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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"authorship_tag": "ABX9TyPFzqiqjfrEaTqnmAjX+pwu",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/Cloud-Dark/294fd539d18af4a64733c073c19ea44a/ai-submission-1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "nF5JWctge4iS",
"outputId": "30ff1abc-0c9a-48a3-f5cb-5a30247e1ce5"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Python 3.10.12\n"
]
}
],
"source": [
"!python --version"
]
},
{
"cell_type": "code",
"source": [
"!pip install -r requirements.txt"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "apG5aa43fIbW",
"outputId": "391db012-cd4b-46e4-d4c2-f70c3d3d478c"
},
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
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]
}
]
},
{
"cell_type": "code",
"source": [
"import gradio as gr\n",
"from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline\n",
"import torch\n",
"import re\n",
"\n",
"# Load the Hugging Face model and tokenizer\n",
"model_name = \"microsoft/DialoGPT-medium\"\n",
"chatbot = pipeline(\"text-generation\", model=model_name)\n"
],
"metadata": {
"id": "LWl5QTBLfVCo"
},
"execution_count": 22,
"outputs": []
},
{
"cell_type": "code",
"source": [
"# Import necessary libraries\n",
"import gradio as gr\n",
"\n",
"# Initialize conversation history\n",
"conversation_history = []\n",
"\n",
"# Function to generate chatbot response\n",
"def chatbot_response(prompt):\n",
" global conversation_history\n",
"\n",
" # Combine previous conversation history with the new prompt\n",
" full_prompt = \"\\n\".join(conversation_history) + f\"\\nYou: {prompt}\\nBot:\"\n",
"\n",
" # Generate response from the model\n",
" outputs = chatbot(prompt, max_length=1000, pad_token_id=50256, do_sample=True)\n",
" response = outputs[0]['generated_text'][len(prompt):].strip()\n",
"\n",
" # Update conversation history\n",
" conversation_history.append(f\"You: {prompt}\")\n",
" conversation_history.append(f\"Bot: {response}\")\n",
"\n",
" # Display last few interactions (limit to recent history)\n",
" history = \"\\n\".join(conversation_history[-6:]) # Show last 3 interactions\n",
" return history\n",
"\n",
"# Create a Gradio interface\n",
"interface = gr.Interface(\n",
" fn=chatbot_response, # Function to handle inputs and return outputs\n",
" inputs=\"text\", # Input type\n",
" outputs=\"text\", # Output type\n",
" title=\"Chatbot with Conversation History\",\n",
" description=\"A simple chatbot that displays the conversation history.\"\n",
")\n",
"\n",
"# Launch the interface\n",
"interface.launch()\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 650
},
"id": "odGt7hhAhGxh",
"outputId": "76c0df34-f49f-4a73-8114-c220e4f83914"
},
"execution_count": 23,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Running Gradio in a Colab notebook requires sharing enabled. Automatically setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
"\n",
"Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
"* Running on public URL: https://1982bb469c97917671.gradio.live\n",
"\n",
"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from the terminal in the working directory to deploy to Hugging Face Spaces (https://huggingface.co/spaces)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.HTML object>"
],
"text/html": [
"<div><iframe src=\"https://1982bb469c97917671.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
]
},
"metadata": {}
},
{
"output_type": "execute_result",
"data": {
"text/plain": []
},
"metadata": {},
"execution_count": 23
}
]
}
]
}
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