PHPackages luminovang/php-ai-models - PHPackages - PHPackages [Skip to content](#main-content)[PHPackages](/)[Directory](/)[Categories](/categories)[Trending](/trending)[Leaderboard](/leaderboard)[Changelog](/changelog)[Analyze](/analyze)[Collections](/collections)[Log in](/login)[Sign up](/register) 1. [Directory](/) 2. / 3. luminovang/php-ai-models ActiveLibrary luminovang/php-ai-models ======================== AI client module for model helper. Integrates OpenAI, Anthropic Claude, and Ollama with a unified interface for chat, vision, embeddings, image generation, speech synthesis, fine-tuning, and more. 1.0.0(1mo ago)00MITPHPPHP ^8 Since Mar 15Pushed 1mo agoCompare [ Source](https://github.com/luminovang/php-ai-models)[ Packagist](https://packagist.org/packages/luminovang/php-ai-models)[ Docs](https://github.com/luminovang/php-ai-models)[ GitHub Sponsors](https://github.com/sponsors/luminovang)[ RSS](/packages/luminovang-php-ai-models/feed)WikiDiscussions main Synced 1mo ago READMEChangelog (1)Dependencies (3)Versions (2)Used By (0) PHP AI Model Helper Class ========================= [](#php-ai-model-helper-class) > **Type:** `const Model: string` *(final-class)* A static catalogue of AI model identifiers. Constants eliminate typos, enable IDE autocompletion, and create a single source across codebase. --- Installation ------------ [](#installation) ``` composer install luminovang/php-ai-models ``` [`Luminova\AI\Model` (enum version)](https://github.com/luminovang/php-ai-models-enum) — PHP string-backed enum class. --- Table of Contents ----------------- [](#table-of-contents) - [Overview](#overview) - [Installation / Import](#installation--import) - [Naming Convention](#naming-convention) - [Constants Reference](#constants-reference) - [OpenAI — GPT-5](#openai--gpt-5-family) - [OpenAI — GPT-4.1](#openai--gpt-41-family) - [OpenAI — GPT-4o](#openai--gpt-4o-family) - [OpenAI — Reasoning (o-series)](#openai--reasoning-o-series) - [OpenAI — Image Generation](#openai--image-generation) - [OpenAI — Text-to-Speech](#openai--text-to-speech) - [OpenAI — Transcription](#openai--transcription) - [OpenAI — Embeddings](#openai--embeddings) - [OpenAI — Moderation](#openai--moderation) - [Claude (Anthropic) — 4.6 Generation](#claude-anthropic--46-generation-current) - [Claude (Anthropic) — 4.5 Generation](#claude-anthropic--45-generation) - [Claude (Anthropic) — 4.1 Generation](#claude-anthropic--41-generation) - [Claude (Anthropic) — 4.0 Generation](#claude-anthropic--40-generation) - [Claude (Anthropic) — 3.7 Generation](#claude-anthropic--37-generation) - [Claude (Anthropic) — 3.5 Generation](#claude-anthropic--35-generation-legacy) - [Ollama — Llama](#ollama--llama-family-meta) - [Ollama — Gemma](#ollama--gemma-family-google) - [Ollama — Mistral / Mixtral](#ollama--mistral--mixtral) - [Ollama — Qwen](#ollama--qwen-family-alibaba) - [Ollama — DeepSeek](#ollama--deepseek-family) - [Ollama — Phi](#ollama--phi-family-microsoft) - [Ollama — Coding Models](#ollama--coding-models) - [Ollama — Vision Models](#ollama--vision-models) - [Ollama — Embedding Models](#ollama--embedding-models) - [Static