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https://github.com/Significant-Gravitas/AutoGPT.git
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Add models metadata
This commit is contained in:
Krzysztof Czerwinski
@@ -79,6 +79,10 @@ class ModelMetadata(NamedTuple):
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provider: str
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context_window: int
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max_output_tokens: int | None
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display_name: str
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provider_name: str
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creator_name: str
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price_tier: Literal[1, 2, 3]
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class LlmModelMeta(EnumMeta):
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@@ -174,21 +178,18 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
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@classmethod
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def __get_pydantic_json_schema__(cls, schema, handler):
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json_schema = handler(schema)
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#TODO this may need to be updated once we have model registry
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llm_model_metadata = {}
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for model in cls:
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model_name = model.value
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provider = model.metadata.provider
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if "/" in model_name:
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creator, title = model_name.split("/", 1)
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else:
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creator = provider
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title = model_name
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metadata = model.metadata
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llm_model_metadata[model_name] = {
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"creator": creator,
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"title": title,
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"provider": provider,
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"creator": metadata.creator_name,
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"creator_name": metadata.creator_name,
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"title": metadata.display_name,
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"provider": metadata.provider,
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"provider_name": metadata.provider_name,
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"name": model_name,
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"price_tier": metadata.price_tier,
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}
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json_schema["llm_model"] = True
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json_schema["llm_model_metadata"] = llm_model_metadata
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@@ -213,119 +214,89 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
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MODEL_METADATA = {
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# https://platform.openai.com/docs/models
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LlmModel.O3: ModelMetadata("openai", 200000, 100000),
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LlmModel.O3_MINI: ModelMetadata("openai", 200000, 100000), # o3-mini-2025-01-31
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LlmModel.O1: ModelMetadata("openai", 200000, 100000), # o1-2024-12-17
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LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536), # o1-mini-2024-09-12
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LlmModel.O3: ModelMetadata("openai", 200000, 100000, "O3", "OpenAI", "OpenAI", 2),
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LlmModel.O3_MINI: ModelMetadata("openai", 200000, 100000, "O3 Mini", "OpenAI", "OpenAI", 1), # o3-mini-2025-01-31
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LlmModel.O1: ModelMetadata("openai", 200000, 100000, "O1", "OpenAI", "OpenAI", 3), # o1-2024-12-17
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LlmModel.O1_MINI: ModelMetadata("openai", 128000, 65536, "O1 Mini", "OpenAI", "OpenAI", 2), # o1-mini-2024-09-12
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# GPT-5 models
