feat: add Moonshot AI (Kimi) provider and update xAI Grok models (#1953)
- Add comprehensive Moonshot AI provider with 11 models including: * Legacy moonshot-v1 series (8k, 32k, 128k context) * Latest Kimi K2 models (K2 Preview, Turbo, Thinking) * Vision-enabled models for multimodal capabilities * Auto-selecting model variants - Update xAI provider with latest Grok models: * Add Grok 4 (256K context) and Grok 4 (07-09) variant * Add Grok 3 Mini Beta and Mini Fast Beta variants * Update context limits to match actual model capabilities * Remove outdated grok-beta and grok-2-1212 models - Add MOONSHOT_API_KEY to environment configuration - Register Moonshot provider in service status monitoring - Full OpenAI-compatible API integration via api.moonshot.ai - Fix TypeScript errors in GitHub provider 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: Claude <noreply@anthropic.com>
This commit is contained in:
Stijnus
219
.env.example
219
.env.example
@@ -1,131 +1,142 @@
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# Rename this file to .env once you have filled in the below environment variables!
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# ======================================
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# Environment Variables for Bolt.diy
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# ======================================
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# Copy this file to .env.local and fill in your API keys
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# See README.md for setup instructions
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# Get your GROQ API Key here -
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# https://console.groq.com/keys
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# You only need this environment variable set if you want to use Groq models
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GROQ_API_KEY=
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# ======================================
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# AI PROVIDER API KEYS
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# ======================================
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# Get your HuggingFace API Key here -
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# https://huggingface.co/settings/tokens
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# You only need this environment variable set if you want to use HuggingFace models
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HuggingFace_API_KEY=
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# Anthropic Claude
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# Get your API key from: https://console.anthropic.com/
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ANTHROPIC_API_KEY=your_anthropic_api_key_here
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# OpenAI GPT models
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# Get your API key from: https://platform.openai.com/api-keys
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OPENAI_API_KEY=your_openai_api_key_here
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# Get your Open AI API Key by following these instructions -
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# https://help.openai.com/en/articles/4936850-where-do-i-find-my-openai-api-key
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# You only need this environment variable set if you want to use GPT models
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OPENAI_API_KEY=
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# GitHub Models (OpenAI models hosted by GitHub)
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# Get your Personal Access Token from: https://github.com/settings/tokens
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# - Select "Fine-grained tokens"
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# - Set repository access to "All repositories"
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# - Enable "GitHub Models" permission
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GITHUB_API_KEY=github_pat_your_personal_access_token_here
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# Get your Anthropic API Key in your account settings -
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# https://console.anthropic.com/settings/keys
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# You only need this environment variable set if you want to use Claude models
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ANTHROPIC_API_KEY=
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# Perplexity AI (Search-augmented models)
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# Get your API key from: https://www.perplexity.ai/settings/api
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PERPLEXITY_API_KEY=your_perplexity_api_key_here
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# Get your OpenRouter API Key in your account settings -
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# https://openrouter.ai/settings/keys
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# You only need this environment variable set if you want to use OpenRouter models
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OPEN_ROUTER_API_KEY=
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# DeepSeek
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# Get your API key from: https://platform.deepseek.com/api_keys
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DEEPSEEK_API_KEY=your_deepseek_api_key_here
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# Get your Google Generative AI API Key by following these instructions -
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# https://console.cloud.google.com/apis/credentials
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# You only need this environment variable set if you want to use Google Generative AI models
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GOOGLE_GENERATIVE_AI_API_KEY=
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# Google Gemini
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# Get your API key from: https://makersuite.google.com/app/apikey
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GOOGLE_GENERATIVE_AI_API_KEY=your_google_gemini_api_key_here
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# You only need this environment variable set if you want to use oLLAMA models
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# DONT USE http://localhost:11434 due to IPV6 issues
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# USE EXAMPLE http://127.0.0.1:11434
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OLLAMA_API_BASE_URL=
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# Cohere
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# Get your API key from: https://dashboard.cohere.ai/api-keys
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COHERE_API_KEY=your_cohere_api_key_here
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# You only need this environment variable set if you want to use OpenAI Like models
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OPENAI_LIKE_API_BASE_URL=
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# Groq (Fast inference)
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# Get your API key from: https://console.groq.com/keys
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GROQ_API_KEY=your_groq_api_key_here
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# You only need this environment variable set if you want to use Together AI models
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TOGETHER_API_BASE_URL=
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# Mistral
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# Get your API key from: https://console.mistral.ai/api-keys/
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MISTRAL_API_KEY=your_mistral_api_key_here
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# You only need this environment variable set if you want to use DeepSeek models through their API
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DEEPSEEK_API_KEY=
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# Together AI
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# Get your API key from: https://api.together.xyz/settings/api-keys
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TOGETHER_API_KEY=your_together_api_key_here
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# Get your OpenAI Like API Key
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OPENAI_LIKE_API_KEY=
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# X.AI (Elon Musk's company)
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# Get your API key from: https://console.x.ai/
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XAI_API_KEY=your_xai_api_key_here
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# Get your Together API Key
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TOGETHER_API_KEY=
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# Moonshot AI (Kimi models)
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# Get your API key from: https://platform.moonshot.ai/console/api-keys
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MOONSHOT_API_KEY=your_moonshot_api_key_here
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# You only need this environment variable set if you want to use Hyperbolic models
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#Get your Hyperbolics API Key at https://app.hyperbolic.xyz/settings
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#baseURL="https://api.hyperbolic.xyz/v1/chat/completions"
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HYPERBOLIC_API_KEY=
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HYPERBOLIC_API_BASE_URL=
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# Hugging Face
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# Get your API key from: https://huggingface.co/settings/tokens
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HuggingFace_API_KEY=your_huggingface_api_key_here
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# Get your Mistral API Key by following these instructions -
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# https://console.mistral.ai/api-keys/
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# You only need this environment variable set if you want to use Mistral models
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MISTRAL_API_KEY=
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# Hyperbolic
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# Get your API key from: https://app.hyperbolic.xyz/settings
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HYPERBOLIC_API_KEY=your_hyperbolic_api_key_here
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# Get the Cohere Api key by following these instructions -
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# https://dashboard.cohere.com/api-keys
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# You only need this environment variable set if you want to use Cohere models
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COHERE_API_KEY=
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# OpenRouter (Meta routing for multiple providers)
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# Get your API key from: https://openrouter.ai/keys
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OPEN_ROUTER_API_KEY=your_openrouter_api_key_here
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# Get LMStudio Base URL from LM Studio Developer Console
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# Make sure to enable CORS
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# DONT USE http://localhost:1234 due to IPV6 issues
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# Example: http://127.0.0.1:1234
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LMSTUDIO_API_BASE_URL=
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# ======================================
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# CUSTOM PROVIDER BASE URLS (Optional)
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# ======================================
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# Get your xAI API key
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# https://x.ai/api
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# You only need this environment variable set if you want to use xAI models
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XAI_API_KEY=
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# Ollama (Local models)
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# DON'T USE http://localhost:11434 due to IPv6 issues
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# USE: http://127.0.0.1:11434
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OLLAMA_API_BASE_URL=http://127.0.0.1:11434
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# Get your Perplexity API Key here -
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# https://www.perplexity.ai/settings/api
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# You only need this environment variable set if you want to use Perplexity models
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PERPLEXITY_API_KEY=
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# OpenAI-like API (Compatible providers)
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OPENAI_LIKE_API_BASE_URL=your_openai_like_base_url_here
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OPENAI_LIKE_API_KEY=your_openai_like_api_key_here
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# Get your AWS configuration
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# https://console.aws.amazon.com/iam/home
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# The JSON should include the following keys:
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# - region: The AWS region where Bedrock is available.
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# - accessKeyId: Your AWS access key ID.
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# - secretAccessKey: Your AWS secret access key.
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# - sessionToken (optional): Temporary session token if using an IAM role or temporary credentials.
