Document Assistance for Speech and Report Drafting: Model Access and Configuration

Data Structure and Source for This Category

The data used for speech and report drafting mainly comes from internal official document archives, previously used formal draft templates, and daily demand documents awaiting drafting. Updates are triggered by individual drafting tasks, with each task corresponding to one document. Archived documents are updated on a project cycle or quarterly basis. Typical document structures include salutations, core arguments, data-backed paragraphs, closing remarks, and dates. Fields include topic, issuing entity, drafting date, and word count statistics, with units based on characters, pages, and word counts.

Constraints Imposed on Model Access and Configuration

Documents in this category have fixed structures and mandatory format requirements. Model outputs must match specified norms such as salutations, argument paragraphs, and closing remarks. Format constraint parameters must be clearly defined during model configuration. Document lengths vary widely, ranging from hundreds of characters to tens of thousands of characters. Single-round context length must be limited to avoid exceeding model threshold limits. Internal data sources require prioritizing model channels adapted to enterprise internal corpora. Token permissions must also be verified to prevent unauthorized model calls. Fields include clear business identifiers, so the model must accurately identify and populate corresponding content. Generation temperature must be adjusted to balance creativity and standardization.

How to Set Configurations

Reference only; verify against the target FastGPT release and deployment documentation.

| temperature | 0.2–0.4 | Required to maintain the standardization and rigor of official documents, avoiding excessive deviation from formal writing styles |

| maxTokens | 2000–4000 token | Conventional output length range for a single drafting task, to avoid truncation of core arguments and closing information |

| quoteMaxToken | 1000–2000 token | Sufficient reference document fragments must be retained to provide credible internal data support for content |

| toolChoice | auto | Automatically call document retrieval tools to supplement compliant data and template references from internal archives |

| AIPROXY_API_TOKEN | Fill in the enterprise-specific proxy token | Ensures permission legitimacy for model calls and secure data transmission |

Three Common Configuration Errors

• Phenomenon: An error message reading "This token is not authorized to use the model: text-embedding-3-large" is returned during model calls. Cause: The corresponding model channel has not been added to FastGPT’s available groups, or the token’s permissions do not cover the specified model type.
• Phenomenon: A "no available channel" prompt appears after configuring the bce-embedding channel. Cause: The channel has not been bound to the model group for the current application, or the interface information in the channel configuration has not passed verification.
• Phenomenon: Pre-configured reranking models cannot be selected when creating an application. Cause: The reranking model configuration item has not been correctly loaded in the global configuration, or the configured reranking model has not passed availability verification.

How to Verify Successful Configuration

• Review the model channel list to confirm all added models show normal available status, with no red error markers.
• Run a test drafting task to check if the generated content follows the standard structure for speeches and report materials.
• Confirm that the AIPROXY_API_TOKEN and AIPROXY_API_ENDPOINT configuration values match official guidelines, with no missing or incorrect characters.
• Adjust the temperature parameter, observe changes in the rigor of generated content, and confirm the parameter takes effect.

These values serve as common starting points, and should be validated against the specific samples of the target deployment.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.