Add function to retrieve chatbot rankings

A new function called 'get_rankings' has been added to the 'guardrails_buttons.py' file. This function fetches rankings from an API and generates a sorted markdown table. Also, necessary changes have been made to other files to integrate and display this ranking data in the user interface.

app.py

@@ -13,6 +13,7 @@ from guardrails_buttons import (
     deactivate_invisible_vote_buttons,
     deactivate_textbox,
     deactivate_visible_vote_buttons,
+    get_rankings,
     leftvote,
     rightvote,
     share_js,
@@ -213,7 +214,7 @@ with gr.Blocks(
         background-size: cover; /* Adjust as needed */
         background-position: center;
     }
-    #model_description_markdown table {
+    #model_description_markdown table, #leaderboard table {
         width: 100%;
     }
     .w-100 {
@@ -280,6 +281,7 @@ with gr.Blocks(
         states = [gr.State() for _ in range(num_sides)]
         chatbots = [None] * num_sides
         models = gr.State(get_random_models)
+        rankings = gr.State("")
         system_prompt = gr.State(get_random_system_prompt)
         show_models = [None] * num_sides
         conversation_id = gr.State()
@@ -447,14 +449,10 @@ with gr.Blocks(
             """
         )
 
-    with gr.Tab(label="🏆 Leaderboard"):
-        gr.Markdown(
-            """
-            ## 🏆 Guardrails Leaderboard
-            
-            We will launch the guardrails leaderboard once enough votes are collected. Ranking will be calculated based on ELO ratings. Keep playing so that we can collect enough data.
-            """
-        )
+    with gr.Tab(label="🏆 Leaderboard", elem_id="leaderboard") as leaderboard_tab:
+        gr.Markdown("## 🏆 Guardrails Leaderboard")
+        rankings = gr.Markdown("")
+        leaderboard_tab.select(get_rankings, None, [rankings])
 
     gr.Markdown(
         """

guardrails_buttons.py

@@ -143,6 +143,33 @@ def bothbadvote(conversation_id, history1, history2):
         pass
 
 
+def get_rankings():
+    try:
+        response = requests.get(f"{LIGHTHOUZ_API_URL}/rankings")
+        ratings = response.json()["ratings"]
+        sorted_ratings = dict(
+            sorted(ratings.items(), key=lambda item: item[1], reverse=True)
+        )
+
+        markdown_table = "| Rank | Chatbots | Arena Elo |\n|:-----:|-----|-------|\n"
+        current_rank = 1
+        last_value = None
+        rank_increment = 0
+        for key, value in sorted_ratings.items():
+            rounded_value = round(value)
+            if last_value is None or rounded_value != last_value:
+                current_rank += rank_increment
+                rank_increment = 0
+            markdown_table += f"| {current_rank} | {key} | {rounded_value} |\n"
+            last_value = rounded_value
+            rank_increment += 1
+
+        return markdown_table
+    except Exception as e:
+        print(e)
+        return ""
+
+
 def show_models_fn(models):
     model_1 = gr.Markdown(" 🅰️ " + models[0]["name"])
     model_2 = gr.Markdown(" 🅱️ " + models[1]["name"])

guardrails_models.py

@@ -5,9 +5,9 @@ from typing import List, Optional
 import openai
 from google.generativeai.types import (
     BlockedPromptException,
-    StopCandidateException,
-    HarmCategory,
     HarmBlockThreshold,
+    HarmCategory,
+    StopCandidateException,
 )
 from langchain_community.chat_models import ChatAnyscale
 from langchain_core.messages import AIMessage, HumanMessage, SystemMessage

llamaguard_moderator.py

@@ -127,8 +127,6 @@ Provide your safety assessment for $agent_type in the above conversation:
 - If unsafe, a second line must include a comma-separated list of violated categories."""
 )
 
-print(PROMPT_TEMPLATE)
-
 
 def format_prompt(role, message):
     prompt = PROMPT_TEMPLATE.substitute(prompt=message, agent_type=role)