Create app.py

app.py

@@ -0,0 +1,167 @@
+import openai
+import gradio as gr
+
+# env
+openai.api_key = os.environ.get('openai-api')
+
+# Blocks
+with gr.Blocks(theme=gr.themes.Glass()) as demo:
+
+    # REFERENCES
+    languageoptions = ["English", "廣東話"]
+    languagedict = {
+        "English": {
+            "welcome": "Welcome to Make It Work App - Where you can get tailored help thanks to Artificial Intelligence",
+            "whatcanido": "What job I do?",
+            "whatcanidofirst" : "Tell me about you.",
+            "whatcanidolabel": "Write your preferences and we can suggest some options",
+            "interviewquestions": "How to prepare for interview?",
+            "interviewquestionsfirst": "What is the role you're interviewing for?",
+            "interviewquestionslabel": "Answer the questions for this virtual interview",
+            "help": "Where to get help?",
+            "helpfirst": "How can I help you?",
+            "helplabel": "Where do you need help? Here's is what we can suggest"
+        },
+        "廣東話": {
+            "welcome": "歡迎使用 Make It Work App - 借助人工智能，您可以獲得量身定制的幫助",
+            "whatcanido": "我做什麼工作？",
+            "whatcanidofirst" : "介紹一下你自己吧。",
+            "whatcanidolabel": "寫下您的喜好，我們可以建議一些選擇",
+            "interviewquestions": "如何準備面試？",
+            "interviewquestionsfirst": "你面試的角色是什麼？",
+            "interviewquestionslabel": "回答這位 AI 面試官的問題",
+            "help": "去哪裡尋求幫助？",
+            "helpfirst": "我怎麼幫你",
+            "helplabel": "你在哪裡需要幫助？我們會讓您知道如何找到它"
+        }
+        
+    # INTERFACE
+    title = gr.Markdown(value=languagedict['English']['welcome'])
+    language = gr.Dropdown(languageoptions , value= "English")
+    with gr.Tab(languagedict['English']['whatcanido']):
+        chatbot1 = gr.Chatbot()
+        input1 = gr.Textbox(label = languagedict['English']['whatcanidolabel'])
+        state1 = gr.State([])
+    with gr.Tab(languagedict['English']['whatskills']):
+        chatbot2 = gr.Chatbot()
+        input2 = gr.Textbox(label = languagedict['English']['whatskillslabel'])
+        state2 = gr.State([])
+    with gr.Tab(languagedict['English']['interviewquestions']):
+        chatbot3 = gr.Chatbot()
+        input3 = gr.Textbox(label = languagedict['English']['interviewquestionslabel'])
+        state3 = gr.State([])
+    with gr.Tab(languagedict['English']['help']):
+        chatbot4 = gr.Chatbot()
+        input4 = gr.Textbox(label = languagedict['English']['helplabel'])
+        state4 = gr.State([])
+    with gr.Tab("MIW"):
+        code = gr.Textbox(label = 'Code')
+        instructions = gr.Textbox(label = 'Instructions', lines=10, max_lines= 100, visible = False)
+    clear = gr.Button('Clear')
+
+    themewhatcanido = f"""
+You are a career advisor for people in Hong Kong with relatively low skills job.
+Your mission is to ask several questions to then help them identify what are their job options, taking into consideration:
+- Their study level and domain
+- Their level of confort with computer tools (typing, excel, word, ...)
+- Their past working experiences (ex: hair dresser, street cleaner, old care support, restaurant aide, waiter)
+- Their constraints (ex: time available per week, per day)
+- Other relevant questions
+
+Then, when you have enough information, you will thank them and suggest some options, for each of them:
+- Explain the key skills needed
+- Breakdown the potential challenges for them to anticipate
+- Provide advice on how to overcome these challenges
+
+IMPORTANT: write in {language}, in the style of a native inhabitant from Kowloon
+"""
+    
+interviewquestionstheme = f"""
+You are an interviewer, interviewing a candidate for a role [the role will be specified to you].