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LlmModel.GPT5_2: ModelMetadata("openai", 400000, 128000),
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LlmModel.GPT5_1: ModelMetadata("openai", 400000, 128000),
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LlmModel.GPT5: ModelMetadata("openai", 400000, 128000),
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LlmModel.GPT5_MINI: ModelMetadata("openai", 400000, 128000),
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LlmModel.GPT5_NANO: ModelMetadata("openai", 400000, 128000),
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LlmModel.GPT5_CHAT: ModelMetadata("openai", 400000, 16384),
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LlmModel.GPT41: ModelMetadata("openai", 1047576, 32768),
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LlmModel.GPT41_MINI: ModelMetadata("openai", 1047576, 32768),
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LlmModel.GPT4O_MINI: ModelMetadata(
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"openai", 128000, 16384
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), # gpt-4o-mini-2024-07-18
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LlmModel.GPT4O: ModelMetadata("openai", 128000, 16384), # gpt-4o-2024-08-06
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LlmModel.GPT4_TURBO: ModelMetadata(
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"openai", 128000, 4096
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), # gpt-4-turbo-2024-04-09
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LlmModel.GPT3_5_TURBO: ModelMetadata("openai", 16385, 4096), # gpt-3.5-turbo-0125
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LlmModel.GPT5_2: ModelMetadata("openai", 400000, 128000, "GPT-5.2", "OpenAI", "OpenAI", 3),
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LlmModel.GPT5_1: ModelMetadata("openai", 400000, 128000, "GPT-5.1", "OpenAI", "OpenAI", 2),
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LlmModel.GPT5: ModelMetadata("openai", 400000, 128000, "GPT-5", "OpenAI", "OpenAI", 1),
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LlmModel.GPT5_MINI: ModelMetadata("openai", 400000, 128000, "GPT-5 Mini", "OpenAI", "OpenAI", 1),
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LlmModel.GPT5_NANO: ModelMetadata("openai", 400000, 128000, "GPT-5 Nano", "OpenAI", "OpenAI", 1),
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LlmModel.GPT5_CHAT: ModelMetadata("openai", 400000, 16384, "GPT-5 Chat Latest", "OpenAI", "OpenAI", 2),
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LlmModel.GPT41: ModelMetadata("openai", 1047576, 32768, "GPT-4.1", "OpenAI", "OpenAI", 1),
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LlmModel.GPT41_MINI: ModelMetadata("openai", 1047576, 32768, "GPT-4.1 Mini", "OpenAI", "OpenAI", 1),
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LlmModel.GPT4O_MINI: ModelMetadata("openai", 128000, 16384, "GPT-4o Mini", "OpenAI", "OpenAI", 1), # gpt-4o-mini-2024-07-18
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LlmModel.GPT4O: ModelMetadata("openai", 128000, 16384, "GPT-4o", "OpenAI", "OpenAI", 2), # gpt-4o-2024-08-06
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LlmModel.GPT4_TURBO: ModelMetadata("openai", 128000, 4096, "GPT-4 Turbo", "OpenAI", "OpenAI", 3), # gpt-4-turbo-2024-04-09
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LlmModel.GPT3_5_TURBO: ModelMetadata("openai", 16385, 4096, "GPT-3.5 Turbo", "OpenAI", "OpenAI", 1), # gpt-3.5-turbo-0125
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# https://docs.anthropic.com/en/docs/about-claude/models
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LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
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"anthropic", 200000, 32000
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), # claude-opus-4-1-20250805
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LlmModel.CLAUDE_4_OPUS: ModelMetadata(
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"anthropic", 200000, 32000
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), # claude-4-opus-20250514
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LlmModel.CLAUDE_4_SONNET: ModelMetadata(
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"anthropic", 200000, 64000
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), # claude-4-sonnet-20250514
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LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
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"anthropic", 200000, 64000
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), # claude-opus-4-5-20251101
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LlmModel.CLAUDE_4_5_SONNET: ModelMetadata(
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"anthropic", 200000, 64000
