What Data for This Category Looks Like
Data for this category mainly comes from customer interviews, bidding documents, vendor product materials, and historical project plans. Four types of documents are routinely produced: technical proposal books, customer requirement research forms, quotation lists, and demo scripts. Data updates follow a per-project cycle, typically updated per order or weekly. Documents are built around customer technical requirements, and include core fields such as technical roadmap, implementation boundaries, and quotation configurations. There are no uniform mandatory units, and matching must be done based on individual project scenarios. Typical users include system integrator pre-sales consultants, solution architects, and sales teams.
What Constraints These Characteristics Impose on the "Multi-turn Dialogue and Prompt Words" Link
Data for this category is scattered and exclusive to individual projects. Multi-turn dialogue must be bound to a single project context to avoid mixing data across projects. Data is dynamically updated as a project progresses, so real-time loading of the latest customer requirement research forms and quotation list content must be supported. Documents include core fields such as technical roadmap and implementation boundaries. Prompt words must accurately target these fields to prevent generating content that exceeds the boundaries of the proposal. Data iterations are frequent during a single project cycle, so the context window size must be limited to avoid interference from old data with current Q&A. Q&A results directly affect bidding and project profitability, so the output of multi-turn dialogue must strictly match confirmed proposal content.
How to Configure
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Conversation history format | Follow the messages array format, arranged in chronological order | FastGPT v4.17.0’s conversation interface requires using the messages parameter to pass conversation history, which complies with standard interface specifications |
| Maximum context window | First 10 rounds of dialogue + recent 7 days of project document snippets | Data for this category is updated per project. Limiting the window avoids interference from old data. 10 rounds of dialogue cover the standard multi-turn process for pre-sales Q&A, and 7-day snippets match the progress rhythm of individual projects |
| Context association rule | Bind chatId and project-specific identifier | chatId can fix a single session context. Binding the project identifier avoids mixing data across projects, which aligns with the project-exclusive data characteristics of this category |
| Variable injection method | Dynamically inject by extracting the variables field from project documents | Documents for this category include variable fields such as requirements and quotations. Dynamically injecting variables ensures Q&A content matches the latest project data |
| Prompt template | Fix the core Q&A direction with technical roadmap and implementation boundaries | The difference between this category and bidding document preparation is that technical roadmap and implementation boundaries are clarified first. Prompt words must guide output that aligns with the positioning of this category |
| Interaction parameter limits | Single dialogue content: 800–1200 characters, response timeout threshold: 600 seconds | Document content for this category is professional and moderately sized. 800–1200 characters can cover the core information of a single round of Q&A. 600 seconds covers the response time for conventional complex interactions |
Three Common Configuration Mistakes
- Phenomenon: Conversation records cannot be exported by project, only a global session list is displayed. Cause:
chatIdand project-specific identifier are not bound, causing the context to be disconnected from single-project data, and unable to match the project-exclusive data characteristics of this category. - Phenomenon: Uploaded attachments cannot be associated with subsequent dialogue content. Cause: The variable injection method is not configured to bind uploaded attachment documents, so the
variablesfield does not load attachment data, making it impossible to achieve context continuity for multi-turn dialogue. - Phenomenon: When calling the
chat/completionsinterface, the returned results do not filter specified knowledge base tags. Cause: Project-specific knowledge base tags are not included in the request, so the retrieval scope covers the full knowledge base, which does not comply with the constraints of single-project data for this category.
How to Confirm the Configuration Is Correct
- Initiate a multi-turn dialogue exclusive to a single project, check that the context only contains documents and dialogue content for that project, and confirm that the context association rule is active.
- Upload project-related requirement research forms or quotation lists, initiate a dialogue containing field queries, check that the reply matches the uploaded document content, and confirm that the variable injection method is active.
- When calling the conversation interface, pass the
messagesparameter andchatIdas required, check that the returned results are associated with the correct session context, and confirm that the conversation history format configuration is active. - Initiate a dialogue that exceeds the preset window limit, check that the system automatically truncates old dialogue content, and confirm that the maximum context window configuration is active.
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.