add app

README.md

@@ -1,8 +1,8 @@
 ---
-title: Ddfd
-emoji: 👀
-colorFrom: gray
-colorTo: indigo
+title: Unlp
+emoji: 🌖
+colorFrom: pink
+colorTo: yellow
 sdk: gradio
 sdk_version: 4.19.2
 app_file: app.py

app.py

@@ -0,0 +1,221 @@
+import gradio as gr
+import pandas as pd
+import random
+import firebase_admin
+from firebase_admin import credentials
+from firebase_admin import firestore
+
+CSV_FILE_PATH = "qa_pairs.csv"
+
+cred = credentials.Certificate("unlpboard_f.json")
+firebase_admin.initialize_app(cred)
+
+def list_models():
+    df = pd.read_csv(CSV_FILE_PATH)
+    return df['model'].unique().tolist()
+
+
+def list_questions():
+    df = pd.read_csv(CSV_FILE_PATH)
+    return df['question'].unique().tolist()
+
+def fetch_questions():
+    questions_ref = db.collection('questions')
+    docs = questions_ref.stream()
+    questions_list = []
+    for doc in docs:
+        question = doc.to_dict()
+        questions_list.append(question)
+    return questions_list
+
+
+def display_answers(question, model1, model2):
+    df = pd.read_csv(CSV_FILE_PATH)
+    answers = {
+        model1: "No answer available for Model 1",
+        model2: "No answer available for Model 2",
+    }
+    for model in [model1, model2]:
+        filtered_df = df[(df['question'] == question) & (df['model'] == model)]
+        if not filtered_df.empty:
+            answers[model] = f"**{model} Answer:**\n{filtered_df['answer'].iloc[0]}"
+    return answers[model1], answers[model2]
+
+
+def update_b(q,m1,a1,m2,a2):
+    print('Model1: ', random_model2)
+    print('Model2: ', random_model2)
+    q, m1, a1, m2, a2 = update_symbols(q, m1, a1, m2, a2)
+    b1 = gr.Button("Vote for Model 1",interactive=True)
+    b2 = gr.Button("It’s a tie!",interactive=True)
+    b3 = gr.Button("Vote for Model 2",interactive=True)
+    b4 = gr.Button("START!", visible = False)
+    return q, m1, a1, m2, a2, b1, b2, b3, b4
+
+
+def update_symbols1(q,m1,a1,m2,a2):
+    print("Voted for Model 1")
+    log_vote(
+        model1=m1,
+        model2=m2,
+        question=q,
+        output1=a1,
+        output2=a2,
+        outcome=m1
+    )
+    votes_ref = db.collection('votes')
+    vote_doc = votes_ref.document(m1).get()
+    if vote_doc.exists:
+        votes_ref.document(m1).update({'count': firestore.Increment(1)})
+    else:
+        votes_ref.document(m1).set({'count': 1})
+    update_total_votes()
+    return update_symbols(q, m1, a1, m2, a2)
+
+
+def update_symbols2(q, m1, a1, m2, a2):
+    print("Voted for Spare")
+    log_vote(
+        model1=m1,
+        model2=m2,
+        question=q,
+        output1=a1,
+        output2=a2,
+        outcome='tie'
+    )
+    update_total_votes()
+    return update_symbols(q, m1, a1, m2, a2)
+
+def update_symbols3(q, m1, a1, m2, a2):
+    print("Voted for Model 2")
+    log_vote(
+        model1=m1,
+        model2=m2,
+        question=q,
+        output1=a1,
+        output2=a2,
+        outcome=m2
+    )
+    votes_ref = db.collection('votes')
+    vote_doc = votes_ref.document(m2).get()
+    if vote_doc.exists:
+        votes_ref.document(m2).update({'count': firestore.Increment(1)})
+    else:
+        votes_ref.document(m2).set({'count': 1})
+    update_total_votes()
+    return update_symbols(q, m1, a1, m2, a2)
+
+def update_symbols(q,m1,a1,m2,a2):
+    random_question = random.choice(questions)
+    random_model1, random_model2 = random.sample(models, 2)
+    answer1, answer2 = display_answers(random_question, random_model1, random_model2)
+    m1 = gr.Markdown(f"{random_model1}", visible=False)
+    a1 = gr.Markdown(answer1)
+    q = gr.Markdown(f"{random_question}")
+    m2 = gr.Markdown(f"{random_model2}", visible=False)
+    a2 = gr.Markdown(answer2)
+    return q,m1,a1,m2,a2
+
+def update_total_votes():
+    votes_ref = db.collection('votes')
+    vote_doc = votes_ref.document('total').get()
+    if vote_doc.exists:
+        votes_ref.document('total').update({'count': firestore.Increment(1)})
+    else:
+        votes_ref.document('total').set({'count': 1})
+
+def log_vote(model1, model2, question, output1, output2, outcome):
+    # Reference to the Firestore collection where votes will be logged
+    votes_log_ref = db.collection('votes_log')
+
+    # Create a new document for this vote
+    vote_data = {
+        'model1': model1,
+        'model2': model2,
+        'question': question,
+        'output1': output1,
+        'output2': output2,
+        'outcome': outcome,
+        'timestamp': firestore.SERVER_TIMESTAMP
+    }
+
+    # Add the vote document to Firestore
+    votes_log_ref.add(vote_data)
+
+
+def fetch_and_format_leaderboard():
+    vote_counts_ref = db.collection('votes')
+    # Ensure you're using FieldPath.document_id() correctly
+    docs = vote_counts_ref.stream()
+
+    leaderboard = []
+    for doc in docs:
+        model_name = doc.id
+        vote_count = doc.to_dict().get('count', 0)
+        leaderboard.append(f"{model_name}: {vote_count} votes")
+
+    # Optional: Sort the leaderboard by vote count in descending order
+    leaderboard.sort(key=lambda x: int(x.split(': ')[1].split(' ')[0]), reverse=True)
+
+    return "\n".join(leaderboard)
+
+#questions = list_questions()
+models = list_models()
+random_question = 'Click any button to start!'
+random_model1, random_model2 = '1', '2'
+answer1, answer2 = display_answers(random_question, random_model1, random_model2)
+
+
+db = firestore.client()
+
+questions = []
+questions_ = fetch_questions()
+for question in questions_:
+    questions.append(question['question_text'])
+
+votes_ref = db.collection('votes')
+
+def create_app():
+
+    print('-----------------------')
+    print(random_question)
+    print(random_model1)
+    print('-----!!!!!!!!!!!!!')
+
+    with gr.Blocks() as app:
+        q = gr.Markdown(f"### Question: {random_question}")
+
+        with gr.Row():
+            with gr.Column():
+                m1 = gr.Markdown(f"{random_model1}", visible=False)
+                a1 = gr.Markdown(answer1)
+
+            with gr.Column():
+                m2 = gr.Markdown(f"{random_model2}", visible=False)
+                a2 = gr.Markdown(answer2)
+
+        with gr.Row():
+            b1 = gr.Button("Vote for Model 1",interactive=False)
+            b2 = gr.Button("It’s a tie!",interactive=False)
+            b3 = gr.Button("Vote for Model 2",interactive=False)
+        with gr.Row():
+            b4 = gr.Button("START!", interactive=True)
+        #with gr.Row():
+        #    b5 = gr.Button("Show Leaderboard")
+
+        initial_leaderboard_data = fetch_and_format_leaderboard()
+        leaderboard_display = gr.Textbox(value=initial_leaderboard_data,label="Leaderboard", placeholder="Leaderboard will be displayed here.",
+                                              lines=30, visible=True)
+        #b5.click(fn=fetch_and_format_leaderboard, inputs=[], outputs=leaderboard_display)
+
+        b4.click(update_b, inputs=[q,m1,a1,m2,a2], outputs=[q,m1,a1,m2,a2,b1,b2,b3, b4])
+        b1.click(update_symbols1, inputs=[q,m1,a1,m2,a2], outputs=[q,m1,a1,m2,a2])
+        b2.click(update_symbols2, inputs=[q, m1, a1, m2, a2], outputs=[q, m1, a1, m2, a2])
+        b3.click(update_symbols3, inputs=[q, m1, a1, m2, a2], outputs=[q, m1, a1, m2, a2])
+        leaderboard_button = gr.Button("Refresh Leaderboard")
+        leaderboard_button.click(fn=fetch_and_format_leaderboard, inputs=[], outputs=leaderboard_display)
+
+    return app
+
+app = create_app()
+app.launch()