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), # claude-sonnet-4-5-20250929
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LlmModel.CLAUDE_4_5_HAIKU: ModelMetadata(
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"anthropic", 200000, 64000
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), # claude-haiku-4-5-20251001
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LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
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"anthropic", 200000, 64000
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), # claude-3-7-sonnet-20250219
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LlmModel.CLAUDE_3_HAIKU: ModelMetadata(
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"anthropic", 200000, 4096
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), # claude-3-haiku-20240307
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LlmModel.CLAUDE_4_1_OPUS: ModelMetadata("anthropic", 200000, 32000, "Claude Opus 4.1", "Anthropic", "Anthropic", 3), # claude-opus-4-1-20250805
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LlmModel.CLAUDE_4_OPUS: ModelMetadata("anthropic", 200000, 32000, "Claude Opus 4", "Anthropic", "Anthropic", 3), # claude-4-opus-20250514
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LlmModel.CLAUDE_4_SONNET: ModelMetadata("anthropic", 200000, 64000, "Claude Sonnet 4", "Anthropic", "Anthropic", 2), # claude-4-sonnet-20250514
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LlmModel.CLAUDE_4_5_OPUS: ModelMetadata("anthropic", 200000, 64000, "Claude Opus 4.5", "Anthropic", "Anthropic", 3), # claude-opus-4-5-20251101
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LlmModel.CLAUDE_4_5_SONNET: ModelMetadata("anthropic", 200000, 64000, "Claude Sonnet 4.5", "Anthropic", "Anthropic", 3), # claude-sonnet-4-5-20250929
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LlmModel.CLAUDE_4_5_HAIKU: ModelMetadata("anthropic", 200000, 64000, "Claude Haiku 4.5", "Anthropic", "Anthropic", 2), # claude-haiku-4-5-20251001
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LlmModel.CLAUDE_3_7_SONNET: ModelMetadata("anthropic", 200000, 64000, "Claude 3.7 Sonnet", "Anthropic", "Anthropic", 2), # claude-3-7-sonnet-20250219
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LlmModel.CLAUDE_3_HAIKU: ModelMetadata("anthropic", 200000, 4096, "Claude 3 Haiku", "Anthropic", "Anthropic", 1), # claude-3-haiku-20240307
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# https://docs.aimlapi.com/api-overview/model-database/text-models
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LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata("aiml_api", 32000, 8000),
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LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata("aiml_api", 128000, 40000),
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LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata("aiml_api", 128000, None),
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LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata("aiml_api", 131000, 2000),
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LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata("aiml_api", 128000, None),
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LlmModel.AIML_API_QWEN2_5_72B: ModelMetadata("aiml_api", 32000, 8000, "Qwen 2.5 72B Instruct Turbo", "AI/ML", "Qwen", 1),
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LlmModel.AIML_API_LLAMA3_1_70B: ModelMetadata("aiml_api", 128000, 40000, "Llama 3.1 Nemotron 70B Instruct", "AI/ML", "Nvidia", 1),
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LlmModel.AIML_API_LLAMA3_3_70B: ModelMetadata("aiml_api", 128000, None, "Llama 3.3 70B Instruct Turbo", "AI/ML", "Meta", 1),
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LlmModel.AIML_API_META_LLAMA_3_1_70B: ModelMetadata("aiml_api", 131000, 2000, "Llama 3.1 70B Instruct Turbo", "AI/ML", "Meta", 1),
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LlmModel.AIML_API_LLAMA_3_2_3B: ModelMetadata("aiml_api", 128000, None, "Llama 3.2 3B Instruct Turbo", "AI/ML", "Meta", 1),
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# https://console.groq.com/docs/models
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LlmModel.LLAMA3_3_70B: ModelMetadata("groq", 128000, 32768),
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LlmModel.LLAMA3_1_8B: ModelMetadata("groq", 128000, 8192),
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LlmModel.LLAMA3_3_70B: ModelMetadata("groq", 128000, 32768, "Llama 3.3 70B Versatile", "Groq", "Groq", 1),
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LlmModel.LLAMA3_1_8B: ModelMetadata("groq", 128000, 8192, "Llama 3.1 8B Instant", "Groq", "Groq", 1),
