更新

app.py

@@ -13,38 +13,42 @@ os.environ["LANGCHAIN_PROJECT"] = "Sequential-Chain"
 
 
 def main():
-    input_checkbox = gr.inputs.Checkbox(label="启用ChatGPT")
-    input_api_key = gr.inputs.Textbox(label="ChatGPT API Key", lines=1)
-    input_api_base = gr.inputs.Textbox(label="ChatGPT API 地址（默认无地址）", lines=1)
-    input_url = gr.inputs.Textbox(label="URL", lines=1)
-    def get_inputs(enabled):
-      if enabled:
-        return [input_api_key, input_api_base]
-      else:
-        return [input_url]
-    inputs = [input_checkbox] + get_inputs(input_checkbox.value)
+    input_checkbox = gr.inputs.Checkbox(label="启用ChatGPT", default=False)
     outputs = "text"
-    update_interface = lambda enabled: gr.Interface(fn=my_inference_function, inputs=get_inputs(enabled), outputs=outputs)
-    interface = gr.Interface(fn=my_inference_function, inputs=inputs, outputs=outputs, examples=[["enabled", "api_key", "api_base", "url"]], title="ChatGPT")
+    interface = gr.Interface(fn=check_model, inputs=input_checkbox, outputs=outputs)
     interface.launch()
 
-def my_inference_function(enabled, api_key, api_base, url):
-        if enabled:
-            os.environ["OPENAI_API_KEY"] = api_key
-            os.environ['OPENAI_API_BASE'] = api_base
-            llm = OpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=1024)
-        else:
-            llm = HuggingFaceHub(repo_id="declare-lab/flan-alpaca-large", model_kwargs={"temperature":0.1, "max_length":512})
+def check_model(enabled):
+  input_api_key = gr.inputs.Textbox(label="ChatGPT API Key", lines=1)
+  input_api_base = gr.inputs.Textbox(label="ChatGPT API 地址（默认无地址）", lines=1)
+  input_url = gr.inputs.Textbox(label="URL", lines=1)
+  if enabled:
+    return [input_url,input_api_key, input_api_base]
+  else:
+    return [input_url]
+
+def my_chatgpt_function(api_key, api_base, url):
+        os.environ["OPENAI_API_KEY"] = api_key
+        os.environ['OPENAI_API_BASE'] = api_base
+        llm = OpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=1024)
         loader = UnstructuredURLLoader(urls=[url])
         data = loader.load()
         chain = load_qa_chain(llm=llm, chain_type="stuff")
         response = chain.run(input_documents=data, question="""请用中文总结文章的内容，并以下面模版给出结果：
-《文章标题》摘要如下：
-## 一句话描述
-文章摘要内容
-## 文章略读
-文章要点""")
+        《文章标题》摘要如下：
+        ## 一句话描述
+        文章摘要内容
+        ## 文章略读
+        文章要点""")
         return response
 
+def my_inference_function(url):
+  llm = HuggingFaceHub(repo_id="declare-lab/flan-alpaca-large", model_kwargs={"temperature":0.1, "max_length":512})
+  loader = UnstructuredURLLoader(urls=[url])
+  data = loader.load()
+  chain = load_qa_chain(llm=llm, chain_type="stuff")
+  response = chain.run(input_documents=data, question="Summarize this article in one paragraph")
+  return response
+
 if __name__ == '__main__':
     main()