brad/LLM_Engineering_OLD
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Merge pull request #847 from sammurira/samuel_bootcamp_wk3

Browse Source 
Samuel bootcamp wk3
This commit is contained in:
Ed Donner
2025-10-26 23:15:29 -04:00
committed by GitHub
parent 18f7e256c3 118954b1df
commit 9f0be613d9
2 changed files with 246 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

229
week3/community-contributions/samuel_bootcamp_wk3/data_generator.ipynb Normal file
View File

@@ -0,0 +1,229 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "2714fa36",
"metadata": {},
"source": [
"## Week 3 Data Generator With Opensource Models\n",
"# Generate synthetic data for Pizza cusromers within Nairobi "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "761622db",
"metadata": {},
"outputs": [],
"source": [
"!pip install requests pandas ipywidgets gradio"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cc7347c4",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import gradio as gr\n",
"from huggingface_hub import InferenceClient\n",
"import random\n",
"import os\n",
"from dotenv import load_dotenv\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f20cd822",
"metadata": {},
"outputs": [],
"source": [
"#Load API Key\n",
"\n",
"load_dotenv(override=True)\n",
"HF_API_KEY = os.getenv('HF_TOKEN')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "856cd8cb",
"metadata": {},
"outputs": [],
"source": [
"\n",
"# Define available models with correct Hugging Face model IDs\n",
"MODELS = {\n",
" \"Mistral-7B\": \"mistralai/Mistral-7B-Instruct-v0.2\",\n",
" \"Llama-2-7B\": \"meta-llama/Llama-2-7b-chat-hf\",\n",
" \"Phi-2\": \"microsoft/phi-2\",\n",
" \"GPT-2\": \"gpt2\"\n",
"}\n",
"\n",
"# Nairobi branches\n",
"BRANCHES = [\"Westlands\", \"Karen\", \"Kilimani\", \"CBD\", \"Parklands\"]\n",
"\n",
"# Global variable to store generated data\n",
"generated_df = None\n",
"\n",
"def generate_feedback_data(model_name, num_records):\n",
" \"\"\"Generate synthetic pizza feedback data using selected AI model\"\"\"\n",
" global generated_df\n",
" \n",
" try:\n",
" # Initialize the Hugging Face Inference Client\n",
" model_id = MODELS[model_name]\n",
" client = InferenceClient(model=model_id, token=None) # Add your HF token if needed\n",
" \n",
" feedback_data = []\n",
" \n",
" for i in range(num_records):\n",
" # Random branch\n",
" branch = random.choice(BRANCHES)\n",
" \n",
" # Generate feedback using the AI model\n",
" prompt = f\"Generate a brief customer feedback comment about a pizza order from {branch} branch in Nairobi. Make it realistic and varied (positive, negative, or neutral). Keep it under 30 words.\"\n",
" \n",
" try:\n",
" response = client.text_generation(\n",
" prompt,\n",
" max_new_tokens=50,\n",
" temperature=0.8\n",
" )\n",
" feedback = response.strip()\n",
" except Exception as e:\n",
" # Fallback to template-based generation if API fails\n",
" feedback = generate_fallback_feedback(branch)\n",
" \n",
" # Generate other fields\n",
" record = {\n",
" \"Customer_ID\": f\"CUST{1000 + i}\",\n",
" \"Branch\": branch,\n",
" \"Rating\": random.randint(1, 5),\n",
" \"Order_Type\": random.choice([\"Delivery\", \"Dine-in\", \"Takeaway\"]),\n",
" \"Feedback\": feedback,\n",
" \"Date\": f\"2024-{random.randint(1, 12):02d}-{random.randint(1, 28):02d}\"\n",
" }\n",
" \n",
" feedback_data.append(record)\n",
" \n",
" # Create DataFrame\n",
" generated_df = pd.DataFrame(feedback_data)\n",
" \n",
" return generated_df, f\"✓ Successfully generated {num_records} records using {model_name}\"\n",
" \n",
" except Exception as e:\n",
" return pd.DataFrame(), f\"✗ Error: {str(e)}\"\n",
"\n",
"def generate_fallback_feedback(branch):\n",
" \"\"\"Fallback feedback generator if API fails\"\"\"\n",
" templates = [\n",
" f\"Great pizza from {branch}! Quick delivery and hot food.\",\n",
" f\"Pizza was cold when it arrived at {branch}. Disappointed.\",\n",
" f\"Excellent service at {branch} branch. Will order again!\",\n",
" f\"Average experience. Pizza was okay but nothing special.\",\n",
" f\"Long wait time at {branch} but the pizza was worth it.\",\n",
" ]\n",
" return random.choice(templates)\n",
"\n",
"def download_csv():\n",
" \"\"\"Save generated data as CSV\"\"\"\n",
" global generated_df\n",
" if generated_df is not None:\n",
" generated_df.to_csv('pizza_feedback_data.csv', index=False)\n",
" return \"CSV downloaded!\"\n",
" return \"No data to download\"\n",
"\n",
"def download_json():\n",
" \"\"\"Save generated data as JSON\"\"\"\n",
" global generated_df\n",
" if generated_df is not None:\n",
" generated_df.to_json('pizza_feedback_data.json', orient='records', indent=2)\n",
" return \"JSON downloaded!\"\n",
" return \"No data to download\"\n",
"\n",
"# Create Gradio interface\n",
"with gr.Blocks(title=\"Pizza Feedback Data Generator\") as demo:\n",
" gr.Markdown(\"\"\"\n",
" # 🍕 Pizza Feedback Data Generator\n",
" Generate synthetic customer feedback for Nairobi pizza branches using AI models\n",
" \"\"\")\n",
" \n",
" with gr.Row():\n",
" with gr.Column():\n",
" model_selector = gr.Radio(\n",
" choices=list(MODELS.keys()),\n",
" label=\"Select AI Model\",\n",
" value=list(MODELS.keys())[0]\n",
" )\n",
" \n",
" num_records_slider = gr.Slider(\n",
" minimum=1,\n",
" maximum=50,\n",
" value=10,\n",
" step=1,\n",
" label=\"Number of Records\"\n",
" )\n",
" \n",
" generate_btn = gr.Button(\"Generate Feedback Data\", variant=\"primary\")\n",
" \n",
" with gr.Row():\n",
" status_output = gr.Textbox(label=\"Status\", interactive=False)\n",
" \n",
" with gr.Row():\n",
" dataframe_output = gr.Dataframe(\n",
" label=\"Generated Feedback Data\",\n",
" interactive=False\n",
" )\n",
" \n",
" with gr.Row():\n",
" csv_btn = gr.Button(\"Download CSV\")\n",
" json_btn = gr.Button(\"Download JSON\")\n",
" \n",
" # Event handlers\n",
" generate_btn.click(\n",
" fn=generate_feedback_data,\n",
" inputs=[model_selector, num_records_slider],\n",
" outputs=[dataframe_output, status_output]\n",
" )\n",
" \n",
" csv_btn.click(\n",
" fn=download_csv,\n",
" outputs=status_output\n",
" )\n",
" \n",
" json_btn.click(\n",
" fn=download_json,\n",
" outputs=status_output\n",
" )\n",
"\n",
"# Launch the interface\n",
"demo.launch()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