Methods](#static-methods) - [`client()`](#clientstring-model-string) - [`forClient()`](#forclientstring-client-array) - [`forCapability()`](#forcapabilitystring-capability-array) - [`capabilities()`](#capabilitiesstring-model-array) - [`isVision()`](#isvisionstring-model-bool) - [`isReasoning()`](#isreasoningstring-model-bool) - [`isEmbedding()`](#isembeddingstring-model-bool) - [`exists()`](#existsstring-model-bool) - [`all()`](#all-array) - [Usage Examples](#usage-examples) - [Basic Usage](#basic-usage) - [Validating User Input](#validating-user-input) - [Iterating a Client's Models](#iterating-a-clients-models) - [Filtering by Capability](#filtering-by-capability) - [Guarding Vision Calls](#guarding-vision-calls) - [Routing by Client](#routing-by-client) --- Overview -------- [](#overview) `Model` is a `final` class that cannot be instantiated. All constants and methods are accessed statically: ``` use Luminova\AI\Model; // Anywhere a model string is expected — pass the constant value. $ai->message('Hello!', ['model' => Model::GPT_4_1_MINI]); $ai->embed('Hello world', ['model' => Model::TEXT_EMBEDDING_3_SMALL]); $ai->vision('Describe this.', '/tmp/img.png', ['model' => Model::LLAVA]); ``` --- Import ------ [](#import) ``` use Luminova\AI\Model; ``` No additional dependencies. The class uses `ReflectionClass` (PHP core) only for the `all()` helper method. --- Naming Convention ----------------- [](#naming-convention) RuleExampleHyphens and dots → underscores`gpt-4.1-mini` → `GPT_4_1_MINI`Size tag suffix (`:8b`)`llama3.1:8b` → `LLAMA_3_1_8B`MoE tag (`8x7b`)`mixtral:8x7b` → `MIXTRAL_8X7B`Versioned snapshot`claude-opus-4-5-20251101` → `CLAUDE_OPUS_4_5_SNAP`Clean alias alongside snapshot`claude-opus-4-5` → `CLAUDE_OPUS_4_5`--- Constants Reference ------------------- [](#constants-reference) ### OpenAI — GPT-5 Family [](#openai--gpt-5-family) ConstantAPI ValueNotes`Model::GPT_5``gpt-5`Flagship model. Complex reasoning, multimodal, 256 K context.`Model::GPT_5_MINI``gpt-5-mini`Faster, more affordable GPT-5 variant.`Model::GPT_5_NANO``gpt-5-nano`Smallest GPT-5; optimized for latency and cost.### OpenAI — GPT-4.1 Family [](#openai--gpt-41-family) ConstantAPI ValueNotes`Model::GPT_4_1``gpt-4.1`1 M token context, instruction-following, coding. Supports fine-tuning.`Model::GPT_4_1_MINI``gpt-4.1-mini`**Default chat model** for the Luminova OpenAI client. Supports fine-tuning.`Model::GPT_4_1_NANO``gpt-4.1-nano`Fastest / cheapest GPT-4.1. Supports fine-tuning.### OpenAI — GPT-4o Family [](#openai--gpt-4o-family) ConstantAPI ValueNotes`Model::GPT_4O``gpt-4o`Multimodal (text + image + audio). 128 K context.`Model::GPT_4O_MINI``gpt-4o-mini`Lightweight GPT-4o. 128 K context.`Model::GPT_4O_AUDIO``gpt-4o-audio-preview`Native audio I/O.`Model::GPT_4O_MINI_AUDIO``gpt-4o-mini-audio-preview`Lower-cost audio variant.`Model::GPT_4O_REALTIME``gpt-4o-realtime-preview`Low-latency real-time speech and text.`Model::GPT_4O_MINI_REALTIME``gpt-4o-mini-realtime-preview`Lower-cost realtime variant.`Model::COMPUTER_USE``computer-use-preview`GUI interaction via the Responses API.### OpenAI — Reasoning (o-series) [](#openai--reasoning-o-series) ConstantAPI ValueNotes`Model::O3``o3`Most capable reasoning model. Supports visual reasoning.`Model::O3_PRO``o3-pro`o3 with extra compute for critical tasks.`Model::O3_DEEP_RESEARCH``o3-deep-research`Multi-step web and document research.`Model::O4_MINI``o4-mini`Fast reasoning; top benchmark for math/coding/vision.