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# https://ollama.com/library
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LlmModel.OLLAMA_LLAMA3_3: ModelMetadata("ollama", 8192, None),
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LlmModel.OLLAMA_LLAMA3_2: ModelMetadata("ollama", 8192, None),
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LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata("ollama", 8192, None),
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LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata("ollama", 8192, None),
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LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768, None),
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LlmModel.OLLAMA_LLAMA3_3: ModelMetadata("ollama", 8192, None, "Llama 3.3", "Ollama", "Meta", 1),
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LlmModel.OLLAMA_LLAMA3_2: ModelMetadata("ollama", 8192, None, "Llama 3.2", "Ollama", "Meta", 1),
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LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata("ollama", 8192, None, "Llama 3", "Ollama", "Meta", 1),
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LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata("ollama", 8192, None, "Llama 3.1 405B", "Ollama", "Meta", 1),
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LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768, None, "Dolphin Mistral Latest", "Ollama", "Mistral", 1),
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# https://openrouter.ai/models
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LlmModel.GEMINI_2_5_PRO: ModelMetadata("open_router", 1050000, 8192),
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LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata("open_router", 1048576, 65535),
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LlmModel.GEMINI_2_5_FLASH: ModelMetadata("open_router", 1048576, 65535),
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LlmModel.GEMINI_2_0_FLASH: ModelMetadata("open_router", 1048576, 8192),
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LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: ModelMetadata(
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"open_router", 1048576, 65535
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),
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LlmModel.GEMINI_2_0_FLASH_LITE: ModelMetadata("open_router", 1048576, 8192),
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LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 128000, 4096),
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LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 128000, 4096),
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LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata("open_router", 128000, 4096),
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LlmModel.DEEPSEEK_CHAT: ModelMetadata("open_router", 64000, 2048),
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LlmModel.DEEPSEEK_R1_0528: ModelMetadata("open_router", 163840, 163840),
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LlmModel.PERPLEXITY_SONAR: ModelMetadata("open_router", 127000, 8000),
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LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata("open_router", 200000, 8000),
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LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: ModelMetadata(
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"open_router",
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128000,
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16000,
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),
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LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: ModelMetadata(
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"open_router", 131000, 4096
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),
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LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: ModelMetadata(
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"open_router", 12288, 12288
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),
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LlmModel.OPENAI_GPT_OSS_120B: ModelMetadata("open_router", 131072, 131072),
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LlmModel.OPENAI_GPT_OSS_20B: ModelMetadata("open_router", 131072, 32768),
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LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata("open_router", 300000, 5120),
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LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata("open_router", 128000, 5120),
