Update app.py

app.py

@@ -43,7 +43,7 @@ def get_learning_curriculum(openapikey,topic):
     )
     tasklist=json.loads(resp['choices'][0]['message']['content'])
 
-    ###Function to search the internet using Duck-Duck-Go exposed as a tool
+    ###Function to search the internet using DuckDuckGo exposed as a tool
     def research_search(search_keyword,question_to_ask,topic):
       llm_predictor = LLMPredictor(llm=OpenAIChat(temperature=0, model_name="gpt-3.5-turbo"))
       service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor)
@@ -90,7 +90,7 @@ def get_learning_curriculum(openapikey,topic):
 with gr.Blocks() as demo:
     gr.Markdown("<h1><center>BabyAGI creates Learning Curriculum</center></h1>")
     gr.Markdown(
-        """ This is the first step of an experiment using BabyAGI as a "framework" to construct focused use cases (ex: learning curriculums). The flow uses two AI agents 1) Task creation agent: to create a task list & questions 2) Task execution agent: to execute the tasks & find answers to the questions. Unlike the original BabyAGI concept, this is not open-ended. \n\nNote: This is a series of experiments to understand AI agents and hence do check the output for quality. OpenAI agents (gpt-3.5-turbo) & llama-index are used. The analysis takes roughly 120 secs & may not always be consistent. An error occurs when the OpenAI Api key is not provided/ ChatGPT API is overloaded/ChatGPT is unable to correctly decipher & format the output\n\n Future directions: 1) Make the task creation more open-ended or longer. 2) Discover multiple learning paths and make ChatGPT introspect on them before finalizing the optimal one 3)Learn from the answers and change the curriculum![visitors](https://visitor-badge.glitch.me/badge?page_id=hra/Curriculum-BabyAGI)"""
+        """ This is the first step of an experiment using BabyAGI as a "framework" to construct focused use cases (ex: learning curriculums). The flow uses two AI agents 1) Task creation agent: to create a task list & questions 2) Task execution agent: to execute the tasks & find answers to the questions. Unlike the original BabyAGI concept, this is not open-ended. \n\nNote: This is a series of experiments to understand AI agents and hence do check the quality of output. OpenAI agents (gpt-3.5-turbo), llama-index & DuckDuckGo search are used. The analysis takes roughly 120 secs & may not always be consistent. An error occurs when the OpenAI Api key is not provided/ ChatGPT API is overloaded/ ChatGPT is unable to correctly decipher & format the output\n\n Future directions: 1) Make the task creation more open-ended or longer. 2) Discover multiple learning paths and make ChatGPT introspect on them before finalizing the optimal one 3)Learn from the answers and change the curriculum![visitors](https://visitor-badge.glitch.me/badge?page_id=hra/Curriculum-BabyAGI)"""
         )
     
     with gr.Row() as row: