What data for this category looks like
Carbon steel marketing content data primarily comes from enterprise ERP systems, sales ledger databases, and marketing material platforms. Two update rhythms are used: regular product quotes are updated weekly, while scenarios such as price adjustments and new product launches are updated in real time. Document structure includes two parts: structured fields and unstructured descriptions. Structured fields include steel grade, specification size, yield strength, tensile strength, unit price, and delivery cycle. Corresponding units are: none, mm, MPa, MPa, yuan/ton, and day respectively. Unstructured content includes product application scenario descriptions, promotional copy, and technical parameter explanations. Document length ranges from hundreds of characters for specification sheets to thousands of characters for application plans.
Constraints imposed on vector models and indexing
The multi-field attribute and differing update rhythms of carbon steel data create clear constraints for the vector model and indexing workflow. Structured fields with fixed-unit numerical parameters require vector models to support semantic vectorization of numerical values with units, to avoid losing parameter precision that would occur with plain text-only models. The mixed real-time and scheduled update rhythm requires indexes to support incremental updates without full reindexing, to reduce resource consumption. The wide range of document lengths requires chunking strategies to adapt to content of varying lengths, to avoid truncating core parameters. The mixed multi-type content structure requires indexes to support joint multi-field retrieval, to enable precise matching of parameters and scenarios.
How to set configurations
| Config Item | Recommended Approach | Rationale |
|---|---|---|
Vector Model Selection | Tencent Hunyuan Vector Model or Custom Vector Model | Supports vectorization of numerical fields with units, and adapts to structured parameters such as steel grades, strength values, and unit prices for carbon steel |
Chunk Length | 800–1200 characters | Carbon steel marketing documents include specification parameters and scenario descriptions. This range can fully cover a single specification description plus accompanying content, and avoids truncating critical numerical values |
Number of Retrieved Results | Top 8–12 results | Carbon steel purchasing decisions require comparison of multiple specification parameters. A sufficient number of retrieved results can cover requirements for different application scenarios |
Similarity Threshold | 0.75–0.85 | Distinguishes parameter differences between similar steel grades, and avoids retrieving unrelated specification documents |
Index Incremental Update Toggle | Enabled | Carbon steel quotes are updated weekly, and price adjustments are updated in real time. Incremental updates can reduce resource consumption from index reindexing |
Custom Vector Database Integration | Enter Qdrant cluster address and API key | Reuses existing self-hosted Qdrant instances with existing carbon steel data, without requiring re-import |
The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material forms, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Issue: No retrieval results after connecting a custom Qdrant database. Cause: Failed to configure field mapping between the Qdrant collection and the FastGPT knowledge base, and failed to align core fields such as steel grades and unit prices for carbon steel.
- Issue: 403 error returned after configuring the Tencent Hunyuan vector model. Cause: Failed to enable API access permissions for the vector model in the corresponding cloud platform console, or the API key was configured incorrectly.
- Issue: Unable to complete channel configuration after enabling the index model. Cause: Failed to complete API key verification for the vector model in the model supplier list first, and proceeded directly to the channel configuration step.
How to confirm the configuration is complete
- Upload a single carbon steel marketing document containing steel grades and specification parameters, and check that the vector generation task status is Completed with no error logs.
- Initiate a retrieval test by entering "Q235B steel plate application scenarios", and confirm that the retrieved results include matching documents, and the similarity values fall within the set threshold range.
- Modify an already ingested carbon steel quote data, wait 10 minutes, then perform a retrieval, and confirm that the results show the latest unit price and delivery cycle.
- Switch to the custom Qdrant database, perform a bulk import test, and confirm that existing historical carbon steel data can be retrieved 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.