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LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 300000, 5120),
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LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 65536, 4096),
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LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4096, 4096),
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LlmModel.META_LLAMA_4_SCOUT: ModelMetadata("open_router", 131072, 131072),
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LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata("open_router", 1048576, 1000000),
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LlmModel.GROK_4: ModelMetadata("open_router", 256000, 256000),
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LlmModel.GROK_4_FAST: ModelMetadata("open_router", 2000000, 30000),
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LlmModel.GROK_4_1_FAST: ModelMetadata("open_router", 2000000, 30000),
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LlmModel.GROK_CODE_FAST_1: ModelMetadata("open_router", 256000, 10000),
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LlmModel.KIMI_K2: ModelMetadata("open_router", 131000, 131000),
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LlmModel.QWEN3_235B_A22B_THINKING: ModelMetadata("open_router", 262144, 262144),
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LlmModel.QWEN3_CODER: ModelMetadata("open_router", 262144, 262144),
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LlmModel.GEMINI_2_5_PRO: ModelMetadata("open_router", 1050000, 8192, "Gemini 2.5 Pro Preview 03.25", "OpenRouter", "Google", 2),
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LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata("open_router", 1048576, 65535, "Gemini 3 Pro Preview", "OpenRouter", "Google", 2),
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LlmModel.GEMINI_2_5_FLASH: ModelMetadata("open_router", 1048576, 65535, "Gemini 2.5 Flash", "OpenRouter", "Google", 1),
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LlmModel.GEMINI_2_0_FLASH: ModelMetadata("open_router", 1048576, 8192, "Gemini 2.0 Flash 001", "OpenRouter", "Google", 1),
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LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: ModelMetadata("open_router", 1048576, 65535, "Gemini 2.5 Flash Lite Preview 06.17", "OpenRouter", "Google", 1),
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LlmModel.GEMINI_2_0_FLASH_LITE: ModelMetadata("open_router", 1048576, 8192, "Gemini 2.0 Flash Lite 001", "OpenRouter", "Google", 1),
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LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 128000, 4096, "Mistral Nemo", "OpenRouter", "Mistralai", 1),
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LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 128000, 4096, "Command R 08.2024", "OpenRouter", "Cohere", 1),
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LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata("open_router", 128000, 4096, "Command R Plus 08.2024", "OpenRouter", "Cohere", 2),
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LlmModel.DEEPSEEK_CHAT: ModelMetadata("open_router", 64000, 2048, "DeepSeek Chat", "OpenRouter", "Deepseek", 1),
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LlmModel.DEEPSEEK_R1_0528: ModelMetadata("open_router", 163840, 163840, "DeepSeek R1 0528", "OpenRouter", "Deepseek", 1),
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LlmModel.PERPLEXITY_SONAR: ModelMetadata("open_router", 127000, 8000, "Sonar", "OpenRouter", "Perplexity", 1),
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LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata("open_router", 200000, 8000, "Sonar Pro", "OpenRouter", "Perplexity", 2),
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LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: ModelMetadata("open_router", 128000, 16000, "Sonar Deep Research", "OpenRouter", "Perplexity", 3),
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LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: ModelMetadata("open_router", 131000, 4096, "Hermes 3 Llama 3.1 405B", "OpenRouter", "Nous Research", 1),
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LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: ModelMetadata("open_router", 12288, 12288, "Hermes 3 Llama 3.1 70B", "OpenRouter", "Nous Research", 1),
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LlmModel.OPENAI_GPT_OSS_120B: ModelMetadata("open_router", 131072, 131072, "GPT-OSS 120B", "OpenRouter", "OpenAI", 1),
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LlmModel.OPENAI_GPT_OSS_20B: ModelMetadata("open_router", 131072, 32768, "GPT-OSS 20B", "OpenRouter", "OpenAI", 1),
