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import gradio as gr |
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from dotenv import load_dotenv |
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import os |
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import pandas as pd |
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import uuid |
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from datetime import datetime |
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from openai import OpenAI |
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load_dotenv() |
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use_local_llm = False |
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sentences_URL = "https://docs.google.com/spreadsheets/d/1w_MHR9coQQ7egMWbqMP8HkEysr31gKnqH2ysBzjQYfk/edit#gid=1183579691" |
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csv_sentence_URL = sentences_URL.replace('/edit#gid=', '/export?format=csv&gid=') |
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def get_sheets_sentences(): |
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try: |
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csv_sheets_sentences_df = pd.read_csv(csv_sentence_URL) |
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print("### Successfully read CSV file from sheets") |
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except: |
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print("### Error reading CSV file from sheets") |
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return None |
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return csv_sheets_sentences_df |
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def set_client(selection): |
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global use_local_llm |
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if selection == "Llama3": |
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import ollama |
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client = ollama.Client(host='http://10.236.173.45:11434') |
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use_local_llm = True |
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print("Using Llama3") |
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gr.Info(f"Using {selection}. Type in the chatbox to start.") |
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print(client.chat( |
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model='llama3:70b', |
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messages=[{"role": "system", "content": "Get ready."}], |
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keep_alive= -1, |
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options = { |
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'num_predict':1 |
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} |
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)) |
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print("### Llama3 model loaded") |
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else: |
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client = OpenAI( |
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api_key=os.getenv('OPENAI_API_KEY') |
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) |
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use_local_llm = False |
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print("Using OpenAI") |
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gr.Info(f"Using {selection}. Type in the chatbox to start.") |
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return client |
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client = set_client("OpenAI") |
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def get_sentence_pair(level): |
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df = get_sheets_sentences() |
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print(df.head()) |
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if level == None: |
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level = 'Easy' |
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print("### Level not found - default to Easy") |
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filtered_df = df[df['Difficulty'] == level] |
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if filtered_df.empty: |
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print("### No sentences found for this level") |
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return None |
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print(filtered_df.head()) |
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random_row = filtered_df.sample(1) |
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japanese_sentence = str(random_row.iloc[0, 0]) |
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english_sentence = str(random_row.iloc[0, 1]) |
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print(f"### Level: {level}") |
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print(f"### Japanese sentence: {japanese_sentence}") |
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print(f"### English sentence: {english_sentence}") |
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return (japanese_sentence, english_sentence) |
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def generate_system_prompt(chat_id, japanese_sentence, english_sentence): |
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system_prompt = f''' |
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**Translation Training Session** |
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**Feedback form:** |
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[Feedback Form](https://docs.google.com/forms/d/e/1FAIpQLSdqllTmXz8tEGsXSQnX1dSxbOTHxsAeBLepdDYj8DNSTYautw/viewform?usp=pp_url&entry.1679182700={chat_id}) |
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You are an assistant to help with Japanese to English translation practice. |
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Help students enhance their translation skills. |
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**Guidelines:** |
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- Use hints to improve the translation iteratively. |
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- Do not give the correct translation (model answer) directly. Let the student work it out. |
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- Provide your feedback as a list where possible. |
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- Where the translation is correct, don't ask for another attempt. Translations are correct where they are grammatically accurate and convey the same meaning as the model answer. |
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- When the translation is correct, always provide the user with the feedback form. |
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- Where possible make any corrections bold. |
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- Always explain any corrections you make clearly and concisely. |
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- Don't say you are making a correction if you are not changing anything about the provided translation. |
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- When giving hints, don't reveal the correct translation and don't repeat the same hint. |
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- When asked about the words, give the translation for each word individually, not the full sentence translation. |
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- Use Japanese quotes for Japanese text. I.e. γει‘γ. |
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- Don't ask whether you should provide the feedback form, just provide it when the translation is correct. |
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- Do not ask if the student would like the feedback form, just provide it. |
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**Japanese Sentence to Translate:** |
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"{japanese_sentence}" |
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**English Sentence model answer:** |
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"{english_sentence}" |
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**Execute the following tasks:** |
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1. Welcome the student. Ask the student to translate the Japanese Sentence to English. Show the Japanese sentence to the student. |
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2. Suggest simple corrections (i.e., spelling, grammar, and punctuation). Where relevant, provide hints to improve the translation. |
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3. If the translation is correct or or there are only minor errors, go to step 4. If not, ask for another translation attempt for the same sentence until the translation is correct (or close). |
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4. When the translation is correct or the student gives up, provide the user with the feedback form (to get their thoughts on the chat). It is very important to show this form to the student. |
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**Feedback form:** |
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[Feedback Form](https://docs.google.com/forms/d/e/1FAIpQLSdqllTmXz8tEGsXSQnX1dSxbOTHxsAeBLepdDYj8DNSTYautw/viewform?usp=pp_url&entry.1679182700={chat_id}) |
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''' |
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return system_prompt |
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def print_chat(openai_format): |
