Data Profile of This Category
Data sources include public industry research reports, regulatory agency disclosure documents, listed company periodic announcements, and public datasets from professional databases. Update frequency aligns with the release cycles of each source. Regulatory documents are updated in real time. Industry research reports are updated in batches based on their release dates. Most documents use a mixed structured and semi-structured format. They include core indicator fields, business analysis paragraphs, and risk warning modules. Some documents have standardized unit identifiers.
Constraints for Multi-turn Dialogue and Prompt Engineering
Diverse data source types and varying update cycles require multi-turn dialogue to support context-aware filtering of recall results by time range. Mixed structured and semi-structured document formats require prompts to clearly define processing boundaries between structured field extraction and natural language analysis. This prevents confusion of information across different modules. Investment research questions for professional services often focus on cross-source validation. Multi-turn dialogue must retain prior question context to support progressive validation logic. It must also limit irrelevant context interference to avoid generating content off-topic for investment research.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 12000–15000 characters | Multi-turn dialogue for professional services investment research covers 3-5 progressive questions. This length retains sufficient context to support cross-source validation |
Recall Count | Top 8–12 entries | Investment research scenarios require integrating information from multiple data sources. Too many recall entries increase context load. Too few fail to support comprehensive analysis logic |
Similarity Threshold | 0.72–0.80 | Investment research data contains many technical terms. This threshold balances precise matching and cross-source associated recall, avoiding missed relevant research reports or announcements |
Reranked Return Count | Top 4–6 entries | Prioritize returning core data sources most relevant to the current query. This reduces information redundancy in multi-turn dialogue and improves response efficiency |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Professional services investment research documents often include long analytical paragraphs. This duration supports parsing large documents and adapts to S3 storage file read latency |
UPLOAD_DATASET_MAX_SIZE | 2000 MB | Meets the need for batch uploading research reports and announcements for professional services investment research. Prevents loading timeouts or storage errors caused by overly large individual datasets |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Each scenario requires individual evaluation. It is recommended to test against your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: After upgrading to version 4.14.3, uploading files or text datasets fails after migrating to S3 storage. Template import functions operate normally. Cause: S3 storage permission configurations and FastGPT storage parameters were not updated synchronously. The interface cannot write to the S3 storage path correctly.
- Symptom: The multi-turn dialogue window returns a 500 status code error, and context from prior questions cannot be associated. Cause: The
maxContextparameter value is too small. Context from prior investment research questions cannot be retained, preventing the model from understanding the logic of progressive questions. - Symptom: After configuring a prompt, specific datasets cannot be specified for search. Returned results include content from all associated datasets. Cause: The prompt does not explicitly bind the dataset identifier, or dataset permission isolation configuration is not enabled. The recall range remains unrestricted.
How to Verify Successful Configuration
- Upload a test industry research report document. Verify upload progress and storage path are correct. Confirm storage configurations are active.
- Initiate a progressive investment research query. For example, first ask about the overall status of an industry, then follow up with financial data for a specific company. Verify the model associates context from prior questions to generate a response.
- Configure a prompt and run a test. Verify recall results only include content from the specified dataset. Confirm dataset permissions and prompt parameters are correctly bound.
- After uploading batch documents, check that field extraction from parsed results matches expectations. Confirm document parsing configurations match the structure of investment research data.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.