From f689f7d963d97b930dfce8645a9decd8e7a526ba Mon Sep 17 00:00:00 2001 From: MW-OAI Date: Wed, 15 Jan 2025 15:39:19 +0000 Subject: [PATCH] Adding consumption usage API CB to repo (#1631) --- authors.yaml | 5 + examples/completions_usage_api.ipynb | 1838 ++++++++++++++++++++++++++ registry.yaml | 9 + 3 files changed, 1852 insertions(+) create mode 100644 examples/completions_usage_api.ipynb diff --git a/authors.yaml b/authors.yaml index f5c95cf9d4..9d40ce1d33 100644 --- a/authors.yaml +++ b/authors.yaml @@ -212,3 +212,8 @@ kylecote-tray: name: "Kyle Cote" website: "https://github.com/kylecote-tray" avatar: "https://avatars.githubusercontent.com/u/53836176" + +MW-OAI: + name: "Mitch Welzen" + website: "https://www.linkedin.com/in/mitchwelzen/" + avatar: "https://media.licdn.com/dms/image/v2/C5603AQHC8-1q4MwH1A/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1592824550774?e=1742428800&v=beta&t=3mudgDyuzNU2a4gx1gue4DPyhaui7kbB7e7U8vyOo-g" diff --git a/examples/completions_usage_api.ipynb b/examples/completions_usage_api.ipynb new file mode 100644 index 0000000000..93db9ac962 --- /dev/null +++ b/examples/completions_usage_api.ipynb @@ -0,0 +1,1838 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# OpenAI Completions Usage API Extended Example\n", + "\n", + "For most of our users, the [default usage and cost dashboards](https://platform.openai.com/usage) are sufficient. However, if you need more detailed data or a custom dashboard, you can use the Completions Usage API.\n", + "\n", + "This notebook demonstrates how to retrieve and visualize usage data from the OpenAI Completions Usage API and Costs API. We'll:\n", + "- Call the API to get completions usage data.\n", + "- Parse the JSON response into a pandas DataFrame.\n", + "- Visualize token usage over time using matplotlib.\n", + "- Use grouping by model to analyze token usage across different models.\n", + "- Display model distribution with a pie chart.\n", + "\n", + "We also include placeholders for all possible API parameters for a comprehensive overview." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "# Install required libraries (if not already installed)\n", + "!pip install requests pandas numpy matplotlib --quiet\n", + "\n", + "# Import libraries\n", + "import requests\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.patches as mpatches\n", + "import time\n", + "import json\n", + "\n", + "# For inline plotting in Jupyter\n", + "%matplotlib inline\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup API Credentials and Parameters\n", + "\n", + "Set up an Admin Key - https://platform.openai.com/settings/organization/admin-keys\n", + "\n", + "Replace `'PLACEHOLDER'` with your actual ADMIN API key. It's best practice to load the key from an environment variable for security.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data retrieved successfully!\n" + ] + } + ], + "source": [ + "# Set up the API key and headers\n", + "OPENAI_ADMIN_KEY = '' \n", + "\n", + "headers = {\n", + " \"Authorization\": f\"Bearer {OPENAI_ADMIN_KEY}\",\n", + " \"Content-Type\": \"application/json\"\n", + "}\n", + "\n", + "# Define the API endpoint\n", + "url = \"https://api.openai.com/v1/organization/usage/completions\"\n", + "\n", + "# Calculate start time: n days ago from now\n", + "days_ago = 30\n", + "start_time = int(time.time()) - (days_ago * 24 * 60 * 60)\n", + "\n", + "# Define parameters with placeholders for all possible options\n", + "params = {\n", + " \"start_time\": start_time, # Required: Start time (Unix seconds)\n", + " # \"end_time\": end_time, # Optional: End time (Unix seconds)\n", + " \"bucket_width\": \"1d\", # Optional: '1m', '1h', or '1d' (default '1d')\n", + " # \"project_ids\": [\"proj_example\"], # Optional: List of project IDs\n", + " # \"user_ids\": [\"user_example\"], # Optional: List of user IDs\n", + " # \"api_key_ids\": [\"key_example\"], # Optional: List of API key IDs\n", + " # \"models\": [\"gpt-4o-mini-2024-07-18\"], # Optional: List of