What the data for this category looks like
Public data for optical modules comes primarily from official specification documents of communications equipment manufacturers, communications industry standard documents, publicly available supply chain quotations and performance parameter databases. Data updates trigger irregularly alongside manufacturer new product launches and industry standard iterations. A single update covers dozens of parameter entries. A single due diligence document typically includes fields such as packaging form, transmission rate, operating temperature range, power consumption, interface type, and transmission distance. Field units mostly use standardized measurement identifiers like Gbps, W, degrees Celsius, kilometers, and similar.
Constraints on multi-turn dialogue and prompt engineering
Dispersed multi-source parameter sources create large variations in document formats for single inputs. Clear parameter alignment rules must be defined in the first prompt to prevent cross-source parameter confusion. Irregular update cycles require adding recall triggers for the latest parameter libraries during multi-turn dialogue, to ensure returned content matches currently available or latest standard optical module parameters. User questions may span multiple parameter dimensions due to the multi-field document structure. Multi-turn follow-up questioning trigger logic must be configured to supplement missing query conditions. The standardized unit system requires prompts to specify unified measurement rules, to avoid mixed units in returned results.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single optical module due diligence documents typically include dozens of parameters. Multi-turn dialogue must retain multi-turn context and multiple document slices. This range covers context requirements for typical scenarios. |
RECALL_TOP_N | Top 6–8 results | Optical modules have many parameter fields. Too many recalled results increase model inference load; too few may miss key performance parameters. This range balances recall coverage and inference efficiency. |
PARSE_FILE_CHUNK_SIZE | 1000–1500 characters | Optical module documents have compact parameter entries. This chunk length ensures single chunks contain complete single-category parameter groups, avoiding broken parameter associations after splitting. |
PROMPT_TEMPLATE | Fixed optical module parameter alignment rules + multi-turn follow-up questioning guidance | Must explicitly require the model to unify units and align parameter naming across sources. Trigger follow-up questioning when user questions lack required conditions, to adapt to multi-field query requirements for optical modules. |
UPLOAD_FILE_MAX_SIZE | 500 MB | Optical module due diligence reports typically include multiple specification diagrams and parameter tables. This size covers upload requirements for most single due diligence documents. |
LOG_RETENTION_DAYS | Calibrated via team testing | Adapts to compliance requirements for log retention across different teams, and avoids redundant logs occupying storage space. |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfiguration Issues
- Phenomenon: After uploading an optical module due diligence document during a dialogue, the model returns a "context length exceeded" error. Cause: The
PARSE_FILE_CHUNK_SIZEparameter is not configured for proper chunking, and the text content of a single document exceeds the context limit supported by the model. - Phenomenon: After the tool call process ends, the dialogue result includes unformatted tool call JSON content. Cause: The
PROMPT_TEMPLATEdoes not explicitly require the model to output only organized due diligence conclusions, and does not hide the original tool call output. - Phenomenon: Images imported from optical module due diligence reports fail to load normally, with missing link domain names. Cause: The document parsing process does not configure image domain name completion rules, and original domain name information is lost when converting Word-format image links to Markdown format.
How to Verify Correct Configuration
- Upload a standard optical module due diligence document with multiple parameters and images, and confirm that parsed text chunks fully retain parameter associations without broken splits.
- Initiate multi-turn questions spanning different parameter dimensions, and confirm that the model automatically supplements missing query conditions, and that returned results use unified units.
- Trigger the tool call workflow, and confirm that the final output only includes organized due diligence conclusions, with no residual original tool call JSON content.
- Check the system log management interface, and confirm that log retention rules and cleanup mechanisms can be configured according to actual usage needs.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.