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LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata("open_router", 300000, 5120, "Nova Lite V1", "OpenRouter", "Amazon", 1),
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LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata("open_router", 128000, 5120, "Nova Micro V1", "OpenRouter", "Amazon", 1),
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LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 300000, 5120, "Nova Pro V1", "OpenRouter", "Amazon", 1),
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LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 65536, 4096, "WizardLM 2 8x22B", "OpenRouter", "Microsoft", 1),
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LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4096, 4096, "MythoMax L2 13B", "OpenRouter", "Gryphe", 1),
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LlmModel.META_LLAMA_4_SCOUT: ModelMetadata("open_router", 131072, 131072, "Llama 4 Scout", "OpenRouter", "Meta", 1),
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LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata("open_router", 1048576, 1000000, "Llama 4 Maverick", "OpenRouter", "Meta", 1),
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LlmModel.GROK_4: ModelMetadata("open_router", 256000, 256000, "Grok 4", "OpenRouter", "xAI", 3),
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LlmModel.GROK_4_FAST: ModelMetadata("open_router", 2000000, 30000, "Grok 4 Fast", "OpenRouter", "xAI", 1),
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LlmModel.GROK_4_1_FAST: ModelMetadata("open_router", 2000000, 30000, "Grok 4.1 Fast", "OpenRouter", "xAI", 1),
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LlmModel.GROK_CODE_FAST_1: ModelMetadata("open_router", 256000, 10000, "Grok Code Fast 1", "OpenRouter", "xAI", 1),
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LlmModel.KIMI_K2: ModelMetadata("open_router", 131000, 131000, "Kimi K2", "OpenRouter", "Moonshotai", 1),
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LlmModel.QWEN3_235B_A22B_THINKING: ModelMetadata("open_router", 262144, 262144, "Qwen 3 235B A22B Thinking 2507", "OpenRouter", "Qwen", 1),
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LlmModel.QWEN3_CODER: ModelMetadata("open_router", 262144, 262144, "Qwen 3 Coder", "OpenRouter", "Qwen", 3),
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# Llama API models
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LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata("llama_api", 128000, 4028),
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LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
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LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
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LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
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LlmModel.LLAMA_API_LLAMA_4_SCOUT: ModelMetadata("llama_api", 128000, 4028, "Llama 4 Scout 17B 16E Instruct FP8", "Llama API", "Meta", 1),
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LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028, "Llama 4 Maverick 17B 128E Instruct FP8", "Llama API", "Meta", 1),
|
||||
LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028, "Llama 3.3 8B Instruct", "Llama API", "Meta", 1),
|
||||
LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028, "Llama 3.3 70B Instruct", "Llama API", "Meta", 1),
|
||||
# v0 by Vercel models
|
||||
LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000),
|
||||
LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000),
|
||||
LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
|
||||
LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000, "v0 1.5 MD", "V0", "V0", 1),
|
||||
LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000, "v0 1.5 LG", "V0", "V0", 1),
|
||||
LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000, "v0 1.0 MD", "V0", "V0", 1),
|
||||
}
|
||||
|
||||
DEFAULT_LLM_MODEL = LlmModel.GPT5_2
|
||||
|
||||
@@ -99,10 +99,15 @@ MODEL_COST: dict[LlmModel, int] = {
|
||||
LlmModel.OPENAI_GPT_OSS_20B: 1,
|
||||
LlmModel.GEMINI_2_5_PRO: 4,
|
||||
LlmModel.GEMINI_3_PRO_PREVIEW: 5,
|
||||
LlmModel.GEMINI_2_5_FLASH: 1,
|
||||
LlmModel.GEMINI_2_0_FLASH: 1,
|
||||
LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
|
||||
LlmModel.GEMINI_2_0_FLASH_LITE: 1,
|
||||
LlmModel.MISTRAL_NEMO: 1,
|
||||
LlmModel.COHERE_COMMAND_R_08_2024: 1,
|
||||
LlmModel.COHERE_COMMAND_R_PLUS_08_2024: 3,
|
||||
LlmModel.DEEPSEEK_CHAT: 2,
|
||||
LlmModel.DEEPSEEK_R1_0528: 1,
|
||||
LlmModel.PERPLEXITY_SONAR: 1,
|
||||
LlmModel.PERPLEXITY_SONAR_PRO: 5,
|
||||
LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: 10,
|
||||
@@ -126,11 +131,6 @@ MODEL_COST: dict[LlmModel, int] = {
|
||||
LlmModel.KIMI_K2: 1,
|
||||
LlmModel.QWEN3_235B_A22B_THINKING: 1,
|
||||
LlmModel.QWEN3_CODER: 9,
|
||||
LlmModel.GEMINI_2_5_FLASH: 1,
|
||||
LlmModel.GEMINI_2_0_FLASH: 1,
|
||||
LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
|
||||
LlmModel.GEMINI_2_0_FLASH_LITE: 1,
|
||||
LlmModel.DEEPSEEK_R1_0528: 1,
|
||||
# v0 by Vercel models
|
||||
LlmModel.V0_1_5_MD: 1,
|
||||
LlmModel.V0_1_5_LG: 2,
|
||||
|
||||
@@ -54,7 +54,7 @@ export default function BuilderPage() {
|
||||
);
|
||||
}
|
||||
|
||||
return isNewFlowEditorEnabled ? (
|
||||
return true ? (
|
||||
<ReactFlowProvider>
|
||||
<Flow />
|
||||
</ReactFlowProvider>
|
||||
|
||||
@@ -2,7 +2,6 @@
|
||||
|
||||
import Image from "next/image";
|
||||
import { Text } from "@/components/atoms/Text/Text";
|
||||
import { toLlmDisplayName } from "../helpers";
|
||||
import claudeImg from "@/components/atoms/LLMItem/assets/claude.svg";
|
||||
import gptImg from "@/components/atoms/LLMItem/assets/gpt.svg";
|
||||
import perplexityImg from "@/components/atoms/LLMItem/assets/perplexity.svg";
|
||||
@@ -31,7 +30,7 @@ export function LlmIcon({ value, size = 20 }: Props) {
|
||||
return (
|
||||
<Image
|
||||
src={src}
|
||||
alt={toLlmDisplayName(value)}
|
||||
alt={value}
|
||||
width={size}
|
||||
height={size}
|
||||
className="rounded-xsmall"
|
||||
@@ -39,7 +38,7 @@ export function LlmIcon({ value, size = 20 }: Props) {
|
||||
);
|
||||
}
|
||||
|
||||
const fallback = toLlmDisplayName(value).slice(0, 1) || "?";
|
||||
const fallback = value?.trim().slice(0, 1).toUpperCase() || "?";
|
||||
return (
|
||||
<div className="flex h-5 w-5 items-center justify-center rounded-xsmall bg-zinc-100">
|
||||
<Text variant="small" className="text-zinc-500">
|
||||
|
||||
@@ -9,7 +9,13 @@ import {
|
||||
} from "@/components/__legacy__/ui/popover";
|
||||
import { Text } from "@/components/atoms/Text/Text";
|
||||
import { cn } from "@/lib/utils";
|
||||
import { groupByCreator, groupByTitle, toLlmDisplayName } from "../helpers";
|
||||
import {
|
||||
getCreatorDisplayName,
|
||||
getModelDisplayName,
|
||||
getProviderDisplayName,
|
||||
groupByCreator,
|
||||
groupByTitle,
|
||||
} from "../helpers";
|
||||
import { LlmModelMetadata } from "../types";
|
||||
import { LlmIcon } from "./LlmIcon";
|
||||
import { LlmMenuHeader } from "./LlmMenuHeader";
|
||||
@@ -39,26 +45,36 @@ export function LlmModelPicker({
|
||||
const [activeTitle, setActiveTitle] = useState<string | null>(null);
|
||||
|
||||
const creators = useMemo(() => {
|
||||
return Array.from(
|
||||
new Set(models.map((model) => model.creator)),
|
||||
).sort((a, b) => toLlmDisplayName(a).localeCompare(toLlmDisplayName(b)));
|
||||
const grouped = groupByCreator(models);
|
||||
return Array.from(grouped.keys()).sort((a, b) => a.localeCompare(b));
|
||||
}, [models]);
|
||||
|
||||
const modelsByCreator = useMemo(() => groupByCreator(models), [models]);
|
||||
|
||||
const creatorIconValues = useMemo(() => {
|
||||
const map = new Map<string, string>();
|
||||
for (const [creator, entries] of modelsByCreator.entries()) {
|
||||
map.set(creator, entries[0]?.creator ?? creator);
|
||||
}
|
||||
return map;
|
||||
}, [modelsByCreator]);
|
||||
|
||||
useEffect(() => {
|
||||
if (!open) {
|
||||
return;
|
||||
}
|
||||
setView("creator");
|
||||
setActiveCreator(selectedModel?.creator ?? creators[0] ?? null);
|
||||
setActiveTitle(selectedModel?.title ?? null);
|
||||
}, [open, selectedModel?.creator, selectedModel?.title, creators]);
|
||||
setActiveCreator(
|
||||
selectedModel ? getCreatorDisplayName(selectedModel) : creators[0] ?? null,
|
||||
);
|
||||
setActiveTitle(selectedModel ? getModelDisplayName(selectedModel) : null);
|
||||
}, [open, selectedModel, creators]);
|
||||
|
||||
const currentCreator = activeCreator ?? creators[0] ?? null;
|
||||
const currentModels = currentCreator
|
||||
? modelsByCreator.get(currentCreator) ?? []
|
||||
: [];
|
||||
const currentCreatorIcon = currentModels[0]?.creator ?? currentCreator;
|
||||
|
||||
const modelsByTitle = useMemo(() => groupByTitle(currentModels), [currentModels]);
|
||||
|
||||
@@ -88,7 +104,9 @@ export function LlmModelPicker({
|
||||
};
|
||||
|
||||
const triggerModel = selectedModel ?? recommendedModel ?? models[0];
|
||||
const triggerTitle = triggerModel ? triggerModel.title : "Select model";
|
||||
const triggerTitle = triggerModel
|
||||
? getModelDisplayName(triggerModel)
|
||||
: "Select model";
|
||||
const triggerCreator = triggerModel?.creator ?? "";
|
||||
|
||||
return (
|
||||
@@ -120,7 +138,7 @@ export function LlmModelPicker({
|
||||
{recommendedModel && (
|
||||
<>
|
||||
<LlmMenuItem
|
||||
title={recommendedModel.title}
