What This Category of Data Looks Like
This category of data comes from raw material quality certificates, heating furnace systems, press collection data, MES systems, non-destructive testing instruments, and customer forging drawings. Daily documents include forging process specifications, cutting cards, heating furnace records, forging process cards, mold life records, heat treatment work orders, and ultrasonic testing reports. This data updates per individual forging, batch of materials, or furnace heat. Document fields include forging number, material grade, furnace batch number, process parameters, testing results, and more. Units include millimeters, degrees Celsius, megapascals, and others.
Constraints Imposed on Knowledge Base Retrieval and Recall by This Category
This category of data updates per individual forging, batch of materials, or furnace heat. Retrieval processes must accurately associate unique identifiers such as forging number and furnace batch number to avoid mixing cross-batch data. Daily documents contain specialized process parameters and testing results. Subdivided fields must be matched to enable precise recall, preventing generic searches from returning irrelevant content. Data sources cover production equipment and testing systems. Some data uses structured numerical values, so systems must support numerical range retrieval. Bidding scenarios require fast access to cost and process data for the corresponding batch. Retrieval response times must align with bidding preparation timelines to avoid delays that disrupt progress.
Configuration Settings
This configuration is adapted for FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Meets the accuracy requirement for matching specialized fields such as forging processes and furnace batch numbers, preventing low-relevance results from being included in bid documents |
limit | Top 8 entries | Balances the comprehensiveness of retrieval results and reading efficiency for bid preparation, avoiding excessive redundant data that causes distraction |
usingReRank | Enabled | Optimizes ranking for specialized structured data, prioritizing recall of process and testing records with the highest match to current forging parameters |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands search terms such as forging number and furnace batch number to associate and match related documents including cutting cards and heating furnace records |
collectionIds | Specify dedicated knowledge base collections for forging processes and testing reports | Isolates production data unrelated to bidding, narrows retrieval scope, and improves response speed |
Three Common Misconfigurations
- Symptom: Calling the API to retrieve a private knowledge base returns empty results. Cause: The
collectionIdsconfiguration item is not correctly specified. The retrieval scope covers non-target knowledge base collections, and the scope is not limited to the dedicated collections for forging processes and testing reports. - Symptom: The chat page or knowledge base page of FastGPT v4.17.0 crashes during loading. Cause: The
limitparameter value is not restricted. A single retrieval returns too much redundant data, exceeding the system memory processing limit. - Symptom: Newly created data indexes fail to recall the latest furnace heat testing reports and heating records. Cause: Incremental update trigger logic is not configured. Full index updates run exclusively, so real-time production data updated per furnace heat cannot be synchronized.
How to Verify Successful Configuration
- Manually enter a forging number and furnace batch number, check whether the retrieval results include related documents such as cutting cards and heating furnace records.
- Review the number of returned retrieval results, confirm that it matches the configured value of the
limitparameter. - Call the API interface to test retrieval, confirm that the
similarityscores of returned results fall within the preset range. - Simulate a bid preparation scenario, retrieve specific process parameters, confirm that the recalled documents match the forging type of the current task.
The values provided here are common starting points, and should be evaluated against the relevant samples associated with the specific use case.