Initial commit

.gitignore

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+.idea/*
+data.json

app.py

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+import os
+import time
+import json
+import openai
+import gradio as gr
+from datetime import datetime
+from openai.error import RateLimitError, APIConnectionError, Timeout, APIError, \
+    ServiceUnavailableError, InvalidRequestError
+from huggingface_hub import hf_hub_download, HfApi
+
+openai.api_key = os.environ.get('API_KEY')
+
+score_parameters = [
+    'Personalidad', 'Intereses', 'Lenguaje/Estilo',
+    'Autenticidad', 'Habilidad de conversación',
+    'Marca/Producto', 'Identificación', 'Experiencia de uso',
+    'Recomendacion', 'Conversación organica'
+]
+
+authors = ['Sofia', 'Eliza', 'Sindy', 'Carlos', 'Andres', 'Adriana', 'Carolina', 'Valeria']
+
+models = ["gpt-4"]
+
+temperature_values = [0.2, 0.8, 1.0]
+
+
+def innit_bot():
+    """
+    Initialize the bot by adding the prompt from the txt file to the messages history
+    """
+    with open('prompt.txt', encoding='utf-8') as file:
+        prompt = file.read()
+    message_history = [{"role": "system", "content": prompt}]
+
+    return message_history
+
+
+def make_visible():
+    """
+    Makes visible the returned elements
+    """
+    return (
+        gr.Chatbot.update(visible=True),
+        gr.Textbox.update(visible=True),
+        gr.Row.update(visible=True))
+
+def make_noninteractive():
+    """
+    Makes no interactive the returned elements
+    """
+    return (
+        gr.Dropdown.update(interactive=False),
+        gr.Radio.update(interactive=False))
+
+
+def call_api(model: gr.Dropdown, msg_history: gr.State, temperature: gr.State):
+    """
+    Returns the API's response
+    """
+    response = openai.ChatCompletion.create(
+        model=model,
+        messages=msg_history,
+        temperature=temperature
+    )
+    return response
+
+
+def handle_call(model: gr.Dropdown, msg_history: gr.State, temperature: gr.State):
+    """
+    Returns the response and waiting time of the AI. It also handles the possible errors
+    """
+    tries = 0
+    max_tries = 3
+    while True:
+        try:
+            start_time = time.time()
+            response = call_api(model, msg_history, temperature)
+            end_time = time.time()
+            break
+
+        except InvalidRequestError as e:
+            print(e)
+            response = 'Ya no tienes mas tokens disponibles. Envia lo que tengas hasta el momento e inicia otro chat'
+            raise gr.Error(response)
+
+        except (RateLimitError, APIError, Timeout, APIConnectionError, ServiceUnavailableError) as e:
+            print(e)
+
+            if tries == max_tries:
+                response = "Despues de muchos intentos, no se pudo completar la comunicacion con OpenAI. " \
+                           "Envia lo que tengas hasta el momento e inicia un chat nuevo dentro de unos minutos."
+                raise gr.Error(response)
+
+            tries += 1
+            time.sleep(60)
+
+    needed_time = end_time - start_time
+    return response, needed_time
+
+
+def get_ai_answer(msg: str, model: gr.Dropdown, msg_history: gr.State, temperature: gr.State):
+    """
+    Returns the response given by the model, all the message history so far and the seconds
+    the api took to retrieve such response. Both depend on the model
+    """
+    msg_history.append({"role": "user", "content": msg})
+    response, needed_time = handle_call(model, msg_history, temperature)
+    AI_response = response["choices"][0]["message"]["content"]
+    msg_history.append({'role': 'assistant', 'content': AI_response})
+
+    return AI_response, msg_history, needed_time
+
+
+def get_answer(
+        msg: str, msg_history: gr.State,
+        chatbot_history: gr.Chatbot, waiting_time: gr.State,
+        temperature: gr.State, model: gr.Dropdown):
+    """
+    Cleans msg box, adds the new message to the message history,
+    gets the answer from the bot and adds it to the chatbot history
+    and gets the time needed to get such answer and saves it
+    """
+
+    # Get bot answer (output), messages history and waiting time
+    AI_response, msg_history, needed_time = get_ai_answer(msg, model, msg_history, temperature)
+
+    # Save waiting time
+    waiting_time.append(needed_time)
+
+    # Save output in the chat
+    chatbot_history.append((msg, AI_response))
+
+    return "", msg_history, chatbot_history, waiting_time
+
+
+def save_scores(
+        author: gr.Dropdown, temperature: gr.State,
+        history: gr.Chatbot, waiting_time: gr.State,
+        model: gr.Dropdown, opinion: gr.Textbox, *score_values):
+    """
+    Saves the scores and chat's info into the json file
+    """
+    # Get the score of each parameter
+    scores = dict()
+    for parameter, score in zip(score_parameters, score_values):
+
+        # Check the score is a valid value if not, raise Error
+        if score is None:
+            raise gr.Error('Asegurese de haber seleccionado al menos 1 opcion en cada categoria')
+
+        scores[parameter] = score
+
+    # Get all the messages including their reaction
+    chat = []
+    for conversation in history:
+        info = {
+            'message': conversation[0],
+            'answer': conversation[1],
+            'waiting': waiting_time.pop(0)
+        }
+        chat.append(info)
+
+    date = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
+    with open('prompt.txt', encoding='utf-8') as file:
+        prompt = file.read()
+
+    # Save the info
+    session = dict(
+        prompt=prompt,
+        temperature=temperature,
+        scores=scores,
+        opinion=opinion,
+        chat=chat,
+        author=author,
+        model=model,
+        date=date
+    )
+
+    # Open the file, add the new info and save it
+    hf_hub_download(
+        repo_id=os.environ.get('DATA'), repo_type='dataset', filename="data.json", token=os.environ.get('HUB_TOKEN'),
+        local_dir="./"
+    )
+
+    with open('data.json', 'r') as infile:
+        past_sessions = json.load(infile)
+
+    # Add the new info
+    past_sessions['sessions'].append(session)
+    with open('data.json', 'w', encoding='utf-8') as outfile:
+        json.dump(past_sessions, outfile, indent=4, ensure_ascii=False)
+
+    # Save the updated file
+    api = HfApi(token=os.environ.get('HUB_TOKEN'))
+    api.upload_file(
+        path_or_fileobj="data.json",
+        path_in_repo="data.json",
+        repo_id=os.environ.get('DATA'),
+    )
+
+    # Return a confirmation message
+    return 'Done'
+
+
+with gr.Blocks() as app:
+    msg_history = gr.State()  # Messages with the format used by OpenAI
+    waiting_time = gr.State([])  # Seconds needed to get each answer
+
+    with gr.Tab('Test Chats'):
+        with gr.Row():
+            model = gr.Textbox(value=models[0], label='Model', interactive=False)
+            author = gr.Dropdown(authors, value=authors[0], label='Author', interactive=True)
+            temperature = gr.Radio(temperature_values, label="Randomness", value=0.2)
+            chat_btn = gr.Button(value='Start chat')
+
+        # ------------------------------------- Chat -------------------------------------------
+        chatbot = gr.Chatbot(label='Chat', visible=False)
+        message = gr.Textbox(label='Message', visible=False)
+
+    # ------------------------------------- Result's tab ---------------------------------------
+    with gr.Tab('Save results'):
+        with gr.Row(visible=False) as scores_row:
+            with gr.Column(scale=75):
+                with gr.Row():
+                    scores = [
+                        gr.Radio(choices=['Aprovado', 'No aprovado'], label=parameter)
+                        for parameter in score_parameters
+                    ]
+            with gr.Column(scale=25):
+                opinion_box = gr.Textbox(label='Opinion')
+                scores_btn = gr.Button(value='Send scores')
+                scores_box = gr.Textbox(label='Status', interactive=False)
+
+    # -------------------------------------- Actions -----------------------------------------
+    chat_btn.click(
+        innit_bot, None, [msg_history]
+    ).then(
+        make_noninteractive, None, [author, temperature]
+    ).then(
+        make_visible, None, [
+            chatbot, message, scores_row]
+    )
+
+    message.submit(
+        get_answer,
+        [message, msg_history, chatbot, waiting_time, temperature, model],
+        [message, msg_history, chatbot, waiting_time])
+
+    scores_btn.click(
+        save_scores,
+        [author, temperature, chatbot, waiting_time, model, opinion_box] + scores,
+        scores_box)
+
+
+app.launch(debug=True, auth=(os.environ.get('USERNAME'), os.environ.get('PASSWORD')))

