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Human+ Core AI Layer
====================
Semua logika AI, RAG, PDF processing, chart, dan report generation.
Cara pakai:
from core.ai_client import call_gemini, get_client
from core.rag_engine import get_vector_store, retrieve_context
from core.pdf_processor import extract_biomarkers
from core.protocol_generator import generate_protocol
from core.chart_builder import build_gauge_chart, GAUGE_PRESETS
from core.report_generator import generate_pdf_report
Modules:
ai_client — Gemini client singleton + call_gemini() wrapper
rag_engine — FAISS vector store loader + MMR retriever
pdf_processor — PDF → structured biomarker list via Gemini
protocol_generator — Biomarker + RAG context → protocol dict via Gemini
chart_builder — Plotly figure builders (gauge, bar, donut)
report_generator — Branded PDF report via reportlab
"""
from core.ai_client import (
get_client,
call_gemini,
pdf_bytes_to_part,
check_client_health,
GeminiClientError,
MODEL_NAME,
)
from core.rag_engine import (
get_vector_store,
retrieve_context,
get_knowledge_stats,
RAGEngineError,
)
from core.pdf_processor import (
extract_biomarkers,
get_raw_extraction_text,
PDFProcessorError,
)
from core.protocol_generator import (
generate_protocol,
generate_protocol_from_raw_text,
ProtocolGeneratorError,
)
from core.chart_builder import (
build_gauge_chart,
build_biomarker_bar_chart,
build_status_donut,
get_gauge_preset,
GAUGE_PRESETS,
)
from core.report_generator import generate_pdf_report
__all__ = [
# ai_client
"get_client", "call_gemini", "pdf_bytes_to_part",
"check_client_health", "GeminiClientError", "MODEL_NAME",
# rag_engine
"get_vector_store", "retrieve_context", "get_knowledge_stats", "RAGEngineError",
# pdf_processor
"extract_biomarkers", "get_raw_extraction_text", "PDFProcessorError",
# protocol_generator
"generate_protocol", "generate_protocol_from_raw_text", "ProtocolGeneratorError",
# chart_builder
"build_gauge_chart", "build_biomarker_bar_chart", "build_status_donut",
"get_gauge_preset", "GAUGE_PRESETS",
# report_generator
"generate_pdf_report",
]
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