This document is written based on FastGPT v4.17.0.
What the data for this category looks like
Data sources for community report handling include report systems, content details, user historical records, and review rules. Update frequency is daily or real-time. Daily produced documents include report tickets, processing records, appeal forms, and user notification templates. Document fields include report ID, involved content link, user historical violation records, review rule entries, disposal results, and other items. There are no unified standard statistical units. Data volume fluctuates with community activity levels.
What constraints do these characteristics impose on multi-turn dialogue and prompt configuration
The data characteristics of community report handling impose multiple constraints on multi-turn dialogue and prompt configuration. Report tickets must be associated with multi-source data such as report systems, content details, and user historical records. Multi-turn dialogue must support gradual retrieval of information from different sources, and fixed context association rules must be used to avoid information misalignment. Real-time updated review rules and user historical records require the dialogue chain to pull the latest data in real time, preventing the use of expired rules. Differences in fields across documents require prompts to clearly specify the call priority and output format for each document, preventing field confusion. Disposal results must match the fixed structure of user notification templates. Prompts must constrain the order and type of output fields to ensure generated notifications align with ticket fields.
How to set the configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the single text length of report tickets and content details, avoids truncating key violation evidence |
| Overlap Length | 100–200 characters | Ensures cross-chunk violation descriptions are not split and lost, maintains context coherence |
| Single Search Limit | Top 3 entries | Limits the number of returned knowledge base entries, adapts to the single-ticket review scenario for report handling |
| Maximum Context Length | 4000 token | Accommodates multi-turn report dialogue history and associated data, prevents context overflow |
chatId | Bound to report ticket ID | Ensures each dialogue is associated with a unique ticket, facilitating traceability of processing records |
variables | Pass current report ID and user historical violation flags | Dynamically loads exclusive data for the corresponding ticket, improving review accuracy |
Three common mistakes
- Phenomenon: The conversation interface returns results that do not carry the knowledge base associated ID. Cause: The report ticket ID bound to the knowledge base is not passed in
variables, making it impossible to associate the corresponding knowledge base entries. - Phenomenon: In a local deployment scenario, images stored as URLs in the knowledge base cannot be output by the model. Cause: The prompt does not explicitly require extracting and formatting image URLs, and no rule for loading image links in the context is configured.
- Phenomenon: The disposal notification generated by the dialogue does not match the preset template format. Cause: The order and required items of output fields are not specified in the prompt, resulting in generated content that does not match appeal forms and notification templates.
How to confirm the configuration is correct
- Initiate a simulated report ticket dialogue, check if the returned results carry the bound ticket ID, and confirm that the
chatIdconfiguration takes effect. - Upload a test knowledge base containing image URLs, initiate a dialogue associated with the ticket, and verify that the model can correctly extract and output image links.
- View the conversation logs, confirm that the number of knowledge base entries returned by each search matches the preset single search limit.
- Check that the
messagesfield correctly passes historical report dialogue records, confirming that the context loading logic works properly.
All provided configuration values 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 2026-10-19.