What the Data for This Category Looks Like
Data sources for commercial real estate marketing content primarily include project investment prospectuses, business district survey reports, tenant lease agreements, marketing promotional materials, and surrounding supporting data documents. Update frequency aligns with project progress: large volumes of documents are generated during new project preparation, with irregular updates when investment promotion changes, supporting facility adjustments, or marketing campaigns launch. Daily maintenance frequency is low.
Document structures fall into three categories: structured table documents (such as floor business type layout tables and rental price lists), semi-structured presentation documents (such as project promotion PPTs), and unstructured text documents (such as investment promotion copy and survey report paragraphs). Common fields include floor area (unit: ㎡), unit rental price (unit: yuan/㎡/day), settled brands, business district radiation scope, transportation supporting station names, and marketing campaign themes.
What Constraints Do These Characteristics Impose on the Document Parsing and Chunking Link
Structured table documents require the parsing process to retain row-column correspondence. Otherwise, the correlation between core fields such as rental price and area will be broken, making subsequent chunking unable to accurately match business information.
Documents with mixed formats need unified parsing logic. This avoids inconsistent chunking standards caused by typesetting differences across formats.
For documents mixing long survey report paragraphs and short tables, avoid splitting complete business information across multiple chunks. Also prevent individual chunks from being too long, which would harm subsequent retrieval efficiency.
The uniqueness of exclusive fields must be preserved. For example, the business district radiation scope and transportation supporting information for a single project must not be chunked repeatedly or omitted.
How to Set the Configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_MAX_SIZE | 500 MB | Commercial real estate marketing documents often include high-definition floor plans, business district maps and other materials. Single-file volume is generally large. 500 MB covers parsing needs for most project materials. |
chunk_size | 800–1200 characters | Commercial real estate documents include long survey report paragraphs and structured tables. This length retains complete correlation between core fields such as business type and rental price, and avoids splitting key information. |
chunk_overlap | 100–150 characters | Contextual connections across chunks must be preserved. For example, rental adjustment descriptions and business type linkage information in adjacent paragraphs ensure semantic coherence during retrieval. |
PARSE_TABLE_ENABLE | Enabled | A large share of commercial real estate documents includes structured content such as floor business type tables and rental price lists. Enabling this parameter retains row-column correspondence for tables, and avoids field matching errors. |
UPLOAD_FILE_TEMP_DIR | /data/fastgpt/upload/ | Temporary parsed files require unified management to avoid path conflicts across different deployment environments. This ensures parsing nodes can normally read uploaded files. |
PARSE_TIMEOUT_SECONDS | 300 seconds | Parsing large-scale investment prospectuses, multi-page PPTs and similar documents takes significant time. 300 seconds completes full parsing for most files, and avoids mid-parsing timeout interruptions. |
The parameter values provided on this page are conventional recommendations used to establish a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing the configuration.
Three Common Mistakes
- Phenomenon: After uploading a file in the server environment, the document parsing node returns a 404 error, while local environment uploads work normally. Cause: The configured temporary file directory
UPLOAD_FILE_TEMP_DIRdoes not match the server's actual deployment path, so the parsing node cannot read the uploaded file. - Phenomenon: Core structured fields such as rental price and area are empty in parsed chunk results. Cause: The
PARSE_TABLE_ENABLEparameter is not enabled, so the table parsing function is inactive, and structured table content from investment prospectuses cannot be extracted. - Phenomenon: After batch pushing files, some chunk results lose exclusive fields such as business district radiation population and transportation supporting facilities. Cause: A reasonable range for
chunk_sizeis not configured, so field information in long paragraphs is split across different chunks, and contextual connections are lost.
How to Confirm the Configuration Is Correct
- Upload an investment prospectus document containing structured tables. Check if the parsed text retains the row-column correspondence of the tables, and confirm
PARSE_TABLE_ENABLEis correctly configured. - Check the temporary file directory on the server. Confirm uploaded files are stored in the path specified by
UPLOAD_FILE_TEMP_DIR, to verify path configuration correctness. - Manually adjust the
chunk_sizeparameter. Upload a long paragraph survey report, and check if chunked content retains complete correlation between core fields, to confirm the value meets business needs. - Push a batch of files to the knowledge base. Check if the total number of parsed chunks matches the number of file pages or paragraphs, to verify overall configuration stability.
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.