Update app.py

app.py

@@ -1,37 +1,46 @@
 import gradio as gr
 import os
-import openai
-import json
-import re
 
-import gradio as gr
-import langchain
-from langchain import OpenAI,PromptTemplate,LLMChain
-
-#need to plugin the part to prompt the user to input the API Key
-import os
-#os.environ["OPENAI_API_KEY"] = "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"
-
-llm = OpenAI(model_name="text-davinci-003",openai_api_key=openai_api_key)
-
-template = 'question:{question}'
-prompt = PromptTemplate(template=template, input_variables=["question"])
-
-chain = LLMChain(llm=llm,prompt=prompt)
-
-
-def answer(question,openai_api_key):
-  os.environ["OPENAI_API_KEY"] = openai_api_key
-  out=chain.run(question)
-  return out
-
-demo = gr.Interface(fn=answer, 
-                    inputs=[
-        gr.Textbox(label="Question:"),
+from langchain.agents import load_tools
+from langchain.agents import initialize_agent
+from langchain.agents import AgentType
+from langchain.llms import OpenAI
+
+def get_response(input, google_cse_id, google_api_key, openai_api_key):
+    os.environ["GOOGLE_CSE_ID"] = google_cse_id
+    os.environ["GOOGLE_API_KEY"] = google_api_key
+    os.environ["OPENAI_API_KEY"] = openai_api_key
+
+    llm = OpenAI(temperature=0)
+    tools = load_tools(["google-search", "llm-math"], llm=llm)
+    agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True, return_intermediate_steps=True)
+
+    response = agent({"input": input})
+    return response["output"], response["intermediate_steps"]
+
+iface = gr.Interface(
+    fn=get_response,
+    inputs=[
+        gr.Textbox(label="Goal definition:"),
+        gr.Textbox(label="Google CSE - ID:", type="text"),
+        gr.Textbox(label="Google API KEY:", type="password"),
         gr.Textbox(label="OpenAI API KEY:", placeholder="sk-...", type="password")
     ],
-                    outputs='text',
-                    title="LangChain Demo",
-                    examples=[['What is the greatest threat to the birds of paradise?']])
-demo.launch()
+    outputs=[
+        gr.Textbox(label="Goal output:"),
+        gr.Json(label="Intermediate Steps")
+    ],
+    title="GPT Agents Demo",
+    description="Demo application of gpt-based agents including two tools (google-search and llm-math). The result and intermediate steps are included."
+)
+
+# error capturing in integration as a component
+
+error_message = ""
 
+try:
+    iface.queue(concurrency_count=20)
+    iface.launch()
+except Exception as e:
+    error_message = "An error occurred: " + str(e)
+    iface.outputs[1].value = error_message