What This Category’s Data Looks Like
Coal chemical industry policy and regulatory basis data primarily comes from official documents, industry standards, and supporting rules issued by the National Energy Administration, Ministry of Emergency Management, coal chemical industry associations, and local state-owned assets supervision departments. The data update schedule is irregular, synchronized with revisions to new national standards, industry specifications, or industrial policy adjustments. Document structures typically include policy document numbers, issuing units, effective dates, main text clauses, and attachment content. Fields include applicable production capacity levels, energy consumption and emission quantitative indicators, implementation deadlines, and penalty clauses. Quantitative indicators mostly use industry-standard professional units.
What Constraints Do These Characteristics Impose on the Vector Models and Indexes Workflow
The formal writing style and long-text structure of coal chemical policy documents require vector chunking to preserve clause integrity, to avoid semantic fragmentation caused by splitting. The irregular update feature requires the index system to support incremental updates and version tagging, to ensure retrieval results use the latest policies. The multiple quantitative indicator and unit fields require the vector model to adapt to the professional semantics of official documents, to avoid semantic matching errors related to units. The independent existence of attachment content requires the index system to simultaneously handle vector generation and associated retrieval for both main text and attachments.
How to Configure
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Coal chemical policy documents are mostly long texts of complete clauses, to avoid splitting that damages clause semantic integrity |
| Overlap Length | 100–150 characters | Connects the context of adjacent chunks, ensuring retrieval continuity for long clauses |
maxToken | 8192 token | Adapts to the input limit of mainstream vector models, covering the token requirements of complete coal chemical policy clauses |
| Similarity Threshold | 0.75–0.85 | Matches the rigor of policy texts, filtering low-relevance retrieval results |
| Single Search Limit | Top 6 entries | Coal chemical policy entries are relatively concentrated; too many results will interfere with business decision-making |
| Reranking | Enabled | Filters low-matching results, improving the accuracy of retrieval results |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Misconfigurations
- Phenomenon: A large number of entries unrelated to the target coal chemical policy appear in retrieval results. Cause: The similarity threshold is set too low, failing to match the rigorous semantic features of policy texts, resulting in low-relevance results being recalled.
- Phenomenon: After uploading coal chemical policy documents, the index completion status cannot be confirmed via the API. Cause: The incremental index verification logic for long-text policy documents is not configured, and only general file upload status judgment is used, which cannot identify complete index time consumption.
- Phenomenon: The vector model call returns a token limit exceeded error. Cause: The
maxTokenparameter is not set, and the maximum token upper limit is not adjusted for long policy clauses, resulting in failure to generate vectors for long texts.
How to Confirm Correct Configuration
- Upload a single coal chemical policy document, check the platform’s chunk preview interface, confirm that chunks do not split complete policy clauses, and fall within the preset chunk length range.
- Initiate a test retrieval, input a business question related to coal chemical policies, verify the matching degree of returned results, and adjust the similarity threshold to a range that meets business requirements.
- Call the file upload API, check the status field returned by the API, confirm that the index completion marker has been generated, and verify the effectiveness of the incremental update logic.
- Check the vector model call logs, confirm that the token count of each call does not exceed the upper limit set by
maxToken, and comply with the application’s configuration requirements.
The values provided are common starting points and should be measured 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.