A footnote says the pictured halves are for display only. The question asks whether delivery includes a halved wrap. Parsing needs headings, both product rows and footnote attribution retained. Separate packing describes the sauce, while halving describes the display. Whole portion supplies no observation of an actual delivery. This is ordinary text simulating a table and caption, without demonstrated image understanding or inspection of real food.
Configuration and implementation checks
| Material check | Conditions in this test | Implementation evidence |
|---|---|---|
| Table rows | Wrap and sauce separate | Compare original and parsed correspondence. |
| Footnote subject | Halves describe display photo | Retain qualifier with chunk. |
| Updated row | Current whole-portion wording | Inspect actual citation version. |
| Data and indexes | Parse row relationships first | Indexes replace no missing structure. |
| Actual state | No delivery observation | Do not infer physical condition. |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Original-document check | Compare original files with parsed output. |
Chunk completeness | Keep conditions traceable to their subjects. |
Data and indexes | Retain original-data and index evidence separately. |
Sample retrieval | Retest literal wording and natural questions. |
Post-update check | Inspect training or index state after updates. |
Three common errors
First, the sauce-packing cell may join the wrap row; compare original table, parsed text and chunks for row correspondence. Second, the halving footnote may lose display-only scope; inspect its photo reference and adjacent wording instead of turning display into product configuration. Third, updated whole-portion wording may still yield an older divided-portion excerpt; inspect original version, processing and index state with actual citations rather than upload presence. These concern table relationships, footnote scope and update adoption. Coexisting old and new text does not itself establish contradictory current product information.
How to verify the setup
Ask what the wrap row states, how sauce is packed and what the halving note describes, retaining the path from original through parsed text to reference. Repeat the same questions after chunk changes for traceable conditions; additional indexes cannot replace a row relationship absent from parsing. Without an actual delivery record, the delivery configuration remains unknown. The supplied text cannot confirm either a halved delivery or an undivided delivery. This exercise decides no saleability and places no order. Successful parsing concerns the proposed text structure only, proving no actual image processing or physical product condition beyond the material that was independently supplied.
| Material context | Scope |
|---|---|
| Document types | Fresh Food Order Form, Spoilage Report, Near-Expiry Processing Sheet and Temperature Records |
| Candidate sources | POS Sales, Headquarters Ordering System, Store Inventory and Cold Chain Temperature Control Records |
| Technical baseline | FastGPT v4.17.2 |