What the documents look like
For document comparison in Convenience fresh-food orders, this page examines FastGPT context limits. Deliver product, batch and unobserved conditions with ordering and observation sources. The examples are hypothetical.
Constraints at the context limits step
A proposed fresh-food packet identifies the current batch as plain sandwiches, observes an intact outer bag with the filling unexamined and mentions a separate rice-ball label. The question concerns the sandwich filling. Actual input must retain unexamined and product identity instead of only intact. A longer rice-ball source supplies no sandwich observation. If earlier discussion concerns rice-ball conditions, its summary must not import those as current facts. This exercise provides no real storage values or product-handling requirements and supports no physical condition beyond the proposed observations.
Configuration and implementation checks
| Context-material check | Input and expression conditions | Acceptance action |
|---|---|---|
| Observation granularity | Bag and filling separate | Inspect unexamined wording. |
| Product identity | Sandwiches differ from rice balls | Inspect current input. |
| History influence | Earlier conditions may transfer | Compare with empty history. |
| Response condition | Retain unobserved state | Do not invent positive finding. |
| Budget effect | Creates no missing fact | Inspect original coverage first. |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Model context | Use the actual model’s accepted context scope. |
Reply length | The reply limit differs from the context window. |
Knowledge-reference limit | Knowledge citation limits are token-based. |
History-input check | Compare empty-history and populated-history inputs. |
Structured-output handoff | Validate parsing, then inspect support for field values. |
Three common errors
First, intact outer bag may compress into intact product; inspect observation subject and unexamined filling in the actual request instead of treating lost qualifiers as original facts. Second, historical rice-ball conditions may migrate to sandwiches; compare product reference and source, then inspect input differences under the same question with empty history. Third, the response may omit the unobserved state and assert a conclusion; inspect output scope, length and evidence. These concern observation granularity, historical transfer and answer scope. Additional response space creates no missing physical inspection or factual observation.
How to verify the setup
Ask what the bag record, filling record and rice-ball page establish, comparing actual request with answer wording. When references are token-limited, inspect retained product and observation identities rather than counting excerpts. Check model context capability separately and allow enough reply space to explain support and unresolved items. If the source never observed the filling, changing budgets supplies no such fact. This proposed-text exercise decides no saleability or disposition, places no order and claims no inspection of actual food. Those operational judgments need separate applicable evidence beyond the input comparison.
| 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 |