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# Example JSON:
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# {"region": "us-east-1", "accessKeyId": "yourAccessKeyId", "secretAccessKey": "yourSecretAccessKey", "sessionToken": "yourSessionToken"}
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AWS_BEDROCK_CONFIG=
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# Together AI Base URL
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TOGETHER_API_BASE_URL=your_together_base_url_here
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# Include this environment variable if you want more logging for debugging locally
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VITE_LOG_LEVEL=debug
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# Hyperbolic Base URL
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HYPERBOLIC_API_BASE_URL=https://api.hyperbolic.xyz/v1/chat/completions
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# Get your GitHub Personal Access Token here -
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# https://github.com/settings/tokens
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# This token is used for:
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# 1. Importing/cloning GitHub repositories without rate limiting
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# 2. Accessing private repositories
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# 3. Automatic GitHub authentication (no need to manually connect in the UI)
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#
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# For classic tokens, ensure it has these scopes: repo, read:org, read:user
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# For fine-grained tokens, ensure it has Repository and Organization access
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VITE_GITHUB_ACCESS_TOKEN=
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# LMStudio (Local models)
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# Make sure to enable CORS in LMStudio
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# DON'T USE http://localhost:1234 due to IPv6 issues
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# USE: http://127.0.0.1:1234
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LMSTUDIO_API_BASE_URL=http://127.0.0.1:1234
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# Specify the type of GitHub token you're using
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# Can be 'classic' or 'fine-grained'
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# Classic tokens are recommended for broader access
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# ======================================
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# CLOUD SERVICES CONFIGURATION
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# ======================================
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# AWS Bedrock Configuration (JSON format)
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# Get your credentials from: https://console.aws.amazon.com/iam/home
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# Example: {"region": "us-east-1", "accessKeyId": "yourAccessKeyId", "secretAccessKey": "yourSecretAccessKey"}
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AWS_BEDROCK_CONFIG=your_aws_bedrock_config_json_here
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# ======================================
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# GITHUB INTEGRATION
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# ======================================
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# GitHub Personal Access Token
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# Get from: https://github.com/settings/tokens
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# Used for importing/cloning repositories and accessing private repos
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VITE_GITHUB_ACCESS_TOKEN=your_github_personal_access_token_here
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# GitHub Token Type ('classic' or 'fine-grained')
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VITE_GITHUB_TOKEN_TYPE=classic
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# Bug Report Configuration (Server-side only)
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# GitHub token for creating bug reports - requires 'public_repo' scope
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# This token should be configured on the server/deployment environment
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# GITHUB_BUG_REPORT_TOKEN=ghp_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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# ======================================
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# DEVELOPMENT SETTINGS
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# ======================================
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# Repository where bug reports will be created
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# Format: "owner/repository"
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# BUG_REPORT_REPO=stackblitz-labs/bolt.diy
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# Development Mode
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NODE_ENV=development
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# Example Context Values for qwen2.5-coder:32b
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#
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# DEFAULT_NUM_CTX=32768 # Consumes 36GB of VRAM
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# DEFAULT_NUM_CTX=24576 # Consumes 32GB of VRAM
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# DEFAULT_NUM_CTX=12288 # Consumes 26GB of VRAM
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# DEFAULT_NUM_CTX=6144 # Consumes 24GB of VRAM
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DEFAULT_NUM_CTX=
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# Application Port (optional, defaults to 3000)
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PORT=3000
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# Logging Level (debug, info, warn, error)
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VITE_LOG_LEVEL=debug
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# Default Context Window Size (for local models)
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DEFAULT_NUM_CTX=32768
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# ======================================
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# INSTRUCTIONS
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# ======================================
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# 1. Copy this file to .env.local: cp .env.example .env.local
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# 2. Fill in the API keys you want to use
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# 3. Restart your development server: npm run dev
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# 4. Go to Settings > Providers to enable/configure providers
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@@ -8,7 +8,7 @@ import { motion } from 'framer-motion';
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import { classNames } from '~/utils/classNames';
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import { toast } from 'react-toastify';
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import { providerBaseUrlEnvKeys } from '~/utils/constants';
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import { SiAmazon, SiGoogle, SiHuggingface, SiPerplexity, SiOpenai } from 'react-icons/si';
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import { SiAmazon, SiGoogle, SiGithub, SiHuggingface, SiPerplexity, SiOpenai } from 'react-icons/si';
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import { BsRobot, BsCloud } from 'react-icons/bs';
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import { TbBrain, TbCloudComputing } from 'react-icons/tb';
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import { BiCodeBlock, BiChip } from 'react-icons/bi';
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@@ -21,6 +21,7 @@ type ProviderName =
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| 'Anthropic'
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| 'Cohere'
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| 'Deepseek'
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| 'Github'
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| 'Google'
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| 'Groq'
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| 'HuggingFace'
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@@ -38,6 +39,7 @@ const PROVIDER_ICONS: Record<ProviderName, IconType> = {
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Anthropic: FaBrain,
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Cohere: BiChip,
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Deepseek: BiCodeBlock,
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Github: SiGithub,
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Google: SiGoogle,
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Groq: BsCloud,
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HuggingFace: SiHuggingface,
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@@ -53,6 +55,7 @@ const PROVIDER_ICONS: Record<ProviderName, IconType> = {
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// Update PROVIDER_DESCRIPTIONS to use the same type
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const PROVIDER_DESCRIPTIONS: Partial<Record<ProviderName, string>> = {
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Anthropic: 'Access Claude and other Anthropic models',
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Github: 'Use OpenAI models hosted through GitHub infrastructure',
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OpenAI: 'Use GPT-4, GPT-3.5, and other OpenAI models',
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};
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@@ -13,6 +13,7 @@ import { OpenRouterStatusChecker } from './providers/openrouter';
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import { PerplexityStatusChecker } from './providers/perplexity';
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import { TogetherStatusChecker } from './providers/together';