`Model::O4_MINI_DEEP_RESEARCH``o4-mini-deep-research`Deep research variant of o4 Mini.### OpenAI — Image Generation [](#openai--image-generation) ConstantAPI ValueNotes`Model::GPT_IMAGE_1_5``gpt-image-1.5`Latest image model. High-resolution + inpainting. Requires approval.`Model::GPT_IMAGE_1``gpt-image-1`**Default image model** for the Luminova OpenAI client. Requires approval.`Model::DALL_E_3``dall-e-3`Generally available. Up to 1792×1024 px.`Model::DALL_E_2``dall-e-2`Previous generation; lower cost.### OpenAI — Text-to-Speech [](#openai--text-to-speech) ConstantAPI ValueNotes`Model::GPT_4O_MINI_TTS``gpt-4o-mini-tts`**Default TTS model.** Voices: `alloy`, `echo`, `fable`, `onyx`, `nova`, `shimmer`.`Model::TTS_1``tts-1`Optimized for real-time use.`Model::TTS_1_HD``tts-1-hd`Higher quality, more natural intonation.### OpenAI — Transcription [](#openai--transcription) ConstantAPI ValueNotes`Model::GPT_4O_TRANSCRIBE``gpt-4o-transcribe`Superior accuracy, multilingual.`Model::GPT_4O_MINI_TRANSCRIBE``gpt-4o-mini-transcribe`Faster, lower-cost. Currently recommended.`Model::WHISPER_1``whisper-1`**Default transcription model.** 99+ languages.### OpenAI — Embeddings [](#openai--embeddings) ConstantAPI ValueNotes`Model::TEXT_EMBEDDING_3_LARGE``text-embedding-3-large`Highest accuracy. 3072-dimensional (reducible). Best for RAG.`Model::TEXT_EMBEDDING_3_SMALL``text-embedding-3-small`**Default embedding model.** 1536-dimensional.`Model::TEXT_EMBEDDING_ADA_002``text-embedding-ada-002`Legacy. Prefer `TEXT_EMBEDDING_3_SMALL` for new work.### OpenAI — Moderation [](#openai--moderation) ConstantAPI ValueNotes`Model::OMNI_MODERATION``omni-moderation-latest`Text + image moderation.`Model::TEXT_MODERATION``text-moderation-latest`Text-only moderation.--- ### Claude (Anthropic) — 4.6 Generation *(current)* [](#claude-anthropic--46-generation-current) ConstantAPI ValueNotes`Model::CLAUDE_OPUS_4_6``claude-opus-4-6`Most capable. ~14.5 h task horizon. 1 M context (beta).`Model::CLAUDE_SONNET_4_6``claude-sonnet-4-6`**Default Claude model.** Preferred by developers over previous Opus.### Claude (Anthropic) — 4.5 Generation [](#claude-anthropic--45-generation) ConstantAPI ValueNotes`Model::CLAUDE_OPUS_4_5``claude-opus-4-5`67% price cut, 76% fewer output tokens vs previous Opus.`Model::CLAUDE_OPUS_4_5_SNAP``claude-opus-4-5-20251101`Pinned snapshot — guaranteed reproducibility.`Model::CLAUDE_SONNET_4_5``claude-sonnet-4-5`Industry-leading agent capabilities.`Model::CLAUDE_HAIKU_4_5``claude-haiku-4-5`Fastest, most cost-effective Claude 4.5.`Model::CLAUDE_HAIKU_4_5_SNAP``claude-haiku-4-5-20251001`Pinned snapshot.### Claude (Anthropic) — 4.1 Generation [](#claude-anthropic--41-generation) ConstantAPI ValueNotes`Model::CLAUDE_OPUS_4_1``claude-opus-4-1`Industry leader for coding and long-horizon agentic tasks.`Model::CLAUDE_OPUS_4_1_SNAP``claude-opus-4-1-20250805`Pinned snapshot.`Model::CLAUDE_SONNET_4_1``claude-sonnet-4-1`Production-ready agents at scale.### Claude (Anthropic) — 4.0 Generation [](#claude-anthropic--40-generation) ConstantAPI ValueNotes`Model::CLAUDE_OPUS_4``claude-opus-4-0`First Claude 4-gen Opus. State-of-the-art coding at release.`Model::CLAUDE_SONNET_4``claude-sonnet-4-0`First Claude 4-gen Sonnet. Fast and context-aware.### Claude (Anthropic) — 3.7 Generation [](#claude-anthropic--37-generation) ConstantAPI ValueNotes`Model::CLAUDE_SONNET_3_7``claude-sonnet-3-7`Introduced extended (hybrid) thinking.