What this category of data looks like
The data for urban investment platform declaration materials and case files mainly comes from internal project declaration ledgers, administrative approval case files, infrastructure project feasibility study reports, debt declaration documents, and land transfer-related documents. Most files are in PDF or Word format, with some including scanned documents and structured tables. Data update cycles align with project timelines. Complete materials are uploaded in batches during a single project declaration. Daily case review materials are updated monthly. Document structures include declaration subject information, project compliance documents, fund calculation tables, and approval process records. Fields include unique project IDs, declaration dates, approval statuses, fund amounts (unit: ten thousand yuan), and other business-specific identifiers.
Constraints imposed on knowledge base retrieval and recall
Documents contain long text passages and structured tables. Retrieval chunking must retain table integrity to avoid breaking business data associations. Fields include unique project IDs. Retrieval must support filtering by these identifiers to limit the material scope to the current urban investment subject. Data is uploaded in batches with uneven update frequencies. The indexing process must support batch monitoring and resumable uploads. Some documents include embedded images. Retrieval results must support visual image display. Additionally, professional business terminology density is high. General retrieval must avoid semantic deviation, ensuring recall results are strongly relevant to declaration and review scenarios.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Adapts to the professional terminology density of urban investment declaration materials, filtering recall results with semantic deviation |
limit | Top 10 entries | Case review requires precise matching of materials related to a single project. Excessive results increase review burden |
searchMode | vector | Declaration materials contain extensive long text and structured data. Vector retrieval better matches semantic associations than keyword retrieval |
usingReRank | Enabled | Improves recall accuracy after long document chunking, filtering chunk results with unmatched semantics |
datasetSearchUsingExtensionQuery | Disabled | Business terminology in urban investment declaration materials is rigorous. No additional query expansion is needed to avoid semantic drift |
collectionIds | Bind the exclusive knowledge base collection of the current urban investment subject | Limits retrieval scope to only the declaration and case data of the current subject, avoiding interference from cross-subject data |
Three Common Mistakes
- Phenomenon: The knowledge base remains in the "Indexing" status for a long time after upload, with no progress updates. Cause: The total size of batch-uploaded documents exceeds the single-batch indexing limit, and the upload was not split.
- Phenomenon: Only image file names are returned in responses, and approval stamps, drawing images cannot be displayed directly. Cause: The document image extraction function is not enabled, or the image embedding format does not meet platform parsing requirements.
- Phenomenon: Parameter parsing fails when using variable references, and the retrieval scope cannot be bound correctly. Cause: The variable format does not follow specifications, half-width parentheses were mistakenly replaced with full-width symbols, or the variable structure was not nested correctly.
How to Confirm Configuration is Correct
- A single test document is uploaded. The index status is checked to change to "Completed" within 5 minutes, confirming the index configuration is effective.
- A search query containing the exclusive project ID is entered. Recall results are verified to only include relevant materials of the current urban investment subject, confirming the
collectionIdsconfiguration is correct. - A retrieval for a document with embedded images is triggered. Image previews included in the response confirm the image extraction function works properly.
- The
similarityparameter is adjusted to 0.78, a professional business terminology query is entered, and the semantic matching degree of recall results is verified to meet scenario requirements.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.