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from typing import Dict, List, Optional, Tuple, Union |
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from pydantic import Field, validator |
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from inference.core.entities.requests.inference import ( |
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BaseRequest, |
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InferenceRequestImage, |
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) |
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from inference.core.env import COGVLM_VERSION_ID |
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class CogVLMInferenceRequest(BaseRequest): |
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"""Request for CogVLM inference. |
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Attributes: |
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api_key (Optional[str]): Roboflow API Key. |
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cog_version_id (Optional[str]): The version ID of CLIP to be used for this request. |
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""" |
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cogvlm_version_id: Optional[str] = Field( |
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default=COGVLM_VERSION_ID, |
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examples=["cogvlm-chat-hf"], |
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description="The version ID of CogVLM to be used for this request. See the huggingface model repo at THUDM.", |
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) |
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model_id: Optional[str] = Field(None) |
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image: InferenceRequestImage = Field( |
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description="Image for CogVLM to look at. Use prompt to specify what you want it to do with the image." |
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) |
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prompt: str = Field( |
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description="Text to be passed to CogVLM. Use to prompt it to describe an image or provide only text to chat with the model.", |
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examples=["Describe this image."], |
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) |
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history: Optional[List[Tuple[str, str]]] = Field( |
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None, |
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description="Optional chat history, formatted as a list of 2-tuples where the first entry is the user prompt" |
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" and the second entry is the generated model response", |
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) |
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@validator("model_id", always=True) |
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def validate_model_id(cls, value, values): |
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if value is not None: |
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return value |
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if values.get("cogvlm_version_id") is None: |
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return None |
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return f"cogvlm/{values['cogvlm_version_id']}" |
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