`Model::CLAUDE_SONNET_3_7_SNAP``claude-3-7-sonnet-20250219`Pinned snapshot.### Claude (Anthropic) — 3.5 Generation *(legacy)* [](#claude-anthropic--35-generation-legacy) ConstantAPI ValueNotes`Model::CLAUDE_SONNET_3_5``claude-3-5-sonnet-20241022`Upgraded Sonnet with computer use (Oct 2024).`Model::CLAUDE_HAIKU_3_5``claude-3-5-haiku-20241022`Lightweight, fast. Ideal for rapid completions.--- ### Ollama — Llama Family (Meta) [](#ollama--llama-family-meta) ConstantAPI ValueNotes`Model::LLAMA_3``llama3`Baseline Llama 3 (8 B). Most widely deployed.`Model::LLAMA_3_1``llama3.1`128 K context support.`Model::LLAMA_3_1_8B``llama3.1:8b`Explicit 8 B tag.`Model::LLAMA_3_1_70B``llama3.1:70b`Large-scale; multi-GPU or high-VRAM.`Model::LLAMA_3_2``llama3.2`Compact (1 B / 3 B). Optimized for edge hardware.`Model::LLAMA_3_2_1B``llama3.2:1b`Ultra-compact for edge and embedded use.`Model::LLAMA_3_2_3B``llama3.2:3b`Small but capable for CLI copilots.`Model::LLAMA_3_3``llama3.3`Latest large Llama (70 B). Excellent long-form chat.`Model::LLAMA_3_3_70B``llama3.3:70b`Explicit 70 B tag.### Ollama — Gemma Family (Google) [](#ollama--gemma-family-google) ConstantAPI ValueNotes`Model::GEMMA_3``gemma3`Current-gen (1 B–27 B). 128 K context; vision-capable (4 B+).`Model::GEMMA_3_4B``gemma3:4b`Vision-capable; fits 8 GB VRAM.`Model::GEMMA_3_12B``gemma3:12b`12–16 GB VRAM sweet spot.`Model::GEMMA_3_27B``gemma3:27b`Flagship Gemma 3 variant.`Model::GEMMA_2``gemma2`Previous gen; proven reliability (2 B, 9 B, 27 B).`Model::GEMMA_2_2B``gemma2:2b`Smallest Gemma 2; edge deployments.`Model::GEMMA_2_9B``gemma2:9b`Good performance within 10 GB VRAM.`Model::GEMMA_2_27B``gemma2:27b`Creative and NLP-focused tasks.### Ollama — Mistral / Mixtral [](#ollama--mistral--mixtral) ConstantAPI ValueNotes`Model::MISTRAL``mistral`Fast 7 B model with strong European language support.`Model::MISTRAL_7B``mistral:7b`Explicit 7 B tag.`Model::MIXTRAL_8X7B``mixtral:8x7b`Mixture-of-Experts; 2 experts active per token.`Model::MIXTRAL_8X22B``mixtral:8x22b`Larger MoE; near-frontier quality for local hardware.### Ollama — Qwen Family (Alibaba) [](#ollama--qwen-family-alibaba) ConstantAPI ValueNotes`Model::QWEN_3``qwen3`Latest generation. Up to 256 K context; strong multilingual.`Model::QWEN_3_4B``qwen3:4b`Compact; fits low-VRAM hardware.`Model::QWEN_3_14B``qwen3:14b`Mid-range; single consumer GPU.`Model::QWEN_3_72B``qwen3:72b`Maximum capability; enterprise-grade.`Model::QWEN_2_5``qwen2.5`Previous gen; 18 T tokens; 128 K context.`Model::QWEN_2_5_7B``qwen2.5:7b``Model::QWEN_2_5_14B``qwen2.5:14b``Model::QWEN_2_5_CODER``qwen2.5-coder`Coding-focused; 87 languages; matches GPT-4o at 32 B.`Model::QWEN_2_5_CODER_7B``qwen2.5-coder:7b`Excellent code quality on limited hardware.`Model::QWEN_2_5_CODER_32B``qwen2.5-coder:32b`Best local coding model at this scale.### Ollama — DeepSeek Family [](#ollama--deepseek-family) ConstantAPI ValueNotes`Model::DEEPSEEK_R1``deepseek-r1`Open reasoning model; matches o3 on key benchmarks.`Model::DEEPSEEK_R1_7B``deepseek-r1:7b`Smallest R1; 8–10 GB VRAM.`Model::DEEPSEEK_R1_14B``deepseek-r1:14b`Best mid-range reasoning for home labs.`Model::DEEPSEEK_R1_32B``deepseek-r1:32b`24 GB+ VRAM setups.`Model::DEEPSEEK_R1_70B``deepseek-r1:70b`Near-frontier; multi-GPU recommended.`Model::DEEPSEEK_CODER``deepseek-coder`87 programming languages; 2 T training tokens.`Model::DEEPSEEK_CODER_33B``deepseek-coder:33b`Top-quality local code generation.### Ollama — Phi Family (Microsoft) [](#ollama--phi-family-microsoft) ConstantAPI ValueNotes`Model::PHI_4``phi4`Latest lightweight model; 14 B, 128 K context.`Model::PHI_4_14B``phi4:14b`Explicit 14 B tag.`Model::PHI_3``phi3`Previous gen (3.8 B Mini / 14 B Medium).`Model::PHI_3_MINI``phi3:mini`3.8 B; suitable for on-device and IoT.### Ollama — Coding Models [](#ollama--coding-models) ConstantAPI ValueNotes`Model::CODE_LLAMA``codellama`Meta's code-focused Llama (7 B–70 B). Fill-in-the-middle support.`Model::CODE_LLAMA_13B``codellama:13b`Good balance of code quality and hardware.`Model::CODE_LLAMA_34B``codellama:34b`High-quality generation for 24 GB VRAM.### Ollama — Vision Models [](#ollama--vision-models) ConstantAPI ValueNotes`Model::LLAVA``llava`**Default vision model** for the Luminova Ollama client.`Model::LLAVA_13B``llava:13b`Stronger vision understanding.`Model::LLAVA_34B``llava:34b`Highest-quality LLaVA; 24+ GB VRAM.`Model::LLAMA_3_2_VISION``llama3.2-vision`Better structured-output than LLaVA.`Model::MOONDREAM``moondream`Tiny (1.8 B); edge devices; fast captioning.`Model::BAKLLAVA``bakllava`Mistral-7B base with LLaVA multimodal fine-tuning.### Ollama — Embedding Models [](#ollama--embedding-models) ConstantAPI ValueNotes`Model::NOMIC_EMBED_TEXT``nomic-embed-text`**Default embedding model.** 8 K context; strong MTEB scores.`Model::MXBAI_EMBED_LARGE``mxbai-embed-large`1024-dimensional; competitive with OpenAI's large model.`Model::ALL_MINILM``all-minilm`384-dimensional; very fast similarity search.--- Static Methods -------------- [](#static-methods) ### `client(string $model): string|null` [](#clientstring-model-stringnull) Return the client short-name for a given model string. Returns `null` for unknown models. ``` Model::client(Model::GPT_4_1_MINI); // 'openai' Model::client(Model::CLAUDE_SONNET_4_6); // 'anthropic' Model::client(Model::LLAVA); // 'ollama' Model::client('my-custom-model'); // null ``` --- ### `forClient(string $client): array` [](#forclientstring-client-array) Return all `['CONST_NAME' => 'model-id']` pairs that belong to a specific client. ``` $openaiModels = Model::forClient('openai'); $anthropicModels = Model::forClient('anthropic'); $ollamaModels = Model::forClient('ollama'); foreach ($ollamaModels as $name => $id) { echo "{$name} => {$id}" . PHP_EOL; } // LLAMA_3 => llama3 // LLAMA_3_1 => llama3.1 // ... ``` --- ### `forCapability(string $capability): array` [](#forcapabilitystring-capability-array) Return all `['CONST_NAME' => 'model-id']` pairs that support a given capability tag. **Available tags:** `chat`, `vision`, `image`, `embedding`, `speech`, `transcription`, `reasoning`, `coding`, `fine-tuning`, `moderation`. ``` $visionModels = Model::forCapability('vision'); $embeddingModels = Model::forCapability('embedding'); $reasoningModels = Model::forCapability('reasoning'); ``` --- ### `capabilities(string $model): array` [](#capabilitiesstring-model-array) Return all capability tags for a given model string. ``` Model::capabilities(Model::O3); // ['chat', 'vision', 'reasoning', 