What Data for This Category Looks Like
Data for infrastructure construction intelligent due diligence reports targeting financial institutions primarily comes from official or project-party retained materials including project approval documents, bidding announcements, construction logs, supervision inspection records, and cost settlement files. Update frequency changes with project phases: weekly progress data syncs during construction, daily settlement detail updates during completion phases. Most documents use a mixed format of structured tables and paragraphs, containing fields such as project number, construction milestone, engineering quantity (units including cubic meters, square meters, tons, etc.), cost amount (units including yuan, ten thousand yuan), and inspection date. Paper materials from some older projects require scanning and recognition to convert into processable formats.
Constraints Imposed on Workflow Orchestration
The multi-source mixed format of infrastructure construction due diligence data requires workflows to support parallel access to different data source types, while adapting to OCR recognition for scanned documents. Document length varies widely; a single cost settlement file may exceed 100,000 words, so segmented processing nodes must be configured to avoid context overflow. The specificity of field units requires a unit verification step in the workflow to prevent mismatches between engineering quantity and cost units. Data update frequencies differ across project phases, so workflows must support triggering corresponding tasks based on project nodes. Routine scheduled tasks can be used during the archiving phase.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 20–30 items | Infrastructure construction due diligence reports need to link multiple historical construction and inspection records. 20–30 context items cover most project linking needs, avoiding model output deviations caused by context overflow. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Scanned archive files or large cost tables for single infrastructure projects take longer to parse. 600 seconds covers the complete processing flow for most large files. |
UPLOAD_FILE_MAX_SIZE | 2000 MB | A single completion settlement file may include multiple scanned construction drawings and multi-page paper documents. 2000 MB can hold complete archive materials for most projects. |
Chunk size | 800–1200 characters | Due diligence reports contain a large number of technical terms and long sentences. A segment length of 800–1200 characters balances model understanding accuracy and sentence integrity. |
Similarity threshold | 0.75–0.85 | Accurate matching of compliance clauses and issue types in due diligence reports is required. A threshold that is too low will cause false matches, while a threshold that is too high will miss potential compliance risks. |
Loop Trigger Condition | Content generated twice consecutively passes verification | Revisions to infrastructure due diligence reports must avoid meaningless repeated adjustments. Two successful verifications confirm that content meets requirements. |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: An AI node is set to 30 context items, but only 2 context items are shown in conversation details, and replies cannot link to historical inspection records. Cause: The
maxContextparameter is only modified on a single AI node, and not synchronized to the global conversation link configuration, resulting in the context parameter not taking effect. - Phenomenon: Uploaded engineering drawings or scanned documents are only parsed as plain text, and cannot be recognized by large models for professional drawing content. Cause: No direct file upload node is configured in the workflow, and the system default general text parsing process is incorrectly used to process professional infrastructure files.
- Phenomenon: The
问题分类node in the workflow has no output results, and cannot trigger subsequent verification steps. Cause: No classification labels and matching rules are configured for the问题分类node, and direct connection to the AI generation node prevents recognition of issue types in due diligence reports.
How to Verify Successful Configuration
- Navigate to the configuration page for each AI node in the workflow, verify that the
maxContextparameter matches the preset value, and initiate a test conversation to check if the number of context items in the conversation details matches. - Upload a single infrastructure project archive file larger than 500 MB, and check if file parsing progress completes within the time set by
PARSE_FILE_TIMEOUT_SECONDS. - Trigger a complete workflow run, check if the
问题分类node outputs expected classification results, and confirm that the loop process terminates according to preset rules. - Upload a scanned drawing of an infrastructure project, and check if the analysis content output by the large model includes professional information related to the drawing. If the output only contains parsed plain text, the configuration is not effective.
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.