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Copy pathvalues.schema.json
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127 lines (127 loc) · 7.24 KB
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{
"type": "object",
"properties": {
"azimuth-llm": {
"type": "object",
"properties": {
"huggingface": {
"type": "object",
"properties": {
"model": {
"type": "string",
"title": "Model",
"description": "The [HuggingFace model](https://huggingface.co/models) to deploy (see [here](https://github.com/stackhpc/azimuth-llm?tab=readme-ov-file#tested-models) for a list of tested models).",
"default": "Qwen/Qwen2-VL-7B-Instruct"
},
"token": {
"type": [
"string",
"null"
],
"title": "Access Token",
"description": "A HuggingFace [access token](https://huggingface.co/docs/hub/security-tokens). Required for [gated models](https://huggingface.co/docs/hub/en/models-gated) (e.g. Llama 3)."
}
},
"required": [
"model"
]
},
"api": {
"type": "object",
"properties": {
"image": {
"type": "object",
"properties": {
"version": {
"type": "string",
"title": "Backend vLLM version",
"description": "The vLLM version to use as a backend. Must be a version tag from [this list](https://github.com/vllm-project/vllm/tags)",
"default": "v0.11.2"
}
}
},
"modelMaxContextLength": {
"title": "Model Context Length",
"description": "An override for the maximum context length to allow, if the model's default is not suitable."
}
}
},
"ui": {
"type": "object",
"properties": {
"appSettings": {
"type": "object",
"properties": {
"model_name": {
"type": "string",
"title": "Model Name",
"description": "Model name supplied to the OpenAI client in frontend web app. Should match huggingface.model above."
},
"page_title": {
"type": "string",
"title": "Page Title",
"description": "The title to display at the top of the chat interface.",
"default": "Vision Model Image Analysis"
},
"llm_params": {
"$comment": "top_k parameter causes vLLM to error for most (all?) vision models so is excluded here",
"type": "object",
"properties": {
"max_tokens": {
"type": "integer",
"title": "Max Tokens",
"description": "The maximum number of new [tokens](https://platform.openai.com/docs/api-reference/chat/create#chat-create-max_tokens) to generate for each LLM responses.",
"default": 1000
},
"temperature": {
"type": "number",
"title": "LLM Temperature",
"description": "The [temperature](https://platform.openai.com/docs/api-reference/chat/create#chat-create-temperature) value to use when generating LLM responses.",
"default": 0,
"minimum": 0,
"maximum": 2
},
"top_p": {
"type": "number",
"title": "LLM Top P",
"description": "The [top p](https://platform.openai.com/docs/api-reference/chat/create#chat-create-top_p) value to use when generating LLM responses.",
"default": 1,
"exclusiveMinimum": 0,
"maximum": 1
},
"top_k": {
"type": "integer",
"title": "LLM Top K",
"description": "The [top k](https://docs.vllm.ai/en/stable/dev/sampling_params.html) value to use when generating LLM responses (must be an integer).",
"default": -1,
"minimum": -1
},
"presence_penalty": {
"type": "number",
"title": "LLM Presence Penalty",
"description": "The [presence penalty](https://platform.openai.com/docs/api-reference/chat/create#chat-create-presence_penalty) to use when generating LLM responses.",
"default": 0,
"minimum": -2,
"maximum": 2
},
"frequency_penalty": {
"type": "number",
"title": "LLM Frequency Penalty",
"description": "The [frequency_penalty](https://platform.openai.com/docs/api-reference/chat/create#chat-create-frequency_penalty) to use when generating LLM responses.",
"default": 0,
"minimum": -2,
"maximum": 2
}
}
}
},
"required": [
"model_name"
]
}
}
}
}
}
}
}