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55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
"""
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ImageToTextNode Module
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"""
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from typing import List, Optional
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from .base_node import BaseNode
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class ImageToTextNode(BaseNode):
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"""
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Retrieve an image from an URL and convert it to text using an ImageToText model.
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Attributes:
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llm_model: An instance of the language model client used for image-to-text conversion.
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verbose (bool): A flag indicating whether to show print statements during execution.
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Args:
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input (str): Boolean expression defining the input keys needed from the state.
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output (List[str]): List of output keys to be updated in the state.
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node_config (dict): Additional configuration for the node.
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node_name (str): The unique identifier name for the node, defaulting to "ImageToText".
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"""
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def __init__(self, input: str, output: List[str], node_config: Optional[dict]=None,
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node_name: str = "ImageToText"):
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super().__init__(node_name, "node", input, output, 1, node_config)
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self.llm_model = node_config["llm_model"]
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self.verbose = False if node_config is None else node_config.get("verbose", False)
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def execute(self, state: dict) -> dict:
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"""
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Generate text from an image using an image-to-text model. The method retrieves the image
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from the URL provided in the state.
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Args:
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state (dict): The current state of the graph. The input keys will be used to fetch the
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correct data types from the state.
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Returns:
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dict: The updated state with the input key containing the text extracted from the image.
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"""
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if self.verbose:
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print("---GENERATING TEXT FROM IMAGE---")
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input_keys = self.get_input_keys(state)
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input_data = [state[key] for key in input_keys]
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url = input_data[0]
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text_answer = self.llm_model.run(url)
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state.update({"image_text": text_answer})
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return state
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