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- {
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- "nbformat": 4,
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- "nbformat_minor": 0,
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- "metadata": {
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- "colab": {
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- "provenance": []
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- },
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- "kernelspec": {
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- "name": "python3",
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- "display_name": "Python 3"
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- },
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- "language_info": {
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- "name": "python"
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- }
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- },
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- "cells": [
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- {
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- "cell_type": "code",
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- "source": [
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- "pip install groq"
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- ],
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- "metadata": {
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- "id": "WVeN8pltcw-Z",
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- "colab": {
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- "base_uri": "https://localhost:8080/"
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- },
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- "outputId": "27da5ac4-bb36-4098-a9f5-8b85b8b9c0f9"
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- },
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- "execution_count": 36,
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- "outputs": [
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- ]
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- }
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- ]
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- },
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- {
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- "cell_type": "code",
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- "source": [
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- "pip install gradio"
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- "metadata": {
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- "colab": {
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- "base_uri": "https://localhost:8080/"
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- },
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- "id": "wo0uk8aSC7Fy",
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- "outputId": "41d54a6f-9f95-4e61-e0ec-2469fbdba511"
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- "execution_count": 37,
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- {
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- "cell_type": "code",
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- "execution_count": 41,
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- "metadata": {
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- "colab": {
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- "base_uri": "https://localhost:8080/",
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- "height": 646
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- },
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- "id": "zeBQLQB_COtN",
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- "outputId": "79852c24-fe4a-447d-8923-3748694f35d9"
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- },
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- "outputs": [
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- {
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- "output_type": "stream",
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- "name": "stdout",
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- "text": [
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- "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
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- "\n",
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- "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
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- "Running on public URL: https://5f879f53ecb6335748.gradio.live\n",
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- "\n",
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- "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
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- ]
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- },
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- {
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- "output_type": "display_data",
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- "data": {
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- "text/plain": [
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- "<IPython.core.display.HTML object>"
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- ],