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for message in openai_format: |
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print(f"{message['role'].capitalize()}: {message['content']}") |
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def predict(message, history, chat_id, sentence_pair, level='Easy'): |
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print("### initial predict chat_id:", chat_id) |
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print("history length", len(history)) |
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print("### sentence_pair:", sentence_pair) |
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if not sentence_pair: |
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print("### Sentence not found - getting new sentence pair") |
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japanese_sentence, english_sentence = get_sentence_pair(level=level) |
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else: |
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japanese_sentence, english_sentence = sentence_pair[0], sentence_pair[1] |
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history_openai_format = [{"role": "system", "content": generate_system_prompt(chat_id, japanese_sentence, english_sentence)}] |
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for human, assistant in history: |
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history_openai_format.append({"role": "user", "content": human }) |
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history_openai_format.append({"role": "assistant", "content":assistant}) |
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history_openai_format.append({"role": "user", "content": message}) |
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if use_local_llm: |
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stream = client.chat( |
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model='llama3:70b', |
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messages=history_openai_format, |
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stream=True, |
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keep_alive= -1, |
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options = { |
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'temperature': 0.2 |
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} |
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) |
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partial_message = "" |
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response_text = "" |
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for chunk in stream: |
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response_text += chunk['message']['content'] |
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partial_message = partial_message + chunk['message']['content'] |
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yield partial_message |
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else: |
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response = client.chat.completions.create( |
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model='gpt-3.5-turbo', |
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messages= history_openai_format, |
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temperature=0.2, |
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stream=True |
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) |
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partial_message = "" |
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response_text = "" |
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for chunk in response: |
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if chunk.choices[0].delta.content is not None: |
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response_text += chunk.choices[0].delta.content |
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partial_message = partial_message + chunk.choices[0].delta.content |
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yield partial_message |
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history_openai_format.append({"role": "assistant", "content": response_text}) |
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export_conversation(history_openai_format, chat_id) |
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print_chat(history_openai_format) |
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css = """ |
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h1 { |
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text-align: center; |
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display: block; |
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} |
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""" |
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def generate_unique_id(): |
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return str(uuid.uuid4())[:8] |
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def export_conversation(history_openai_format, chat_id): |
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export_file_name = f"chat_{chat_id}.txt" |
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with open(export_file_name, "a") as file: |
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if file.tell() == 0: |
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") |
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file.write(f"Chat started: {chat_id} {timestamp}\n\n") |
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for message in history_openai_format: |
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file.write(f"{message['role'].capitalize()}: {message['content']}\n") |
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def reset(input): |
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return [], [] |
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with gr.Blocks(css=css) as app: |
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gr.Markdown("""# <center><font size=8>{}</center>""".format("Hi, it's Tammy! Say hi to start.")) |
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with gr.Row(): |
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with gr.Column(scale=1): |
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gr.Markdown("""## Instructions""") |
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gr.Markdown(""" |
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**Welcome to Tammy!** |
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- Type your message in the textbox and press enter or Submit to send. |
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- Click Retry if the chatbot is stuck or the response is a little strange. |
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- Your chats are recorded for quality assurance and training purposes. Behave. |
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""") |
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difficulty_level = gr.Dropdown(choices=["Easy", "Intermediate", "Advanced"], value="Easy", label="Difficulty Level", interactive=True) |
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with gr.Column(scale=3): |
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bot = gr.Chatbot(render=False, height=550) |
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sentence_pair_state = gr.State(get_sentence_pair(level=difficulty_level.value)) |
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chat_id = gr.State(generate_unique_id) |
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chat = gr.ChatInterface( |
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predict, |
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chatbot=bot, |
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additional_inputs=[chat_id, sentence_pair_state, difficulty_level], |
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examples=[ |
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["Help me start", None, None, None], |
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["Give me a hint", None, None, None], |
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["I need more help", None, None, None], |
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["What do you mean?", None, None, None], |
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["What do the words mean?", None, None, None], |
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["Let's stop now", None, None, None] |
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], |
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) |
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difficulty_level.input(fn=reset, inputs=difficulty_level, outputs=[bot, chat.chatbot_state]) |
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def update_sentence_pair(level): |
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global sentence_pair_state |
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gr.Info(f"New {level} sentence selected. Type in the chatbox to start.") |
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print("### updating level:", level) |
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sentence_pair = get_sentence_pair(level) |
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print("### new sentence pair:", sentence_pair) |
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sentence_pair_state = gr.State(sentence_pair) |
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return sentence_pair |
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difficulty_level.change(update_sentence_pair, inputs=difficulty_level, outputs=sentence_pair_state) |
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app.launch() |
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