qa_pairs.csv

@@ -0,0 +1,8 @@
+question,answer,model
+What is the capital of France?,Paris,Model A
+What is the capital of France?,Brussels,Model B
+What is the capital of France?,Kyiv,Model C
+Who wrote '1984'?,George Orwell,Model A
+What is the speed of light?,"Approximately 299,792 kilometers per second",Model B
+What is the largest ocean?,Pacific Ocean,Model B
+Who painted the Mona Lisa?,Leonardo da Vinci,Model C

requirements.txt

@@ -0,0 +1,2 @@
+firebase-admin
+pandas

unlpboard_f.json

@@ -0,0 +1,13 @@
+{
+  "type": "service_account",
+  "project_id": "unlpboard",
+  "private_key_id": "cb34c2f851e6be6a6e1561c3cd5e3bb3492295b6",
+  "private_key": "-----BEGIN PRIVATE KEY-----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\ngMLcBMCeNTmPm8uvQL9U4PdvmQ==\n-----END PRIVATE KEY-----\n",
+  "client_email": "firebase-adminsdk-bj4ah@unlpboard.iam.gserviceaccount.com",
+  "client_id": "103161232823398026076",
+  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
+  "token_uri": "https://oauth2.googleapis.com/token",
+  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
+  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-bj4ah%40unlpboard.iam.gserviceaccount.com",
+  "universe_domain": "googleapis.com"
+}