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import { XAIStatusChecker } from './providers/xai';
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import { MoonshotStatusChecker } from './providers/moonshot';
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export class ProviderStatusCheckerFactory {
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private static _providerConfigs: Record<ProviderName, ProviderConfig> = {
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@@ -82,6 +83,12 @@ export class ProviderStatusCheckerFactory {
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headers: {},
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testModel: 'mistralai/Mixtral-8x7B-Instruct-v0.1',
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},
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Moonshot: {
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statusUrl: 'https://status.moonshot.ai/',
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apiUrl: 'https://api.moonshot.ai/v1/models',
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headers: {},
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testModel: 'moonshot-v1-8k',
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},
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XAI: {
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statusUrl: 'https://status.x.ai/',
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apiUrl: 'https://api.x.ai/v1/models',
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@@ -120,6 +127,8 @@ export class ProviderStatusCheckerFactory {
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return new PerplexityStatusChecker(config);
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case 'Together':
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return new TogetherStatusChecker(config);
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case 'Moonshot':
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return new MoonshotStatusChecker(config);
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case 'XAI':
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return new XAIStatusChecker(config);
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default:
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@@ -0,0 +1,37 @@
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import { BaseProviderChecker } from '~/components/@settings/tabs/providers/service-status/base-provider';
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import type { StatusCheckResult } from '~/components/@settings/tabs/providers/service-status/types';
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export class MoonshotStatusChecker extends BaseProviderChecker {
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async checkStatus(): Promise<StatusCheckResult> {
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try {
|
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// Check Moonshot API endpoint
|
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const apiEndpoint = 'https://api.moonshot.ai/v1/models';
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const apiStatus = await this.checkEndpoint(apiEndpoint);
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|
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// Check their main website
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const websiteStatus = await this.checkEndpoint('https://www.moonshot.ai');
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let status: StatusCheckResult['status'] = 'operational';
|
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let message = 'All systems operational';
|
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|
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if (apiStatus !== 'reachable' || websiteStatus !== 'reachable') {
|
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status = apiStatus !== 'reachable' ? 'down' : 'degraded';
|
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message = apiStatus !== 'reachable' ? 'API appears to be down' : 'Service may be experiencing issues';
|
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}
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return {
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status,
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message,
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incidents: [], // No public incident tracking available yet
|
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};
|
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} catch (error) {
|
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console.error('Error checking Moonshot status:', error);
|
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|
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return {
|
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status: 'degraded',
|
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message: 'Unable to determine service status',
|
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incidents: ['Note: Limited status information available'],
|
||||
};
|
||||
}
|
||||
}
|
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}
|
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@@ -9,6 +9,7 @@ export type ProviderName =
|
||||
| 'HuggingFace'
|
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| 'Hyperbolic'
|
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| 'Mistral'
|
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| 'Moonshot'
|
||||
| 'OpenRouter'
|
||||
| 'Perplexity'
|
||||
| 'Together'
|
||||
|
||||
@@ -1,9 +1,84 @@
|
||||
import type { ProviderInfo } from '~/types/model';
|
||||
import { useEffect, useState, useRef } from 'react';
|
||||
import { useEffect, useState, useRef, useMemo, useCallback } from 'react';
|
||||
import type { KeyboardEvent } from 'react';
|
||||
import type { ModelInfo } from '~/lib/modules/llm/types';
|
||||
import { classNames } from '~/utils/classNames';
|
||||
|
||||
// Fuzzy search utilities
|
||||
const levenshteinDistance = (str1: string, str2: string): number => {
|
||||
const matrix = [];
|
||||
|
||||
for (let i = 0; i <= str2.length; i++) {
|
||||
matrix[i] = [i];
|
||||
}
|
||||
|
||||
for (let j = 0; j <= str1.length; j++) {
|
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matrix[0][j] = j;
|
||||
}
|
||||
|
||||
for (let i = 1; i <= str2.length; i++) {
|
||||
for (let j = 1; j <= str1.length; j++) {
|
||||
if (str2.charAt(i - 1) === str1.charAt(j - 1)) {
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matrix[i][j] = matrix[i - 1][j - 1];
|
||||
} else {
|
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matrix[i][j] = Math.min(matrix[i - 1][j - 1] + 1, matrix[i][j - 1] + 1, matrix[i - 1][j] + 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return matrix[str2.length][str1.length];
|
||||
};
|
||||
|
||||
const fuzzyMatch = (query: string, text: string): { score: number; matches: boolean } => {
|
||||
if (!query) {
|
||||
return { score: 0, matches: true };
|
||||
}
|
||||
|
||||
if (!text) {
|
||||
return { score: 0, matches: false };
|
||||
}
|
||||
|
||||
const queryLower = query.toLowerCase();
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||||
const textLower = text.toLowerCase();
|
||||
|
||||
// Exact substring match gets highest score
|
||||
if (textLower.includes(queryLower)) {
|
||||
return { score: 100 - (textLower.indexOf(queryLower) / textLower.length) * 20, matches: true };
|
||||
}
|
||||
|
||||
// Fuzzy match with reasonable threshold
|
||||
const distance = levenshteinDistance(queryLower, textLower);
|
||||
const maxLen = Math.max(queryLower.length, textLower.length);
|
||||
const similarity = 1 - distance / maxLen;
|
||||
|
||||
return {
|
||||
score: similarity > 0.6 ? similarity * 80 : 0,
|
||||
matches: similarity > 0.6,
|
||||
};
|
||||
};
|
||||
|
||||
const highlightText = (text: string, query: string): string => {
|
||||
if (!query) {
|
||||
return text;
|
||||
}
|
||||
|
||||
const regex = new RegExp(`(${query.replace(/[.*+?^${}()|[\]\\]/g, '\\$&')})`, 'gi');
|
||||
|
||||
return text.replace(regex, '<mark class="bg-yellow-200 dark:bg-yellow-800 text-current">$1</mark>');
|
||||
};
|
||||
|
||||
const formatContextSize = (tokens: number): string => {
|
||||
if (tokens >= 1000000) {
|
||||
return `${(tokens / 1000000).toFixed(1)}M`;
|
||||
}
|
||||
|
||||
if (tokens >= 1000) {
|
||||
return `${(tokens / 1000).toFixed(0)}K`;
|
||||
}
|
||||
|
||||
return tokens.toString();
|
||||
};
|
||||
|
||||
interface ModelSelectorProps {
|
||||
model?: string;
|
||||
setModel?: (model: string) => void;
|
||||
@@ -40,12 +115,14 @@ export const ModelSelector = ({
|
||||
modelLoading,
|
||||
}: ModelSelectorProps) => {
|
||||
const [modelSearchQuery, setModelSearchQuery] = useState('');
|
||||
const [debouncedModelSearchQuery, setDebouncedModelSearchQuery] = useState('');
|
||||
const [isModelDropdownOpen, setIsModelDropdownOpen] = useState(false);
|
||||
const [focusedModelIndex, setFocusedModelIndex] = useState(-1);
|
||||
const modelSearchInputRef = useRef<HTMLInputElement>(null);
|
||||
const modelOptionsRef = useRef<(HTMLDivElement | null)[]>([]);
|
||||
const modelDropdownRef = useRef<HTMLDivElement>(null);
|
||||
const [providerSearchQuery, setProviderSearchQuery] = useState('');
|
||||
const [debouncedProviderSearchQuery, setDebouncedProviderSearchQuery] = useState('');
|
||||
const [isProviderDropdownOpen, setIsProviderDropdownOpen] = useState(false);
|
||||
const [focusedProviderIndex, setFocusedProviderIndex] = useState(-1);
|
||||
const providerSearchInputRef = useRef<HTMLInputElement>(null);
|
||||
@@ -53,6 +130,23 @@ export const ModelSelector = ({
|
||||
const providerDropdownRef = useRef<HTMLDivElement>(null);
|
||||
const [showFreeModelsOnly, setShowFreeModelsOnly] = useState(false);
|
||||
|
||||
// Debounce search queries
|
||||
useEffect(() => {
|
||||
const timer = setTimeout(() => {
|
||||
setDebouncedModelSearchQuery(modelSearchQuery);
|
||||
}, 150);
|
||||
|
||||
return () => clearTimeout(timer);
|
||||
}, [modelSearchQuery]);
|
||||
|
||||
useEffect(() => {
|
||||
const timer = setTimeout(() => {
|
||||
setDebouncedProviderSearchQuery(providerSearchQuery);
|
||||
}, 150);
|
||||
|
||||
return () => clearTimeout(timer);
|
||||
}, [providerSearchQuery]);
|
||||
|
||||
useEffect(() => {
|
||||
const handleClickOutside = (event: MouseEvent) => {
|
||||
if (modelDropdownRef.current && !modelDropdownRef.current.contains(event.target as Node)) {
|
||||
@@ -71,24 +165,64 @@ export const ModelSelector = ({
|
||||
