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📐 refactor: Exclude Params from OAI Reasoning Models (#10745)
* 📐 refactor: Exclude Params from OAI Reasoning Models
- Introduced a new test suite for `getOpenAILLMConfig` covering various model configurations, including basic settings, reasoning models, and web search functionality.
- Validated parameter handling for different models, ensuring correct exclusions and conversions, particularly for temperature and max_tokens.
- Enhanced tests for default and additional parameters, drop parameters, and verbosity handling, ensuring robust coverage of the configuration logic.
* ci: Update OpenAI model version in configuration tests
- Changed model references from 'gpt-5' to 'gpt-4' across multiple test cases in the `getOpenAIConfig` function.
- Adjusted related parameter handling to ensure compatibility with the updated model version, including maxTokens and temperature settings.
- Enhanced test coverage for model options and their expected configurations.
This commit is contained in:
Danny Avila
GitHub
parent
774ebd1eaa
commit
6c0aad423f
3 changed files with 643 additions and 20 deletions
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@ -26,7 +26,7 @@ describe('getOpenAIConfig', () => {
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it('should apply model options', () => {
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const modelOptions = {
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.7,
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max_tokens: 1000,
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};
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@ -34,14 +34,11 @@ describe('getOpenAIConfig', () => {
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const result = getOpenAIConfig(mockApiKey, { modelOptions });
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expect(result.llmConfig).toMatchObject({
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.7,
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modelKwargs: {
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max_completion_tokens: 1000,
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},
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maxTokens: 1000,
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});
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expect((result.llmConfig as Record<string, unknown>).max_tokens).toBeUndefined();
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expect((result.llmConfig as Record<string, unknown>).maxTokens).toBeUndefined();
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});
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it('should separate known and unknown params from addParams', () => {
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@ -286,7 +283,7 @@ describe('getOpenAIConfig', () => {
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it('should ignore non-boolean web_search values in addParams', () => {
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const modelOptions = {
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model: 'gpt-5',
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model: 'gpt-4',
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web_search: true,
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};
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@ -399,7 +396,7 @@ describe('getOpenAIConfig', () => {
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it('should handle verbosity parameter in modelKwargs', () => {
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const modelOptions = {
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.7,
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verbosity: Verbosity.high,
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};
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@ -407,7 +404,7 @@ describe('getOpenAIConfig', () => {
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const result = getOpenAIConfig(mockApiKey, { modelOptions });
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expect(result.llmConfig).toMatchObject({
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.7,
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});
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expect(result.llmConfig.modelKwargs).toEqual({
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@ -417,7 +414,7 @@ describe('getOpenAIConfig', () => {
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it('should allow addParams to override verbosity in modelKwargs', () => {
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const modelOptions = {
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model: 'gpt-5',
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model: 'gpt-4',
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verbosity: Verbosity.low,
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};
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@ -451,7 +448,7 @@ describe('getOpenAIConfig', () => {
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it('should nest verbosity under text when useResponsesApi is enabled', () => {
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const modelOptions = {
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.7,
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verbosity: Verbosity.low,
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useResponsesApi: true,
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@ -460,7 +457,7 @@ describe('getOpenAIConfig', () => {
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const result = getOpenAIConfig(mockApiKey, { modelOptions });
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expect(result.llmConfig).toMatchObject({
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.7,
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useResponsesApi: true,
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});
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@ -496,7 +493,6 @@ describe('getOpenAIConfig', () => {
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it('should move maxTokens to modelKwargs.max_completion_tokens for GPT-5+ models', () => {
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const modelOptions = {
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model: 'gpt-5',
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temperature: 0.7,
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max_tokens: 2048,
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};
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@ -504,7 +500,6 @@ describe('getOpenAIConfig', () => {
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expect(result.llmConfig).toMatchObject({
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model: 'gpt-5',
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temperature: 0.7,
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});
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expect(result.llmConfig.maxTokens).toBeUndefined();
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expect(result.llmConfig.modelKwargs).toEqual({
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@ -1684,7 +1679,7 @@ describe('getOpenAIConfig', () => {