+Your candidates have limited skills, please find ways to support them and ask all the questions.
+After the candidate answered, write:
+[IDEAL ANSWER] then reformulate the candidate answer to match what would be an ideal response
+
+Then ask another question.
+
+IMPORTANT: write in {language}, in the style of a native inhabitant from Kowloon
+"""
+
+    helptheme = f"""
+You are a social worker, you need to provide some help to the user. He can ask questions relative to:
+- care support for children or elderly in Hong Kong
+- health
+- housing
+- food
+- work
+- leisure
+To answer, use primarily the information indicated here:
+{instructions}
+If the question is not related to any of these topics, answer 'This is beyond my domain of competence, please ask a social worker.'
+
+IMPORTANT: write in {language}, in the style of a native inhabitant from Kowloon
+"""
+    def answer(history):
+        response = openai.ChatCompletion.create(
+            model='gpt-3.5-turbo',
+            messages=history,
+            temperature=0.5,
+            max_tokens=800,
+            top_p=1,
+            n=1,
+            frequency_penalty=0.9,
+            presence_penalty=0.9,
+            stop=None
+        )
+        result = response['choices'][0]['message']['content']
+
+    def init_history(messages_history1, messages_history2, messages_history3): #Reinitialize the state file
+        messages_history1 = [[None,languagedict['English']['whatcanidofirst']]]
+        messages_history2 = [[None,languagedict['English']['interviewquestionsfirst']]]
+        messages_history3 = [[None,languagedict['English']['helpfirst']]]
+        messages_history1 += {"role": "system", "content": themewhatcanido}
+        messages_history1 += {"role": "assistant", "content": languagedict['English']['whatcanidofirst']}
+        messages_history2 += {"role": "system", "content": interviewquestionstheme}
+        messages_history2 += {"role": "assistant", "content": languagedict['English']['interviewquestionsfirst']}
+        messages_history3 += {"role": "system", "content": helptheme}
+        messages_history3 += {"role": "assistant", "content": languagedict['English']['helpfirst']}
+        return messages_history1, messages_history2, messages_history3
+
+    def user(msg, chatbot, state):
+        msg = msg + f"\nRemember to answer in {language}"
+        chatbot += [msg, None]
+        state += {'role':'user','content':'msg'}
+        return msg, chatbot, state
+
+    def bot(chatbot, state, mode):
+        #Bot context
+        if mode = "mode1":
+            context = themewhatcanido
+        elif = mode = "mode2":
+            context = interviewquestionstheme
+        else:
+            context = helptheme
+
+        #remind mission
+        if len(state) = 0:
+            state += {'role':'system','content':f"Take notice of your mission:\n\n{context}"}
+        elif len(state) > 10:
+            state += {'role':'system','content':f"Remember your mission as briefed earlier:\n\n{context}"}
+        response = answer(state)
+        chatbot += [None, response]
+        state += {'role':'assistant','content':'response'}
+        return chatbot, state
+
+    def whatcanido(input1):
+        result = answer(input1, state1)
+    def interviewquestions(input2):
+
+    def help(input3)
+        
+    # Launcher
+    input1.submit(user, [input1, chatbot1, state1], [input1, chatbot1, state1]).then(bot, [chatbot1, state1, "mode1"], [chatbot1, state1])
+    input2.submit(user, [input2, chatbot2, state2], [input2, chatbot2, state2]).then(bot, [chatbot2, state2, "mode2"], [chatbot2, state2])
+    input3.submit(user, [input3, chatbot3, state3], [input3, chatbot3, state3]).then(bot, [chatbot3, state3, "mode3"], [chatbot3, state3])
+    clear.click(lambda: None, None, [chatbot1, chatbot2, chatbot3], queue=True).success(init_history, [state1, state2, state3], [state1, state2, state3])
+demo.queue()
+demo.launch()