models\n", + " # \"batch\": False, # Optional: True for batch jobs, False for non-batch\n", + " # \"group_by\": [\"model\"], # Optional: Fields to group by\n", + " \"limit\": 7, # Optional: Number of buckets to return, this will chunk the data into 7 buckets\n", + " # \"page\": \"cursor_string\" # Optional: Cursor for pagination\n", + "}\n", + "\n", + "# Initialize an empty list to store all data\n", + "all_data = []\n", + "\n", + "# Initialize pagination cursor\n", + "page_cursor = None\n", + "\n", + "# Loop to handle pagination\n", + "while True:\n", + " if page_cursor:\n", + " params[\"page\"] = page_cursor\n", + "\n", + " response = requests.get(url, headers=headers, params=params)\n", + "\n", + " if response.status_code == 200:\n", + " data_json = response.json()\n", + " all_data.extend(data_json.get(\"data\", [])) \n", + "\n", + " page_cursor = data_json.get(\"next_page\")\n", + " if not page_cursor:\n", + " break \n", + " else:\n", + " print(f\"Error: {response.status_code}\")\n", + " break \n", + "\n", + "if all_data:\n", + " print(\"Data retrieved successfully!\")\n", + "else:\n", + " print(\"Issue: No data available to retrieve.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Inspect the JSON Response\n", + "\n", + "Let's take a look at the raw JSON response from the API to understand its structure.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[\n", + " {\n", + " \"object\": \"bucket\",\n", + " \"start_time\": 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\"api_key_id\": null,\n", + " \"model\": null,\n", + " \"batch\": null,\n", + " \"service_tier\": null,\n", + " \"input_cached_tokens\": 76544,\n", + " \"input_audio_tokens\": 5776,\n", + " \"output_audio_tokens\": 3166\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"object\": \"bucket\",\n", + " \"start_time\": 1736812800,\n", + " \"end_time\": 1736899200,\n", + " \"results\": [\n", + " {\n", + " \"object\": \"organization.usage.completions.result\",\n", + " \"input_tokens\": 52786,\n", + " \"output_tokens\": 38204,\n", + " \"num_model_requests\": 157,\n", + " \"project_id\": null,\n", + " \"user_id\": null,\n", + " \"api_key_id\": null,\n", + " \"model\": null,\n", + " \"batch\": null,\n", + " \"service_tier\": null,\n", + " \"input_cached_tokens\": 5440,\n", + " \"input_audio_tokens\": 4066,\n", + " \"output_audio_tokens\": 1097\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"object\": \"bucket\",\n", + " \"start_time\": 1736899200,\n", + " \"end_time\": 1736937980,\n", + " \"results\": [\n", + " {\n", + " \"object\": \"organization.usage.completions.result\",\n", + " \"input_tokens\": 9588,\n", + " \"output_tokens\": 224,\n", + " \"num_model_requests\": 34,\n", + " \"project_id\": null,\n", + " \"user_id\": null,\n", + " \"api_key_id\": null,\n", + " \"model\": null,\n", + " \"batch\": null,\n", + " \"service_tier\": null,\n", + " \"input_cached_tokens\": 192,\n", + " \"input_audio_tokens\": 349,\n", + " \"output_audio_tokens\": 499\n", + " }\n", + " ]\n", + " }\n", + "]\n" + ] + } + ], + "source": [ + "print(json.dumps(all_data, indent=2))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parse the API Response and Create a DataFrame\n", + "\n", + "Now we will parse the JSON data, extract relevant fields, and create a pandas DataFrame for easier manipulation and analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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start_datetimeend_datetimestart_timeend_timeinput_tokensoutput_tokensinput_cached_tokensinput_audio_tokensoutput_audio_tokensnum_model_requestsproject_iduser_idapi_key_idmodelbatchservice_tier
02024-12-16 10:46:172024-12-17173434597717343936003002455348745312000298NoneNoneNoneNoneNoneNone
12024-12-17 00:00:002024-12-1817343936001734480000890001NoneNoneNoneNoneNoneNone
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32024-12-19 00:00:002024-12-20173456640017346528001916251153584212181248338NoneNoneNoneNoneNoneNone
42024-12-20 00:00:002024-12-2117346528001734739200508822486700028NoneNoneNoneNoneNoneNone