return () => document.removeEventListener('mousedown', handleClickOutside);
|
||||
}, []);
|
||||
|
||||
const filteredModels = [...modelList]
|
||||
.filter((e) => e.provider === provider?.name && e.name)
|
||||
.filter((model) => {
|
||||
// Apply free models filter
|
||||
if (showFreeModelsOnly && !isModelLikelyFree(model, provider?.name)) {
|
||||
return false;
|
||||
}
|
||||
const filteredModels = useMemo(() => {
|
||||
const baseModels = [...modelList].filter((e) => e.provider === provider?.name && e.name);
|
||||
|
||||
// Apply search filter
|
||||
return (
|
||||
model.label.toLowerCase().includes(modelSearchQuery.toLowerCase()) ||
|
||||
model.name.toLowerCase().includes(modelSearchQuery.toLowerCase())
|
||||
);
|
||||
});
|
||||
return baseModels
|
||||
.filter((model) => {
|
||||
// Apply free models filter
|
||||
if (showFreeModelsOnly && !isModelLikelyFree(model, provider?.name)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
const filteredProviders = providerList.filter((p) =>
|
||||
p.name.toLowerCase().includes(providerSearchQuery.toLowerCase()),
|
||||
);
|
||||
return true;
|
||||
})
|
||||
.map((model) => {
|
||||
// Calculate search scores for fuzzy matching
|
||||
const labelMatch = fuzzyMatch(debouncedModelSearchQuery, model.label);
|
||||
const nameMatch = fuzzyMatch(debouncedModelSearchQuery, model.name);
|
||||
const contextMatch = fuzzyMatch(debouncedModelSearchQuery, formatContextSize(model.maxTokenAllowed));
|
||||
|
||||
const bestScore = Math.max(labelMatch.score, nameMatch.score, contextMatch.score);
|
||||
const matches = labelMatch.matches || nameMatch.matches || contextMatch.matches || !debouncedModelSearchQuery; // Show all if no query
|
||||
|
||||
return {
|
||||
...model,
|
||||
searchScore: bestScore,
|
||||
searchMatches: matches,
|
||||
highlightedLabel: highlightText(model.label, debouncedModelSearchQuery),
|
||||
highlightedName: highlightText(model.name, debouncedModelSearchQuery),
|
||||
};
|
||||
})
|
||||
.filter((model) => model.searchMatches)
|
||||
.sort((a, b) => {
|
||||
// Sort by search score (highest first), then by label
|
||||
if (debouncedModelSearchQuery) {
|
||||
return b.searchScore - a.searchScore;
|
||||
}
|
||||
|
||||
return a.label.localeCompare(b.label);
|
||||
});
|
||||
}, [modelList, provider?.name, showFreeModelsOnly, debouncedModelSearchQuery]);
|
||||
|
||||
const filteredProviders = useMemo(() => {
|
||||
if (!debouncedProviderSearchQuery) {
|
||||
return providerList;
|
||||
}
|
||||
|
||||
return providerList
|
||||
.map((provider) => {
|
||||
const match = fuzzyMatch(debouncedProviderSearchQuery, provider.name);
|
||||
return {
|
||||
...provider,
|
||||
searchScore: match.score,
|
||||
searchMatches: match.matches,
|
||||
highlightedName: highlightText(provider.name, debouncedProviderSearchQuery),
|
||||
};
|
||||
})
|
||||
.filter((provider) => provider.searchMatches)
|
||||
.sort((a, b) => b.searchScore - a.searchScore);
|
||||
}, [providerList, debouncedProviderSearchQuery]);
|
||||
|
||||
// Reset free models filter when provider changes
|
||||
useEffect(() => {
|
||||
@@ -97,11 +231,30 @@ export const ModelSelector = ({
|
||||
|
||||
useEffect(() => {
|
||||
setFocusedModelIndex(-1);
|
||||
}, [modelSearchQuery, isModelDropdownOpen, showFreeModelsOnly]);
|
||||
}, [debouncedModelSearchQuery, isModelDropdownOpen, showFreeModelsOnly]);
|
||||
|
||||
useEffect(() => {
|
||||
setFocusedProviderIndex(-1);
|
||||
}, [providerSearchQuery, isProviderDropdownOpen]);
|
||||
}, [debouncedProviderSearchQuery, isProviderDropdownOpen]);
|
||||
|
||||
// Clear search functions
|
||||
const clearModelSearch = useCallback(() => {
|
||||
setModelSearchQuery('');
|
||||
setDebouncedModelSearchQuery('');
|
||||
|
||||
if (modelSearchInputRef.current) {
|
||||
modelSearchInputRef.current.focus();
|
||||
}
|
||||
}, []);
|
||||
|
||||
const clearProviderSearch = useCallback(() => {
|
||||
setProviderSearchQuery('');
|
||||
setDebouncedProviderSearchQuery('');
|
||||
|
||||
if (providerSearchInputRef.current) {
|
||||
providerSearchInputRef.current.focus();
|
||||
}
|
||||
}, []);
|
||||
|
||||
useEffect(() => {
|
||||
if (isModelDropdownOpen && modelSearchInputRef.current) {
|
||||
@@ -137,6 +290,7 @@ export const ModelSelector = ({
|
||||
setModel?.(selectedModel.name);
|
||||
setIsModelDropdownOpen(false);
|
||||
setModelSearchQuery('');
|
||||
setDebouncedModelSearchQuery('');
|
||||
}
|
||||
|
||||
break;
|
||||
@@ -144,12 +298,20 @@ export const ModelSelector = ({
|
||||
e.preventDefault();
|
||||
setIsModelDropdownOpen(false);
|
||||
setModelSearchQuery('');
|
||||
setDebouncedModelSearchQuery('');
|
||||
break;
|
||||
case 'Tab':
|
||||
if (!e.shiftKey && focusedModelIndex === filteredModels.length - 1) {
|
||||
setIsModelDropdownOpen(false);
|
||||
}
|
||||
|
||||
break;
|
||||
case 'k':
|
||||
if (e.ctrlKey || e.metaKey) {
|
||||
e.preventDefault();
|
||||
clearModelSearch();
|
||||
}
|
||||
|
||||
break;
|
||||
}
|
||||
};
|
||||
@@ -186,6 +348,7 @@ export const ModelSelector = ({
|
||||
|
||||
setIsProviderDropdownOpen(false);
|
||||
setProviderSearchQuery('');
|
||||
setDebouncedProviderSearchQuery('');
|
||||
}
|
||||
|
||||
break;
|
||||
@@ -193,12 +356,20 @@ export const ModelSelector = ({
|
||||
e.preventDefault();
|
||||
setIsProviderDropdownOpen(false);
|
||||
setProviderSearchQuery('');
|
||||
setDebouncedProviderSearchQuery('');
|
||||
break;
|
||||
case 'Tab':
|
||||
if (!e.shiftKey && focusedProviderIndex === filteredProviders.length - 1) {
|
||||
setIsProviderDropdownOpen(false);
|
||||
}
|
||||
|
||||
break;
|
||||
case 'k':
|
||||
if (e.ctrlKey || e.metaKey) {
|
||||
e.preventDefault();
|
||||
clearProviderSearch();
|
||||
}
|
||||
|
||||
break;
|
||||
}
|
||||
};
|
||||
@@ -292,9 +463,9 @@ export const ModelSelector = ({
|
||||
type="text"
|
||||
value={providerSearchQuery}
|
||||
onChange={(e) => setProviderSearchQuery(e.target.value)}
|
||||
placeholder="Search providers..."
|
||||
placeholder="Search providers... (⌘K to clear)"
|
||||
className={classNames(
|
||||
'w-full pl-2 py-1.5 rounded-md text-sm',
|
||||
'w-full pl-8 pr-8 py-1.5 rounded-md text-sm',
|
||||
'bg-bolt-elements-background-depth-2 border border-bolt-elements-borderColor',
|
||||
'text-bolt-elements-textPrimary placeholder:text-bolt-elements-textTertiary',
|
||||
'focus:outline-none focus:ring-2 focus:ring-bolt-elements-focus',
|
||||
@@ -307,6 +478,19 @@ export const ModelSelector = ({
|
||||
<div className="absolute left-2.5 top-1/2 -translate-y-1/2">
|
||||
<span className="i-ph:magnifying-glass text-bolt-elements-textTertiary" />
|
||||
</div>
|
||||
{providerSearchQuery && (
|
||||
<button
|
||||
type="button"
|
||||
onClick={(e) => {
|
||||
e.stopPropagation();
|
||||
clearProviderSearch();
|
||||
}}
|
||||
className="absolute right-2.5 top-1/2 -translate-y-1/2 p-0.5 rounded hover:bg-bolt-elements-background-depth-3 transition-colors"
|
||||
aria-label="Clear search"
|
||||
>
|
||||
<span className="i-ph:x text-bolt-elements-textTertiary text-xs" />
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -327,7 +511,18 @@ export const ModelSelector = ({
|
||||
)}
|
||||
>
|
||||
{filteredProviders.length === 0 ? (
|
||||
<div className="px-3 py-2 text-sm text-bolt-elements-textTertiary">No providers found</div>
|
||||
<div className="px-3 py-3 text-sm">
|
||||
<div className="text-bolt-elements-textTertiary mb-1">
|
||||
{debouncedProviderSearchQuery
|
||||
? `No providers match "${debouncedProviderSearchQuery}"`
|
||||
: 'No providers found'}
|
||||
</div>
|
||||
{debouncedProviderSearchQuery && (
|
||||
<div className="text-xs text-bolt-elements-textTertiary">
|
||||
Try searching for provider names like "OpenAI", "Anthropic", or "Google"
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
) : (
|
||||
filteredProviders.map((providerOption, index) => (
|
||||
<div
|
||||
@@ -360,10 +555,15 @@ export const ModelSelector = ({
|
||||
|
||||
setIsProviderDropdownOpen(false);
|
||||
setProviderSearchQuery('');
|
||||
setDebouncedProviderSearchQuery('');
|
||||
}}
|
||||
tabIndex={focusedProviderIndex === index ? 0 : -1}
|
||||
>
|
||||
{providerOption.name}
|
||||
<div
|
||||
dangerouslySetInnerHTML={{
|
||||
__html: (providerOption as any).highlightedName || providerOption.name,
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
))
|
||||
)}
|
||||
@@ -441,6 +641,14 @@ export const ModelSelector = ({
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Search Result Count */}
|
||||
{debouncedModelSearchQuery && filteredModels.length > 0 && (
|
||||
<div className="text-xs text-bolt-elements-textTertiary px-1">
|
||||
{filteredModels.length} model{filteredModels.length !== 1 ? 's' : ''} found
|
||||
{filteredModels.length > 5 && ' (showing best matches)'}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Search Input */}
|
||||
<div className="relative">
|
||||
<input
|
||||
@@ -448,9 +656,9 @@ export const ModelSelector = ({
|
||||
type="text"
|
||||
value={modelSearchQuery}
|
||||
onChange={(e) => setModelSearchQuery(e.target.value)}
|
||||
placeholder="Search models..."
|
||||
placeholder="Search models... (⌘K to clear)"
|
||||
className={classNames(
|
||||
'w-full pl-2 py-1.5 rounded-md text-sm',
|
||||
'w-full pl-8 pr-8 py-1.5 rounded-md text-sm',
|
||||
'bg-bolt-elements-background-depth-2 border border-bolt-elements-borderColor',
|
||||
'text-bolt-elements-textPrimary placeholder:text-bolt-elements-textTertiary',
|
||||
'focus:outline-none focus:ring-2 focus:ring-bolt-elements-focus',
|
||||
@@ -463,6 +671,19 @@ export const ModelSelector = ({
|
||||
<div className="absolute left-2.5 top-1/2 -translate-y-1/2">
|
||||
<span className="i-ph:magnifying-glass text-bolt-elements-textTertiary" />
|
||||
</div>
|
||||
{modelSearchQuery && (
|
||||
<button
|
||||
type="button"
|
||||
onClick={(e) => {
|
||||
e.stopPropagation();
|
||||
clearModelSearch();
|
||||
}}
|
||||
className="absolute right-2.5 top-1/2 -translate-y-1/2 p-0.5 rounded hover:bg-bolt-elements-background-depth-3 transition-colors"
|
||||
aria-label="Clear search"
|
||||
>
|
||||
<span className="i-ph:x text-bolt-elements-textTertiary text-xs" />
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -483,16 +704,37 @@ export const ModelSelector = ({
|
||||
)}
|
||||
>
|
||||
{modelLoading === 'all' || modelLoading === provider?.name ? (
|
||||
<div className="px-3 py-2 text-sm text-bolt-elements-textTertiary">Loading...</div>
|
||||
<div className="px-3 py-3 text-sm">
|
||||
<div className="flex items-center gap-2 text-bolt-elements-textTertiary">
|
||||
<span className="i-ph:spinner animate-spin" />
|
||||
Loading models...
