dhumra_chatbot_assistant (#1)

- dhumra_chatbot_assistant (e3f487df95df380fa8c33e0285858189df641cb2)
- Create chat.py (1f0db1a18eaa00956dba459f110dc5700d2db99a)
- Create app.py (dd6858768fe5a3610c6e742133696853e7e93400)

app.py

@@ -0,0 +1,130 @@
+import os
+import uuid
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import gradio as gr
+import requests
+
+from chat import ChatGpt
+
+# Environment Variables
+DEBUG = bool(os.getenv("DEBUG", False))
+VERBOSE = bool(os.getenv("V", False))
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+BING_TRANSLATE_API_KEY = os.getenv("BING_TRANSLATE_API_KEY")
+
+# Type Definitions
+ROLE_USER = "user"
+ROLE_ASSISTANT = "assistant"
+CHATGPT_MSG = Dict[str, str]  # {"role": "user|assistant", "content": "text"}
+CHATGPT_HISTROY = List[CHATGPT_MSG]
+CHATBOT_MSG = Tuple[str, str]  # (user_message, bot_response)
+CHATBOT_HISTORY = List[CHATBOT_MSG]
+
+# Constants
+LANG_BO = "bo"
+LANG_MEDIUM = "en"
+
+chatbot = ChatGpt(OPENAI_API_KEY)
+
+
+def bing_translate(text: str, from_lang: str, to_lang: str):
+    if DEBUG:
+        if from_lang != "bo":
+            return "ཀཀཀཀཀཀ"
+        return "aaaaa"
+    headers = {
+        "Ocp-Apim-Subscription-Key": BING_TRANSLATE_API_KEY,
+        "Content-Type": "application/json",
+        "Ocp-Apim-Subscription-Region": "australiaeast",
+        "X-ClientTraceId": str(uuid.uuid4()),
+    }
+    resp = requests.post(
+        url="https://api.cognitive.microsofttranslator.com/translate",
+        params={"api-version": "3.0", "from": from_lang, "to": to_lang},
+        json=[{"text": text}],
+        headers=headers,
+    )
+    result = resp.json()
+    if resp.status_code == 200:
+        return result[0]["translations"][0]["text"]
+    else:
+        raise Exception("Error in translation API: ", result)
+
+
+def user(input_bo: str, history_bo: list):
+    history_bo.append([input_bo, None])
+    return "", history_bo
+
+
+def bot(history_bo: list, chat_id: str):
+    """Translate user input to English, send to OpenAI, translate response to Tibetan, and return to user.
+
+    Args:
+        input_bo (str): Tibetan input from user
+        history_bo (CHATBOT_HISTORY): Tibetan history of gradio chatbot
+        history_en (CHATGPT_HISTORY): English history of OpenAI ChatGPT
+
+    Returns:
+        history_bo (CHATBOT_HISTORY): Tibetan history of gradio chatbot
+        history_en (CHATGPT_HISTORY): English history of OpenAI ChatGPT
+    """
+    input_bo = history_bo[-1][0]
+    input_ = bing_translate(input_bo, LANG_BO, LANG_MEDIUM)
+    response = chatbot.generate_response(input_)
+    resopnse_bo = bing_translate(response, LANG_MEDIUM, LANG_BO)
+    history_bo[-1][1] = resopnse_bo
+    if VERBOSE:
+        print("------------------------")
+        print(history_bo)
+        print(history_en)
+        print("------------------------")
+
+    return history_bo
+
+
+def get_chat_id():
+    chatbot.clear_history()
+    return str(uuid.uuid4())
+
+
+css_fn = Path(__file__).resolve().parent / "static" / "app.css"
+assert css_fn.exists() and css_fn.is_file(), f"CSS file not found: {css_fn}"
+
+with gr.Blocks(css=str(css_fn), theme=gr.themes.Soft()) as demo:
+    chat_id = gr.State(value=get_chat_id)
+    history_en = gr.State(value=[])
+    history_bo = gr.Chatbot(label="Tibetan Chatbot", elem_id="maiChatHistory")
+
+    input_bo = gr.Textbox(
+        show_label=False,
+        placeholder="Type here...",
+        elem_id="maiChatInput",
+    )
+    input_submit_btn = gr.Button("Submit")
+    input_bo.submit(
+        fn=user,
+        inputs=[input_bo, history_bo],
+        outputs=[input_bo, history_bo],
+        queue=False,
+    ).then(
+        fn=bot,
+        inputs=[history_bo, chat_id],
+        outputs=[history_bo],
+    )
+    input_submit_btn.click(
+        fn=user,
+        inputs=[input_bo, history_bo],
+        outputs=[input_bo, history_bo],
+        queue=False,
+    ).then(
+        fn=bot,
+        inputs=[history_bo, chat_id],
+        outputs=[history_bo],
+    )
+
+    clear = gr.Button("Clear")
+    clear.click(lambda: [], None, history_bo, queue=False)
+
+demo.launch()

chat.py

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+import os
+from typing import Tuple
+
+import openai
+
+
+class ChatGpt:
+    def __init__(self, api_key, max_tokens=4096):
+        self.api_key = api_key
+        self.max_tokens = max_tokens
+        self.message_history = []
+        self.total_tokens = 0
+
+        # Set up the OpenAI API client
+        openai.api_key = self.api_key
+
+    def clear_history(self):
+        self.message_history = []
+        self.total_tokens = 0
+
+    def add_message(self, role: str, content: str):
+        self.message_history.append({"role": role, "content": content})
+        self._truncate_history()
+
+    def add_system_message(self, content: str):
+        self.add_message("system", content)
+
+    def generate_response(self, user_input: str) -> str:
+        self.add_message("user", user_input)
+        response = self._call_openai_api(self.message_history)
+        self.add_message("assistant", response)
+
+        return response
+
+    def _truncate_history(self):
+        while self.total_tokens > self.max_tokens:
+            if self.message_history[0]["role"] != "system":
+                self.message_history.pop(0)
+            else:
+                break
+
+    def _call_openai_api(self, messages) -> str:
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo", messages=messages
+        )
+        self.total_tokens += response["usage"]["total_tokens"]
+        return response["choices"][0]["message"]["content"].strip()
+
+
+if __name__ == "__main__":
+    chat = ChatGpt(os.getenv("OPENAI_API_KEY"))
+
+    chat.add_system_message("The assistant can answer questions and tell jokes.")
+    user_input = "Tell me a joke."
+    user_msg, bot_response = chat.generate_response(user_input)
+    assert user_msg == user_input
+    print("User:", user_msg)
+    print("Assistant:", bot_response)
+    print("Total Tokens:", chat.total_tokens)
+
+    user_input = "another one"
+    user_msg, bot_response = chat.generate_response(user_input)
+    assert user_msg == user_input
+    print("User:", user_msg)
+    print("Assistant:", bot_response)
+    print("Total Tokens:", chat.total_tokens)

requirements.txt

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+gradio==3.26.0
+requests==2.28.2
+openai==0.27.4, <1.0