|
||||
title={getModelDisplayName(recommendedModel)}
|
||||
subtitle="Recommended"
|
||||
icon={<LlmIcon value={recommendedModel.creator} />}
|
||||
onClick={() => handleSelectModel(recommendedModel.name)}
|
||||
@@ -131,10 +149,14 @@ export function LlmModelPicker({
|
||||
{creators.map((creator) => (
|
||||
<LlmMenuItem
|
||||
key={creator}
|
||||
title={toLlmDisplayName(creator)}
|
||||
icon={<LlmIcon value={creator} />}
|
||||
title={creator}
|
||||
icon={<LlmIcon value={creatorIconValues.get(creator) ?? creator} />}
|
||||
showChevron={true}
|
||||
isActive={selectedModel?.creator === creator}
|
||||
isActive={
|
||||
selectedModel
|
||||
? getCreatorDisplayName(selectedModel) === creator
|
||||
: false
|
||||
}
|
||||
onClick={() => {
|
||||
setActiveCreator(creator);
|
||||
setView("model");
|
||||
@@ -146,7 +168,7 @@ export function LlmModelPicker({
|
||||
{view === "model" && currentCreator && (
|
||||
<div className="flex flex-col">
|
||||
<LlmMenuHeader
|
||||
label={toLlmDisplayName(currentCreator)}
|
||||
label={currentCreator}
|
||||
onBack={() => setView("creator")}
|
||||
/>
|
||||
<div className="border-b border-zinc-200" />
|
||||
@@ -154,10 +176,14 @@ export function LlmModelPicker({
|
||||
<LlmMenuItem
|
||||
key={entry.title}
|
||||
title={entry.title}
|
||||
icon={<LlmIcon value={currentCreator} />}
|
||||
icon={<LlmIcon value={currentCreatorIcon} />}
|
||||
rightSlot={<LlmPriceTier tier={entry.entries[0]?.price_tier} />}
|
||||
showChevron={entry.providerCount > 1}
|
||||
isActive={selectedModel?.title === entry.title}
|
||||
isActive={
|
||||
selectedModel
|
||||
? getModelDisplayName(selectedModel) === entry.title
|
||||
: false
|
||||
}
|
||||
onClick={() => {
|
||||
if (entry.providerCount > 1) {
|
||||
setActiveTitle(entry.title);
|
||||
@@ -180,7 +206,7 @@ export function LlmModelPicker({
|
||||
{providerEntries.map((entry) => (
|
||||
<LlmMenuItem
|
||||
key={`${entry.title}-${entry.provider}`}
|
||||
title={toLlmDisplayName(entry.provider)}
|
||||
title={getProviderDisplayName(entry)}
|
||||
icon={<LlmIcon value={entry.provider} />}
|
||||
isActive={selectedModel?.provider === entry.provider}
|
||||
onClick={() => handleSelectModel(entry.name)}
|
||||
|
||||
@@ -1,38 +1,12 @@
|
||||
import { LlmModelMetadata } from "./types";
|
||||
|
||||
const displayNameOverrides: Record<string, string> = {
|
||||
aiml_api: "AI/ML",
|
||||
anthropic: "Anthropic",
|
||||
openai: "OpenAI",
|
||||
open_router: "Open Router",
|
||||
llama_api: "Llama API",
|
||||
groq: "Groq",
|
||||
ollama: "Ollama",
|
||||
v0: "V0",
|
||||
};
|
||||
|
||||
export function toLlmDisplayName(value: string): string {
|
||||
if (!value) {
|
||||
return "";
|
||||
}
|
||||
const normalized = value.toLowerCase();
|
||||
if (displayNameOverrides[normalized]) {
|
||||
return displayNameOverrides[normalized];
|
||||
}
|
||||
return value
|
||||
.split(/[_-]/)
|
||||
.map((word) =>
|
||||
word.length ? word[0].toUpperCase() + word.slice(1).toLowerCase() : "",
|
||||
)
|
||||
.join(" ");
|
||||
}
|
||||
|
||||
export function groupByCreator(models: LlmModelMetadata[]) {
|
||||
const map = new Map<string, LlmModelMetadata[]>();
|
||||
for (const model of models) {
|
||||
const existing = map.get(model.creator) ?? [];
|
||||
const key = getCreatorDisplayName(model);
|
||||
const existing = map.get(key) ?? [];
|
||||
existing.push(model);
|
||||
map.set(model.creator, existing);
|
||||
map.set(key, existing);
|
||||
}
|
||||
return map;
|
||||
}
|
||||
@@ -40,9 +14,22 @@ export function groupByCreator(models: LlmModelMetadata[]) {
|
||||
export function groupByTitle(models: LlmModelMetadata[]) {
|
||||
const map = new Map<string, LlmModelMetadata[]>();
|
||||
for (const model of models) {
|
||||
const existing = map.get(model.title) ?? [];
|
||||
const displayName = getModelDisplayName(model);
|
||||
const existing = map.get(displayName) ?? [];
|
||||
existing.push(model);
|
||||
map.set(model.title, existing);
|
||||
map.set(displayName, existing);
|
||||
}
|
||||
return map;
|
||||
}
|
||||
|
||||
export function getCreatorDisplayName(model: LlmModelMetadata): string {
|
||||
return model.creator_name || model.creator || "";
|
||||
}
|
||||
|
||||
export function getModelDisplayName(model: LlmModelMetadata): string {
|
||||
return model.title || model.name || "";
|
||||
}
|
||||
|
||||
export function getProviderDisplayName(model: LlmModelMetadata): string {
|
||||
return model.provider_name || model.provider || "";
|
||||
}
|
||||
|
||||
@@ -1,7 +1,9 @@
|
||||
export type LlmModelMetadata = {
|
||||
creator: string;
|
||||
creator_name: string;
|
||||
title: string;
|
||||
provider: string;
|
||||
provider_name: string;
|
||||
name: string;
|
||||
price_tier?: number;
|
||||
};
|
||||
|
||||
Reference in New Issue
Block a user