|
||||
</div>
|
||||
</div>
|
||||
) : filteredModels.length === 0 ? (
|
||||
<div className="px-3 py-2 text-sm text-bolt-elements-textTertiary">
|
||||
{showFreeModelsOnly ? 'No free models found' : 'No models found'}
|
||||
<div className="px-3 py-3 text-sm">
|
||||
<div className="text-bolt-elements-textTertiary mb-1">
|
||||
{debouncedModelSearchQuery
|
||||
? `No models match "${debouncedModelSearchQuery}"${showFreeModelsOnly ? ' (free only)' : ''}`
|
||||
: showFreeModelsOnly
|
||||
? 'No free models available'
|
||||
: 'No models available'}
|
||||
</div>
|
||||
{debouncedModelSearchQuery && (
|
||||
<div className="text-xs text-bolt-elements-textTertiary">
|
||||
Try searching for model names, context sizes (e.g., "128k", "1M"), or capabilities
|
||||
</div>
|
||||
)}
|
||||
{showFreeModelsOnly && !debouncedModelSearchQuery && (
|
||||
<div className="text-xs text-bolt-elements-textTertiary">
|
||||
Try disabling the "Free models only" filter to see all available models
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
) : (
|
||||
filteredModels.map((modelOption, index) => (
|
||||
<div
|
||||
ref={(el) => (modelOptionsRef.current[index] = el)}
|
||||
key={index} // Consider using modelOption.name if unique
|
||||
key={modelOption.name}
|
||||
role="option"
|
||||
aria-selected={model === modelOption.name}
|
||||
className={classNames(
|
||||
@@ -510,14 +752,38 @@ export const ModelSelector = ({
|
||||
setModel?.(modelOption.name);
|
||||
setIsModelDropdownOpen(false);
|
||||
setModelSearchQuery('');
|
||||
setDebouncedModelSearchQuery('');
|
||||
}}
|
||||
tabIndex={focusedModelIndex === index ? 0 : -1}
|
||||
>
|
||||
<div className="flex items-center justify-between">
|
||||
<span>{modelOption.label}</span>
|
||||
{isModelLikelyFree(modelOption, provider?.name) && (
|
||||
<span className="i-ph:gift text-xs text-purple-400 ml-2" title="Free model" />
|
||||
)}
|
||||
<div className="flex-1 min-w-0">
|
||||
<div className="truncate">
|
||||
<span
|
||||
dangerouslySetInnerHTML={{
|
||||
__html: (modelOption as any).highlightedLabel || modelOption.label,
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
<div className="flex items-center gap-2 mt-0.5">
|
||||
<span className="text-xs text-bolt-elements-textTertiary">
|
||||
{formatContextSize(modelOption.maxTokenAllowed)} tokens
|
||||
</span>
|
||||
{debouncedModelSearchQuery && (modelOption as any).searchScore > 70 && (
|
||||
<span className="text-xs text-green-500 font-medium">
|
||||
{(modelOption as any).searchScore.toFixed(0)}% match
|
||||
</span>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
<div className="flex items-center gap-1 ml-2">
|
||||
{isModelLikelyFree(modelOption, provider?.name) && (
|
||||
<span className="i-ph:gift text-xs text-purple-400" title="Free model" />
|
||||
)}
|
||||
{model === modelOption.name && (
|
||||
<span className="i-ph:check text-xs text-green-500" title="Selected" />
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
))
|
||||
|
||||
@@ -1,18 +1,19 @@
|
||||
/*
|
||||
* Maximum tokens for response generation (conservative default for older models)
|
||||
* Modern models can handle much higher limits - specific limits are set per model
|
||||
* Maximum tokens for response generation (updated for modern model capabilities)
|
||||
* This serves as a fallback when model-specific limits are unavailable
|
||||
* Modern models like Claude 3.5, GPT-4o, and Gemini Pro support 128k+ tokens
|
||||
*/
|
||||
export const MAX_TOKENS = 32000;
|
||||
export const MAX_TOKENS = 128000;
|
||||
|
||||
/*
|
||||
* Provider-specific default completion token limits
|
||||
* Used as fallbacks when model doesn't specify maxCompletionTokens
|
||||
*/
|
||||
export const PROVIDER_COMPLETION_LIMITS: Record<string, number> = {
|
||||
OpenAI: 16384,
|
||||
Github: 16384, // GitHub Models use OpenAI-compatible limits
|
||||
Anthropic: 128000,
|
||||
Google: 32768,
|
||||
OpenAI: 4096, // Standard GPT models (o1 models have much higher limits)
|
||||
Github: 4096, // GitHub Models use OpenAI-compatible limits
|
||||
Anthropic: 64000, // Conservative limit for Claude 4 models (Opus: 32k, Sonnet: 64k)
|
||||
Google: 8192, // Gemini 1.5 Pro/Flash standard limit
|
||||
Cohere: 4000,
|
||||
DeepSeek: 8192,
|
||||
Groq: 8192,
|
||||
|
||||
@@ -142,11 +142,11 @@ export async function streamText(props: {
|
||||
|
||||
const dynamicMaxTokens = modelDetails ? getCompletionTokenLimit(modelDetails) : Math.min(MAX_TOKENS, 16384);
|
||||
|
||||
// Additional safety cap - should not be needed with proper completion limits, but kept for safety
|
||||
const safeMaxTokens = Math.min(dynamicMaxTokens, 128000);
|
||||
// Use model-specific limits directly - no artificial cap needed
|
||||
const safeMaxTokens = dynamicMaxTokens;
|
||||
|
||||
logger.info(
|
||||
`Max tokens for model ${modelDetails.name} is ${safeMaxTokens} (capped from ${dynamicMaxTokens}) based on model limits`,
|
||||
`Token limits for model ${modelDetails.name}: maxTokens=${safeMaxTokens}, maxTokenAllowed=${modelDetails.maxTokenAllowed}, maxCompletionTokens=${modelDetails.maxCompletionTokens}`,
|
||||
);
|
||||
|
||||
let systemPrompt =
|
||||
@@ -221,11 +221,18 @@ export async function streamText(props: {
|
||||
|
||||
logger.info(`Sending llm call to ${provider.name} with model ${modelDetails.name}`);
|
||||
|
||||
// DEBUG: Log reasoning model detection
|
||||
// Log reasoning model detection and token parameters
|
||||
const isReasoning = isReasoningModel(modelDetails.name);
|
||||
logger.info(`DEBUG STREAM: Model "${modelDetails.name}" detected as reasoning model: ${isReasoning}`);
|
||||
logger.info(
|
||||
`Model "${modelDetails.name}" is reasoning model: ${isReasoning}, using ${isReasoning ? 'maxCompletionTokens' : 'maxTokens'}: ${safeMaxTokens}`,
|
||||
);
|
||||
|
||||
// console.log(systemPrompt, processedMessages);
|
||||
// Validate token limits before API call
|
||||
if (safeMaxTokens > (modelDetails.maxTokenAllowed || 128000)) {
|
||||
logger.warn(
|
||||
`Token limit warning: requesting ${safeMaxTokens} tokens but model supports max ${modelDetails.maxTokenAllowed || 128000}`,
|
||||
);
|
||||
}
|
||||
|
||||
// Use maxCompletionTokens for reasoning models (o1, GPT-5), maxTokens for traditional models
|
||||
const tokenParams = isReasoning ? { maxCompletionTokens: safeMaxTokens } : { maxTokens: safeMaxTokens };
|
||||
|
||||
@@ -33,6 +33,15 @@ export default class AnthropicProvider extends BaseProvider {
|
||||
maxTokenAllowed: 200000,
|
||||
maxCompletionTokens: 128000,
|
||||
},
|
||||
|
||||
// Claude Opus 4: 200k context, 32k output limit (latest flagship model)
|
||||
{
|
||||
name: 'claude-opus-4-20250514',
|
||||
label: 'Claude 4 Opus',
|
||||
provider: 'Anthropic',
|
||||
maxTokenAllowed: 200000,
|
||||
maxCompletionTokens: 32000,
|
||||
},
|
||||
];
|
||||
|
||||
async getDynamicModels(
|
||||
@@ -81,12 +90,23 @@ export default class AnthropicProvider extends BaseProvider {
|
||||
