What This Type of Data Looks Like
Thermal industry research report data primarily comes from industry association public reports, quarterly financial reports of thermal supply enterprises, regulatory agency policy documents, and securities firm industry analysis reports. Update frequency adjusts based on industry trends, with concentrated updates during quarterly earnings seasons, plus supplementary content after policy releases. Most documents are a mix of structured and semi-structured content, including fields such as research report title, issuing institution, and release date. Core data fields include 供热负荷, unit heating cost, and heating days, with corresponding units of megawatts, yuan/gigajoule, and days respectively. Full text sections include industry trend analysis and specific project cases.
Constraints on Vector Models and Indexing
Thermal industry research reports include structured numerical fields and semi-structured analytical text. Vector mapping must support both numerical features and natural language semantics. A single vector model may overlook correlations between critical business data without this support. Centralized report updates require indexes to support incremental synchronization. This reduces resource consumption from full index rebuilding. Core business field units and definitions stay fixed. Vector models must preserve consistent semantics across fields to avoid cross-field confusion. Some reports include project-level details with wide variation in text length. Adaptive segmentation rules must be configured to accommodate document chunks of different lengths.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Thermal industry research reports contain long-form analytical text and structured data blocks. This range balances semantic completeness and indexing granularity, avoiding overly long chunks that disperse semantics or overly short chunks that lose context |
vector_model | text-embedding-ada-002 or bge-large-zh-v1.5 | These models have good adaptability to industry terminology and structured field semantics, and can accurately map semantic correlations of proprietary thermal industry data |
index_incremental_sync | Enabled | Updates to thermal industry research reports are concentrated during quarterly nodes. Incremental synchronization reduces computational overhead of full indexing, adapting to business update rhythms |
retrieval_top_k | Top 5–7 results | Core business data in thermal industry research reports is highly concentrated. Too many retrieved results will introduce irrelevant analytical content, while too few will fail to cover complete business scenarios |
parse_file_timeout_seconds | 600 seconds | A single thermal industry research report may contain multi-page project details and data tables. A longer timeout ensures complete parsing of all content |
similarity_threshold | 0.72–0.8 | Low-relevance generic industry analysis content must be filtered out, retaining only research report fragments directly related to thermal business |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: After upgrading the version, the same CSV-format thermal industry research report data cannot be chunked normally, and the interface returns a
400 Bad Requesterror. Cause: The new version updated the format validation rules for CSV fields. The original data is missing the required供热负荷field, or the unit format does not meet the new validation requirements. - Symptom: The knowledge base indexing task shows a
pendingstatus for more than 2 hours, with no indexing completion progress displayed. Cause:index_incremental_syncwas not configured to be enabled, and no sharding processing was set during full indexing. The large volume of thermal industry research report data leads to exhaustion of computational resources. - Symptom: After switching the vector model, the knowledge base reference results are empty, with no relevant research report content returned. Cause: The vector index for the existing knowledge base was not regenerated. The vector embeddings from the old model are incompatible with the new model format.
How to Verify Proper Configuration
- Upload a single thermal industry research report sample, review the chunking results, and confirm each chunk contains complete business fields and analytical text with no truncation or missing fields.
- Run a small-scale indexing task, check the indexing progress logs, and confirm there are no timeout or format validation errors.
- Initiate a test query, enter thermal industry proprietary terminology, verify the field completeness and semantic relevance of the retrieved results, and adjust the threshold to a range that meets business requirements.
- Simulate an incremental update scenario, upload new research report data, confirm that the indexing task only processes the new content, with no full index rebuilding triggered.
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.