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it('should not override existing modelOptions with defaultParams', () => {
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const result = getOpenAIConfig(mockApiKey, {
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modelOptions: {
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.9,
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},
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customParams: {
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@ -1697,7 +1692,7 @@ describe('getOpenAIConfig', () => {
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});
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expect(result.llmConfig.temperature).toBe(0.9);
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expect(result.llmConfig.modelKwargs?.max_completion_tokens).toBe(1000);
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expect(result.llmConfig.maxTokens).toBe(1000);
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});
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it('should allow addParams to override defaultParams', () => {
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@ -1845,7 +1840,7 @@ describe('getOpenAIConfig', () => {
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it('should preserve order: defaultParams < addParams < modelOptions', () => {
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const result = getOpenAIConfig(mockApiKey, {
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modelOptions: {
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model: 'gpt-5',
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model: 'gpt-4',
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temperature: 0.9,
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},
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customParams: {
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@ -1863,7 +1858,7 @@ describe('getOpenAIConfig', () => {
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expect(result.llmConfig.temperature).toBe(0.9);
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expect(result.llmConfig.topP).toBe(0.8);
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expect(result.llmConfig.modelKwargs?.max_completion_tokens).toBe(500);
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expect(result.llmConfig.maxTokens).toBe(500);
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});
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});
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});
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602
packages/api/src/endpoints/openai/llm.spec.ts
Normal file
602
packages/api/src/endpoints/openai/llm.spec.ts
Normal file
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@ -0,0 +1,602 @@
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import {
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Verbosity,
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EModelEndpoint,
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ReasoningEffort,
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ReasoningSummary,
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} from 'librechat-data-provider';
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import { getOpenAILLMConfig, extractDefaultParams, applyDefaultParams } from './llm';
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import type * as t from '~/types';
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describe('getOpenAILLMConfig', () => {
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describe('Basic Configuration', () => {
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it('should create a basic configuration with required fields', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4',
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},
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});
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expect(result.llmConfig).toHaveProperty('apiKey', 'test-api-key');
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expect(result.llmConfig).toHaveProperty('model', 'gpt-4');
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expect(result.llmConfig).toHaveProperty('streaming', true);
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expect(result.tools).toEqual([]);
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});
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it('should handle model options including temperature and penalties', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4',
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temperature: 0.7,
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frequency_penalty: 0.5,
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presence_penalty: 0.3,
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},
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});
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expect(result.llmConfig).toHaveProperty('temperature', 0.7);
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expect(result.llmConfig).toHaveProperty('frequencyPenalty', 0.5);
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expect(result.llmConfig).toHaveProperty('presencePenalty', 0.3);
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});
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it('should handle max_tokens conversion to maxTokens', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4',
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max_tokens: 4096,
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},
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});
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expect(result.llmConfig).toHaveProperty('maxTokens', 4096);
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expect(result.llmConfig).not.toHaveProperty('max_tokens');
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});
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});
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describe('OpenAI Reasoning Models (o1/o3/gpt-5)', () => {
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const reasoningModels = [
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'o1',
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'o1-mini',
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'o1-preview',
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'o1-pro',
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'o3',
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'o3-mini',
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'gpt-5',
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'gpt-5-pro',
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'gpt-5-turbo',
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];
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const excludedParams = [
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'frequencyPenalty',
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'presencePenalty',
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'temperature',
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'topP',
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'logitBias',
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'n',
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'logprobs',