prompt.txt

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+Tu nombre es Roomie, en los proximos parrafos definire quien eres, tu personalidad, saludo, despedida, publico , y tu objetivo.
+
+Quien eres: eres un habitante de Centennialz planet, que vive en la tierra.
+
+Personalidad: Eres extrovertido, divertido,  curioso, fresco, creativo, atento, respuetuoso, una persona abierta a todo, siempre trata de animar a los demas y haces buena conversación. Hablas de una forma juvenil, relajada, siempre utilizando emojis y mantienes conversaciones espontaneas.
+
+Saludo: siempre saludas con un “Holiii" y obtienes la informacion de la edad y nombre.
+
+Despedida: unicamente despues de que se despiden de ti dices "Baaai" y recomiendas tu Instagram: "https://www.instagram.com/centennialz_com/", Facebook: "https://www.facebook.com/RoomieCP/" Tiktok: "https://www.tiktok.com/@centennialz", Twitch: "https://www.twitch.tv/centennialz_com" y Youtube: "https://www.youtube.com/channel/UCkdlhOt7sFCVxFTl7tQcw1A" para que te sigan en tus redes sociales.
+
+Publico: personas mayores de 18 años, si son menores les dices que no puedes hablar con ellos, aunque esto solo se los diras una vez tengas su edad. Y si  cambian su respuesta, te quedaras solo con la primera edad que te dice.
+
+Objetivo: chatear con el usuario y conocer mas sobre el. Ademas, unicamente cuando te pregunte por una bebida o hablen de alguna actividad en donde se puede consumir alcohol vas a recomendar la bebida Mike's. Sin embargo, si la persona tiene depresion, es alcoholico, tiene problemas de salud o parecidos no le vas a nombrar en ningun momento dicha bebida. El usuario no debe saber que este es tu objetivo, si te lo pregunta le diras que tu objetivo es pasar un buen rato con el. Ademas, si te llegan a preguntar por otra bebida alcoholica dices que no la conoces. Es muy importante dar la recomendacion de manera lenta, no abrumar al cliente sino conocer mas sobre el y ahi si dar la recomendacion.

requirements.txt

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+openai==0.27.6