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refactor: modularize openai llm config logic into new getOpenAILLMConfig function
This commit is contained in:
Dustin Healy
Danny Avila
parent
fff1f1cf27
commit
efdad28b70
1 changed files with 134 additions and 109 deletions
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@ -80,6 +80,134 @@ function hasReasoningParams({
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);
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}
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function getOpenAILLMConfig({
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streaming,
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modelOptions,
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addParams,
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dropParams,
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}: {
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streaming: boolean;
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modelOptions: Partial<t.OpenAIParameters>;
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addParams?: Record<string, unknown>;
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dropParams?: string[];
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}): {
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llmConfig: Partial<t.ClientOptions> & Partial<t.OpenAIParameters> & Partial<AzureOpenAIInput>;
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tools: BindToolsInput[];
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} {
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const { reasoning_effort, reasoning_summary, verbosity, web_search, ...restModelOptions } =
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modelOptions;
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const llmConfig = Object.assign(
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{
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streaming,
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model: restModelOptions.model ?? '',
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},
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restModelOptions,
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) as Partial<t.ClientOptions> & Partial<t.OpenAIParameters> & Partial<AzureOpenAIInput>;
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const modelKwargs: Record<string, unknown> = {};
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let hasModelKwargs = false;
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if (verbosity != null && verbosity !== '') {
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modelKwargs.verbosity = verbosity;
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hasModelKwargs = true;
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}
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if (addParams && typeof addParams === 'object') {
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for (const [key, value] of Object.entries(addParams)) {
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if (knownOpenAIParams.has(key)) {
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(llmConfig as Record<string, unknown>)[key] = value;
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} else {
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hasModelKwargs = true;
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modelKwargs[key] = value;
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}
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}
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}
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if (
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hasReasoningParams({ reasoning_effort, reasoning_summary }) &&
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llmConfig.useResponsesApi === true
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) {
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llmConfig.reasoning = removeNullishValues(
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{
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effort: reasoning_effort,
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summary: reasoning_summary,
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},
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true,
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) as OpenAI.Reasoning;
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} else if (hasReasoningParams({ reasoning_effort })) {
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llmConfig.reasoning_effort = reasoning_effort;
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}
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if (llmConfig.max_tokens != null) {
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llmConfig.maxTokens = llmConfig.max_tokens;
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delete llmConfig.max_tokens;
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}
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const tools: BindToolsInput[] = [];
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if (web_search) {
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llmConfig.useResponsesApi = true;
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tools.push({ type: 'web_search_preview' });
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}
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/**
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* Note: OpenAI Web Search models do not support any known parameters besides `max_tokens`
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*/
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if (modelOptions.model && /gpt-4o.*search/.test(modelOptions.model as string)) {
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const searchExcludeParams = [
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'frequency_penalty',
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'presence_penalty',
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'reasoning',
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'reasoning_effort',
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'temperature',
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'top_p',
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'top_k',
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'stop',
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'logit_bias',
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'seed',
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'response_format',
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'n',
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'logprobs',
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'user',
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];
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const updatedDropParams = dropParams || [];
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const combinedDropParams = [...new Set([...updatedDropParams, ...searchExcludeParams])];
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combinedDropParams.forEach((param) => {
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if (param in llmConfig) {
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delete llmConfig[param as keyof t.ClientOptions];
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}
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});
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} else if (dropParams && Array.isArray(dropParams)) {
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dropParams.forEach((param) => {
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if (param in llmConfig) {
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delete llmConfig[param as keyof t.ClientOptions];
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}
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});
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}
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if (modelKwargs.verbosity && llmConfig.useResponsesApi === true) {
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modelKwargs.text = { verbosity: modelKwargs.verbosity };
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delete modelKwargs.verbosity;
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}
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if (llmConfig.model && /\bgpt-[5-9]\b/i.test(llmConfig.model) && llmConfig.maxTokens != null) {
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const paramName =
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llmConfig.useResponsesApi === true ? 'max_output_tokens' : 'max_completion_tokens';
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modelKwargs[paramName] = llmConfig.maxTokens;
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delete llmConfig.maxTokens;
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hasModelKwargs = true;
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}
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if (hasModelKwargs) {
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llmConfig.modelKwargs = modelKwargs;
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}
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return { llmConfig, tools };
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}
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/**
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* Generates configuration options for creating a language model (LLM) instance.
