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349c3cf7b8
Enhance `LLMNode` with multimodal capability, introducing support for image outputs. This implementation extracts base64-encoded images from LLM responses, saves them to the storage service, and records the file metadata in the `ToolFile` table. In conversations, these images are rendered as markdown-based inline images. Additionally, the images are included in the LLMNode's output as file variables, enabling subsequent nodes in the workflow to utilize them. To integrate file outputs into workflows, adjustments to the frontend code are necessary. For multimodal output functionality, updates to related model configurations are required. Currently, this capability has been applied exclusively to Google's Gemini models. Close #15814. Signed-off-by: -LAN- <laipz8200@outlook.com> Co-authored-by: -LAN- <laipz8200@outlook.com>
26 lines
882 B
Python
26 lines
882 B
Python
from flask_sqlalchemy import SQLAlchemy
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from sqlalchemy import MetaData
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POSTGRES_INDEXES_NAMING_CONVENTION = {
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"ix": "%(column_0_label)s_idx",
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"uq": "%(table_name)s_%(column_0_name)s_key",
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"ck": "%(table_name)s_%(constraint_name)s_check",
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"fk": "%(table_name)s_%(column_0_name)s_fkey",
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"pk": "%(table_name)s_pkey",
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}
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metadata = MetaData(naming_convention=POSTGRES_INDEXES_NAMING_CONVENTION)
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# ****** IMPORTANT NOTICE ******
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#
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# NOTE(QuantumGhost): Avoid directly importing and using `db` in modules outside of the
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# `controllers` package.
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#
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# Instead, import `db` within the `controllers` package and pass it as an argument to
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# functions or class constructors.
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#
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# Directly importing `db` in other modules can make the code more difficult to read, test, and maintain.
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#
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# Whenever possible, avoid this pattern in new code.
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db = SQLAlchemy(metadata=metadata)
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