update

.gitignore

@@ -0,0 +1,2 @@
+__pycache__/*
+

README.md

@@ -12,6 +12,10 @@ pinned: false
 # Medical Knowledge Graph Construction (medKGC)
 
 ## Overview
+A automated annotion tool using LLMs to help medical annotators annotate the input radiology reports.  
+
+这个工具涉及了Named Entity Recognition，relation extraction, named entity normalization，最终结果会以知识图谱的形式输出。
+
 medKGC is a medical text knowledge graph construction and review system. It supports entity recognition, relation extraction, and visualization of medical reports, providing a convenient review interface.
 
 ## Deployment
@@ -33,6 +37,9 @@ pip install -r requirements.txt
 streamlit run app.py
 ```
 
+
+
+
 ## Core Features
 
 ### 1. Data Processing
@@ -102,7 +109,7 @@ def find_relations_with_entities(entities, entities_data):
 ## TODO
 1. [ ] Add data export functionality
 2. [ ] Named Entity Recognition
-   1. [ ] 增加输入框   
+   1. [ ] 增加输入框
    2. [ ] 调用llms
 3. [ ] Relation Extraction
    1. [ ] Add relation editing functionality

app_ui.py

@@ -7,10 +7,10 @@ from app_logic import *
 def display_entity_selections(selections):
     """Display entity selections in a grid layout"""
     st.subheader("Selected Entities:")
-    
+
     # 使用columns来水平排列按钮
     cols = st.columns(4)  # 每行4个按钮
-    
+
     for i, entity in enumerate(selections):
         col_idx = i % 4
         with cols[col_idx]:
@@ -144,23 +144,23 @@ def handle_review_submission(selected_report, selections, entities_data):
 
 def setup_input_selection():
     """设置输入方式选择"""
-    st.subheader("选择输入方式")
+    st.subheader("Select Input Method")
     input_method = st.radio(
-        "请选择输入方式",
-        ["从数据集选择", "手动输入文本"],
+        "Select Input Method",
+        ["Select from Dataset", "Manual Text Input"],
         key="input_method"
     )
-    
-    if input_method == "手动输入文本":
+
+    if input_method == "Manual Text Input":
         user_text = st.text_area(
-            "请输入放射学报告文本",
+            "Please Input Radiology Report Text",
             height=200,
-            placeholder="在此输入报告文本...",
+            placeholder="Enter report text here...",
             key="user_input_text"
         )
-        if st.button("分析文本"):
+        if st.button("Analyze Text"):
             return {"type": "user_input", "text": user_text}
     else:
         return {"type": "dataset"}
-    
+
     return None

start.sh

@@ -0,0 +1,8 @@
+#! /usr/bin/env bash
+# Source conda to enable 'conda activate'
+source "$(conda info --base)/etc/profile.d/conda.sh"
+conda activate medkgc
+# Install dependencies
+pip install -r requirements.txt
+# Start the Streamlit app
+streamlit run app.py