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" + ], + "text/plain": [ + " start_datetime end_datetime start_time end_time input_tokens \\\n", + "0 2024-12-16 10:46:17 2024-12-17 1734345977 1734393600 300245 \n", + "1 2024-12-17 00:00:00 2024-12-18 1734393600 1734480000 8 \n", + "2 2024-12-18 00:00:00 2024-12-19 1734480000 1734566400 19287 \n", + "3 2024-12-19 00:00:00 2024-12-20 1734566400 1734652800 19162 \n", + "4 2024-12-20 00:00:00 2024-12-21 1734652800 1734739200 50882 \n", + "\n", + " output_tokens input_cached_tokens input_audio_tokens \\\n", + "0 534874 53120 0 \n", + "1 9 0 0 \n", + "2 1770 15104 47248 \n", + "3 5115 3584 21218 \n", + "4 24867 0 0 \n", + "\n", + " output_audio_tokens num_model_requests project_id user_id api_key_id \\\n", + "0 0 298 None None None \n", + "1 0 1 None None None \n", + "2 6403 24 None None None \n", + "3 12483 38 None None None \n", + "4 0 28 None None None \n", + "\n", + " model batch service_tier \n", + "0 None None None \n", + "1 None None None \n", + "2 None None None \n", + "3 None None None \n", + "4 None None None " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Initialize a list to hold parsed records\n", + "records = []\n", + "\n", + "# Iterate through the data to extract bucketed data\n", + "for bucket in all_data: \n", + " start_time = bucket.get(\"start_time\")\n", + " end_time = bucket.get(\"end_time\")\n", + " for result in bucket.get(\"results\", []):\n", + " records.append({\n", + " \"start_time\": start_time,\n", + " \"end_time\": end_time,\n", + " \"input_tokens\": result.get(\"input_tokens\", 0),\n", + " \"output_tokens\": result.get(\"output_tokens\", 0),\n", + " \"input_cached_tokens\": result.get(\"input_cached_tokens\", 0),\n", + " \"input_audio_tokens\": result.get(\"input_audio_tokens\", 0),\n", + " \"output_audio_tokens\": result.get(\"output_audio_tokens\", 0),\n", + " \"num_model_requests\": result.get(\"num_model_requests\", 0),\n", + " \"project_id\": result.get(\"project_id\"),\n", + " \"user_id\": result.get(\"user_id\"),\n", + " \"api_key_id\": result.get(\"api_key_id\"),\n", + " \"model\": result.get(\"model\"),\n", + " \"batch\": result.get(\"batch\"),\n", + " \"service_tier\": result.get(\"service_tier\")\n", + " })\n", + "\n", + "# Create a DataFrame from the records\n", + "df = pd.DataFrame(records)\n", + "\n", + "# Convert Unix timestamps to datetime for readability\n", + "df['start_datetime'] = pd.to_datetime(df['start_time'], unit='s')\n", + "df['end_datetime'] = pd.to_datetime(df['end_time'], unit='s')\n", + "\n", + "# Reorder columns for better readability\n", + "df = df[\n", + " [\n", + " \"start_datetime\", \"end_datetime\", \"start_time\", \"end_time\",\n", + " \"input_tokens\", \"output_tokens\", \"input_cached_tokens\",\n", + " \"input_audio_tokens\", \"output_audio_tokens\", \"num_model_requests\",\n", + " \"project_id\", \"user_id\", \"api_key_id\", \"model\", \"batch\", \"service_tier\"\n", + " ]\n", + "]\n", + "\n", + "# Display the DataFrame\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualize Token Usage Over Time\n", + "\n", + "We'll create a bar chart to visualize input and output token usage for each time bucket.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if not df.empty:\n", + " plt.figure(figsize=(12, 6))\n", + " \n", + " # Create bar charts for input and output tokens\n", + " width = 0.35 # width of the bars\n", + " indices = range(len(df))\n", + " \n", + " plt.bar(indices, df['input_tokens'], width=width, label='Input Tokens', alpha=0.7)\n", + " plt.bar([i + width for i in indices], df['output_tokens'], width=width, label='Output Tokens', alpha=0.7)\n", + " \n", + " # Set labels and ticks\n", + " plt.xlabel('Time Bucket')\n", + " plt.ylabel('Number of Tokens')\n", + " plt.title('Daily Input vs Output Token Usage Last 30 Days')\n", + " plt.xticks([i + width/2 for i in indices], [dt.strftime('%Y-%m-%d') for dt in df['start_datetime']], rotation=45)\n", + " plt.legend()\n", + " plt.tight_layout()\n", + " plt.show()\n", + "else:\n", + " print(\"No data available to plot.