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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,145 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "aaceb216-d941-44a2-acef-cf11ea2df53f", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# Feedback Analysis Example\n", | ||
| "## Prerequisites\n", | ||
| "Download conversation log using Athena. Following is an example query to get conversation with user's feedback:\n", | ||
| "\n", | ||
| "```sql\n", | ||
| "SELECT \n", | ||
| " d.newimage.PK.S AS UserId,\n", | ||
| " d.newimage.SK.S AS ConvId,\n", | ||
| " d.newimage.TotalPrice.N AS TotalPrice,\n", | ||
| " d.newimage.MessageMap.S AS MessageMap\n", | ||
| "FROM \n", | ||
| " bedrockchatstack_usage_analysis.ddb_export d\n", | ||
| "WHERE \n", | ||
| " d.datehour BETWEEN '2024/04/01/00' AND '2024/04/29/23'\n", | ||
| " AND REGEXP_LIKE(d.newimage.MessageMap.S, '\"feedback\":((?!\\snull).)')\n", | ||
| "ORDER BY\n", | ||
| " d.datehour DESC\n", | ||
| "```" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "4897c330-b12d-4bfe-88c9-6c770d98649f", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import pandas as pd\n", | ||
| "import json" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "47bc6a80-bbdf-4ead-9693-d74aa3860b40", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from IPython import display\n", | ||
| "\n", | ||
| "def extract_conversation(data):\n", | ||
| " # Extract conversation to display.\n", | ||
| " conversation = []\n", | ||
| "\n", | ||
| " for key, value in data.items():\n", | ||
| " if key not in (\"system\", \"instruction\"):\n", | ||
| " # print(f\"key: {key}\")\n", | ||
| " # print(f\"value: {value}\")\n", | ||
| " role = value['role']\n", | ||
| " feedback = value.get('feedback')\n", | ||
| " used_chunks = value.get('used_chunks')\n", | ||
| " content = value['content'][0]['body']\n", | ||
| "\n", | ||
| " content = content.replace('\\\\n', '\\n')\n", | ||
| "\n", | ||
| " conversation.append(f\"### {role.capitalize()}:\\n\\n{content.strip()}\")\n", | ||
| " if feedback:\n", | ||
| " category = feedback.get('category')\n", | ||
| " comment = feedback.get('comment')\n", | ||
| " conversation.append(f\"### feedback:\\n\\ncategory: {category}\\n\\ncomment: {comment}\")\n", | ||
| " \n", | ||
| " if used_chunks:\n", | ||
| " conversation.append(f\"### used_chunks:\\n\\n{used_chunks}\")\n", | ||
| "\n", | ||
| " return \"\\n\\n\".join(conversation)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "25388648-cc07-47d5-a214-245320c97e1c", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Enter downloaded csv file path from athena\n", | ||
| "filepath = './xxx.csv'\n", | ||
| "df = pd.read_csv(filepath)\n", | ||
| "df.head()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "7a6fc548-3d1c-4b12-947a-1dd5c6468c75", | ||
| "metadata": { | ||
| "tags": [] | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# Display conversation with feedback and used RAG chunks\n", | ||
| "display.Markdown(extract_conversation(json.loads(df[\"MessageMap\"].iloc[1])))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "65d7b127-091c-4afb-97c2-d4ae7552b3a6", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "8f9d7cbb-746a-4ce6-a398-7eb292e988cf", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "conda_python3", | ||
| "language": "python", | ||
| "name": "conda_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": "3.10.13" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |