.

individual_analyzes.py

@@ -1,4 +1,5 @@
 import streamlit as st
+import os
 from transformers import pipeline
 from utils import read_poems_from_directory
 import matplotlib.pyplot as plt
@@ -6,6 +7,10 @@ import matplotlib.pyplot as plt
 sentiment_classifier = pipeline("sentiment-analysis")
 emotion_classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True)
 
+# Directory for poems
+poems_directory = "./poems"
+os.makedirs(poems_directory, exist_ok=True)
+
 def analyze_poem(poem):
     sentiment = sentiment_classifier(poem)[0]
     emotion_scores = emotion_classifier(poem)[0]
@@ -26,22 +31,35 @@ def plot_emotion_scores(emotion_scores):
     return fig
 
 def analyze_individual_page():
-    st.header("Analyze Poems")
-    poems_directory = "poems"
-    
+    st.header("Analyze Individual Poems")
+
+    # Sidebar for file upload and listing files
+    st.sidebar.title("Upload New Poem")
+    uploaded_file = st.sidebar.file_uploader("Choose a text file", type="txt")
+
+    if uploaded_file is not None:
+        with open(os.path.join(poems_directory, uploaded_file.name), "wb") as f:
+            f.write(uploaded_file.getbuffer())
+        st.sidebar.success(f"Uploaded {uploaded_file.name}")
+
+    st.sidebar.title("Available Poems")
+    poem_files = [f for f in os.listdir(poems_directory) if f.endswith(".txt")]
+    st.sidebar.write("\n".join(poem_files))
+
     poems = read_poems_from_directory(poems_directory)
     
     if poems:
-        for i, poem in enumerate(poems, start=1):
-            st.subheader(f"Poem {i}")
-            st.text(poem)
-            sentiment, emotion, emotion_scores = analyze_poem(poem)
-            st.write(f"Sentiment: {sentiment['label']} (score: {sentiment['score']:.2f})")
-            st.write(f"Emotion: {emotion}")
-            
-            # Plot emotion scores
-            fig = plot_emotion_scores(emotion_scores)
-            st.pyplot(fig)
+        selected_poem = st.selectbox("Select a poem to analyze", range(len(poems)), format_func=lambda i: f"Poem {i+1}")
+        
+        st.subheader(f"Analyzing Poem {selected_poem + 1}")
+        st.text(poems[selected_poem])
+        sentiment, emotion, emotion_scores = analyze_poem(poems[selected_poem])
+        st.write(f"Sentiment: {sentiment['label']} (score: {sentiment['score']:.2f})")
+        st.write(f"Dominant Emotion: {emotion}")
+        
+        # Plot emotion scores
+        fig = plot_emotion_scores(emotion_scores)
+        st.pyplot(fig)
     else:
         st.warning("No poems found in the 'poems' directory.")