What Data for This Category Looks Like
This category’s data primarily comes from enterprise existing IT system inventories, official directories of domestic hardware and software, project test environment outputs, and publicly available vendor materials. Daily produced documents include adaptation lists, compatibility test reports, migration plans, and issue ledgers. Common fields include original system component information, domestic replacement selections, compatibility verification results, risk levels, and migration plan milestones. Data updates follow the cycle of a single trusted innovation replacement project, or synchronize the latest domestic hardware and software directories quarterly.
Constraints for Multi-turn Dialogue and Prompts
Existing data sources are scattered and have inconsistent formats. Multi-turn dialogue must support cross-data source information integration. This prevents missing key adaptation details in single requests. Diverse document structures require prompts to use dedicated guidance rules for each document type. This ensures core content such as adaptation lists and test results can be accurately extracted during reviews. Data update cycles are long. Multi-turn dialogue must retain historical verification records. This avoids repeated verification of confirmed adaptation items. It must also support dynamic addition of the latest domestic hardware and software information.
Configuration Setup
Deployments for this scenario require FastGPT v4.17.0 or later. Correctly configure the server environment variables AIPROXY_API_ENDPOINT and AIPROXY_API_TOKEN. Do not use these variables as substitutes for service deployment settings in workflow global variables, application API request headers, or the general model management page.
AIPROXY_API_ENDPOINT is the root address of the AI Proxy service. An example is http://aiproxy:3000. Do not append /v1 or /chat/completions. This is not the address of a single model service such as VLLM, Ollama, or Xinference.
AIPROXY_API_TOKEN is the AI Proxy administrator token. It must match the AI Proxy server configuration and cannot be empty. This is not an application API key, model vendor secret, application-issued token, or request-estimated token count.
Missing these two variables will cause startup verification to fail. The core configurations for multi-turn dialogue and prompts are listed below:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Maximum context length | 8000–10000 tokens | Matches the average length of trusted innovation adaptation review documents, avoids truncating key adaptation information |
| Historical conversation retention rounds | Last 10 historical records | Retains recent review verification results, reduces repeated verification of confirmed adaptation items |
| Prompt variables | Pass the current project’s adaptation list ID, test environment identifier | Automatically associates project-specific data, eliminates need to repeatedly enter project information |
| Single request token limit | 12000 tokens | Covers complete code snippets and review document content, avoids request truncation |
Three Common Configuration Errors
- Symptom: Multi-turn dialogue does not distinguish prompt roles, leading to chaotic review logic. Cause: The fixed workflow for trusted innovation adaptation reviews is not used to split prompt roles. Validation rules and content to be reviewed are mixed together.
- Symptom: Conversation interface calls do not carry file association parameters. This makes it impossible to read code to be reviewed. Cause: The file transfer logic for front-end uploads and interface calls is confused. Correct file identifiers are not passed as required by documentation.
- Symptom: Configured project variables do not take effect. This prevents dialogue from associating adaptation lists. Cause: Variable values are not passed in the
variablesrequest parameter. Application global variables are incorrectly used instead of dialogue-level variables for passing.
How to Confirm Successful Configuration
- Check that request parameters pass the project adaptation list ID and test environment identifier corresponding to the prompt variables. Ensure dialogue can automatically associate project-specific data.
- View multi-turn dialogue context records. Confirm historical review results are correctly retained, and no repeated verification of confirmed adaptation items occurs.
- Test single request token consumption. Confirm it does not exceed the configured single request token limit, and no content truncation occurs.
- Simulate a code review request. Check that prompts guide the model to prioritize extracting compatibility verification results and migration risk information.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.