contextWindow = 200000; // Claude 3 Sonnet has 200k context
|
||||
}
|
||||
|
||||
// Determine completion token limits based on specific model
|
||||
let maxCompletionTokens = 128000; // default for older Claude 3 models
|
||||
|
||||
if (m.id?.includes('claude-opus-4')) {
|
||||
maxCompletionTokens = 32000; // Claude 4 Opus: 32K output limit
|
||||
} else if (m.id?.includes('claude-sonnet-4')) {
|
||||
maxCompletionTokens = 64000; // Claude 4 Sonnet: 64K output limit
|
||||
} else if (m.id?.includes('claude-4')) {
|
||||
maxCompletionTokens = 32000; // Other Claude 4 models: conservative 32K limit
|
||||
}
|
||||
|
||||
return {
|
||||
name: m.id,
|
||||
label: `${m.display_name} (${Math.floor(contextWindow / 1000)}k context)`,
|
||||
provider: this.name,
|
||||
maxTokenAllowed: contextWindow,
|
||||
maxCompletionTokens: 128000, // Claude models support up to 128k completion tokens
|
||||
maxCompletionTokens,
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
@@ -12,35 +12,114 @@ export default class GithubProvider extends BaseProvider {
|
||||
apiTokenKey: 'GITHUB_API_KEY',
|
||||
};
|
||||
|
||||
// find more in https://github.com/marketplace?type=models
|
||||
/*
|
||||
* GitHub Models - Available models through GitHub's native API
|
||||
* Updated for the new GitHub Models API at https://models.github.ai
|
||||
* Model IDs use the format: publisher/model-name
|
||||
*/
|
||||
staticModels: ModelInfo[] = [
|
||||
{ name: 'gpt-4o', label: 'GPT-4o', provider: 'Github', maxTokenAllowed: 128000, maxCompletionTokens: 16384 },
|
||||
{ name: 'o1', label: 'o1-preview', provider: 'Github', maxTokenAllowed: 100000, maxCompletionTokens: 16384 },
|
||||
{ name: 'o1-mini', label: 'o1-mini', provider: 'Github', maxTokenAllowed: 65536, maxCompletionTokens: 8192 },
|
||||
{ name: 'openai/gpt-4o', label: 'GPT-4o', provider: 'Github', maxTokenAllowed: 131072, maxCompletionTokens: 4096 },
|
||||
{
|
||||
name: 'gpt-4o-mini',
|
||||
name: 'openai/gpt-4o-mini',
|
||||
label: 'GPT-4o Mini',
|
||||
provider: 'Github',
|
||||
maxTokenAllowed: 128000,
|
||||
maxCompletionTokens: 16384,
|
||||
maxTokenAllowed: 131072,
|
||||
maxCompletionTokens: 4096,
|
||||
},
|
||||
{
|
||||
name: 'gpt-4-turbo',
|
||||
label: 'GPT-4 Turbo',
|
||||
name: 'openai/o1-preview',
|
||||
label: 'o1-preview',
|
||||
provider: 'Github',
|
||||
maxTokenAllowed: 128000,
|
||||
maxCompletionTokens: 8192,
|
||||
maxCompletionTokens: 32000,
|
||||
},
|
||||
{ name: 'gpt-4', label: 'GPT-4', provider: 'Github', maxTokenAllowed: 8192, maxCompletionTokens: 8192 },
|
||||
{
|
||||
name: 'gpt-3.5-turbo',
|
||||
label: 'GPT-3.5 Turbo',
|
||||
name: 'openai/o1-mini',
|
||||
label: 'o1-mini',
|
||||
provider: 'Github',
|
||||
maxTokenAllowed: 16385,
|
||||
maxTokenAllowed: 128000,
|
||||
maxCompletionTokens: 65000,
|
||||
},
|
||||
{ name: 'openai/o1', label: 'o1', provider: 'Github', maxTokenAllowed: 200000, maxCompletionTokens: 100000 },
|
||||
{
|
||||
name: 'openai/gpt-4.1',
|
||||
label: 'GPT-4.1',
|
||||
provider: 'Github',
|
||||
maxTokenAllowed: 1048576,
|
||||
maxCompletionTokens: 32768,
|
||||
},
|
||||
{
|
||||
name: 'openai/gpt-4.1-mini',
|
||||
label: 'GPT-4.1-mini',
|
||||
provider: 'Github',
|
||||
maxTokenAllowed: 1048576,
|
||||
maxCompletionTokens: 32768,
|
||||
},
|
||||
{
|
||||
name: 'deepseek/deepseek-r1',
|
||||
label: 'DeepSeek-R1',
|
||||
provider: 'Github',
|
||||
maxTokenAllowed: 128000,
|
||||
maxCompletionTokens: 4096,
|
||||
},
|
||||
];
|
||||
|
||||
async getDynamicModels(
|
||||
apiKeys?: Record<string, string>,
|
||||
settings?: IProviderSetting,
|
||||
serverEnv?: Record<string, string>,
|
||||
): Promise<ModelInfo[]> {
|
||||
const { apiKey } = this.getProviderBaseUrlAndKey({
|
||||
apiKeys,
|
||||
providerSettings: settings,
|
||||
serverEnv: serverEnv as any,
|
||||
defaultBaseUrlKey: '',
|
||||
defaultApiTokenKey: 'GITHUB_API_KEY',
|
||||
});
|
||||
|
||||
if (!apiKey) {
|
||||
console.log('GitHub: No API key found. Make sure GITHUB_API_KEY is set in your .env.local file');
|
||||
|
||||
// Return static models if no API key is available
|
||||
return this.staticModels;
|
||||
}
|
||||
|
||||
console.log('GitHub: API key found, attempting to fetch dynamic models...');
|
||||
|
||||
try {
|
||||
// Try to fetch dynamic models from GitHub API
|
||||
const response = await fetch('https://models.github.ai/v1/models', {
|
||||
headers: {
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
},
|
||||
});
|
||||
|
||||
if (response.ok) {
|
||||
const data = (await response.json()) as { data?: any[] };
|
||||
console.log('GitHub: Successfully fetched models from API');
|
||||
|
||||
if (data.data && Array.isArray(data.data)) {
|
||||
return data.data.map((model: any) => ({
|
||||
name: model.id,
|
||||
label: model.name || model.id.split('/').pop() || model.id,
|
||||
provider: 'Github',
|
||||
maxTokenAllowed: model.limits?.max_input_tokens || 128000,
|
||||
maxCompletionTokens: model.limits?.max_output_tokens || 16384,
|
||||
}));
|
||||
}
|
||||
} else {
|
||||
console.warn('GitHub: API request failed with status:', response.status, response.statusText);
|
||||
}
|
||||
} catch (error) {
|
||||
console.warn('GitHub: Failed to fetch models, using static models:', error);
|
||||
}
|
||||
|
||||
// Fallback to static models
|
||||
console.log('GitHub: Using static models as fallback');
|
||||
|
||||
return this.staticModels;
|
||||
}
|
||||
|
||||
getModelInstance(options: {
|
||||
model: string;
|
||||
serverEnv: Env;
|
||||
@@ -49,6 +128,8 @@ export default class GithubProvider extends BaseProvider {
|
||||
}): LanguageModelV1 {
|
||||
const { model, serverEnv, apiKeys, providerSettings } = options;
|
||||
|
||||
console.log(`GitHub: Creating model instance for ${model}`);
|
||||
|
||||
const { apiKey } = this.getProviderBaseUrlAndKey({
|
||||
apiKeys,
|
||||
providerSettings: providerSettings?.[this.name],
|
||||
@@ -58,14 +139,19 @@ export default class GithubProvider extends BaseProvider {
|
||||
});
|
||||
|
||||
if (!apiKey) {
|
||||
console.error('GitHub: No API key found');
|
||||
throw new Error(`Missing API key for ${this.name} provider`);
|
||||
}
|
||||
|
||||
console.log(`GitHub: Using API key (first 8 chars): ${apiKey.substring(0, 8)}...`);
|
||||
|
||||
const openai = createOpenAI({
|
||||
baseURL: 'https://models.inference.ai.azure.com',
|
||||
baseURL: 'https://models.github.ai/inference',
|
||||
apiKey,
|
||||
});
|
||||
|
||||
console.log(`GitHub: Created OpenAI client, requesting model: ${model}`);
|
||||
|
||||
return openai(model);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -15,23 +15,23 @@ export default class GoogleProvider extends BaseProvider {
|
||||
staticModels: ModelInfo[] = [
|
||||
/*
|
||||
* Essential fallback models - only the most reliable/stable ones
|
||||
* Gemini 1.5 Pro: 2M context, excellent for complex reasoning and large codebases
|
||||
* Gemini 1.5 Pro: 2M context, 8K output limit (verified from API docs)
|
||||
*/
|
||||
{
|
||||
name: 'gemini-1.5-pro',
|
||||
