Update app.py

app.py

@@ -1,64 +1,35 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+import pandas as pd
+import matplotlib.pyplot as plt
+import gradio as gr
 
-    messages.append({"role": "user", "content": message})
+def analyze_csv(file):
+    df = pd.read_csv(file.name)
 
-    response = ""
+    # 统计分析
+    stats = df.describe().loc[["mean", "std", "min", "max"]].round(2).to_string()
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    # 生成图像：Income vs SpendingScore
+    plt.figure(figsize=(6, 4))
+    plt.scatter(df["Income"], df["SpendingScore"], alpha=0.7)
+    plt.title("Income vs Spending Score")
+    plt.xlabel("Income")
+    plt.ylabel("Spending Score")
+    plt.grid(True)
 
-        response += token
-        yield response
+    img_path = "income_vs_score.png"
+    plt.savefig(img_path)
+    plt.close()
 
+    return stats, img_path
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+iface = gr.Interface(
+    fn=analyze_csv,
+    inputs=gr.File(label="Upload CSV File", file_types=[".csv"]),
+    outputs=[gr.Text(label="📊 Statistical Summary"), gr.Image(label="📈 Income vs Spending Score")],
+    title="📊 表格分析大模型",
+    description="上传一个CSV表格，我将输出统计分析结果并展示一张图表。"
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    iface.launch()