What the data for this category looks like
Text annotation project data primarily comes from raw corpora provided by clients, annotation samples produced by internal annotation platforms, domain-specific vocabularies, and quality inspection sampling results. Core documents circulated daily include annotation specifications, sample packages, quality inspection reports, and problem feedback forms. Data updates are usually synchronized daily or with each batch of annotation tasks. A single data entry typically contains fields such as original text, annotation tags, entity positions, and intent classification. All content focuses on semantic topics, with no image-related dimensional information.
What constraints these characteristics impose on multi-turn dialogue and prompt configuration
The data characteristics of text annotation projects impose multiple constraints on multi-turn dialogue and prompt configuration. First, data is updated synchronously daily or per batch, and sources include client-customized vocabularies and exclusive annotation specifications. Prompts must adapt to the rule details of individual batches. Multi-turn dialogue must retain batch context to avoid rule confusion across batches. Second, core data revolves around semantic entities, boundaries, and intent. Interactions must focus on text-based semantic questions, and do not require support for image-based interaction logic. Additionally, frequent quality inspection disputes and sample arbitration requirements mean prompts must preset response frameworks for common Q&A scenarios to improve Q&A efficiency.
How to set the configurations
The following configurations are optimized for the customer support scenario of text annotation projects, and apply to FastGPT v4.17.0:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Generate a unique value by combining annotation batch and client ID | Used to bind exclusive annotation rules and context for a single batch, avoiding rule confusion across batch interactions |
messages | Retain the first 15–20 conversation history entries | Adapt to the multi-turn traceability needs of annotation Q&A, while controlling resource usage by context |
variables | Preset annotation specification version, current sample package number, and quality inspection pass threshold | Inject dynamically updated business parameters into prompts to adapt to customized requirements for each batch |
| Maximum context length | 8000–12000 token | Accommodate complete annotation specifications, historical conversations, and sample details, avoiding truncation of key information |
| Voice input toggle | Disabled by default, enabled only when needed | Core interaction for text annotation scenarios is text-based. Voice input is an unnecessary feature, reducing model call costs |
Three common configuration mistakes
- Phenomenon: No response or incorrect format return after receiving image requests in multi-turn dialogue. Cause: Image processing logic is not configured for the text annotation scenario. The interaction defaults to supporting only text input, and cannot parse non-text format request content.
- Phenomenon: Voice conversation fails to generate transcribed text after enabling the voice input function. Cause: The corresponding voice model is not bound, or the voice-to-text trigger parameters are not configured, causing the transcription process to fail to start normally.
- Phenomenon: The dialog box cannot display a download button after obtaining a BLOB object via an HTTP node. Cause: The MIME type and file name parameters of the BLOB object are not passed to the conversation response, or the interaction rules for file download are not configured, preventing the front end from rendering the download component.
How to verify successful configuration
- Initiate a query for a single batch of annotation rules, verify that the conversation context only retains the exclusive vocabulary and specification content of that batch, with no redundant information from other batches.
- Enable the voice input toggle, input a voice test content, verify that the corresponding transcribed text can be generated normally. Disable the toggle, and confirm that no voice interaction entry appears.
- Call an HTTP node to return a test file in BLOB format, verify that the dialog box displays a download button and can normally trigger the download operation.
- Initiate a follow-up question about multi-turn annotation boundaries, verify that the historical conversation context can be correctly called, with no key information truncated or lost.
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 2026-10-19.