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- "text/html": [
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- "<div><iframe src=\"https://5f879f53ecb6335748.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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- ]
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- },
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- "metadata": {}
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- },
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- {
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- "output_type": "execute_result",
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- "data": {
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- "text/plain": []
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- },
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- "metadata": {},
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- "execution_count": 41
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- }
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- ],
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- "source": [
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- "from groq import Groq\n",
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- "import gradio as gr\n",
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- "\n",
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- "# Initialize the Groq client with your API key\n",
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- "client = Groq(\n",
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- " api_key=\"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\"\n",
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- ")\n",
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- "\n",
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- "# List to maintain the conversation history, starting with a default prompt\n",
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- "conversation_history = [\n",
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- " {\"role\": \"system\", \"content\": \"You are an assistant in a trivia game focused on Nigerian music.\"}\n",
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- "]\n",
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- "\n",
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- "# Function to get the initial LLM output and start the conversation\n",
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- "def start_trivia_game():\n",
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- " # Initial message to start the game\n",
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- " initial_message = \"Start a Trivia on Nigeria music. Assess the answer and provide the percentage score\"\n",
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- "\n",
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- " # Add the initial message to the conversation history\n",
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- " conversation_history.append({\"role\": \"user\", \"content\": initial_message})\n",
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- "\n",
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- " # Get completion from the LLM for the initial question\n",
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- " completion = client.chat.completions.create(\n",
209
- " model=\"llama-3.1-70b-versatile\",\n",
210
- " messages=conversation_history,\n",
211
- " temperature=1,\n",
212
- " max_tokens=1024,\n",
213
- " top_p=1,\n",
214
- " stream=True,\n",
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- " stop=None,\n",
216
- " )\n",
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- "\n",
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- " llm_output = \"\"\n",
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- " for chunk in completion:\n",
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- " llm_output += chunk.choices[0].delta.content or \"\"\n",
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- "\n",
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- " # Add the assistant's response to the conversation history\n",
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- " conversation_history.append({\"role\": \"assistant\", \"content\": llm_output})\n",
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- "\n",
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- " return llm_output\n",
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- "\n",
227
- "# Function to handle user response and continue the conversation\n",
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- "def continue_trivia_game(user_response):\n",
229
- " # Add user's response to the conversation history\n",
230
- " conversation_history.append({\"role\": \"user\", \"content\": user_response})\n",
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- "\n",
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- " # Get completion from the LLM for the user's response\n",
233
- " completion = client.chat.completions.create(\n",
234
- " model=\"llama-3.1-70b-versatile\",\n",
235
- " messages=conversation_history,\n",
236
- " temperature=1,\n",
237
- " max_tokens=1024,\n",
238
- " top_p=1,\n",
239
- " stream=True,\n",
240
- " stop=None,\n",
241
- " )\n",
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- "\n",
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- " llm_output = \"\"\n",
