open-notebook/open_notebook/graphs/content_processing/__init__.py
2024-11-11 17:32:35 -03:00

145 lines
4.6 KiB
Python

import os
from typing import Any, Dict
import magic
from langgraph.graph import END, START, StateGraph
from loguru import logger
from open_notebook.exceptions import UnsupportedTypeException
from open_notebook.graphs.content_processing.audio import extract_audio
from open_notebook.graphs.content_processing.office import (
SUPPORTED_OFFICE_TYPES,
extract_office_content,
)
from open_notebook.graphs.content_processing.pdf import (
SUPPORTED_FITZ_TYPES,
extract_pdf,
)
from open_notebook.graphs.content_processing.state import ContentState
from open_notebook.graphs.content_processing.text import extract_txt
from open_notebook.graphs.content_processing.url import extract_url, url_provider
from open_notebook.graphs.content_processing.video import extract_best_audio_from_video
from open_notebook.graphs.content_processing.youtube import extract_youtube_transcript
async def source_identification(state: ContentState) -> Dict[str, str]:
"""
Identify the content source based on parameters
"""
if state.get("content"):
doc_type = "text"
elif state.get("file_path"):
doc_type = "file"
elif state.get("url"):
doc_type = "url"
else:
raise ValueError("No source provided.")
return {"source_type": doc_type}
async def file_type(state: ContentState) -> Dict[str, Any]:
"""
Identify the file using python-magic
"""
return_dict = {}
file_path = state.get("file_path")
if file_path is not None:
return_dict["identified_type"] = magic.from_file(file_path, mime=True)
return_dict["title"] = os.path.basename(file_path)
return return_dict
async def file_type_edge(data: ContentState) -> str:
assert data.get("identified_type"), "Type not identified"
identified_type = data["identified_type"]
if identified_type == "text/plain":
return "extract_txt"
elif identified_type in SUPPORTED_FITZ_TYPES:
return "extract_pdf"
elif identified_type in SUPPORTED_OFFICE_TYPES:
return "extract_office_content"
elif identified_type.startswith("video"):
return "extract_best_audio_from_video"
elif identified_type.startswith("audio"):
return "extract_audio"
else:
raise UnsupportedTypeException(
f"Unsupported file type: {data.get('identified_type')}"
)
async def delete_file(data: ContentState) -> Dict[str, Any]:
if data.get("delete_source"):
logger.debug(f"Deleting file: {data.get('file_path')}")
file_path = data.get("file_path")
if file_path is not None:
try:
os.remove(file_path)
return {"file_path": None}
except FileNotFoundError:
logger.warning(f"File not found while trying to delete: {file_path}")
else:
logger.debug("Not deleting file")
return {}
async def url_type_router(x: ContentState) -> str:
return x.get("identified_type", "")
async def source_type_router(x: ContentState) -> str:
return x.get("source_type", "")
# Create workflow
workflow = StateGraph(ContentState)
# Add nodes
workflow.add_node("source", source_identification)
workflow.add_node("url_provider", url_provider)
workflow.add_node("file_type", file_type)
workflow.add_node("extract_txt", extract_txt)
workflow.add_node("extract_pdf", extract_pdf)
workflow.add_node("extract_url", extract_url)
workflow.add_node("extract_office_content", extract_office_content)
workflow.add_node("extract_best_audio_from_video", extract_best_audio_from_video)
workflow.add_node("extract_audio", extract_audio)
workflow.add_node("extract_youtube_transcript", extract_youtube_transcript)
workflow.add_node("delete_file", delete_file)
# Add edges
workflow.add_edge(START, "source")
workflow.add_conditional_edges(
"source",
source_type_router,
{
"url": "url_provider",
"file": "file_type",
"text": END,
},
)
workflow.add_conditional_edges(
"file_type",
file_type_edge,
)
workflow.add_conditional_edges(
"url_provider",
url_type_router,
{"article": "extract_url", "youtube": "extract_youtube_transcript"},
)
workflow.add_edge("url_provider", END)
workflow.add_edge("file_type", END)
workflow.add_edge("extract_url", END)
workflow.add_edge("extract_txt", END)
workflow.add_edge("extract_youtube_transcript", END)
workflow.add_edge("extract_pdf", "delete_file")
workflow.add_edge("extract_office_content", "delete_file")
workflow.add_edge("extract_best_audio_from_video", "extract_audio")
workflow.add_edge("extract_audio", "delete_file")
workflow.add_edge("delete_file", END)
# Compile graph
graph = workflow.compile()