'coding'] Model::capabilities(Model::NOMIC_EMBED_TEXT); // ['embedding'] Model::capabilities(Model::DALL_E_3); // ['image'] ``` --- ### `isVision(string $model): bool` [](#isvisionstring-model-bool) ``` Model::isVision(Model::GPT_4_1); // true Model::isVision(Model::LLAVA); // true Model::isVision(Model::NOMIC_EMBED_TEXT); // false ``` --- ### `isReasoning(string $model): bool` [](#isreasoningstring-model-bool) ``` Model::isReasoning(Model::O3); // true Model::isReasoning(Model::DEEPSEEK_R1); // true Model::isReasoning(Model::GPT_4_1_MINI); // false ``` --- ### `isEmbedding(string $model): bool` [](#isembeddingstring-model-bool) ``` Model::isEmbedding(Model::TEXT_EMBEDDING_3_SMALL); // true Model::isEmbedding(Model::NOMIC_EMBED_TEXT); // true Model::isEmbedding(Model::GPT_4_1); // false ``` --- ### `exists(string $model): bool` [](#existsstring-model-bool) Check whether a model string is catalogued. Useful for validating user-supplied input before sending it to a client API. ``` Model::exists(Model::GPT_4_1_MINI); // true Model::exists('my-custom-model'); // false ``` --- ### `all(): array` [](#all-array) Return every public constant as a `['CONST_NAME' => 'model-id']` map using reflection. Private constants (`PROVIDER_MAP`, `CAPABILITY_MAP`) are automatically excluded. ``` $all = Model::all(); // [ // 'GPT_5' => 'gpt-5', // 'GPT_5_MINI' => 'gpt-5-mini', // 'GPT_4_1_MINI' => 'gpt-4.1-mini', // ... // ] echo count(Model::all()); // 103 ``` --- Usage Examples -------------- [](#usage-examples) ### Basic Usage [](#basic-usage) ``` use Luminova\AI\Model; use Luminova\AI\AI; // Chat $reply = AI::Openai($key)->message('Hello!', [ 'model' => Model::GPT_4_1_MINI, ]); // Chat with Claude $reply = AI::Anthropic($key)->message('Summarise this.', [ 'model' => Model::CLAUDE_SONNET_4_6, ]); // Local inference with Ollama $reply = AI::Ollama()->message('Explain recursion.', [ 'model' => Model::LLAMA_3_2, ]); // Embeddings $vector = AI::Openai($key)->embed('Hello world', [ 'model' => Model::TEXT_EMBEDDING_3_SMALL, ]); // Vision $output = AI::Openai($key)->vision('What is in this image?', '/tmp/photo.jpg', [ 'model' => Model::GPT_4_1, ]); ``` --- ### Validating User Input [](#validating-user-input) ``` $userModel = $request->get('model', Model::GPT_4_1_MINI); if (!Model::exists($userModel)) { throw new InvalidArgumentException("Unknown model: {$userModel}"); } $reply = $ai->message('Hello!', ['model' => $userModel]); ``` --- ### Iterating a Client's Models [](#iterating-a-clients-models) ``` // Build a select list for a UI $options = []; foreach (Model::forClient('openai') as $name => $id) { $options[$id] = str_replace('_', ' ', ucfirst(strtolower($name))); } // ['gpt-4.1-mini' => 'Gpt 4 1 mini', ...] ``` --- ### Filtering by Capability [](#filtering-by-capability) ``` // Only offer vision-capable models in the UI $visionModels = Model::forCapability('vision'); // Only offer embedding models for the vector store config $embeddingModels = Model::forCapability('embedding'); // Show reasoning models separately $reasoningModels = Model::forCapability('reasoning'); ``` --- ### Guarding Vision Calls [](#guarding-vision-calls) ``` function analyzeImage(string $prompt, string $imagePath, string $model): array { if (!Model::isVision($model)) { throw new RuntimeException( "Model '{$model}' does not support vision. " . "Try: " . Model::GPT_4_1 . " or " . Model::LLAVA ); } return AI::getInstance()->vision($prompt, $imagePath, ['model' => $model]); } analyzeImage('Describe this chart.', '/tmp/q4.png', Model::GPT_4_1); // OK analyzeImage('Describe this chart.', '/tmp/q4.png', Model::WHISPER_1); // throws ``` --- ### Routing by Client [](#routing-by-client) ``` use Luminova\AI\AI; use Luminova\AI\Model; function chat(string $prompt, string $model): array { $client = Model::client($model); return match ($client) { 'openai' => AI::Openai($_ENV['OPENAI_KEY'])->message($prompt, ['model' => $model]), 'anthropic' => AI::Anthropic($_ENV['ANTHROPIC_KEY'])->message($prompt, ['model' => $model]), 'ollama' => AI::Ollama()->message($prompt, ['model' => $model]), default => throw new RuntimeException("Unsupported client: {$client}"), }; } chat('Tell me a joke.', Model::GPT_4_1_MINI); // routed to OpenAI chat('Tell me a joke.', Model::CLAUDE_SONNET_4_6); // routed to Anthropic chat('Tell me a joke.', Model::LLAMA_3_2); // routed to Ollama ``` --- See Also -------- [](#see-also) - [`Luminova\AI\Model` (enum version)](https://github.com/luminovang/php-ai-models-enum) — PHP 8.1+ string-backed enum with instance methods and type-safe signatures. ### Health Score 35 — LowBetter than 79% of packages Maintenance95 Actively maintained with recent releases Popularity0 Limited adoption so far Community6 Small or concentrated contributor base Maturity33 Early-stage or recently created project Bus Factor1 Top contributor holds 100% of commits — single point of failure How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window. **Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores. **Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement. **Maturity (30%)** — Project age, version count, PHP version support, and release stability. ### Release Activity Cadence Unknown Total 1 Last Release 55d ago ### Community Maintainers ![](https://www.gravatar.com/avatar/ce34af529a4ed50696211a2b4d330fbadd2d1738bc5d010523eb4a85cf342b17?d=identicon)[peterujah](/maintainers/peterujah) --- Top Contributors [![peterujah](https://avatars.githubusercontent.com/u/16369609?v=4)](https://github.com/peterujah "peterujah (11 commits)") --- Tags aiopenaimachine learningvisionclaudellmanthropicgptollamaspeechembeddingsphp aifine-tuningluminovaai-model ### Code Quality TestsPHPUnit Static AnalysisPHPStan Code StylePHP CS Fixer Type Coverage Yes ### Embed Badge ![Health badge](/badges/luminovang-php-ai-models/health.svg) ``` [![Health](https://phpackages.com/badges/luminovang-php-ai-models/health.svg)](https://phpackages.com/packages/luminovang-php-ai-models) ``` ### Alternatives [cognesy/instructor-php The complete AI toolkit for PHP: unified LLM API, structured outputs, agents, and coding agent control 310107.9k1](/packages/cognesy-instructor-php)[vizra/vizra-adk Vizra Agent Development Kit - A comprehensive Laravel package for building intelligent AI agents. 29026.1k](/packages/vizra-vizra-adk)[helgesverre/toon Token-Oriented Object Notation - A compact data format for reducing token consumption when sending structured data to LLMs 11841.4k9](/packages/helgesverre-toon)[sbsaga/toon 🧠 TOON for Laravel — a compact, human-readable, and token-efficient data format for AI prompts & LLM contexts. 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