Update app.py

app.py

@@ -1,23 +1,23 @@
 import os
 import shutil
 import gradio as gr
-from transformers import ReactCodeAgent, HfApiEngine, Tool
+from smolagents import CodeAgent, HfApiModel, Tool
 import pandas as pd
 
 from gradio import Chatbot
-from transformers.agents import stream_to_gradio
+from smolagents import stream_to_gradio
 from huggingface_hub import login
 from gradio.data_classes import FileData
 
 login(os.getenv("HUGGINGFACEHUB_API_TOKEN"))
 
-llm_engine = HfApiEngine("meta-llama/Meta-Llama-3.1-70B-Instruct")
+llm_engine = HfApiModel("Qwen/Qwen2.5-Coder-32B-Instruct")
 
-agent = ReactCodeAgent(
+agent = CodeAgent(
     tools=[],
-    llm_engine=llm_engine,
+    model=model,
     additional_authorized_imports=["numpy", "pandas", "matplotlib.pyplot", "seaborn", "scipy.stats"],
-    max_iterations=10,
+    max_steps=10,
 )
 
 base_prompt = """You are an expert data analyst.
@@ -105,9 +105,9 @@ with gr.Blocks(
         secondary_hue=gr.themes.colors.blue,
     )
 ) as demo:
-    gr.Markdown("""# Llama-3.1 Data analyst 📊🤔
+    gr.Markdown("""# Qwen-2.5-Coder Data analyst 📊🤔
 
-Drop a `.csv` file below, add notes to describe this data if needed, and **Llama-3.1-70B will analyze the file content and draw figures for you!**""")
+Drop a `.csv` file below, add notes to describe this data if needed, and **`Qwen2.5-Coder-32B-Instruct` will analyze the file content and draw figures for you!**""")
     file_input = gr.File(label="Your file to analyze")
     text_input = gr.Textbox(
         label="Additional notes to support the analysis"
@@ -118,7 +118,7 @@ Drop a `.csv` file below, add notes to describe this data if needed, and **Llama
         type="messages",
         avatar_images=(
             None,
-            "https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png",
+            "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/smolagents/mascot.png",
         ),
     )
     gr.Examples(