Update ui/ui_core.py
Browse files- ui/ui_core.py +13 -13
ui/ui_core.py
CHANGED
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@@ -6,16 +6,15 @@ import gradio as gr
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from tabulate import tabulate
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from typing import List, Optional
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# ✅ Add src to Python path
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "src"))
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from txagent.txagent import TxAgent
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def safe_extract_table_data(table: List[List[str]]) -> List[str]:
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"""Safely extract data from a PDF table row by row."""
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extracted_rows = []
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if not table or not isinstance(table, list):
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return extracted_rows
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-
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for row in table:
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if not row or not isinstance(row, list):
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continue
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@@ -29,7 +28,6 @@ def safe_extract_table_data(table: List[List[str]]) -> List[str]:
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return extracted_rows
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def extract_all_text_from_csv_or_excel(file_path: str, progress=None, index=0, total=1) -> str:
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"""Safely extract text from CSV or Excel files with error handling."""
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try:
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if not os.path.exists(file_path):
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return f"File not found: {file_path}"
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@@ -44,7 +42,6 @@ def extract_all_text_from_csv_or_excel(file_path: str, progress=None, index=0, t
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if progress:
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progress((index + 1) / total, desc=f"Processed table: {os.path.basename(file_path)}")
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# Safely check for grouping columns
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group_column = None
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for col in ["Booking Number", "Form Name"]:
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if col in df.columns:
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@@ -71,7 +68,6 @@ def extract_all_text_from_csv_or_excel(file_path: str, progress=None, index=0, t
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return f"Error parsing file {os.path.basename(file_path)}: {str(e)}"
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def extract_all_text_from_pdf(file_path: str, progress=None, index=0, total=1) -> str:
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"""Safely extract text from PDF files with comprehensive error handling."""
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extracted = []
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try:
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if not os.path.exists(file_path):
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@@ -111,7 +107,6 @@ def create_ui(agent: TxAgent):
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conversation_state = gr.State([])
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def handle_chat(message: str, history: list, conversation: list, uploaded_files: list, progress=gr.Progress()):
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"""Handle chat with comprehensive error handling for file processing."""
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context = (
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"You are an expert clinical AI assistant reviewing medical form or interview data. "
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"Your job is to analyze this data and reason about any information or red flags that a human doctor might have overlooked. "
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@@ -162,10 +157,15 @@ def create_ui(agent: TxAgent):
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for update in generator:
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try:
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if isinstance(update, list):
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cleaned = [
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-
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if cleaned:
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final_response = cleaned
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yield cleaned
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@@ -190,4 +190,4 @@ def create_ui(agent: TxAgent):
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["Is there anything abnormal in the attached blood work report?"]
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], inputs=message_input)
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return demo
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from tabulate import tabulate
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from typing import List, Optional
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# ✅ Fix: Add src to Python path with correct parentheses
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "src")))
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from txagent.txagent import TxAgent
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def safe_extract_table_data(table: List[List[str]]) -> List[str]:
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extracted_rows = []
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if not table or not isinstance(table, list):
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return extracted_rows
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for row in table:
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if not row or not isinstance(row, list):
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continue
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return extracted_rows
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def extract_all_text_from_csv_or_excel(file_path: str, progress=None, index=0, total=1) -> str:
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try:
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if not os.path.exists(file_path):
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return f"File not found: {file_path}"
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if progress:
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progress((index + 1) / total, desc=f"Processed table: {os.path.basename(file_path)}")
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group_column = None
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for col in ["Booking Number", "Form Name"]:
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if col in df.columns:
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return f"Error parsing file {os.path.basename(file_path)}: {str(e)}"
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def extract_all_text_from_pdf(file_path: str, progress=None, index=0, total=1) -> str:
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extracted = []
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try:
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if not os.path.exists(file_path):
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conversation_state = gr.State([])
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def handle_chat(message: str, history: list, conversation: list, uploaded_files: list, progress=gr.Progress()):
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context = (
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"You are an expert clinical AI assistant reviewing medical form or interview data. "
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"Your job is to analyze this data and reason about any information or red flags that a human doctor might have overlooked. "
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for update in generator:
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try:
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if isinstance(update, list):
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cleaned = [
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msg for msg in update
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if hasattr(msg, 'role')
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and not (
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msg.role == "assistant"
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and hasattr(msg, 'content')
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and msg.content.strip().startswith("🧰")
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)
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]
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if cleaned:
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final_response = cleaned
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yield cleaned
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["Is there anything abnormal in the attached blood work report?"]
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], inputs=message_input)
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return demo
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