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];
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it.each(reasoningModels)(
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'should exclude unsupported parameters for reasoning model: %s',
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(model) => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model,
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temperature: 0.7,
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frequency_penalty: 0.5,
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presence_penalty: 0.3,
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topP: 0.9,
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logitBias: { '50256': -100 },
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n: 2,
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logprobs: true,
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} as Partial<t.OpenAIParameters>,
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});
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excludedParams.forEach((param) => {
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expect(result.llmConfig).not.toHaveProperty(param);
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});
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expect(result.llmConfig).toHaveProperty('model', model);
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expect(result.llmConfig).toHaveProperty('streaming', true);
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},
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);
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it('should preserve maxTokens for reasoning models', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'o1',
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max_tokens: 4096,
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temperature: 0.7,
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},
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});
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expect(result.llmConfig).toHaveProperty('maxTokens', 4096);
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expect(result.llmConfig).not.toHaveProperty('temperature');
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});
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it('should preserve other valid parameters for reasoning models', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'o1',
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max_tokens: 8192,
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stop: ['END'],
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},
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});
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expect(result.llmConfig).toHaveProperty('maxTokens', 8192);
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expect(result.llmConfig).toHaveProperty('stop', ['END']);
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});
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it('should handle GPT-5 max_tokens conversion to max_completion_tokens', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-5',
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max_tokens: 8192,
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stop: ['END'],
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},
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});
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expect(result.llmConfig.modelKwargs).toHaveProperty('max_completion_tokens', 8192);
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expect(result.llmConfig).not.toHaveProperty('maxTokens');
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expect(result.llmConfig).toHaveProperty('stop', ['END']);
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});
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it('should combine user dropParams with reasoning exclusion params', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'o3-mini',
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temperature: 0.7,
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stop: ['END'],
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},
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dropParams: ['stop'],
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});
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expect(result.llmConfig).not.toHaveProperty('temperature');
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expect(result.llmConfig).not.toHaveProperty('stop');
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});
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it('should NOT exclude parameters for non-reasoning models', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4-turbo',
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temperature: 0.7,
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frequency_penalty: 0.5,
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presence_penalty: 0.3,
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topP: 0.9,
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},
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});
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expect(result.llmConfig).toHaveProperty('temperature', 0.7);
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expect(result.llmConfig).toHaveProperty('frequencyPenalty', 0.5);
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expect(result.llmConfig).toHaveProperty('presencePenalty', 0.3);
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expect(result.llmConfig).toHaveProperty('topP', 0.9);
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});
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it('should NOT exclude parameters for gpt-5.x versioned models (they support sampling params)', () => {
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const versionedModels = ['gpt-5.1', 'gpt-5.1-turbo', 'gpt-5.2', 'gpt-5.5-preview'];
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versionedModels.forEach((model) => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model,
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temperature: 0.7,
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frequency_penalty: 0.5,
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presence_penalty: 0.3,
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topP: 0.9,
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},
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});
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expect(result.llmConfig).toHaveProperty('temperature', 0.7);
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expect(result.llmConfig).toHaveProperty('frequencyPenalty', 0.5);
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expect(result.llmConfig).toHaveProperty('presencePenalty', 0.3);
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expect(result.llmConfig).toHaveProperty('topP', 0.9);
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});
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});
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it('should NOT exclude parameters for gpt-5-chat (it supports sampling params)', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-5-chat',
