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Api podcast migration (#93)

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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
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Luis Novo 2025-07-17 08:36:11 -03:00 • committed by GitHub
parent 9814103cc8
commit d7b0fff954
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125 changed files with 16177 additions and 3296 deletions
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13
open_notebook/graphs/source.py
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@ -13,7 +13,6 @@ from open_notebook.domain.content_settings import ContentSettings
from open_notebook.domain.notebook import Asset, Source
from open_notebook.domain.transformation import Transformation
from open_notebook.graphs.transformation import graph as transform_graph
from open_notebook.utils import surreal_clean
class SourceState(TypedDict):
@ -46,23 +45,23 @@ async def content_process(state: SourceState) -> dict:
return {"content_state": processed_state}
def save_source(state: SourceState) -> dict:
async def save_source(state: SourceState) -> dict:
content_state = state["content_state"]
source = Source(
asset=Asset(url=content_state.url, file_path=content_state.file_path),
full_text=surreal_clean(content_state.content),
full_text=content_state.content,
title=content_state.title,
)
source.save()
await source.save()
if state["notebook_id"]:
logger.debug(f"Adding source to notebook {state['notebook_id']}")
source.add_to_notebook(state["notebook_id"])
await source.add_to_notebook(state["notebook_id"])
if state["embed"]:
logger.debug("Embedding content for vector search")
source.vectorize()
await source.vectorize()
return {"source": source}
@ -97,7 +96,7 @@ async def transform_content(state: TransformationState) -> Optional[dict]:
result = await transform_graph.ainvoke(
dict(input_text=content, transformation=transformation)
)
source.add_insight(transformation.title, surreal_clean(result["output"]))
await source.add_insight(transformation.title, result["output"])
return {
"transformation": [
{