What the data for this category looks like
Solar PV research report data primarily comes from brokerage research institute power and equipment track research teams, industry association public reports, and third-party industrial data platforms. Updates are triggered by core events, including new installed capacity policy announcements, silicon material price fluctuations, and the release of quarterly industry data. The structure of individual documents includes modules such as core industrial data, regional installed capacity analysis, and industrial chain link breakdown. Fields include installed capacity unit GW, module price unit yuan/W, industrial chain link names, and more. Character counts vary widely across individual documents.
What constraints do these characteristics impose on the model access and configuration workflow?
Professional units and industrial terminology in solar PV research reports require models to accurately identify and associate corresponding data dimensions, to avoid retrieval bias caused by unit confusion. The wide range of character counts per document means adaptive segmentation strategies are needed to prevent truncation of core industrial data. Frequently updated documents require vector database sync cycles aligned with industry event timelines, to avoid retrieving outdated data. The multi-module document structure requires models to accurately locate core data paragraphs, to improve retrieval targeting.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
segment length | 800–1200 characters | Solar PV research reports contain long paragraphs of industrial chain analysis and data modules. This segmentation range balances context completeness and model inference efficiency |
recall count | top 10–15 results | Solar PV track data is scattered across research reports for different industrial chain links. A sufficient number of candidate documents must be recalled to cover core data dimensions |
rerank return count | top 3–5 results | The rerank model is used to filter the most relevant core data. This range avoids inputting excessive redundant data into the model while retaining key information |
similarity threshold | 0.75–0.85 | Semantic similarity of industrial terminology in the solar PV sector is relatively high. This threshold filters irrelevant matching results while retaining effectively associated research report content |
vector database sync interval | every 6 hours | Solar PV industry data is updated frequently alongside policy and price fluctuations. Regular sync ensures the timeliness of retrieved data |
toolChoice supported models | open-source large models that support function calling | Solar PV research report retrieval requires calling data extraction tools, which requires models compatible with the toolChoice feature |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to conduct testing on local samples prior to finalizing settings.
Three common configuration errors
- Phenomenon: After enabling the rerank model, only a single highest-similarity research report entry is returned. Cause: The
rerank return countparameter was not configured correctly, with the default value set to 1, resulting in only a single output result. - Phenomenon: In a single workflow, multimodal data is incorrectly assigned to a plain text model for processing, resulting in format errors. Cause: No binding rules were set between data types and models, and no type filtering configuration was used via workflow nodes to distinguish between plain text and multimodal inputs.
- Phenomenon: An error indicating model incompatibility occurs when calling the toolChoice feature. Cause: A model that supports the toolChoice feature was not selected. Some open-source models do not support the function calling protocol and cannot trigger tool calling logic.
How to verify successful configuration
- Upload a single solar PV research report, check the segmented text block length in the knowledge base parsing log to confirm it matches the configured segmentation range.
- Enter a query related to solar PV module prices, verify the number of recalled research reports to confirm it matches the configured recall count.
- After enabling the rerank model, check the context content input to the model to confirm the number of reranked research reports meets the configured requirements.
- After configuring the vector database sync interval, wait for the corresponding duration and check the vector database update records to confirm the sync logic is triggered normally.
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.