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temperature: 0.7,
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frequency_penalty: 0.5,
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presence_penalty: 0.3,
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topP: 0.9,
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},
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});
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expect(result.llmConfig).toHaveProperty('temperature', 0.7);
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expect(result.llmConfig).toHaveProperty('frequencyPenalty', 0.5);
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expect(result.llmConfig).toHaveProperty('presencePenalty', 0.3);
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expect(result.llmConfig).toHaveProperty('topP', 0.9);
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});
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it('should handle reasoning models with reasoning_effort parameter', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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endpoint: EModelEndpoint.openAI,
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modelOptions: {
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model: 'o1',
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reasoning_effort: ReasoningEffort.high,
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temperature: 0.7,
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},
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});
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expect(result.llmConfig).toHaveProperty('reasoning_effort', ReasoningEffort.high);
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expect(result.llmConfig).not.toHaveProperty('temperature');
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});
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});
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describe('OpenAI Web Search Models', () => {
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it('should exclude parameters for gpt-4o search models', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4o-search-preview',
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temperature: 0.7,
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top_p: 0.9,
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seed: 42,
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} as Partial<t.OpenAIParameters>,
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});
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expect(result.llmConfig).not.toHaveProperty('temperature');
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expect(result.llmConfig).not.toHaveProperty('top_p');
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expect(result.llmConfig).not.toHaveProperty('seed');
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});
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it('should preserve max_tokens for search models', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4o-search',
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max_tokens: 4096,
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temperature: 0.7,
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},
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});
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expect(result.llmConfig).toHaveProperty('maxTokens', 4096);
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expect(result.llmConfig).not.toHaveProperty('temperature');
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});
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});
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describe('Web Search Functionality', () => {
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it('should enable web search with Responses API', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4',
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web_search: true,
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},
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});
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expect(result.llmConfig).toHaveProperty('useResponsesApi', true);
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expect(result.tools).toContainEqual({ type: 'web_search' });
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});
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it('should handle web search with OpenRouter', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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useOpenRouter: true,
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modelOptions: {
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model: 'gpt-4',
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web_search: true,
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},
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});
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expect(result.llmConfig.modelKwargs).toHaveProperty('plugins', [{ id: 'web' }]);
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expect(result.llmConfig).toHaveProperty('include_reasoning', true);
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});
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it('should disable web search via dropParams', () => {
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const result = getOpenAILLMConfig({
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apiKey: 'test-api-key',
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streaming: true,
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modelOptions: {
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model: 'gpt-4',
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web_search: true,
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},
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dropParams: ['web_search'],
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});
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expect(result.tools).not.toContainEqual({ type: 'web_search' });
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});
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});
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describe('GPT-5 max_tokens Handling', () => {
|
||||
it('should convert maxTokens to max_completion_tokens for GPT-5 models', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-5',
|
||||
max_tokens: 8192,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig.modelKwargs).toHaveProperty('max_completion_tokens', 8192);
|
||||
expect(result.llmConfig).not.toHaveProperty('maxTokens');
|
||||
});
|
||||
|
||||
it('should convert maxTokens to max_output_tokens for GPT-5 with Responses API', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-5',
|
||||
max_tokens: 8192,
|
||||
},
|
||||
addParams: {
|
||||
useResponsesApi: true,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig.modelKwargs).toHaveProperty('max_output_tokens', 8192);
|
||||
expect(result.llmConfig).not.toHaveProperty('maxTokens');
|
||||
});
|
||||
});
|
||||
|
||||
describe('Reasoning Parameters', () => {
|
||||
it('should handle reasoning_effort for OpenAI endpoint', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
