Update ui/ui_core.py

ui/ui_core.py

@@ -1,30 +1,22 @@
-
 import sys
 import os
 
 # ✅ Add src to Python path
 sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "src")))
 
-from txagent.txagent import TxAgent  # ✅ Now this will work
+from txagent.txagent import TxAgent
 import pandas as pd
 import pdfplumber
 import gradio as gr
 
-
-def extract_structured_text_from_csv(file_path):
+def extract_all_text_from_csv(file_path):
     try:
         df = pd.read_csv(file_path)
-        relevant_columns = [
-            "Booking Number", "Form Name", "Form Item",
-            "Item Response", "Interviewer", "Interview Date"
-        ]
-        df = df[[col for col in relevant_columns if col in df.columns]]
         return df.to_string(index=False)
     except Exception as e:
         return f"Error parsing CSV: {e}"
 
-
-def extract_structured_text_from_pdf(file_path):
+def extract_all_text_from_pdf(file_path):
     extracted = []
     try:
         with pdfplumber.open(file_path) as pdf:
@@ -38,10 +30,9 @@ def extract_structured_text_from_pdf(file_path):
     except Exception as e:
         return f"Error parsing PDF: {e}"
 
-
 def create_ui(agent: TxAgent):
     with gr.Blocks(theme=gr.themes.Soft()) as demo:
-        gr.Markdown("<h1 style='text-align: center;'>\ud83d\udc8a TxAgent: Therapeutic Reasoning</h1>")
+        gr.Markdown("<h1 style='text-align: center;'>💊 TxAgent: Therapeutic Reasoning</h1>")
         chatbot = gr.Chatbot(label="TxAgent", height=600, type="messages")
 
         file_upload = gr.File(label="Upload Medical File", file_types=[".pdf", ".txt", ".docx", ".jpg", ".png", ".csv"], file_count="multiple")
@@ -51,9 +42,9 @@ def create_ui(agent: TxAgent):
 
         def handle_chat(message, history, conversation, uploaded_files):
             context = (
-                "You are a clinical AI reviewing patient form data from interviews. "
-                "Your task is to analyze the responses, dates, and items, and reason step-by-step about "
-                "what the doctor might have overlooked. Do not summarize or answer yet — just reason step-by-step first."
+                "You are a clinical AI reviewing medical interview or form data. "
+                "Analyze the extracted content and reason step-by-step about what the doctor could have missed. "
+                "Don't answer yet — just reason."
             )
 
             if uploaded_files:
@@ -61,9 +52,12 @@ def create_ui(agent: TxAgent):
                 for file in uploaded_files:
                     path = file.name
                     if path.endswith(".csv"):
-                        extracted_text += extract_structured_text_from_csv(path) + "\n"
+                        extracted_text += extract_all_text_from_csv(path) + "\n"
                     elif path.endswith(".pdf"):
-                        extracted_text += extract_structured_text_from_pdf(path) + "\n"
+                        extracted_text += extract_all_text_from_pdf(path) + "\n"
+                    else:
+                        extracted_text += f"(Uploaded file: {os.path.basename(path)})\n"
+
                 message = f"{context}\n\n---\n{extracted_text.strip()}\n---\n\nNow reason what the doctor might have missed."
 
             generator = agent.run_gradio_chat(
@@ -88,4 +82,4 @@ def create_ui(agent: TxAgent):
             ["Upload the files"],
         ], inputs=message_input)
 
-    return demo
+    return demo