\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visual Example: Grouping by Model\n", + "\n", + "In this section, we retrieve and visualize usage data grouped by model and project_id. This can help you see the total tokens used by each model over the specified period.\n", + "\n", + "### Note on Grouping Parameter\n", + "\n", + "- If you do not specify a `group_by` parameter, fields such as `project_id`, `model`, and others will return as `null`. \n", + " Although the `group_by` parameter is optional, it is recommended to include it in most cases to retrieve meaningful data.\n", + " \n", + "- You can specify multiple group fields by separating them with commas. For example: `group_by=[\"model\", \"project_id\"]`." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data retrieved successfully!\n" + ] + }, + { + "data": { + "text/html": [ + "
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start_datetimeend_datetimestart_timeend_timeinput_tokensoutput_tokensinput_cached_tokensinput_audio_tokensoutput_audio_tokensnum_model_requestsproject_iduser_idapi_key_idmodelbatchservice_tier
02024-12-16 10:46:292024-12-1717343459891734393600224831548800032proj_frFrNmknEESBPFLqlnYutIA9NoneNonegpt-4o-2024-08-06NoneNone
12024-12-16 10:46:292024-12-171734345989173439360022454439900032proj_frFrNmknEESBPFLqlnYutIA9NoneNonegpt-3.5-turbo-0125NoneNone
22024-12-16 10:46:292024-12-171734345989173439360038084800024proj_VV4ZAjd6ALfFd9uh0vY8joR1NoneNonegpt-4o-mini-2024-07-18NoneNone
32024-12-16 10:46:292024-12-171734345989173439360037236800013proj_VV4ZAjd6ALfFd9uh0vY8joR1NoneNonegpt-4o-2024-08-06NoneNone
42024-12-16 10:46:292024-12-1717343459891734393600134314680007proj_L67gOme4S2nBA8aQieEOwLy7NoneNonegpt-4o-2024-08-06NoneNone
\n", + "
" + ], + "text/plain": [ + " start_datetime end_datetime start_time end_time input_tokens \\\n", + "0 2024-12-16 10:46:29 2024-12-17 1734345989 1734393600 22483 \n", + "1 2024-12-16 10:46:29 2024-12-17 1734345989 1734393600 22454 \n", + "2 2024-12-16 10:46:29 2024-12-17 1734345989 1734393600 380 \n", + "3 2024-12-16 10:46:29 2024-12-17 1734345989 1734393600 372 \n", + "4 2024-12-16 10:46:29 2024-12-17 1734345989 1734393600 1343 \n", + "\n", + " output_tokens input_cached_tokens input_audio_tokens \\\n", + "0 15488 0 0 \n", + "1 4399 0 0 \n", + "2 848 0 0 \n", + "3 368 0 0 \n", + "4 1468 0 0 \n", + "\n", + " output_audio_tokens num_model_requests project_id \\\n", + "0 0 32 proj_frFrNmknEESBPFLqlnYutIA9 \n", + "1 0 32 proj_frFrNmknEESBPFLqlnYutIA9 \n", + "2 0 24 proj_VV4ZAjd6ALfFd9uh0vY8joR1 \n", + "3 0 13 proj_VV4ZAjd6ALfFd9uh0vY8joR1 \n", + "4 0 7 proj_L67gOme4S2nBA8aQieEOwLy7 \n", + "\n", + " user_id api_key_id model batch service_tier \n", + "0 None None gpt-4o-2024-08-06 None None \n", + "1 None None gpt-3.5-turbo-0125 None None \n", + "2 None None gpt-4o-mini-2024-07-18 None None \n", + "3 None None gpt-4o-2024-08-06 None None \n", + "4 None None gpt-4o-2024-08-06 None None " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Calculate start time: n days ago from now\n", + "days_ago = 30\n", + "start_time = int(time.time()) - (days_ago * 24 * 60 * 60)\n", + "\n", + "# Define parameters with grouping by model and project_id\n", + "params = {\n", + " \"start_time\": start_time, # Required: Start time (Unix seconds)\n", + " \"bucket_width\": \"1d\", # Optional: '1m', '1h', or '1d' (default '1d')\n", + " \"group_by\": [\"model\", \"project_id\"], # Group data by model and project_id\n", + " \"limit\": 7 # Optional: Number of buckets to return\n", + "}\n", + "\n", + "# Initialize an empty list to store all data\n", + "all_group_data = []\n", + "\n", + "# Initialize pagination cursor\n", + "page_cursor = None\n", + "\n", + "# Loop to handle pagination\n", + "while True:\n", + " if page_cursor:\n", + " params[\"page\"] = page_cursor\n", + "\n", + " response = requests.get(url, headers=headers, params=params)\n", + "\n", + " if response.status_code == 200:\n", + " data_json = response.json()\n", + " all_group_data.extend(data_json.get(\"data\", []))\n", + "\n", + " page_cursor = data_json.get(\"next_page\")\n", + " if not page_cursor:\n", + " break \n", + " else:\n", + " print(f\"Error: {response.status_code}\")\n", + " break \n", + "\n", + "if all_group_data:\n", + " print(\"Data retrieved successfully!