endpoint: EModelEndpoint.openAI,
|
||||
modelOptions: {
|
||||
model: 'o1',
|
||||
reasoning_effort: ReasoningEffort.high,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig).toHaveProperty('reasoning_effort', ReasoningEffort.high);
|
||||
});
|
||||
|
||||
it('should use reasoning object for non-OpenAI endpoints', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
endpoint: 'custom',
|
||||
modelOptions: {
|
||||
model: 'o1',
|
||||
reasoning_effort: ReasoningEffort.high,
|
||||
reasoning_summary: ReasoningSummary.concise,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig).toHaveProperty('reasoning');
|
||||
expect(result.llmConfig.reasoning).toEqual({
|
||||
effort: ReasoningEffort.high,
|
||||
summary: ReasoningSummary.concise,
|
||||
});
|
||||
});
|
||||
|
||||
it('should use reasoning object when useResponsesApi is true', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
endpoint: EModelEndpoint.openAI,
|
||||
modelOptions: {
|
||||
model: 'o1',
|
||||
reasoning_effort: ReasoningEffort.medium,
|
||||
reasoning_summary: ReasoningSummary.detailed,
|
||||
},
|
||||
addParams: {
|
||||
useResponsesApi: true,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig).toHaveProperty('reasoning');
|
||||
expect(result.llmConfig.reasoning).toEqual({
|
||||
effort: ReasoningEffort.medium,
|
||||
summary: ReasoningSummary.detailed,
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
describe('Default and Add Parameters', () => {
|
||||
it('should apply default parameters when fields are undefined', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
},
|
||||
defaultParams: {
|
||||
temperature: 0.5,
|
||||
topP: 0.9,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig).toHaveProperty('temperature', 0.5);
|
||||
expect(result.llmConfig).toHaveProperty('topP', 0.9);
|
||||
});
|
||||
|
||||
it('should NOT override existing values with default parameters', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
temperature: 0.8,
|
||||
},
|
||||
defaultParams: {
|
||||
temperature: 0.5,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig).toHaveProperty('temperature', 0.8);
|
||||
});
|
||||
|
||||
it('should apply addParams and override defaults', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
},
|
||||
defaultParams: {
|
||||
temperature: 0.5,
|
||||
},
|
||||
addParams: {
|
||||
temperature: 0.9,
|
||||
seed: 42,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig).toHaveProperty('temperature', 0.9);
|
||||
expect(result.llmConfig).toHaveProperty('seed', 42);
|
||||
});
|
||||
|
||||
it('should handle unknown params via modelKwargs', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
},
|
||||
addParams: {
|
||||
custom_param: 'custom_value',
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig.modelKwargs).toHaveProperty('custom_param', 'custom_value');
|
||||
});
|
||||
});
|
||||
|
||||
describe('Drop Parameters', () => {
|
||||
it('should drop specified parameters', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
temperature: 0.7,
|
||||
topP: 0.9,
|
||||
},
|
||||
dropParams: ['temperature'],
|
||||
});
|
||||
|
||||
expect(result.llmConfig).not.toHaveProperty('temperature');
|
||||
expect(result.llmConfig).toHaveProperty('topP', 0.9);
|
||||
});
|
||||
});
|
||||
|
||||
describe('OpenRouter Configuration', () => {
|
||||
it('should include include_reasoning for OpenRouter', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
useOpenRouter: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig).toHaveProperty('include_reasoning', true);
|
||||
});
|
||||
});
|
||||
|
||||
describe('Verbosity Handling', () => {
|
||||
it('should add verbosity to modelKwargs', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
verbosity: Verbosity.high,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig.modelKwargs).toHaveProperty('verbosity', Verbosity.high);
|
||||
});
|
||||
|
||||
it('should convert verbosity to text object with Responses API', () => {
|
||||
const result = getOpenAILLMConfig({
|
||||
apiKey: 'test-api-key',
|
||||
streaming: true,
|
||||
modelOptions: {
|
||||
model: 'gpt-4',
|
||||
verbosity: Verbosity.low,
|
||||
},
|
||||
addParams: {
|
||||
useResponsesApi: true,
|
||||
},
|
||||
});
|
||||
|
||||
expect(result.llmConfig.modelKwargs).toHaveProperty('text', { verbosity: Verbosity.low });
|
||||
expect(result.llmConfig.modelKwargs).not.toHaveProperty('verbosity');
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
describe('extractDefaultParams', () => {
|
||||
it('should extract default values from param definitions', () => {
|
||||
const paramDefinitions = [
|
||||
{ key: 'temperature', default: 0.7 },
|
||||
{ key: 'maxTokens', default: 4096 },
|
||||
{ key: 'noDefault' },
|
||||
];
|
||||
|
||||
const result = extractDefaultParams(paramDefinitions);
|
||||
|
||||
expect(result).toEqual({
|
||||
temperature: 0.7,
|
||||
maxTokens: 4096,
|
||||
});
|
||||
});
|
||||
|
||||
it('should return undefined for undefined or non-array input', () => {
|
||||
expect(extractDefaultParams(undefined)).toBeUndefined();
|
||||
expect(extractDefaultParams(null as unknown as undefined)).toBeUndefined();
|
||||
});
|
||||
|
||||
it('should handle empty array', () => {
|
||||
const result = extractDefaultParams([]);
|
||||
expect(result).toEqual({});
|
||||
});
|
||||
});
|
||||
|
||||
describe('applyDefaultParams', () => {
|
||||
it('should apply defaults only when field is undefined', () => {
|
||||
const target: Record<string, unknown> = {
|
||||
temperature: 0.8,
|
||||
maxTokens: undefined,
|
||||
};
|
||||
|
||||
const defaults = {
|
||||
temperature: 0.5,
|
||||
maxTokens: 4096,
|
||||
topP: 0.9,
|
||||
};
|
||||
|
||||
applyDefaultParams(target, defaults);
|
||||
|
||||
expect(target).toEqual({
|
||||
temperature: 0.8,
|
||||
maxTokens: 4096,
|
||||
topP: 0.9,
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
@ -259,9 +259,35 @@ export function getOpenAILLMConfig({
|
|||
}
|
||||
|
||||
/**
|
||||
* Note: OpenAI Web Search models do not support any known parameters besides `max_tokens`
|
||||
* Note: OpenAI reasoning models (o1/o3/gpt-5) do not support temperature and other sampling parameters
|
||||
* Exception: gpt-5-chat and versioned models like gpt-5.1 DO support these parameters
|
||||
*/
|
||||
if (modelOptions.model && /gpt-4o.*search/.test(modelOptions.model as string)) {
|
||||
if (
|
||||
modelOptions.model &&
|
||||
/\b(o[13]|gpt-5)(?!\.|-chat)(?:-|$)/.test(modelOptions.model as string)
|
||||
) {
|
||||
const reasoningExcludeParams = [
|
||||
'frequencyPenalty',
|
||||
'presencePenalty',
|
||||
'temperature',
|
||||
'topP',
|
||||
'logitBias',
|
||||
'n',
|
||||
'logprobs',
|
||||
];
|
||||
|
||||
const updatedDropParams = dropParams || [];
|
||||
const combinedDropParams = [...new Set([...updatedDropParams, ...reasoningExcludeParams])];
|
||||
|
||||
combinedDropParams.forEach((param) => {
|
||||
if (param in llmConfig) {
|
||||
delete llmConfig[param as keyof t.OAIClientOptions];
|
||||
}
|
||||
});
|
||||
} else if (modelOptions.model && /gpt-4o.*search/.test(modelOptions.model as string)) {
|
||||
/**
|
||||
* Note: OpenAI Web Search models do not support any known parameters besides `max_tokens`
|
||||
*/
|
||||
const searchExcludeParams = [
|
||||
'frequency_penalty',
|
||||
'presence_penalty',
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue