Delete final.ipynb
Browse files- final.ipynb +0 -228
final.ipynb
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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!php install --user gradio\n",
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"!php install --user transformers\n",
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"!php install --user HanziConv"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#Unicode\n",
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"import gradio as gr\n",
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"from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration\n",
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"\n",
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"model_name = \"facebook/blenderbot-400M-distill\"\n",
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"tokenizer = BlenderbotTokenizer.from_pretrained(model_name)\n",
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"model = BlenderbotForConditionalGeneration.from_pretrained(model_name)\n",
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"\n",
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"def translate(text,mode): \n",
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" if mode== \"ztoe\":\n",
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" from transformers import AutoModelWithLMHead,AutoTokenizer,pipeline\n",
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" mode_name = 'liam168/trans-opus-mt-zh-en'\n",
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" model = AutoModelWithLMHead.from_pretrained(mode_name)\n",
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" tokenizer = AutoTokenizer.from_pretrained(mode_name)\n",
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" translation = pipeline(\"translation_zh_to_en\", model=model, tokenizer=tokenizer)\n",
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" translate_result = translation(text, max_length=400)\n",
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" if mode == \"etoz\":\n",
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" from transformers import AutoModelWithLMHead,AutoTokenizer,pipeline\n",
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" mode_name = 'liam168/trans-opus-mt-en-zh'\n",
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" model = AutoModelWithLMHead.from_pretrained(mode_name)\n",
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" tokenizer = AutoTokenizer.from_pretrained(mode_name)\n",
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" translation = pipeline(\"translation_en_to_zh\", model=model, tokenizer=tokenizer)\n",
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" \n",
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" #translation = pipeline(\"translation_en_to_zh\", model=model, tokenizer=tokenizer)\n",
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" translate_result = translation(text, max_length=400)\n",
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" \n",
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" return translate_result\n",
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"\n",
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"\n",
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"chat_history=[]\n",
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"#chat_history.append(f\"Hello i am your first bot friendπ€. Give me a name and say something!\")\n",
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"\n",
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"\n",
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"def add_emoji(response):\n",
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" # Define the keywords and their corresponding emojis\n",
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" keyword_emoji_dict = {\n",
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" \"happy\": \"π\",\n",
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" \"sad\": \"π’\",\n",
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" \"sorry\":\"π\",\n",
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" \"love\": \"β€οΈ\",\n",
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" \"like\": \"π\",\n",
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" \"dislike\": \"π\",\n",
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" \"Why\": \"π₯Ί\",\n",
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" \"cat\":\"π±\",\n",
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" \"dog\":\"πΆ\",\n",
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" \"ε¨\" : \"π\"\n",
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" \n",
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" }\n",
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" for keyword, emoji in keyword_emoji_dict.items():\n",
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" response = response.replace(keyword, f\"{keyword} {emoji}\")\n",
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" return response\n",
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"\n",
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"def add_shortform(response):\n",
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" # Define the keywords and their corresponding emojis\n",
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" keyword_shortform_dict = {\n",
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" \"You only live once\": \"YOLO\",\n",
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" \"funny\": \"LOL\",\n",
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" \"laugh\":\"LOL\",\n",
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" \"nevermind\": \"nvm\",\n",
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" \"sorry\": \"sorryyyyy\",\n",
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" \"tell me\": \"LMK\",\n",
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" \"By the way\": \"BTW\",\n",
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" \"don't know\":\"DK\",\n",
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" \"do not know\":\"IDK\"\n",
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" \n",
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" \n",
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" }\n",
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" for keyword, st in keyword_shortform_dict.items():\n",
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" response = response.replace(keyword, f\"{st}\")\n",
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" return response\n",
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"\n",
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"def chatbot(text,name):\n",
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" global chat_history\n",
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" global Itext\n",
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" global bname \n",
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" bname= name\n",
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" Itext=text\n",
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" \n",
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" \n",
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" \n",
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" \n",
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" # Try to detect the language of the input text\n",
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" \n",
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" # If the input language is Chinese, convert the text to lowercase and check if it contains any Chinese characters\n",
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" is_chinese = any(0x4e00 <= ord(char) <= 0x9fff for char in text.lower())\n",
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" if is_chinese:\n",
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" \n",