244
- " for chunk in completion:\n",
245
- " llm_output += chunk.choices[0].delta.content or \"\"\n",
246
- "\n",
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- " # Add the assistant's response to the conversation history\n",
248
- " conversation_history.append({\"role\": \"assistant\", \"content\": llm_output})\n",
249
- "\n",
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- " return llm_output\n",
251
- "\n",
252
- "# Start the game and get the initial LLM output\n",
253
- "initial_output = start_trivia_game()\n",
254
- "\n",
255
- "# Using gr.Blocks to create the interface\n",
256
- "with gr.Blocks() as demo:\n",
257
- " # Title and Description\n",
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- " gr.Markdown(\"# Trivia Game\\nA simple trivia game using Groq's LLama 3 LLM API.\")\n",
259
- "\n",
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- " # LLM Output Textbox\n",
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- " llm_output = gr.Textbox(label=\"LLM Output\", placeholder=\"The output from the LLM will appear here\", lines=10, value=initial_output)\n",
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- "\n",
263
- " # User Response Textbox\n",
264
- " user_response = gr.Textbox(label=\"Your Response\", placeholder=\"Type your response here\", lines=3)\n",
265
- "\n",
266
- " # Button to submit the user's response and update the LLM output\n",
267
- " submit_button = gr.Button(\"Submit\")\n",
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- "\n",
269
- " # Function to update the LLM output upon submission\n",
270
- " def update_llm_output(user_input):\n",
271
- " # Update the LLM output and return it\n",
272
- " return continue_trivia_game(user_input)\n",
273
- "\n",
274
- " # Define interactions\n",
275
- " submit_button.click(fn=update_llm_output, inputs=user_response, outputs=llm_output)\n",
276
- "\n",
277
- "# Launch the Gradio app\n",
278
- "demo.launch()\n",
279
- "\n"
280
- ]
281
- },
282
- {
283
- "cell_type": "code",
284
- "source": [
285
- "from groq import Groq\n",
286
- "import gradio as gr\n",
287
- "\n",
288
- "# Initialize the Groq client with your API key\n",
289
- "client = Groq(\n",
290
- " api_key=\"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\"\n",
291
- ")\n",
292
- "\n",
293
- "# List to maintain the conversation history\n",
294
- "conversation_history = [\n",
295
- " {\"role\": \"system\", \"content\": \"You are an assistant in a trivia game focused on Nigerian music.\"}\n",
296
- "]\n",
297
- "\n",
298
- "# Function to get the LLM output and update the conversation history\n",
299
- "def trivia_game(user_response):\n",
300
- " # Add user's response to the conversation history\n",
301
- " conversation_history.append({\"role\": \"user\", \"content\": user_response})\n",
302
- "\n",
303
- " # Get completion from the LLM\n",
304
- " completion = client.chat.completions.create(\n",
305
- " model=\"llama-3.1-70b-versatile\",\n",
306
- " messages=conversation_history,\n",
307
- " temperature=1,\n",
308
- " max_tokens=1024,\n",
309
- " top_p=1,\n",
310
- " stream=True,\n",
311
- " stop=None,\n",
312
- " )\n",
313
- "\n",
314
- " llm_output = \"\"\n",
315
- " for chunk in completion:\n",
316
- " llm_output += chunk.choices[0].delta.content or \"\"\n",
317
- "\n",
318
- " # Add the assistant's response to the conversation history\n",
319
- " conversation_history.append({\"role\": \"assistant\", \"content\": llm_output})\n",
320
- "\n",
321
- " return llm_output\n",
322
- "\n",
323
- "# Creating Gradio Interface\n",
324
- "llm_output = gr.Textbox(label=\"LLM Output\", placeholder=\"The output from the LLM will appear here\", lines=10)\n",
325
- "user_response = gr.Textbox(label=\"Your Response\", placeholder=\"Type your response here\", lines=3)\n",
326
- "\n",
327
- "demo = gr.Interface(\n",
328
- " fn=trivia_game,\n",
329
- " inputs=user_response,\n",
330
- " outputs=llm_output,\n",
331
- " title=\"Trivia Game\",\n",
332
- " description=\"A simple trivia game using Groq's LLama 3 LLM API\"\n",
333
- ")\n",
334
- "\n",
335
- "# Starting the Gradio app\n",
336
- "demo.launch()\n",
337
- "\n"
338
- ],
339
- "metadata": {
340
- "colab": {
341
- "base_uri": "https://localhost:8080/",
342
- "height": 646
343
- },
344
- "id": "M9Uz7BJ6NOkO",
345
- "outputId": "6aa70fee-3bf7-46b7-e232-393e8352e5af"
346
- },
347
- "execution_count": null,
348
- "outputs": [
349
- {
350
- "output_type": "stream",
351
- "name": "stdout",
352
- "text": [
353
- "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
354
- "\n",
355
- "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
356
- "Running on public URL: https://f24a7676e50f0183bd.gradio.live\n",
357
- "\n",
358
- "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
359
- ]
360
- },
361
- {
362
- "output_type": "display_data",
363
- "data": {
364
- "text/plain": [
365
- "<IPython.core.display.HTML object>"
366
- ],
367
- "text/html": [
368
- "<div><iframe src=\"https://f24a7676e50f0183bd.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
369
- ]
370
- },
371
- "metadata": {}
372
- },
373
- {
374
- "output_type": "execute_result",
375
- "data": {
376
- "text/plain": []
377
- },
378
- "metadata": {},
379
- "execution_count": 33
380
- }
381
- ]
382
- },
383
- {
384
- "cell_type": "code",
385
- "source": [
386
- "from groq import Groq\n",
387
- "import gradio as gr\n",
388
