What the data for this category looks like
Optical and optoelectronics investment research data comes primarily from public industry research reports, listed companies’ periodic reports, monthly monitoring data from industry associations, and publicly available technical documents from supply chain manufacturers. Update frequency falls into three categories: listed companies’ periodic reports are released quarterly, industry research reports are updated irregularly per project, supply chain technical parameters are adjusted irregularly alongside product iterations, and monthly monitoring data is updated weekly. Document structures include structured tables such as production capacity and revenue data, paragraph-style industry analysis, and detailed lists of segmented product parameters. Core fields include report release time, enterprise entity, product model, panel size, production capacity scale, R&D investment amount, and process node, with corresponding units of inches, ten thousand wafers per month, 100 million yuan, and nanometers.
What constraints these characteristics impose on multi-turn dialogue and prompting
Optical and optoelectronics data contains a large number of professional technical parameters and structured numerical values. Multi-turn dialogue must accurately retain the parameter comparison logic across different rounds to avoid context loss. The update frequencies of different data sources vary significantly, so prompts must clearly define the data time range to prevent the introduction of outdated production capacity or technical parameters. There are subtle differences in the units of segmented products such as inches and nanometers, so prompts must mandate clear parameter units to avoid confusion across product categories. Large research report documents have considerable length, so the context window size must be limited to prevent redundant information from interfering with dialogue logic.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Optical and optoelectronics research reports often include cross-enterprise parameter comparisons, and a longer context can fully retain the parameter association logic of multi-turn dialogues |
recallCount | Top 6–8 entries | This category of data contains a large number of segmented technical parameters and production capacity data, so enough recalled entries are needed to cover investment research queries across different dimensions |
similarityThreshold | 0.72–0.78 | Optical and optoelectronics parameters have high precision requirements. A threshold that is too low will introduce irrelevant technical data, while a threshold that is too high may miss comparison information for different models of the same product category |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large industry research reports or multi-page supply chain data tables takes a long time; this setting avoids interrupting the parsing process due to timeout |
fileParseMaxSize | 1000 MB | Adapt to the upload requirements of large industry research reports and avoid upload errors triggered by oversized files |
promptTemplate | Follow the format of "define time range + parameter comparison" | Clearly define the data time range to avoid using outdated production capacity or technical parameters, and standardize the output format for parameter comparisons |
maxResponseToken | 2000–3000 characters | Investment research analysis needs to fully present parameter comparisons or trend deductions. A reasonable character limit balances response completeness and interface load |
The parameter values provided on this page are all common starting points for configuration. The actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing the settings.
Three Common Misconfigurations
- An
unAuthChaterror code is returned when calling the dialogue interface, even though the apikey configuration is correct. Cause: The exclusive investment research knowledge base for optical and optoelectronics is not associated with the corresponding dialogue application, resulting in failed permission verification. - The AI dialogue response contains line breaks, triggering a JSON request failure. Cause: No line break escaping rule was added in the prompt configuration, or no string escaping processing was performed on the response content, resulting in broken JSON format.
- An error occurs when uploading an industry research report file, while the text dialogue function works normally. Cause: The
fileParseMaxSizeparameter was not adjusted to a threshold suitable for large research reports, or the file format is not supported by the parsing engine.
How to Verify Proper Configuration
- Initiate two consecutive queries. First, query the panel size parameters of one enterprise, then query the parameters of another enterprise in the same product category, and check whether the dialogue context retains the parameter comparison basis from the previous round.
- Upload a research report file containing multi-page technical data tables, and confirm that it can be properly associated with the knowledge base after parsing is complete.
- Construct a test query containing line breaks, and check that the line breaks in the AI response have been properly processed with no format errors.
- Initiate a query with parameter precision requirements, and check that the matching degree of the recalled results conforms to the preset precision rules.
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.