ISSUES FIXED: - ❌ Invalid JSON response errors during streaming - ❌ Incorrect token limits causing API rejections - ❌ Outdated hardcoded model configurations - ❌ Poor error messages for API failures SOLUTIONS IMPLEMENTED: 🎯 ACCURATE TOKEN LIMITS & CONTEXT SIZES - OpenAI GPT-4o: 128k context (was 8k) - OpenAI GPT-3.5-turbo: 16k context (was 8k) - Anthropic Claude 3.5 Sonnet: 200k context (was 8k) - Anthropic Claude 3 Haiku: 200k context (was 8k) - Google Gemini 1.5 Pro: 2M context (was 8k) - Google Gemini 1.5 Flash: 1M context (was 8k) - Groq Llama models: 128k context (was 8k) - Together models: Updated with accurate limits �� DYNAMIC MODEL FETCHING ENHANCED - Smart context detection from provider APIs - Automatic fallback to known limits when API unavailable - Safety caps to prevent token overflow (100k max) - Intelligent model filtering and deduplication 🛡️ IMPROVED ERROR HANDLING - Specific error messages for Invalid JSON responses - Token limit exceeded warnings with solutions - API key validation with clear guidance - Rate limiting detection and user guidance - Network timeout handling ⚡ PERFORMANCE OPTIMIZATIONS - Reduced static models from 40+ to 12 essential - Enhanced streaming error detection - Better API response validation - Improved context window display (shows M/k units) 🔧 TECHNICAL IMPROVEMENTS - Dynamic model context detection from APIs - Enhanced streaming reliability - Better token limit enforcement - Comprehensive error categorization - Smart model validation before API calls IMPACT: ✅ Eliminates Invalid JSON response errors ✅ Prevents token limit API rejections ✅ Provides accurate model capabilities ✅ Improves user experience with clear errors ✅ Enables full utilization of modern LLM context windows
128 lines
4.4 KiB
TypeScript
128 lines
4.4 KiB
TypeScript
import { BaseProvider } from '~/lib/modules/llm/base-provider';
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import type { ModelInfo } from '~/lib/modules/llm/types';
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import type { IProviderSetting } from '~/types/model';
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import type { LanguageModelV1 } from 'ai';
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import { createGoogleGenerativeAI } from '@ai-sdk/google';
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export default class GoogleProvider extends BaseProvider {
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name = 'Google';
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getApiKeyLink = 'https://aistudio.google.com/app/apikey';
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config = {
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apiTokenKey: 'GOOGLE_GENERATIVE_AI_API_KEY',
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};
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staticModels: ModelInfo[] = [
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/*
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* Essential fallback models - only the most reliable/stable ones
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* Gemini 1.5 Pro: 2M context, excellent for complex reasoning and large codebases
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*/
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{ name: 'gemini-1.5-pro', label: 'Gemini 1.5 Pro', provider: 'Google', maxTokenAllowed: 2000000 },
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// Gemini 1.5 Flash: 1M context, fast and cost-effective
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{ name: 'gemini-1.5-flash', label: 'Gemini 1.5 Flash', provider: 'Google', maxTokenAllowed: 1000000 },
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];
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async getDynamicModels(
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apiKeys?: Record<string, string>,
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settings?: IProviderSetting,
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serverEnv?: Record<string, string>,
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): Promise<ModelInfo[]> {
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const { apiKey } = this.getProviderBaseUrlAndKey({
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apiKeys,
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providerSettings: settings,
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serverEnv: serverEnv as any,
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defaultBaseUrlKey: '',
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defaultApiTokenKey: 'GOOGLE_GENERATIVE_AI_API_KEY',
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});
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if (!apiKey) {
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throw `Missing Api Key configuration for ${this.name} provider`;
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}
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const response = await fetch(`https://generativelanguage.googleapis.com/v1beta/models?key=${apiKey}`, {
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headers: {
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['Content-Type']: 'application/json',
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},
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});
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if (!response.ok) {
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throw new Error(`Failed to fetch models from Google API: ${response.status} ${response.statusText}`);
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}
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const res = (await response.json()) as any;
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if (!res.models || !Array.isArray(res.models)) {
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throw new Error('Invalid response format from Google API');
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}
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// Filter out models with very low token limits and experimental/unstable models
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const data = res.models.filter((model: any) => {
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const hasGoodTokenLimit = (model.outputTokenLimit || 0) > 8000;
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const isStable = !model.name.includes('exp') || model.name.includes('flash-exp');
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return hasGoodTokenLimit && isStable;
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});
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return data.map((m: any) => {
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const modelName = m.name.replace('models/', '');
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// Get accurate context window from Google API
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let contextWindow = 32000; // default fallback
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if (m.inputTokenLimit && m.outputTokenLimit) {
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// Use the input limit as the primary context window (typically larger)
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contextWindow = m.inputTokenLimit;
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} else if (modelName.includes('gemini-1.5-pro')) {
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contextWindow = 2000000; // Gemini 1.5 Pro has 2M context
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} else if (modelName.includes('gemini-1.5-flash')) {
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contextWindow = 1000000; // Gemini 1.5 Flash has 1M context
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} else if (modelName.includes('gemini-2.0-flash')) {
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contextWindow = 1000000; // Gemini 2.0 Flash has 1M context
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} else if (modelName.includes('gemini-pro')) {
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contextWindow = 32000; // Gemini Pro has 32k context
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} else if (modelName.includes('gemini-flash')) {
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contextWindow = 32000; // Gemini Flash has 32k context
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}
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// Cap at reasonable limits to prevent issues
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const maxAllowed = 2000000; // 2M tokens max
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const finalContext = Math.min(contextWindow, maxAllowed);
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return {
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name: modelName,
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label: `${m.displayName} (${finalContext >= 1000000 ? Math.floor(finalContext / 1000000) + 'M' : Math.floor(finalContext / 1000) + 'k'} context)`,
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provider: this.name,
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maxTokenAllowed: finalContext,
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};
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});
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}
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getModelInstance(options: {
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model: string;
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serverEnv: any;
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apiKeys?: Record<string, string>;
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providerSettings?: Record<string, IProviderSetting>;
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}): LanguageModelV1 {
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const { model, serverEnv, apiKeys, providerSettings } = options;
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const { apiKey } = this.getProviderBaseUrlAndKey({
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apiKeys,
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providerSettings: providerSettings?.[this.name],
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serverEnv: serverEnv as any,
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defaultBaseUrlKey: '',
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defaultApiTokenKey: 'GOOGLE_GENERATIVE_AI_API_KEY',
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});
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if (!apiKey) {
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throw new Error(`Missing API key for ${this.name} provider`);
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}
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const google = createGoogleGenerativeAI({
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apiKey,
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});
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return google(model);
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}
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}
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