What the data for this category looks like
Data related to document and material drafting for state-owned capital operation companies mainly comes from regulatory documents released by state-owned assets supervision departments, group internal management systems, annual investment and financing plans, articles of association amendments, and various approval documents. Data update rhythms fall into two categories: state-owned assets policy documents are updated quarterly or annually per regulatory requirements; internal business documents are updated in real time as projects progress and systems are revised. Document structures include document numbers, issuing units, effective dates, main text chapters and attachments. Fields include standardized state-owned assets document numbers, amount units (ten thousand yuan / hundred million yuan), project cycles, and more. Individual document lengths range from hundreds of words of system excerpts to tens of thousands of words of investment and financing plans.
What constraints these characteristics impose on the knowledge base retrieval and recall link
The authoritative nature of state-owned assets policy documents requires retrieval results to match the latest effective dates. The retrieval link must support filtering metadata by effective time. Internal business documents are lengthy, so chunking must balance context integrity to avoid losing the associative logic of professional terms after splitting. Documents include standardized fields such as document numbers and amount units. Retrieval must support precise filtering by metadata to ensure recalled content matches business scenarios. Update rhythms vary widely across different documents. A flexible synchronization trigger mechanism must be configured to distinguish trigger conditions for scheduled full updates and real-time incremental updates.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.85 | Documents related to state-owned capital operations contain a large number of professional compliance terms. A threshold that is too low will introduce irrelevant content, while a threshold that is too high will miss precise matching results related to compliance. This range is calibrated based on actual testing. |
limit | Top 8–12 results | Document drafting requires covering multi-dimensional compliance basis. Too many recalled results will exceed the context window limit of FastGPT v4.17.0, while too few will fail to cover all relevant content. |
searchMode | Semantic + metadata hybrid mode | Business documents contain both semantic practical content and structured metadata. The hybrid mode can balance semantic matching and precise filtering. |
usingReRank | Enabled | Long documents face semantic fragmentation after chunking. Reranking optimizes the professional relevance ranking of recalled results. |
datasetSearchUsingExtensionQuery | Enabled | Document drafting often requires associating policy interpretations and practical details. Extended queries can supplement implied compliance requirements. |
collectionIds | Specify state-owned assets policy library + internal business document library | Official compliance basis and internal practical standards must be distinguished to avoid interference from irrelevant content across libraries in retrieval results. |
Three common misconfigurations
- Issue: Retrieval result paragraphs do not show citation sources at the end. Cause: Metadata field extraction rules are not configured, or the function switch for associated citations is not enabled. This prevents binding document information such as document numbers and issuing units to recalled results.
- Issue: The number of results returned by a single search does not match the configured
limitparameter. Cause: Some document chunks repeatedly hit search terms, and result deduplication logic is not enabled. This causes redundant results to be included. - Issue: Retrieval response times out. Cause: The total character count of recalled documents exceeds the system context window limit. Chunk length is not adjusted or the
limitvalue is not reduced, leading to context overflow.
How to verify the configuration is correct
- Upload a state-owned assets supervision policy document and one internal investment and financing plan. Initiate a query containing policy keywords. Verify that returned results include metadata citations such as the document number and issuing unit of the corresponding document.
- Adjust the
similarityparameter to 0.78. Initiate three identical queries. Verify that the number of returned results stays stable within the configuredlimitrange. - Import a batch of updated documents. Trigger a knowledge base synchronization task. Verify that the update time of corresponding documents in the system knowledge base is updated synchronously.
- Enable the
usingReRankfunction. Initiate a query containing multiple professional terms such as "state-owned assets supervision" and "investment and financing". Verify that the returned results are sorted according to professional relevance logic.
The configuration values provided are common starting points. They should be assessed against relevant samples in use.
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.