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from typing import Dict, Optional
import logging
import time
from lpm_kernel.file_data.document import Document
from lpm_kernel.L0.l0_generator import L0Generator
from lpm_kernel.L0.models import (
InsighterInput,
SummarizerInput,
FileInfo,
BioInfo,
DocumentType,
)
from lpm_kernel.configs.config import Config
from lpm_kernel.file_data.document_dto import DocumentDTO
logger = logging.getLogger(__name__)
class InsightKernel:
def __init__(self):
self.generator = L0Generator()
config = Config.from_env()
self.preferred_language = config.get("PREFER_LANGUAGE", "en")
def analyze(self, doc: DocumentDTO) -> Dict:
"""Generate document insight"""
try:
self.generator.preferred_language = self.preferred_language
document_type = DocumentType.from_mime_type(doc.mime_type)
if document_type is DocumentType.TEXT:
return {
"title": "",
"insight": doc.raw_content,
}
# Prepare input data
file_info = FileInfo(
data_type=document_type.value,
filename=doc.name,
content="",
file_content={"content": doc.raw_content},
)
bio_info = BioInfo(global_bio="", status_bio="", about_me="")
insighter_input = InsighterInput(file_info=file_info, bio_info=bio_info)
insight_result = self.generator.insighter(insighter_input)
return {
"title": insight_result.get("title"),
"insight": insight_result.get("insight"),
}
except Exception as e:
logger.error(f"Failed to generate insight: {str(e)}", exc_info=True)
raise Exception(f"Error generating insight: {e}")
class SummaryKernel:
def __init__(self):
self.generator = L0Generator()
config = Config.from_env()
self.preferred_language = config.get("PREFER_LANGUAGE", "en")
def analyze(self, doc: DocumentDTO, insight: str = "") -> Dict:
"""Generate document summary"""
try:
self.generator.preferred_language = self.preferred_language
document_type = DocumentType.from_mime_type(doc.mime_type)
if document_type is DocumentType.TEXT:
return {
"title": "",
"summary": doc.raw_content,
"keywords": [],
}
# Prepare input data
file_info = FileInfo(
data_type=document_type.value,
filename=doc.name,
content="",
file_content={"content": doc.raw_content},
)
summarizer_input = SummarizerInput(file_info=file_info, insight=insight)
# Call LLM
summary_result = self.generator.summarizer(summarizer_input)
return {
"title": summary_result.get("title"),
"summary": summary_result.get("summary"),
"keywords": summary_result.get("keywords", []),
}
except Exception as e:
logger.error(f"Failed to generate summary: {str(e)}", exc_info=True)
raise Exception(f"Error generating summary: {e}")
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