\")\n", + "else:\n", + " print(\"Issue: No data available to retrieve.\")\n", + "\n", + "# Initialize a list to hold parsed records\n", + "records = []\n", + "\n", + "# Iterate through the data to extract bucketed data\n", + "for bucket in all_group_data:\n", + " start_time = bucket.get(\"start_time\")\n", + " end_time = bucket.get(\"end_time\")\n", + " for result in bucket.get(\"results\", []):\n", + " records.append({\n", + " \"start_time\": start_time,\n", + " \"end_time\": end_time,\n", + " \"input_tokens\": result.get(\"input_tokens\", 0),\n", + " \"output_tokens\": result.get(\"output_tokens\", 0),\n", + " \"input_cached_tokens\": result.get(\"input_cached_tokens\", 0),\n", + " \"input_audio_tokens\": result.get(\"input_audio_tokens\", 0),\n", + " \"output_audio_tokens\": result.get(\"output_audio_tokens\", 0),\n", + " \"num_model_requests\": result.get(\"num_model_requests\", 0),\n", + " \"project_id\": result.get(\"project_id\", \"N/A\"),\n", + " \"user_id\": result.get(\"user_id\", \"N/A\"),\n", + " \"api_key_id\": result.get(\"api_key_id\", \"N/A\"),\n", + " \"model\": result.get(\"model\", \"N/A\"),\n", + " \"batch\": result.get(\"batch\", \"N/A\"),\n", + " \"service_tier\": result.get(\"service_tier\", \"N/A\")\n", + " })\n", + "\n", + "# Create a DataFrame from the records\n", + "df = pd.DataFrame(records)\n", + "\n", + "# Convert Unix timestamps to datetime for readability\n", + "df['start_datetime'] = pd.to_datetime(df['start_time'], unit='s', errors='coerce')\n", + "df['end_datetime'] = pd.to_datetime(df['end_time'], unit='s', errors='coerce')\n", + "\n", + "# Reorder columns for better readability\n", + "df = df[\n", + " [\n", + " \"start_datetime\", \"end_datetime\", \"start_time\", \"end_time\",\n", + " \"input_tokens\", \"output_tokens\", \"input_cached_tokens\",\n", + " \"input_audio_tokens\", \"output_audio_tokens\", \"num_model_requests\",\n", + " \"project_id\", \"user_id\", \"api_key_id\", \"model\", \"batch\", \"service_tier\"\n", + " ]\n", + "]\n", + "\n", + "# Display the DataFrame\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parse the API Response into DataFrame and render a stacked bar chart\n", + "\n", + "Now we will parse the JSON data, extract relevant fields, and create a pandas DataFrame for easier manipulation and analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Group data by model and project_id and aggregate model request counts\n", + "grouped_by_model_project = (\n", + " df.groupby([\"model\", \"project_id\"])\n", + " .agg({\n", + " \"num_model_requests\": \"sum\",\n", + " })\n", + " .reset_index()\n", + ")\n", + "\n", + "# Determine unique models and project IDs for plotting and color mapping\n", + "models = sorted(grouped_by_model_project['model'].unique())\n", + "project_ids = sorted(grouped_by_model_project['project_id'].unique())\n", + "distinct_colors = [\n", + " \"#1f77b4\", \"#ff7f0e\", \"#2ca02c\", \"#d62728\", \"#9467bd\",\n", + " \"#8c564b\", \"#e377c2\", \"#7f7f7f\", \"#bcbd22\", \"#17becf\"\n", + "]\n", + "project_color_mapping = {pid: distinct_colors[i % len(distinct_colors)] for i, pid in enumerate(project_ids)}\n", + "\n", + "# Calculate total number of requests per project_id for legend\n", + "project_totals = (\n", + " grouped_by_model_project.groupby(\"project_id\")[\"num_model_requests\"].sum()\n", + " .sort_values(ascending=False) # Sort by highest total first\n", + ")\n", + "\n", + "# Set up bar positions\n", + "n_models = len(models)\n", + "bar_width = 0.6\n", + "x = np.arange(n_models)\n", + "\n", + "plt.figure(figsize=(12, 6))\n", + "\n", + "# Plot stacked bars for each model\n", + "for model_idx, model in enumerate(models):\n", + " # Filter data for the