What the data for this category looks like
Data for this category comes primarily from customer interviews, bidding documents, vendor product materials, and historical project plans. Update frequency is per order or weekly. Daily generated documents include technical proposals, customer requirement surveys, quotation lists, and demo scripts. Common fields include technical roadmap, implementation boundaries, compliance requirements, and quotation items. There are no fixed universal units; values adjust based on the content of each individual document.
What constraints these characteristics impose on model integration and configuration
Pre-sales technical proposal data is sourced from scattered locations and mostly consists of unstructured text. This requires model integration to support parsing of multi-format documents. Update frequency varies by project progress. Configurable context length must be flexibly adjusted to fit different scales of proposal documents. Documents include content related to compliance requirements. Model configuration must prioritize accuracy of compliance reviews. Unlike the bidding document preparation category, technical roadmap and implementation boundaries must be clarified first. The model must prioritize extracting core boundary information from proposals to ensure output aligns with pre-sales business needs.
Recommended Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Pre-sales technical proposals typically include multiple related documents. This setting covers full context to ensure completeness of compliance reviews |
maxTokens | 4000–6000 token | Compliance review output for a single proposal must include complete content such as technical roadmap and boundary descriptions. This fits standard output lengths |
temperature | 0.1–0.3 | Compliance reviews require precise, non-divergent output. This avoids irrelevant statements caused by overly high parameter values |
AIPROXY_API_ENDPOINT | Fill in according to the private deployment environment, for example http://aiproxy:3000. Do not append paths such as /v1 or /chat/completions | Required environment variable for App/Admin server. Adapts to the root access address of enterprise internal AI Proxy services, ensuring data transmission security |
toolChoice | auto | Automatically calls built-in compliance verification tools without manual triggering. Fits daily operation habits of pre-sales consultants |
quoteMaxToken | 2000 token | Retains sufficient original text reference fragments for compliance traceability and customer verification |
Three Common Configuration Mistakes
- After upgrading FastGPT v4.17.0 and running the deployment script, simple applications throw uncaught exceptions. The interface displays an uncaught exception prompt box. Background logs show context length exceeded errors. Troubleshooting step: Verify if the
maxContextparameter matches the context length requirements of the current task. - The model is configured to disable thought output, but the answer still includes
<think>tags. Formatted thought blocks appear in the output content. Troubleshooting step: Check if the format verification parameter for the corresponding model was not configured correctly, or if the model’s native thought tag output rules were not matched. - The workflow problem classification node cannot select an AI model. No available model options appear in the drop-down list. Troubleshooting step: Check if the required
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENenvironment variables were not configured on the App/Admin server, or if access permissions for upstream model channels were not set properly.
How to Verify a Successful Configuration
- Upload a single pre-sales technical proposal document, run the compliance review task, and confirm the output includes complete compliance clause extraction with no redundant thought content.
- Run a local test script, and check the console log for no uncaught exceptions and no context length exceeded errors.
- Navigate to the workflow configuration page, and confirm AI model options can be selected normally and associated with preset pre-sales document data sources.
- Submit a test bidding document fragment, and confirm the output compliance review result includes the corresponding original text reference fragments.
The values given here 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.