17
week3/community-contributions/samuel_bootcamp_wk3/pizza_feedback_data.csv Normal file
View File

@@ -0,0 +1,17 @@
Customer_ID,Branch,Rating,Order_Type,Feedback,Date
CUST1000,Westlands,1,Dine-in,Great pizza from Westlands! Quick delivery and hot food.,2024-10-17
CUST1001,CBD,1,Takeaway,Excellent service at CBD branch. Will order again!,2024-11-24
CUST1002,Kilimani,1,Delivery,Excellent service at Kilimani branch. Will order again!,2024-09-03
CUST1003,Parklands,5,Takeaway,Great pizza from Parklands! Quick delivery and hot food.,2024-08-05
CUST1004,Westlands,3,Delivery,Great pizza from Westlands! Quick delivery and hot food.,2024-01-12
CUST1005,CBD,5,Delivery,Great pizza from CBD! Quick delivery and hot food.,2024-01-10
CUST1006,Kilimani,1,Delivery,Long wait time at Kilimani but the pizza was worth it.,2024-09-12
CUST1007,Parklands,2,Delivery,Great pizza from Parklands! Quick delivery and hot food.,2024-05-27
CUST1008,Parklands,3,Dine-in,Excellent service at Parklands branch. Will order again!,2024-12-01
CUST1009,CBD,1,Dine-in,Excellent service at CBD branch. Will order again!,2024-10-09
CUST1010,Parklands,1,Takeaway,Average experience. Pizza was okay but nothing special.,2024-04-03
CUST1011,Westlands,2,Dine-in,Pizza was cold when it arrived at Westlands. Disappointed.,2024-01-02
CUST1012,Karen,2,Takeaway,Pizza was cold when it arrived at Karen. Disappointed.,2024-03-26
CUST1013,Westlands,3,Dine-in,Long wait time at Westlands but the pizza was worth it.,2024-11-17
CUST1014,Westlands,5,Takeaway,Average experience. Pizza was okay but nothing special.,2024-03-01
CUST1015,Parklands,3,Delivery,Excellent service at Parklands branch. Will order again!,2024-03-18
1 Customer_ID Branch Rating Order_Type Feedback Date
2 CUST1000 Westlands 1 Dine-in Great pizza from Westlands! Quick delivery and hot food. 2024-10-17
3 CUST1001 CBD 1 Takeaway Excellent service at CBD branch. Will order again! 2024-11-24
4 CUST1002 Kilimani 1 Delivery Excellent service at Kilimani branch. Will order again! 2024-09-03
5 CUST1003 Parklands 5 Takeaway Great pizza from Parklands! Quick delivery and hot food. 2024-08-05
6 CUST1004 Westlands 3 Delivery Great pizza from Westlands! Quick delivery and hot food. 2024-01-12
7 CUST1005 CBD 5 Delivery Great pizza from CBD! Quick delivery and hot food. 2024-01-10
8 CUST1006 Kilimani 1 Delivery Long wait time at Kilimani but the pizza was worth it. 2024-09-12
9 CUST1007 Parklands 2 Delivery Great pizza from Parklands! Quick delivery and hot food. 2024-05-27
10 CUST1008 Parklands 3 Dine-in Excellent service at Parklands branch. Will order again! 2024-12-01
11 CUST1009 CBD 1 Dine-in Excellent service at CBD branch. Will order again! 2024-10-09
12 CUST1010 Parklands 1 Takeaway Average experience. Pizza was okay but nothing special. 2024-04-03
13 CUST1011 Westlands 2 Dine-in Pizza was cold when it arrived at Westlands. Disappointed. 2024-01-02
14 CUST1012 Karen 2 Takeaway Pizza was cold when it arrived at Karen. Disappointed. 2024-03-26
15 CUST1013 Westlands 3 Dine-in Long wait time at Westlands but the pizza was worth it. 2024-11-17
16 CUST1014 Westlands 5 Takeaway Average experience. Pizza was okay but nothing special. 2024-03-01
17 CUST1015 Parklands 3 Delivery Excellent service at Parklands branch. Will order again! 2024-03-18