Create app.py

app.py

@@ -0,0 +1,45 @@
+import gradio as gr
+from transformers import pipeline
+
+llm = pipeline("text-generation", model="gpt2")  # 替换为你喜欢的模型
+
+def run_chain(prompts):
+    results = []
+    context = ""
+    for p in prompts:
+        prompt = p.replace("{input}", context)
+        response = llm(prompt, max_new_tokens=100)[0]["generated_text"]
+        # 提取新增部分
+        new_output = response[len(prompt):].strip()
+        results.append(new_output)
+        context = new_output
+    return results
+
+with gr.Blocks() as demo:
+    prompt_boxes = []
+    output_boxes = []
+
+    with gr.Row():
+        prompt_list = gr.State([])
+        out_list = gr.State([])
+
+    def add_prompt(prompt_list, out_list):
+        prompt_list.append("")
+        out_list.append("")
+        return prompt_list, out_list
+
+    add_btn = gr.Button("➕ 添加一个 Prompt")
+    run_btn = gr.Button("🚀 运行 Chain")
+
+    prompts_display = gr.Textbox(lines=15, label="Prompt Chain (用{input}引用上一轮输出)", interactive=True, elem_id="prompt_chain")
+    outputs_display = gr.Textbox(lines=15, label="模型输出", interactive=False)
+
+    def run_all(prompts_str):
+        prompts = prompts_str.strip().split("\n---\n")
+        outputs = run_chain(prompts)
+        return "\n---\n".join(outputs)
+
+    add_btn.click(fn=add_prompt, inputs=[prompt_list, out_list], outputs=[prompt_list, out_list])
+    run_btn.click(fn=run_all, inputs=prompts_display, outputs=outputs_display)
+
+demo.launch()