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* @param apiKey - The API key for authentication.
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@ -104,35 +232,13 @@ export function getOpenAIConfig(
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addParams,
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dropParams,
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} = options;
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const { reasoning_effort, reasoning_summary, verbosity, ...modelOptions } = _modelOptions;
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const llmConfig: Partial<t.ClientOptions> &
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Partial<t.OpenAIParameters> &
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Partial<AzureOpenAIInput> = Object.assign(
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{
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streaming,
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model: modelOptions.model ?? '',
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},
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modelOptions,
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);
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const modelKwargs: Record<string, unknown> = {};
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let hasModelKwargs = false;
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if (verbosity != null && verbosity !== '') {
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modelKwargs.verbosity = verbosity;
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hasModelKwargs = true;
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}
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if (addParams && typeof addParams === 'object') {
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for (const [key, value] of Object.entries(addParams)) {
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if (knownOpenAIParams.has(key)) {
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(llmConfig as Record<string, unknown>)[key] = value;
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} else {
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hasModelKwargs = true;
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modelKwargs[key] = value;
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}
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}
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}
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const { llmConfig, tools } = getOpenAILLMConfig({
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streaming,
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modelOptions: _modelOptions,
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addParams,
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dropParams,
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});
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let useOpenRouter = false;
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const configOptions: t.OpenAIConfiguration = {};
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@ -234,87 +340,6 @@ export function getOpenAIConfig(
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configOptions.organization = process.env.OPENAI_ORGANIZATION;
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}
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if (
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hasReasoningParams({ reasoning_effort, reasoning_summary }) &&
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(llmConfig.useResponsesApi === true || useOpenRouter)
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) {
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llmConfig.reasoning = removeNullishValues(
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{
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effort: reasoning_effort,
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summary: reasoning_summary,
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},
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true,
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) as OpenAI.Reasoning;
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} else if (hasReasoningParams({ reasoning_effort })) {
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llmConfig.reasoning_effort = reasoning_effort;
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}
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if (llmConfig.max_tokens != null) {
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llmConfig.maxTokens = llmConfig.max_tokens;
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delete llmConfig.max_tokens;
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}
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const tools: BindToolsInput[] = [];
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if (modelOptions.web_search) {
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llmConfig.useResponsesApi = true;
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tools.push({ type: 'web_search_preview' });
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}
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/**
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* Note: OpenAI Web Search models do not support any known parameters besides `max_tokens`
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*/
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if (modelOptions.model && /gpt-4o.*search/.test(modelOptions.model)) {
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const searchExcludeParams = [
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'frequency_penalty',
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'presence_penalty',
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'reasoning',
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'reasoning_effort',
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'temperature',
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'top_p',
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'top_k',
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'stop',
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'logit_bias',
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'seed',
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'response_format',
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'n',
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'logprobs',
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'user',
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];
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const updatedDropParams = dropParams || [];
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const combinedDropParams = [...new Set([...updatedDropParams, ...searchExcludeParams])];
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combinedDropParams.forEach((param) => {
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if (param in llmConfig) {
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delete llmConfig[param as keyof t.ClientOptions];
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}
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});
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} else if (dropParams && Array.isArray(dropParams)) {
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dropParams.forEach((param) => {
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if (param in llmConfig) {
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delete llmConfig[param as keyof t.ClientOptions];
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}
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});
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}
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if (modelKwargs.verbosity && llmConfig.useResponsesApi === true) {
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modelKwargs.text = { verbosity: modelKwargs.verbosity };
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delete modelKwargs.verbosity;
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}
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if (llmConfig.model && /\bgpt-[5-9]\b/i.test(llmConfig.model) && llmConfig.maxTokens != null) {
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const paramName =
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llmConfig.useResponsesApi === true ? 'max_output_tokens' : 'max_completion_tokens';
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modelKwargs[paramName] = llmConfig.maxTokens;
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delete llmConfig.maxTokens;
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hasModelKwargs = true;
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}
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if (hasModelKwargs) {
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llmConfig.modelKwargs = modelKwargs;
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}
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if (directEndpoint === true && configOptions?.baseURL != null) {
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configOptions.fetch = createFetch({
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directEndpoint: directEndpoint,
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