3.5 KiB
description, argument-hint
| description | argument-hint |
|---|---|
| Verify model parameterSpecs match API-validated sweep data | openai | anthropic | gemini | xai (or empty for all) |
Verify LLM Parameters
Compare model parameterSpecs in definition files against API-validated sweep data.
If $ARGUMENTS provided, verify only that dialect, which includes reading the pair of sweep results and model defintions. Otherwise verify all four, and read the pairs in sequence.
Files
Sweep results (source of truth for select parameters):
tools/develop/llm-parameter-sweep/llm-{dialect}-parameters-sweep.jsonBy the time you see these files, the repo owner has already updated them viatools/develop/llm-parameter-sweep/sweep.sh(very long running, 15 min per vendor).
Model definitions (source of truth for model defintions for the user and application, including constants, interfaces, supported parameters and sometimes allowed parameter values):
- OpenAI:
src/modules/llms/server/openai/models/openai.models.ts - Anthropic:
src/modules/llms/server/anthropic/anthropic.models.ts - Gemini:
src/modules/llms/server/gemini/gemini.models.ts - xAI:
src/modules/llms/server/openai/models/xai.models.ts
Task
The sweep data is the source of truth for allowed model parameter values or value ranges, and for the fn function-calling capability probe.
For each model in the sweep, verify the model definition exposes exactly those capabilities - no more, no less. This includes:
- The parameter is present in parameterSpecs
- The paramId variant covers exactly the values from the sweep, if applicable
LLM_IF_OAI_Fnininterfacesmatches"roundtrip"in the sweep'sfnarray (see below)- etc.
Report models where the definition doesn't match the sweep.
Parameter Mapping
Example parameter mapping. Note that new parameters may have been added to both the definition, and the sweep. The objective of the sweep is to hint at model definition values, but the model definitions are what matters for Big-AGI, and need to be carefully updated, otherwise thousands of clients may break.
| Dialect | Sweep Key | Model paramId |
|---|---|---|
| OpenAI | oai-reasoning-effort |
llmVndOaiEffort |
| OpenAI | oai-verbosity |
llmVndOaiVerbosity |
| OpenAI | oai-image-generation |
llmVndOaiImageGeneration |
| OpenAI | oai-web-search |
llmVndOaiWebSearchContext |
| Anthropic | ant-effort |
llmVndAntEffort |
| Anthropic | ant-thinking-budget |
llmVndAntThinkingBudget |
| Gemini | gemini-thinking-level |
llmVndGemEffort |
| Gemini | gemini-thinking-budget |
llmVndGeminiThinkingBudget |
| xAI | xai-web-search |
llmVndXaiWebSearch |
Function-Calling Capability (fn)
The sweep fn array is a capability probe (not a paramId). "roundtrip" is the authoritative signal - full tool-call -> response -> coherent follow-up. LLM_IF_OAI_Fn in the model's interfaces must track "roundtrip": present iff present.
Flag:
"roundtrip"in sweep butLLM_IF_OAI_Fnmissing (or vice versa)fncontains"auto"/"required"without"roundtrip"- partial capability, call it out
Output
Report first for every model the expected values from the sweep, then the actual values from the definition, then the mismatches.
Finally make one table for each dialect listing all models with mismatches and the specific issues.