Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Data mainly comes from internal party building archives in the refinery and chemical sector, official documents issued by the party committee, and monthly team learning ledgers. Party committee documents update in real time upon issuance. Team learning materials update once per month. Most documents use Markdown or PDF format with hierarchical headings. They include metadata fields such as release document number, issuing unit, and release date. Some materials link to safety learning requirements for corresponding production teams. Common field units include internal statistical terms such as person-times, hours, and batches.
Constraints for Model Access and Configuration from Data Characteristics
Internal party building materials include exclusive metadata fields. Model access must retain information such as release document number and issuing unit to support Q&A traceability. This adds configuration constraints for metadata binding. Monthly updated team learning materials require the vector database sync cycle to match the update rhythm. This prevents data lag. Some materials link to production team safety requirements, and document lengths vary widely. Text chunking and embedding configurations must be adapted to different lengths. This prevents information loss from long text truncation.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Refinery and chemical party building materials often combine content from production teams. Single linked documents have relatively long lengths, so sufficient context must be retained |
maxTokens | 4000 token | Controls the length of single-round responses, to adapt to receiving limits of internal systems and external channels |
quoteMaxToken | 2000–3000 token | Matches the average length of single documents in refinery and chemical party building materials, to ensure complete quoted content |
temperature | 0.3–0.5 | Maintains the rigor of party building Q&A, to avoid generating content that deviates from official documents |
AIPROXY_API_ENDPOINT | Fill in the actual address according to the deployment platform | Adapts to the access path of self-developed or third-party deployed large models |
AIPROXY_API_TOKEN | Fill in the key assigned by the platform | Ensures compliance of identity verification for interface calls |
Three Common Configuration Mistakes
- Enabling the reranking model leads to only one reference result being returned. Phenomenon: The Q&A interface displays only 1 reference document. Interface logs show only a single result is passed to the model. Cause:
quoteMaxTokenis set to the length of a single document. Only the highest similarity result can be fully included in the context. - Parsing failure occurs after uploading refinery and chemical party building PDF files. Phenomenon: The interface shows "file parsing failed". The interface returns status code 400. Cause: Special fields such as production team numbers embedded in refinery and chemical party building materials are not adapted. This triggers format errors during chunking.
- Model call timeout occurs. Phenomenon: No response is returned for over 30 seconds during a single round of Q&A. The interface returns status code 504. Cause:
maxContextis set too large. The model takes too long to load the context, exceeding the system's default timeout threshold.
How to Verify Successful Configuration
- Upload one official party building document issued by the refinery and chemical sector party committee. Check if reference results include metadata fields such as release document number and issuing unit.
- Submit a party building Q&A query that includes "team safety learning". Verify that the response content matches official document statements.
- Review system interface logs. Confirm that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare configured correctly, with no identity verification errors. - Adjust the
temperatureparameter to 0.4. Verify that the response rigor meets party building Q&A requirements.
The values provided are common starting points, and should be evaluated against the user'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.