Upload more metrics and fix some issues in app.py

app.py

@@ -2,7 +2,6 @@ import os
 import streamlit as st
 import json
 import tarfile
-from base64 import b64encode
 
 st.set_page_config(layout="wide")
 
@@ -13,10 +12,8 @@ st.markdown("""The K2 gallery allows one to browse the output of various evaluat
 
 
 with st.sidebar:
-    with open(os.path.join(PARENT_DIR, "k2-logo.svg"), 'r') as f:
-        b64 = b64encode(f.read().encode('utf-8')).decode("utf-8")
-        html = f"<img src='https://www.llm360.ai/images/logo-highres.png' width='100' /><img src='data:image/svg+xml;base64,{b64}' width='100' />"
-        st.markdown(html, unsafe_allow_html=True)
+    html = f"<img src='https://www.llm360.ai/images/logo-highres.png' width='100' /><img src='https://huggingface.co/spaces/LLM360/k2-eval-gallery/raw/main/k2-logo.svg' width='100' />"
+    st.markdown(html, unsafe_allow_html=True)
 
     metric = st.radio(
         "Choose a metric", options=os.listdir(os.path.join(EVAL_DIR))
@@ -28,18 +25,24 @@ with st.sidebar:
 
 col1, col2 = st.columns(2)
 
-with col1:
-    st.header("Checkpoint A")
-    ckpt = st.selectbox('Select a checkpoint', sorted(os.listdir(os.path.join(EVAL_DIR, metric, n_shot))), key="A1")
+def render_column(col_label):
+    st.header(f"Checkpoint {col_label}")
+    ckpt = st.select_slider('Select a checkpoint', sorted(os.listdir(os.path.join(EVAL_DIR, metric, n_shot))), key=col_label + '1')
     st.write(f'Veiwing Evaluation Results for Checkpoint: `{ckpt}`')
-    file = st.selectbox("Select a file", sorted(os.listdir(os.path.join(EVAL_DIR, metric, n_shot, ckpt))), key="A2")
-    with tarfile.open(os.path.join(EVAL_DIR, metric, n_shot, ckpt, file), "r:gz") as f:
-        st.json(json.load(f.extractfile(f.next())))
+    file = st.selectbox("Select a file", sorted(f_name[:-len(".tar.gz")] for f_name in os.listdir(os.path.join(EVAL_DIR, metric, n_shot, ckpt))), key=col_label + '2')
+    file += ".tar.gz"
+    with tarfile.open(os.path.join(EVAL_DIR, metric, n_shot, ckpt, file), "r:gz") as tar:
+        f = tar.extractfile(tar.next())
+        eval_json = json.load(f)
+        if isinstance(eval_json, list):
+            doc_id = st.slider("Select a document id", 0, len(eval_json) - 1, 0, 1, key=col_label + '3')
+            st.json(eval_json[doc_id])
+        else:
+            st.json(eval_json)
+        f.close()
+
+with col1:
+    render_column('A')
 
 with col2:
-    st.header("Checkpoint B")
-    ckpt = st.selectbox('Select a checkpoint', sorted(os.listdir(os.path.join(EVAL_DIR, metric, n_shot))), key="B1")
-    st.write(f'Veiwing Evaluation Results for Checkpoint: `{ckpt}`')
-    file = st.selectbox("Select a file", sorted(os.listdir(os.path.join(EVAL_DIR, metric, n_shot, ckpt))), key="B2")
-    with tarfile.open(os.path.join(EVAL_DIR, metric, n_shot, ckpt, file), "r:gz") as f:
-        st.json(json.load(f.extractfile(f.next())))
+    render_column('B')