Update app.py for Part4

app.py

@@ -236,42 +236,35 @@ def get_sorted_cosine_similarity(embeddings_metadata):
 
     return sorted_cosine_sim
 
-
-def plot_piechart(sorted_cosine_scores_items):
-    sorted_cosine_scores = np.array([
-            sorted_cosine_scores_items[index][1]
-            for index in range(len(sorted_cosine_scores_items))
-        ]
-    )
-    categories = st.session_state.categories.split(" ")
-    categories_sorted = [
-        categories[sorted_cosine_scores_items[index][0]]
-        for index in range(len(sorted_cosine_scores_items))
-    ]
-    fig, ax = plt.subplots()
-    ax.pie(sorted_cosine_scores, labels=categories_sorted, autopct="%1.1f%%")
-    st.pyplot(fig)  # Figure
+#
+# def plot_piechart(sorted_cosine_scores_items):
+#     sorted_cosine_scores = np.array([
+#             sorted_cosine_scores_items[index][1]
+#             for index in range(len(sorted_cosine_scores_items))
+#         ]
+#     )
+#     categories = st.session_state.categories.split(" ")
+#     categories_sorted = [
+#         categories[sorted_cosine_scores_items[index][0]]
+#         for index in range(len(sorted_cosine_scores_items))
+#     ]
+#     fig, ax = plt.subplots()
+#     ax.pie(sorted_cosine_scores, labels=categories_sorted, autopct="%1.1f%%")
+#     st.pyplot(fig)  # Figure
 
 
 def plot_piechart_helper(sorted_cosine_scores_items):
-    sorted_cosine_scores = np.array(
-        [
-            sorted_cosine_scores_items[index][1]
-            for index in range(len(sorted_cosine_scores_items))
-        ]
-    )
-    categories = st.session_state.categories.split(" ")
-    categories_sorted = [
-        categories[sorted_cosine_scores_items[index][0]]
-        for index in range(len(sorted_cosine_scores_items))
-    ]
+    sorted_cosine_scores = np.array(list(sorted_cosine_scores_items.values()))
+    categories_sorted = list(sorted_cosine_scores_items.keys())
+
     fig, ax = plt.subplots(figsize=(3, 3))
     my_explode = np.zeros(len(categories_sorted))
     my_explode[0] = 0.2
     if len(categories_sorted) == 3:
-        my_explode[1] = 0.1  # explode this by 0.2
+        my_explode[1] = 0.1
     elif len(categories_sorted) > 3:
         my_explode[2] = 0.05
+
     ax.pie(
         sorted_cosine_scores,
         labels=categories_sorted,
@@ -314,10 +307,13 @@ def plot_piecharts(sorted_cosine_scores_models):
 
 
 def plot_alatirchart(sorted_cosine_scores_models):
+
+
     models = list(sorted_cosine_scores_models.keys())
     tabs = st.tabs(models)
     figs = {}
     for model in models:
+        # modified
         figs[model] = plot_piechart_helper(sorted_cosine_scores_models[model])
 
     for index in range(len(tabs)):
@@ -325,12 +321,6 @@ def plot_alatirchart(sorted_cosine_scores_models):
             st.pyplot(figs[models[index]])
 
 
-# 测试
-
-import os
-print("Current Working Directory:", os.getcwd())
-
-
 ### Text Search ###
 st.sidebar.title("GloVe Twitter")
 st.sidebar.markdown(
@@ -343,17 +333,14 @@ Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. *GloVe: Gl
 )
 
 
-# 初始化 Session State 变量
 if 'categories' not in st.session_state:
     st.session_state['categories'] = "Flowers Colors Cars Weather Food"
 if 'text_search' not in st.session_state:
     st.session_state['text_search'] = "Roses are red, trucks are blue, and Seattle is grey right now"
 
-# ... [其余 Streamlit 代码]
 
 model_type = st.sidebar.selectbox("Choose the model", ("25d", "50d"), index=1)
 
-
 st.title("Search Based Retrieval Demo")
 st.subheader(
     "Pass in space separated categories you want this search demo to be about."
@@ -364,12 +351,11 @@ st.subheader(
 # )
 
 
-# 用户输入的 categories
+# categories of user input
 user_categories = st.text_input(
     label="Categories", value=st.session_state.categories
 )
 
-# 更新 Session State 变量 - 修改的地方
 st.session_state.categories = user_categories
 
 # st.text_input(
@@ -395,7 +381,6 @@ user_text_search = st.text_input(
 
 )
 
-# 更新 Session State 变量 - 修改的地方
 st.session_state.text_search = user_text_search
 # st.session_state.text_search = text_search
 
@@ -449,25 +434,21 @@ if st.session_state.text_search:
         + " as per different Embeddings"
     )
 
-    # print(sorted_cosine_sim_glove)
-    # print(sorted_cosine_sim_transformer)
-    # print(sorted_distilbert)
-    # Altair Chart for all models
-    # plot_alatirchart(
-    #     {
-    #         "glove_" + str(model_type): sorted_cosine_sim_glove,
-    #         "sentence_transformer_384": sorted_cosine_sim_transformer,
-    #     }
-    # )
-    # "distilbert_512": sorted_distilbert})
-
-    # 修改的地方！
-    # Display the closest category result for GloVe and Sentence Transformer Embeddings
-    st.write(f"The closest category  in GloVe embeddings is: {list(sorted_cosine_sim_glove.keys())[0]}")
+    print(sorted_cosine_sim_glove)
+    print(sorted_cosine_sim_transformer)
+
+    st.write(f"Closest category using GloVe embeddings : {list(sorted_cosine_sim_glove.keys())[0]}")
     st.write(
-        f"The closest category    in Sentence Transformer embeddings is: {list(sorted_cosine_sim_transformer.keys())[0]}")
+        f"Closest category using Sentence Transformer embeddings : {list(sorted_cosine_sim_transformer.keys())[0]}")
+
+    plot_alatirchart(
+        {
+            "glove_" + str(model_type): sorted_cosine_sim_glove,
+            "sentence_transformer_384": sorted_cosine_sim_transformer,
+        }
+    )
 
     st.write("")
     st.write(
-        "Demo developed by [Dr. Karthik Mohan](https://www.linkedin.com/in/karthik-mohan-72a4b323/)"
+        "Demo developed by [V50](https://huggingface.co/spaces/ericlkc/V50)"
     )