mirror of
https://github.com/lfnovo/open-notebook.git
synced 2026-05-02 05:10:34 +00:00
d7b0fff954
Creates the API layer for Open Notebook Creates a services API gateway for the Streamlit front-end Migrates the SurrealDB SDK to the official one Change all database calls to async New podcast framework supporting multiple speaker configurations Implement the surreal-commands library for async processing Improve docker image and docker-compose configurations
124 lines
No EOL
4.7 KiB
Python
124 lines
No EOL
4.7 KiB
Python
"""
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Transformations service layer using API.
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"""
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from datetime import datetime
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from typing import Dict, List
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from loguru import logger
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from api.client import api_client
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from open_notebook.domain.transformation import Transformation
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class TransformationsService:
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"""Service layer for transformations operations using API."""
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def __init__(self):
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logger.info("Using API for transformations operations")
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def get_all_transformations(self) -> List[Transformation]:
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"""Get all transformations."""
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transformations_data = api_client.get_transformations()
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# Convert API response to Transformation objects
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transformations = []
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for trans_data in transformations_data:
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transformation = Transformation(
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name=trans_data["name"],
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title=trans_data["title"],
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description=trans_data["description"],
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prompt=trans_data["prompt"],
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apply_default=trans_data["apply_default"],
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)
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transformation.id = trans_data["id"]
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transformation.created = datetime.fromisoformat(trans_data["created"].replace('Z', '+00:00'))
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transformation.updated = datetime.fromisoformat(trans_data["updated"].replace('Z', '+00:00'))
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transformations.append(transformation)
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return transformations
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def get_transformation(self, transformation_id: str) -> Transformation:
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"""Get a specific transformation."""
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trans_data = api_client.get_transformation(transformation_id)
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transformation = Transformation(
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name=trans_data["name"],
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title=trans_data["title"],
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description=trans_data["description"],
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prompt=trans_data["prompt"],
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apply_default=trans_data["apply_default"],
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)
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transformation.id = trans_data["id"]
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transformation.created = datetime.fromisoformat(trans_data["created"].replace('Z', '+00:00'))
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transformation.updated = datetime.fromisoformat(trans_data["updated"].replace('Z', '+00:00'))
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return transformation
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def create_transformation(
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self,
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name: str,
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title: str,
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description: str,
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prompt: str,
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apply_default: bool = False
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) -> Transformation:
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"""Create a new transformation."""
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trans_data = api_client.create_transformation(
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name=name,
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title=title,
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description=description,
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prompt=prompt,
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apply_default=apply_default
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)
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transformation = Transformation(
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name=trans_data["name"],
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title=trans_data["title"],
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description=trans_data["description"],
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prompt=trans_data["prompt"],
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apply_default=trans_data["apply_default"],
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)
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transformation.id = trans_data["id"]
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transformation.created = datetime.fromisoformat(trans_data["created"].replace('Z', '+00:00'))
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transformation.updated = datetime.fromisoformat(trans_data["updated"].replace('Z', '+00:00'))
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return transformation
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def update_transformation(self, transformation: Transformation) -> Transformation:
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"""Update a transformation."""
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updates = {
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"name": transformation.name,
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"title": transformation.title,
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"description": transformation.description,
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"prompt": transformation.prompt,
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"apply_default": transformation.apply_default,
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}
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trans_data = api_client.update_transformation(transformation.id, **updates)
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# Update the transformation object with the response
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transformation.name = trans_data["name"]
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transformation.title = trans_data["title"]
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transformation.description = trans_data["description"]
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transformation.prompt = trans_data["prompt"]
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transformation.apply_default = trans_data["apply_default"]
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transformation.updated = datetime.fromisoformat(trans_data["updated"].replace('Z', '+00:00'))
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return transformation
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def delete_transformation(self, transformation_id: str) -> bool:
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"""Delete a transformation."""
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api_client.delete_transformation(transformation_id)
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return True
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def execute_transformation(
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self,
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transformation_id: str,
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input_text: str,
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model_id: str
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) -> Dict[str, str]:
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"""Execute a transformation on input text."""
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result = api_client.execute_transformation(
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transformation_id=transformation_id,
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input_text=input_text,
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model_id=model_id
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)
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return result
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# Global service instance
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transformations_service = TransformationsService() |