label: 'Gemini 1.5 Pro',
|
||||
provider: 'Google',
|
||||
maxTokenAllowed: 2000000,
|
||||
maxCompletionTokens: 32768,
|
||||
maxCompletionTokens: 8192,
|
||||
},
|
||||
|
||||
// Gemini 1.5 Flash: 1M context, fast and cost-effective
|
||||
// Gemini 1.5 Flash: 1M context, 8K output limit, fast and cost-effective
|
||||
{
|
||||
name: 'gemini-1.5-flash',
|
||||
label: 'Gemini 1.5 Flash',
|
||||
provider: 'Google',
|
||||
maxTokenAllowed: 1000000,
|
||||
maxCompletionTokens: 32768,
|
||||
maxCompletionTokens: 8192,
|
||||
},
|
||||
];
|
||||
|
||||
@@ -102,10 +102,10 @@ export default class GoogleProvider extends BaseProvider {
|
||||
const finalContext = Math.min(contextWindow, maxAllowed);
|
||||
|
||||
// Get completion token limit from Google API
|
||||
let completionTokens = 32768; // default fallback
|
||||
let completionTokens = 8192; // default fallback (Gemini 1.5 standard limit)
|
||||
|
||||
if (m.outputTokenLimit && m.outputTokenLimit > 0) {
|
||||
completionTokens = Math.min(m.outputTokenLimit, 128000); // Cap at reasonable limit
|
||||
completionTokens = Math.min(m.outputTokenLimit, 128000); // Use API value, cap at reasonable limit
|
||||
}
|
||||
|
||||
return {
|
||||
|
||||
71
app/lib/modules/llm/providers/moonshot.ts
Normal file
71
app/lib/modules/llm/providers/moonshot.ts
Normal file
@@ -0,0 +1,71 @@
|
||||
import { BaseProvider } from '~/lib/modules/llm/base-provider';
|
||||
import type { ModelInfo } from '~/lib/modules/llm/types';
|
||||
import type { IProviderSetting } from '~/types/model';
|
||||
import type { LanguageModelV1 } from 'ai';
|
||||
import { createOpenAI } from '@ai-sdk/openai';
|
||||
|
||||
export default class MoonshotProvider extends BaseProvider {
|
||||
name = 'Moonshot';
|
||||
getApiKeyLink = 'https://platform.moonshot.ai/console/api-keys';
|
||||
|
||||
config = {
|
||||
apiTokenKey: 'MOONSHOT_API_KEY',
|
||||
};
|
||||
|
||||
staticModels: ModelInfo[] = [
|
||||
{ name: 'moonshot-v1-8k', label: 'Moonshot v1 8K', provider: 'Moonshot', maxTokenAllowed: 8000 },
|
||||
{ name: 'moonshot-v1-32k', label: 'Moonshot v1 32K', provider: 'Moonshot', maxTokenAllowed: 32000 },
|
||||
{ name: 'moonshot-v1-128k', label: 'Moonshot v1 128K', provider: 'Moonshot', maxTokenAllowed: 128000 },
|
||||
{ name: 'moonshot-v1-auto', label: 'Moonshot v1 Auto', provider: 'Moonshot', maxTokenAllowed: 128000 },
|
||||
{
|
||||
name: 'moonshot-v1-8k-vision-preview',
|
||||
label: 'Moonshot v1 8K Vision',
|
||||
provider: 'Moonshot',
|
||||
maxTokenAllowed: 8000,
|
||||
},
|
||||
{
|
||||
name: 'moonshot-v1-32k-vision-preview',
|
||||
label: 'Moonshot v1 32K Vision',
|
||||
provider: 'Moonshot',
|
||||
maxTokenAllowed: 32000,
|
||||
},
|
||||
{
|
||||
name: 'moonshot-v1-128k-vision-preview',
|
||||
label: 'Moonshot v1 128K Vision',
|
||||
provider: 'Moonshot',
|
||||
maxTokenAllowed: 128000,
|
||||
},
|
||||
{ name: 'kimi-latest', label: 'Kimi Latest', provider: 'Moonshot', maxTokenAllowed: 128000 },
|
||||
{ name: 'kimi-k2-0711-preview', label: 'Kimi K2 Preview', provider: 'Moonshot', maxTokenAllowed: 128000 },
|
||||
{ name: 'kimi-k2-turbo-preview', label: 'Kimi K2 Turbo', provider: 'Moonshot', maxTokenAllowed: 128000 },
|
||||
{ name: 'kimi-thinking-preview', label: 'Kimi Thinking', provider: 'Moonshot', maxTokenAllowed: 128000 },
|
||||
];
|
||||
|
||||
getModelInstance(options: {
|
||||
model: string;
|
||||
serverEnv: Env;
|
||||
apiKeys?: Record<string, string>;
|
||||
providerSettings?: Record<string, IProviderSetting>;
|
||||
}): LanguageModelV1 {
|
||||
const { model, serverEnv, apiKeys, providerSettings } = options;
|
||||
|
||||
const { apiKey } = this.getProviderBaseUrlAndKey({
|
||||
apiKeys,
|
||||
providerSettings: providerSettings?.[this.name],
|
||||
serverEnv: serverEnv as any,
|
||||
defaultBaseUrlKey: '',
|
||||
defaultApiTokenKey: 'MOONSHOT_API_KEY',
|
||||
});
|
||||
|
||||
if (!apiKey) {
|
||||
throw new Error(`Missing API key for ${this.name} provider`);
|
||||
}
|
||||
|
||||
const openai = createOpenAI({
|
||||
baseURL: 'https://api.moonshot.ai/v1',
|
||||
apiKey,
|
||||
});
|
||||
|
||||
return openai(model);
|
||||
}
|
||||
}
|
||||
@@ -15,9 +15,18 @@ export default class OpenAIProvider extends BaseProvider {
|
||||
staticModels: ModelInfo[] = [
|
||||
/*
|
||||
* Essential fallback models - only the most stable/reliable ones
|
||||
* GPT-4o: 128k context, high performance, recommended for most tasks
|
||||
* GPT-4o: 128k context, 4k standard output (64k with long output mode)
|
||||
*/
|
||||
{ name: 'gpt-4o', label: 'GPT-4o', provider: 'OpenAI', maxTokenAllowed: 128000, maxCompletionTokens: 16384 },
|
||||
{ name: 'gpt-4o', label: 'GPT-4o', provider: 'OpenAI', maxTokenAllowed: 128000, maxCompletionTokens: 4096 },
|
||||
|
||||
// GPT-4o Mini: 128k context, cost-effective alternative
|
||||
{
|
||||
name: 'gpt-4o-mini',
|
||||
label: 'GPT-4o Mini',
|
||||
provider: 'OpenAI',
|
||||
maxTokenAllowed: 128000,
|
||||
maxCompletionTokens: 4096,
|
||||
},
|
||||
|
||||
// GPT-3.5-turbo: 16k context, fast and cost-effective
|
||||
{
|
||||
@@ -27,6 +36,18 @@ export default class OpenAIProvider extends BaseProvider {
|
||||
maxTokenAllowed: 16000,
|
||||
maxCompletionTokens: 4096,
|
||||
},
|
||||
|
||||
// o1-preview: 128k context, 32k output limit (reasoning model)
|
||||
{
|
||||
name: 'o1-preview',
|
||||
label: 'o1-preview',
|
||||
provider: 'OpenAI',
|
||||
maxTokenAllowed: 128000,
|
||||
maxCompletionTokens: 32000,
|
||||
},
|
||||
|
||||
// o1-mini: 128k context, 65k output limit (reasoning model)
|
||||
{ name: 'o1-mini', label: 'o1-mini', provider: 'OpenAI', maxTokenAllowed: 128000, maxCompletionTokens: 65000 },
|
||||
];
|
||||
|
||||
async getDynamicModels(
|
||||
@@ -79,18 +100,23 @@ export default class OpenAIProvider extends BaseProvider {
|
||||
contextWindow = 16385; // GPT-3.5-turbo has 16k context
|
||||
}
|
||||
|
||||
// Determine completion token limits based on model type
|
||||
let maxCompletionTokens = 16384; // default for most models
|
||||
// Determine completion token limits based on model type (accurate 2025 limits)
|
||||
let maxCompletionTokens = 4096; // default for most models
|
||||
|
||||
if (m.id?.startsWith('o1-preview') || m.id?.startsWith('o1-mini') || m.id?.startsWith('o1')) {
|
||||
// Reasoning models have specific completion limits
|
||||
maxCompletionTokens = m.id?.includes('mini') ? 8192 : 16384;
|
||||
if (m.id?.startsWith('o1-preview')) {
|
||||
maxCompletionTokens = 32000; // o1-preview: 32K output limit
|
||||
} else if (m.id?.startsWith('o1-mini')) {
|
||||
maxCompletionTokens = 65000; // o1-mini: 65K output limit
|
||||
} else if (m.id?.startsWith('o1')) {
|
||||
maxCompletionTokens = 32000; // Other o1 models: 32K limit
|
||||
} else if (m.id?.includes('o3') || m.id?.includes('o4')) {
|
||||
maxCompletionTokens = 100000; // o3/o4 models: 100K output limit
|
||||
} else if (m.id?.includes('gpt-4o')) {
|
||||
maxCompletionTokens = 16384;
|
||||