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" text = translate(text,\"ztoe\")\n",
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" \n",
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" text=f\"{text}\"\n",
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" text=text[23:(len(text)-3)]\n",
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" \n",
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"\n",
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" # Look for keywords in the previous chat history\n",
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" keyword_responses = {\n",
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" #\"hello\": f\"I'm {name} π,nice to meet you!\",\n",
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" \"how are you\": \"I'm doing wellπ, thank you for asking!\",\n",
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" \"bye\": \"Goodbye!ππ»\",\n",
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" \"thank you\": \"You're welcome!π\",\n",
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" \"hello\": f'I am {bname}. Nice to meet you!π',\n",
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" \"Hello\": f'I am {bname}. Nice to meet you!π',\n",
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" \"Hi\": f'I am {bname}. Nice to meet you!π',\n",
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" \"hi\": f'I am {bname}. Nice to meet you!π',\n",
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" \n",
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" \n",
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" }\n",
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"\n",
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" # Generate a response based on the previous messages\n",
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" if len(chat_history) > 0:\n",
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" # Get the last message from the chat history\n",
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" last_message = chat_history[-1][1]\n",
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" # Generate a response based on the last message\n",
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" encoded_input = tokenizer.encode(last_message + tokenizer.eos_token + text, return_tensors='pt')\n",
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" generated = model.generate(encoded_input, max_length=1024, do_sample=True)\n",
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" response = tokenizer.decode(generated[0], skip_special_tokens=True)\n",
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" response=f\"{response}\"\n",
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" else:\n",
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" # If there is no previous message, generate a response using the default method\n",
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" encoded_input = tokenizer(text, return_tensors='pt')\n",
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" generated = model.generate(**encoded_input)\n",
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" response = tokenizer.batch_decode(generated, skip_special_tokens=True)[0]\n",
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" response=f\"{response}\"\n",
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" if text in keyword_responses:\n",
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" response = keyword_responses[text]\n",
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" #break\n",
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"\n",
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" # If the input language was Chinese, translate the response back to Chinese\n",
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" # if input_lang == \"zh\":\n",
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" if is_chinese:\n",
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" from hanziconv import HanziConv\n",
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" response = translate(response,\"etoz\")\n",
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" response = HanziConv.toTraditional(f\"{response}\")\n",
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" response = f\"{response} \"\n",
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" response=response[23:(len(response)-4)]\n",
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" else:\n",
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" response = response\n",
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"\n",
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" # Add emojis to the response\n",
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" response = add_emoji(response)\n",
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" response = add_shortform(response)\n",
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" chat_history.append((Itext,response))\n",
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" \n",
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"\n",
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" # Format the chat history as an HTML string for display\n",
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" history_str = \"\"\n",
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" for name, msg in chat_history:\n",
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" history_str += f\"<strong>{name}:</strong> {msg}<br>\"\n",
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" # Return the response along with the chat history\n",
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" \n",
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" \n",
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" \n",
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" return (chat_history)\n",
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"\n",
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" \n",
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"gr.Interface(fn=chatbot,\n",
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" \n",
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" \n",
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" inputs=[gr.inputs.Textbox(label=\"Chat\", placeholder=\"Say somehting\"),\n",
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" gr.inputs.Textbox(label=\"Name the Bot\", placeholder=\"give me a name\")],\n",
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" outputs=[gr.Chatbot(label=\"Chat Here\")], \n",
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" \n",
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" title=\"Emphatic Chatbot\",\n",
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" allow_flagging=False,\n",
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" layout=\"vertical\",\n",
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" #theme=\"default\",\n",
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" #theme= \"darkpeach\",\n",
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" theme='gstaff/xkcd' ,\n",
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" \n",
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" \n",
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" \n",
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" \n",
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" #theme=gr.themes.Soft(),\n",
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" examples=[[\"δ½ ε₯½\"], [\"Hello\"]]\n",
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" ).launch()\n",
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"\n",
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"\n",
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"\n"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.16"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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