- "\n",
389
- "# Initialize the Groq client with your API key\n",
390
- "client = Groq(\n",
391
- " api_key=\"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\"\n",
392
- ")\n",
393
- "\n",
394
- "# List to maintain the conversation history, starting with a default prompt\n",
395
- "conversation_history = [\n",
396
- " {\"role\": \"system\", \"content\": \"You are an assistant in a trivia game focused on Nigerian music.\"}\n",
397
- "]\n",
398
- "\n",
399
- "# Function to get the initial LLM output and start the conversation\n",
400
- "def start_trivia_game():\n",
401
- " # Initial message to start the game\n",
402
- " initial_message = \"Start a Trivia on Nigeria music. Assess the answer and provide the percentage score\"\n",
403
- "\n",
404
- " # Add the initial message to the conversation history\n",
405
- " conversation_history.append({\"role\": \"user\", \"content\": initial_message})\n",
406
- "\n",
407
- " # Get completion from the LLM for the initial question\n",
408
- " completion = client.chat.completions.create(\n",
409
- " model=\"llama-3.1-70b-versatile\",\n",
410
- " messages=conversation_history,\n",
411
- " temperature=1,\n",
412
- " max_tokens=1024,\n",
413
- " top_p=1,\n",
414
- " stream=True,\n",
415
- " stop=None,\n",
416
- " )\n",
417
- "\n",
418
- " llm_output = \"\"\n",
419
- " for chunk in completion:\n",
420
- " llm_output += chunk.choices[0].delta.content or \"\"\n",
421
- "\n",
422
- " # Add the assistant's response to the conversation history\n",
423
- " conversation_history.append({\"role\": \"assistant\", \"content\": llm_output})\n",
424
- "\n",
425
- " return llm_output\n",
426
- "\n",
427
- "# Function to handle user response and continue the conversation\n",
428
- "def continue_trivia_game(user_response):\n",
429
- " # Add user's response to the conversation history\n",
430
- " conversation_history.append({\"role\": \"user\", \"content\": user_response})\n",
431
- "\n",
432
- " # Get completion from the LLM for the user's response\n",
433
- " completion = client.chat.completions.create(\n",
434
- " model=\"llama-3.1-70b-versatile\",\n",
435
- " messages=conversation_history,\n",
436
- " temperature=1,\n",
437
- " max_tokens=1024,\n",
438
- " top_p=1,\n",
439
- " stream=True,\n",
440
- " stop=None,\n",
441
- " )\n",
442
- "\n",
443
- " llm_output = \"\"\n",
444
- " for chunk in completion:\n",
445
- " llm_output += chunk.choices[0].delta.content or \"\"\n",
446
- "\n",
447
- " # Add the assistant's response to the conversation history\n",
448
- " conversation_history.append({\"role\": \"assistant\", \"content\": llm_output})\n",
449
- "\n",
450
- " return llm_output\n",
451
- "\n",
452
- "# Start the game and get the initial LLM output\n",
453
- "initial_output = start_trivia_game()\n",
454
- "\n",
455
- "# Creating Gradio Interface\n",
456
- "llm_output = gr.Textbox(label=\"LLM Output\", placeholder=\"The output from the LLM will appear here\", lines=10, value=initial_output)\n",
457
- "user_response = gr.Textbox(label=\"Your Response\", placeholder=\"Type your response here\", lines=3)\n",
458
- "\n",
459
- "demo = gr.Interface(\n",
460
- " fn=continue_trivia_game,\n",
461
- " inputs=user_response,\n",
462
- " outputs=llm_output,\n",
463
- " title=\"TriviaVilla--Nigerian Music Trivia Game\",\n",
464
- " description=\"How much do you know Nigerian Music? Here is a simple trivia game on Nigerian Music using LLama 3.1\",\n",
465
- ")\n",
466
- "\n",
467
- "# Starting the Gradio app\n",
468
- "demo.launch()\n",
469
- "\n"
470
- ],
471
- "metadata": {
472
- "colab": {
473
- "base_uri": "https://localhost:8080/",
474
- "height": 646
475
- },
476
- "id": "dUpGIo3eHT6t",
477
- "outputId": "a56d0ca1-43ad-4092-d756-24b01ec9ae58"
478
- },
479
- "execution_count": null,
480
- "outputs": [
481
- {
482
- "output_type": "stream",
483
- "name": "stdout",
484
- "text": [
485
- "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
486
- "\n",
487
- "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
488
- "Running on public URL: https://0d7874273562a8d25f.gradio.live\n",
489
- "\n",
490
- "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
491
- ]
492
- },
493
- {
494
- "output_type": "display_data",
495
- "data": {
496
- "text/plain": [
497
- "<IPython.core.display.HTML object>"
498
- ],
499
- "text/html": [
500
- "<div><iframe src=\"https://0d7874273562a8d25f.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
501
- ]
502
- },
503
- "metadata": {}
504
- },
505
- {
506
- "output_type": "execute_result",
507
- "data": {
508
- "text/plain": []
509
- },
510
- "metadata": {},
511
- "execution_count": 35
512
- }
513
- ]
514
- },
515
- {
516
- "cell_type": "code",
517
- "source": [],
518
- "metadata": {
519
- "colab": {
520
- "base_uri": "https://localhost:8080/",
521
- "height": 106
522
- },
523
- "id": "U1vMYZkFDYgh",
524
- "outputId": "66ef485d-d9c8-4949-91da-f4620b3a03da"
525
- },
526
- "execution_count": null,
527
- "outputs": [
528
- {
529
- "output_type": "error",
530
- "ename": "SyntaxError",
531
- "evalue": "invalid syntax (<ipython-input-6-45df297f8215>, line 1)",
532
- "traceback": [
533
- "\u001b[0;36m File \u001b[0;32m\"<ipython-input-6-45df297f8215>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m export Groq_API_KEY= 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\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
534
- ]
535
- }
536
- ]
537
- }
538
- ]
539
- }