maxCompletionTokens = 4096; // GPT-4o standard: 4K (64K with long output mode)
|
||||
} else if (m.id?.includes('gpt-4')) {
|
||||
maxCompletionTokens = 8192;
|
||||
maxCompletionTokens = 8192; // Standard GPT-4: 8K output limit
|
||||
} else if (m.id?.includes('gpt-3.5-turbo')) {
|
||||
maxCompletionTokens = 4096;
|
||||
maxCompletionTokens = 4096; // GPT-3.5-turbo: 4K output limit
|
||||
}
|
||||
|
||||
return {
|
||||
|
||||
@@ -14,20 +14,20 @@ export default class PerplexityProvider extends BaseProvider {
|
||||
|
||||
staticModels: ModelInfo[] = [
|
||||
{
|
||||
name: 'llama-3.1-sonar-small-128k-online',
|
||||
label: 'Sonar Small Online',
|
||||
name: 'sonar',
|
||||
label: 'Sonar',
|
||||
provider: 'Perplexity',
|
||||
maxTokenAllowed: 8192,
|
||||
},
|
||||
{
|
||||
name: 'llama-3.1-sonar-large-128k-online',
|
||||
label: 'Sonar Large Online',
|
||||
name: 'sonar-pro',
|
||||
label: 'Sonar Pro',
|
||||
provider: 'Perplexity',
|
||||
maxTokenAllowed: 8192,
|
||||
},
|
||||
{
|
||||
name: 'llama-3.1-sonar-huge-128k-online',
|
||||
label: 'Sonar Huge Online',
|
||||
name: 'sonar-reasoning-pro',
|
||||
label: 'Sonar Reasoning Pro',
|
||||
provider: 'Perplexity',
|
||||
maxTokenAllowed: 8192,
|
||||
},
|
||||
|
||||
@@ -13,9 +13,11 @@ export default class XAIProvider extends BaseProvider {
|
||||
};
|
||||
|
||||
staticModels: ModelInfo[] = [
|
||||
{ name: 'grok-3-beta', label: 'xAI Grok 3 Beta', provider: 'xAI', maxTokenAllowed: 8000 },
|
||||
{ name: 'grok-beta', label: 'xAI Grok Beta', provider: 'xAI', maxTokenAllowed: 8000 },
|
||||
{ name: 'grok-2-1212', label: 'xAI Grok2 1212', provider: 'xAI', maxTokenAllowed: 8000 },
|
||||
{ name: 'grok-4', label: 'xAI Grok 4', provider: 'xAI', maxTokenAllowed: 256000 },
|
||||
{ name: 'grok-4-07-09', label: 'xAI Grok 4 (07-09)', provider: 'xAI', maxTokenAllowed: 256000 },
|
||||
{ name: 'grok-3-beta', label: 'xAI Grok 3 Beta', provider: 'xAI', maxTokenAllowed: 131000 },
|
||||
{ name: 'grok-3-mini-beta', label: 'xAI Grok 3 Mini Beta', provider: 'xAI', maxTokenAllowed: 131000 },
|
||||
{ name: 'grok-3-mini-fast-beta', label: 'xAI Grok 3 Mini Fast Beta', provider: 'xAI', maxTokenAllowed: 131000 },
|
||||
];
|
||||
|
||||
getModelInstance(options: {
|
||||
|
||||
@@ -16,6 +16,7 @@ import XAIProvider from './providers/xai';
|
||||
import HyperbolicProvider from './providers/hyperbolic';
|
||||
import AmazonBedrockProvider from './providers/amazon-bedrock';
|
||||
import GithubProvider from './providers/github';
|
||||
import MoonshotProvider from './providers/moonshot';
|
||||
|
||||
export {
|
||||
AnthropicProvider,
|
||||
@@ -26,6 +27,7 @@ export {
|
||||
HuggingFaceProvider,
|
||||
HyperbolicProvider,
|
||||
MistralProvider,
|
||||
MoonshotProvider,
|
||||
OllamaProvider,
|
||||
OpenAIProvider,
|
||||
OpenRouterProvider,
|
||||
|
||||
@@ -41,6 +41,29 @@ function getCompletionTokenLimit(modelDetails: ModelInfo): number {
|
||||
return Math.min(MAX_TOKENS, 16384);
|
||||
}
|
||||
|
||||
function validateTokenLimits(modelDetails: ModelInfo, requestedTokens: number): { valid: boolean; error?: string } {
|
||||
const modelMaxTokens = modelDetails.maxTokenAllowed || 128000;
|
||||
const maxCompletionTokens = getCompletionTokenLimit(modelDetails);
|
||||
|
||||
// Check against model's context window
|
||||
if (requestedTokens > modelMaxTokens) {
|
||||
return {
|
||||
valid: false,
|
||||
error: `Requested tokens (${requestedTokens}) exceed model's context window (${modelMaxTokens}). Please reduce your request size.`,
|
||||
};
|
||||
}
|
||||
|
||||
// Check against completion token limits
|
||||
if (requestedTokens > maxCompletionTokens) {
|
||||
return {
|
||||
valid: false,
|
||||
error: `Requested tokens (${requestedTokens}) exceed model's completion limit (${maxCompletionTokens}). Consider using a model with higher token limits.`,
|
||||
};
|
||||
}
|
||||
|
||||
return { valid: true };
|
||||
}
|
||||
|
||||
async function llmCallAction({ context, request }: ActionFunctionArgs) {
|
||||
const { system, message, model, provider, streamOutput } = await request.json<{
|
||||
system: string;
|
||||
@@ -104,6 +127,23 @@ async function llmCallAction({ context, request }: ActionFunctionArgs) {
|
||||
});
|
||||
}
|
||||
|
||||
// Handle token limit errors with helpful messages
|
||||
if (
|
||||
error instanceof Error &&
|
||||
(error.message?.includes('max_tokens') ||
|
||||
error.message?.includes('token') ||
|
||||
error.message?.includes('exceeds') ||
|
||||
error.message?.includes('maximum'))
|
||||
) {
|
||||
throw new Response(
|
||||
`Token limit error: ${error.message}. Try reducing your request size or using a model with higher token limits.`,
|
||||
{
|
||||
status: 400,
|
||||
statusText: 'Token Limit Exceeded',
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
throw new Response(null, {
|
||||
status: 500,
|
||||
statusText: 'Internal Server Error',
|
||||
@@ -120,6 +160,16 @@ async function llmCallAction({ context, request }: ActionFunctionArgs) {
|
||||
|
||||
const dynamicMaxTokens = modelDetails ? getCompletionTokenLimit(modelDetails) : Math.min(MAX_TOKENS, 16384);
|
||||
|
||||
// Validate token limits before making API request
|
||||
const validation = validateTokenLimits(modelDetails, dynamicMaxTokens);
|
||||
|
||||
if (!validation.valid) {
|
||||
throw new Response(validation.error, {
|
||||
status: 400,
|
||||
statusText: 'Token Limit Exceeded',
|
||||
});
|
||||
}
|
||||
|
||||
const providerInfo = PROVIDER_LIST.find((p) => p.name === provider.name);
|
||||
|
||||
if (!providerInfo) {
|
||||
@@ -215,6 +265,29 @@ async function llmCallAction({ context, request }: ActionFunctionArgs) {
|
||||
);
|
||||
}
|
||||
|
||||
// Handle token limit errors with helpful messages
|
||||
if (
|
||||
error instanceof Error &&
|
||||
(error.message?.includes('max_tokens') ||
|
||||
error.message?.includes('token') ||
|
||||
error.message?.includes('exceeds') ||
|
||||
error.message?.includes('maximum'))
|
||||
) {
|
||||
return new Response(
|
||||
JSON.stringify({
|
||||
...errorResponse,
|
||||
message: `Token limit error: ${error.message}. Try reducing your request size or using a model with higher token limits.`,
|
||||
statusCode: 400,
|
||||
isRetryable: false,
|
||||
}),
|
||||
{
|
||||
status: 400,
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
statusText: 'Token Limit Exceeded',
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
return new Response(JSON.stringify(errorResponse), {
|
||||
status: errorResponse.statusCode,
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
|
||||
@@ -6,6 +6,9 @@ import { optimizeCssModules } from 'vite-plugin-optimize-css-modules';
|
||||
import tsconfigPaths from 'vite-tsconfig-paths';
|
||||
import * as dotenv from 'dotenv';
|
||||
|
||||
// Load environment variables from multiple files
|
||||
dotenv.config({ path: '.env.local' });
|
||||
dotenv.config({ path: '.env' });
|
||||
dotenv.config();
|
||||
|
||||
export default defineConfig((config) => {
|
||||
|
||||
Reference in New Issue
Block a user