feat: add alibaba coding plan as provider (#32)
* add alibaba coding plan as provider * add alibaba coding plan as provider
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@@ -11,8 +11,8 @@ This repository is the **single source of truth** for all installable content de
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| [Hands](#hands) | 14 | User-facing "apps" — agent + tools + settings + dashboard |
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| [Hands](#hands) | 14 | User-facing "apps" — agent + tools + settings + dashboard |
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| [Agents](#agents) | 32 | Autonomous agent definitions with model config and tools |
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| [Agents](#agents) | 32 | Autonomous agent definitions with model config and tools |
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| [Integrations](#integrations) | 25 | MCP server connections (GitHub, Slack, DBs, etc.) |
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| [Integrations](#integrations) | 25 | MCP server connections (GitHub, Slack, DBs, etc.) |
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| [Providers](#providers) | 48 | LLM provider & model metadata with pricing |
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| [Providers](#providers) | 49 | LLM provider & model metadata with pricing |
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| [Models](#providers) | 223 | Individual model definitions across all providers |
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| [Models](#providers) | 339 | Individual model definitions across all providers |
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| [Aliases](#aliases) | 70 | Short names mapped to canonical model IDs |
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| [Aliases](#aliases) | 70 | Short names mapped to canonical model IDs |
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| [Plugins](#plugins) | 10 | Memory, guardrails, and conversation plugins |
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| [Plugins](#plugins) | 10 | Memory, guardrails, and conversation plugins |
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| [Skills](#skills) | 2 | Reusable prompt templates and Python scripts |
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| [Skills](#skills) | 2 | Reusable prompt templates and Python scripts |
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@@ -44,7 +44,7 @@ librefang-registry/
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├── providers/ # LLM provider & model metadata
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├── providers/ # LLM provider & model metadata
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│ ├── anthropic.toml
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│ ├── anthropic.toml
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│ ├── openai.toml
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│ ├── openai.toml
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│ └── ... (48 providers, 223 models)
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│ └── ... (49 providers, 339 models)
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├── plugins/ # Memory, guardrails, and utility plugins
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├── plugins/ # Memory, guardrails, and utility plugins
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│ ├── episodic-memory/
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│ ├── episodic-memory/
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│ ├── guardrails/
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│ ├── guardrails/
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@@ -195,9 +195,9 @@ is_secret = true
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Provider files define LLM providers and their models with pricing, context windows, and capability flags. See [schema.toml](schema.toml) for the full field reference.
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Provider files define LLM providers and their models with pricing, context windows, and capability flags. See [schema.toml](schema.toml) for the full field reference.
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**48 providers** including: Anthropic, OpenAI, Google Gemini, DeepSeek, Groq, Mistral, Cohere, xAI, Together, Fireworks, Ollama (local), LM Studio (local), vLLM (self-hosted), and many more.
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**49 providers** including: Anthropic, OpenAI, Google Gemini, DeepSeek, Groq, Mistral, Cohere, xAI, Together, Fireworks, Ollama (local), LM Studio (local), vLLM (self-hosted), Alibaba Coding Plan, and many more.
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**223 models** with metadata for each: pricing (input/output per token), context window size, capability flags (vision, function calling, streaming), and tier classification.
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**339 models** with metadata for each: pricing (input/output per token), context window size, capability flags (vision, function calling, streaming), and tier classification.
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### Aliases
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### Aliases
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@@ -0,0 +1,115 @@
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# Alibaba Coding Plan — https://www.alibabacloud.com/help/en/model-studio/coding-plan
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# Models: 8 (Pro plan: $50/month with quota-based access)
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# Note: Monthly subscription for AI coding tools. Uses plan-specific API key (sk-sp-xxxxx)
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# and dedicated base URL (https://coding-intl.dashscope.aliyuncs.com/v1)
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[provider]
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id = "alibaba-coding-plan"
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display_name = "Alibaba Coding Plan (Intl)"
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api_key_env = "ALIBABA_CODING_PLAN_API_KEY"
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base_url = "https://coding-intl.dashscope.aliyuncs.com/v1"
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key_required = true
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[[models]]
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id = "alibaba-coding-plan/qwen3.5-plus"
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display_name = "Qwen 3.5 Plus"
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tier = "smart"
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context_window = 1000000
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max_output_tokens = 65536
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = true
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supports_streaming = true
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aliases = []
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[[models]]
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id = "alibaba-coding-plan/qwen3-max-2026-01-23"
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display_name = "Qwen 3 Max (2026-01-23)"
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tier = "frontier"
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context_window = 262144
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max_output_tokens = 65536
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = false
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supports_streaming = true
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aliases = []
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[[models]]
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id = "alibaba-coding-plan/qwen3-coder-next"
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display_name = "Qwen 3 Coder Next"
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tier = "frontier"
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context_window = 262144
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max_output_tokens = 65536
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = false
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supports_streaming = true
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aliases = []
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[[models]]
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id = "alibaba-coding-plan/qwen3-coder-plus"
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display_name = "Qwen 3 Coder Plus"
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tier = "smart"
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context_window = 1000000
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max_output_tokens = 65536
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = false
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supports_streaming = true
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aliases = []
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[[models]]
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id = "alibaba-coding-plan/MiniMax-M2.5"
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display_name = "MiniMax M2.5"
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tier = "balanced"
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context_window = 196608
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max_output_tokens = 32768
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = false
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supports_streaming = true
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aliases = []
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[[models]]
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id = "alibaba-coding-plan/glm-5"
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display_name = "GLM 5"
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tier = "frontier"
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context_window = 202752
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max_output_tokens = 16384
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = false
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supports_streaming = true
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aliases = []
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[[models]]
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id = "alibaba-coding-plan/glm-4.7"
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display_name = "GLM 4.7"
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tier = "smart"
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context_window = 202752
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max_output_tokens = 16384
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = false
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supports_streaming = true
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aliases = []
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[[models]]
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id = "alibaba-coding-plan/kimi-k2.5"
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display_name = "Kimi K2.5"
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tier = "smart"
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context_window = 262144
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max_output_tokens = 32768
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input_cost_per_m = 0.0
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output_cost_per_m = 0.0
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supports_tools = true
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supports_vision = true
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supports_streaming = true
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aliases = []
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