Delete final.ipynb

final.ipynb

@@ -1,228 +0,0 @@
-{
- "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!php install --user gradio\n",
-    "!php install --user transformers\n",
-    "!php install --user HanziConv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#Unicode\n",
-    "import gradio as gr\n",
-    "from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration\n",
-    "\n",
-    "model_name = \"facebook/blenderbot-400M-distill\"\n",
-    "tokenizer = BlenderbotTokenizer.from_pretrained(model_name)\n",
-    "model = BlenderbotForConditionalGeneration.from_pretrained(model_name)\n",
-    "\n",
-    "def translate(text,mode):  \n",
-    "    if mode== \"ztoe\":\n",
-    "        from transformers import AutoModelWithLMHead,AutoTokenizer,pipeline\n",
-    "        mode_name = 'liam168/trans-opus-mt-zh-en'\n",
-    "        model = AutoModelWithLMHead.from_pretrained(mode_name)\n",
-    "        tokenizer = AutoTokenizer.from_pretrained(mode_name)\n",
-    "        translation = pipeline(\"translation_zh_to_en\", model=model, tokenizer=tokenizer)\n",
-    "        translate_result = translation(text, max_length=400)\n",
-    "    if mode ==  \"etoz\":\n",
-    "        from transformers import AutoModelWithLMHead,AutoTokenizer,pipeline\n",
-    "        mode_name = 'liam168/trans-opus-mt-en-zh'\n",
-    "        model = AutoModelWithLMHead.from_pretrained(mode_name)\n",
-    "        tokenizer = AutoTokenizer.from_pretrained(mode_name)\n",
-    "        translation = pipeline(\"translation_en_to_zh\", model=model, tokenizer=tokenizer)\n",
-    "        \n",
-    "        #translation = pipeline(\"translation_en_to_zh\", model=model, tokenizer=tokenizer)\n",
-    "        translate_result = translation(text, max_length=400)\n",
-    "        \n",
-    "    return translate_result\n",
-    "\n",
-    "\n",
-    "chat_history=[]\n",
-    "#chat_history.append(f\"Hello i am your first bot friend🤓. Give me a name and say something!\")\n",
-    "\n",
-    "\n",
-    "def add_emoji(response):\n",
-    "    # Define the keywords and their corresponding emojis\n",
-    "    keyword_emoji_dict = {\n",
-    "        \"happy\": \"😀\",\n",
-    "        \"sad\": \"😢\",\n",
-    "        \"sorry\":\"😞\",\n",
-    "        \"love\": \"❤️\",\n",
-    "        \"like\": \"👍\",\n",
-    "        \"dislike\": \"👎\",\n",
-    "        \"Why\": \"🥺\",\n",
-    "        \"cat\":\"🐱\",\n",
-    "        \"dog\":\"🐶\",\n",
-    "        \"嗨\" :  \"😎\"\n",
-    "        \n",
-    "    }\n",
-    "    for keyword, emoji in keyword_emoji_dict.items():\n",
-    "        response = response.replace(keyword, f\"{keyword} {emoji}\")\n",
-    "    return response\n",
-    "\n",
-    "def add_shortform(response):\n",
-    "    # Define the keywords and their corresponding emojis\n",
-    "    keyword_shortform_dict = {\n",
-    "        \"You only live once\": \"YOLO\",\n",
-    "        \"funny\": \"LOL\",\n",
-    "        \"laugh\":\"LOL\",\n",
-    "        \"nevermind\": \"nvm\",\n",
-    "        \"sorry\": \"sorryyyyy\",\n",
-    "        \"tell me\": \"LMK\",\n",
-    "        \"By the way\": \"BTW\",\n",
-    "        \"don't know\":\"DK\",\n",
-    "        \"do not know\":\"IDK\"\n",
-    "        \n",
-    "        \n",
-    "    }\n",
-    "    for keyword, st in keyword_shortform_dict.items():\n",
-    "        response = response.replace(keyword, f\"{st}\")\n",
-    "    return response\n",
-    "\n",
-    "def chatbot(text,name):\n",
-    "    global chat_history\n",
-    "    global Itext\n",
-    "    global bname \n",
-    "    bname= name\n",
-    "    Itext=text\n",
-    "    \n",
-    "    \n",
-    "    \n",
-    "    \n",
-    "    # Try to detect the language of the input text\n",
-    "  \n",
-    "    # If the input language is Chinese, convert the text to lowercase and check if it contains any Chinese characters\n",
-    "    is_chinese = any(0x4e00 <= ord(char) <= 0x9fff for char in text.lower())\n",
-    "    if is_chinese:\n",
-    "            \n",
-    "            text = translate(text,\"ztoe\")\n",
-    "        \n",
-    "            text=f\"{text}\"\n",
-    "            text=text[23:(len(text)-3)]\n",
-    "            \n",
-    "\n",
-    "    # Look for keywords in the previous chat history\n",
-    "    keyword_responses = {\n",
-    "        #\"hello\": f\"I'm {name} 😄,nice to meet you!\",\n",
-    "        \"how are you\": \"I'm doing well😄, thank you for asking!\",\n",
-    "        \"bye\": \"Goodbye!👊🏻\",\n",
-    "        \"thank you\": \"You're welcome!😃\",\n",
-    "        \"hello\": f'I am {bname}. Nice to meet you!😎',\n",
-    "        \"Hello\": f'I am {bname}. Nice to meet you!😎',\n",
-    "        \"Hi\": f'I am {bname}. Nice to meet you!😎',\n",
-    "        \"hi\": f'I am {bname}. Nice to meet you!😎',\n",
-    "        \n",
-    "        \n",
-    "    }\n",
-    "\n",
-    "            # Generate a response based on the previous messages\n",
-    "    if len(chat_history) > 0:\n",
-    "                # Get the last message from the chat history\n",
-    "                last_message = chat_history[-1][1]\n",
-    "                # Generate a response based on the last message\n",
-    "                encoded_input = tokenizer.encode(last_message + tokenizer.eos_token + text, return_tensors='pt')\n",
-    "                generated = model.generate(encoded_input, max_length=1024, do_sample=True)\n",
-    "                response = tokenizer.decode(generated[0], skip_special_tokens=True)\n",
-    "                response=f\"{response}\"\n",
-    "    else:\n",
-    "                # If there is no previous message, generate a response using the default method\n",
-    "                encoded_input = tokenizer(text, return_tensors='pt')\n",
-    "                generated = model.generate(**encoded_input)\n",
-    "                response = tokenizer.batch_decode(generated, skip_special_tokens=True)[0]\n",
-    "                response=f\"{response}\"\n",
-    "    if text in keyword_responses:\n",
-    "            response = keyword_responses[text]\n",
-    "            #break\n",
-    "\n",
-    "    # If the input language was Chinese, translate the response back to Chinese\n",
-    "   # if input_lang == \"zh\":\n",
-    "    if is_chinese:\n",
-    "        from hanziconv import HanziConv\n",
-    "        response = translate(response,\"etoz\")\n",
-    "        response = HanziConv.toTraditional(f\"{response}\")\n",
-    "        response = f\"{response} \"\n",
-    "        response=response[23:(len(response)-4)]\n",
-    "    else:\n",
-    "            response = response\n",
-    "\n",
-    "    # Add emojis to the response\n",
-    "    response = add_emoji(response)\n",
-    "    response = add_shortform(response)\n",
-    "    chat_history.append((Itext,response))\n",
-    " \n",
-    "\n",
-    "    # Format the chat history as an HTML string for display\n",
-    "    history_str = \"\"\n",
-    "    for name, msg in chat_history:\n",
-    "        history_str += f\"<strong>{name}:</strong> {msg}<br>\"\n",
-    "    # Return the response along with the chat history\n",
-    "    \n",
-    "    \n",
-    "    \n",
-    "    return (chat_history)\n",
-    "\n",
-    " \n",
-    "gr.Interface(fn=chatbot,\n",
-    "                    \n",
-    "                    \n",
-    "                     inputs=[gr.inputs.Textbox(label=\"Chat\", placeholder=\"Say somehting\"),\n",
-    "                       gr.inputs.Textbox(label=\"Name the Bot\", placeholder=\"give me a name\")],\n",
-    "                     outputs=[gr.Chatbot(label=\"Chat Here\")], \n",
-    "                    \n",
-    "                     title=\"Emphatic Chatbot\",\n",
-    "                     allow_flagging=False,\n",
-    "                     layout=\"vertical\",\n",
-    "                     #theme=\"default\",\n",
-    "                     #theme= \"darkpeach\",\n",
-    "                     theme='gstaff/xkcd' ,\n",
-    "                    \n",
-    "                 \n",
-    "                     \n",
-    "                   \n",
-    "                     #theme=gr.themes.Soft(),\n",
-    "                     examples=[[\"你好\"], [\"Hello\"]]\n",
-    "                    ).launch()\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
-  }
- ],
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-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
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-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
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