What the Data for This Category Looks Like
Data related to bids and quotations for cosmetics manufacturing comes from registered or filed formulas, raw material safety documents, weighing and emulsification filling equipment data, ERP/MES systems, laboratory test records, and packaging material version archives. Daily documents include formula process sheets, weighing and feeding records, emulsification filling records, cleaning and site clearance records, semi-finished and finished product inspection reports, and label review documents. Data updates occur per production batch or each line change. Fields include batch number, raw material dosage, filing number, and restricted substance content. Units include g, mL, expiration date, and others.
Constraints Imposed on Workflow Orchestration
The bid and quotation workflow for cosmetics manufacturing must align with the traits of scattered data sources and update frequency that varies per batch. Multiple data sources pull data from distinct systems such as ERP, MES, and laboratories. This requires the workflow to support pulling data across multiple nodes and bind the batch number as an associated parameter, to ensure data maps to the correct production batch. Each line change triggers data updates, so the workflow must trigger based on production events to match the update rhythm of each batch. Formulas and labels must meet filing requirements, so the workflow must add a filing data verification node to prevent inconsistent formulas and filings. Bid documents must link to actual production data, so the workflow must integrate field verification across multiple links to ensure data accuracy.
Configuration Settings
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
variables | Bind batch number, filed formula number, raw material safety document version, set context parameter to 1000 tokens | Bid documents must link to filing data and actual production parameters for the corresponding batch, and control the token usage limit for each AI node |
| Node Trigger Rule | Trigger after each production batch is completed | Match the data update frequency of each line change in cosmetics manufacturing, and align with business rhythm |
nodeId | Bind the IDs of raw material verification node, label review node, and quotation calculation node | Orchestrate multiple nodes to execute in sequence, and ensure the verification and quotation process is correct |
| Single Call Timeout | 600 seconds | Balance the waiting time for ERP/MES interface calls and process efficiency |
| Single Database Query Limit | Top 5 entries | Match the core data volume required for bid documents |
| Retry Count | 3 times | Handle retries for temporary interface call failures |
Three Common Misconfigurations
- When orchestrating multiple AI large model conversation nodes, token accumulation exceeds the limit. The symptom is a node execution error prompting insufficient tokens. The cause is that independent context parameters are not configured for each node's
variables, leading to shared token count accumulation across multiple nodes. - Calling a specified database returns empty query results. The symptom is no data in the database query node output. The cause is that the query condition in
variablesis not correctly bound, and production data for the corresponding batch is not linked. - After publishing the channel link, an "undefined" is not valid JSON error is returned. The symptom is that the interface return format does not conform to standard JSON structure. The cause is that the workflow output is not unified to a standard format, and the output structure is not verified during local testing.
How to Verify a Correct Configuration
- Check the parameters configured in
variables, confirm that the filing formula number, raw material dosage and other data for the current production batch are bound, and match the batch data in ERP/MES. - After triggering the workflow, view the execution logs of each node, confirm that the execution results of the raw material verification and label review nodes meet expectations.
- Generate the channel link and call it, confirm that the returned result is in standard JSON format, with no missing fields or undefined values.
- Simulate a line change and trigger the workflow, confirm that all orchestrated nodes are executed in the preset sequence.
The values provided here are common starting points and should be evaluated against the reader's own samples.