current model\n", + " model_data = grouped_by_model_project[grouped_by_model_project['model'] == model]\n", + " \n", + " bottom = 0\n", + " # Stack segments for each project ID within the bars\n", + " for _, row in model_data.iterrows():\n", + " color = project_color_mapping[row['project_id']]\n", + " plt.bar(x[model_idx], row['num_model_requests'], width=bar_width,\n", + " bottom=bottom, color=color)\n", + " bottom += row['num_model_requests']\n", + "\n", + "# Labeling and styling\n", + "plt.xlabel('Model')\n", + "plt.ylabel('Number of Model Requests')\n", + "plt.title('Total Model Requests by Model and Project ID Last 30 Days')\n", + "plt.xticks(x, models, rotation=45, ha=\"right\")\n", + "\n", + "# Create a sorted legend with totals\n", + "handles = [\n", + " mpatches.Patch(\n", + " color=project_color_mapping[pid],\n", + " label=f\"{pid} (Total: {total})\"\n", + " )\n", + " for pid, total in project_totals.items()\n", + "]\n", + "plt.legend(handles=handles, bbox_to_anchor=(1.05, 1), loc='upper left')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visual Example: Model Distribution Pie Chart\n", + "\n", + "This section visualizes the distribution of token usage across different models using a pie chart.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "records = []\n", + "for bucket in all_group_data:\n", + " for result in bucket.get(\"results\", []):\n", + " records.append({\n", + " \"project_id\": result.get(\"project_id\", \"N/A\"),\n", + " \"num_model_requests\": result.get(\"num_model_requests\", 0),\n", + " })\n", + "\n", + "# Create a DataFrame\n", + "df = pd.DataFrame(records)\n", + "\n", + "# Aggregate data by project_id\n", + "grouped_by_project = (\n", + " df.groupby(\"project_id\")\n", + " .agg({\"num_model_requests\": \"sum\"})\n", + " .reset_index()\n", + ")\n", + "\n", + "# Visualize Pie Chart\n", + "if not grouped_by_project.empty:\n", + " # Filter out rows where num_model_requests == 0\n", + " filtered_grouped_by_project = grouped_by_project[grouped_by_project['num_model_requests'] > 0]\n", + " \n", + " # Calculate the total model requests after filtering\n", + " total_requests = filtered_grouped_by_project['num_model_requests'].sum()\n", + " \n", + " if total_requests > 0:\n", + " # Calculate percentage of total for each project\n", + " filtered_grouped_by_project['percentage'] = (\n", + " filtered_grouped_by_project['num_model_requests'] / total_requests\n", + " ) * 100\n", + " \n", + " # Separate \"Other\" projects (below 5%)\n", + " other_projects = filtered_grouped_by_project[filtered_grouped_by_project['percentage'] < 5]\n", + " main_projects = filtered_grouped_by_project[filtered_grouped_by_project['percentage'] >= 5]\n", + " \n", + " # Sum up \"Other\" projects\n", + " if not other_projects.empty:\n", + " other_row = pd.DataFrame({\n", + " \"project_id\": [\"Other\"],\n", + " \"num_model_requests\": [other_projects['num_model_requests'].sum()],\n", + " \"percentage\": [other_projects['percentage'].sum()]\n", + " })\n", + " filtered_grouped_by_project = pd.concat([main_projects, other_row], ignore_index=True)\n", + " \n", + " # Sort by number of requests for better legend organization\n", + " filtered_grouped_by_project = filtered_grouped_by_project.sort_values(by=\"num_model_requests\", ascending=False)\n", + " \n", + " # Main pie chart for distribution of model requests by project_id\n", + " plt.figure(figsize=(10, 8))\n", + " plt.pie(\n", + " filtered_grouped_by_project['num_model_requests'], \n", + " labels=filtered_grouped_by_project['project_id'], \n", + " autopct=lambda p: f'{p:.1f}%\\n({int(p * total_requests / 100):,})',\n", + " startangle=140,\n", + " textprops={'fontsize': 10}\n", + " )\n", + " plt.title('Distribution of Model Requests by Project ID', fontsize=14)\n", + " plt.axis('equal') # Equal aspect ratio ensures pie chart is circular.\n", + " plt.tight_layout()\n", + " plt.show()\n", + " \n", + " # If there are \"Other\" projects, generate a second pie chart for breakdown\n", + " if not other_projects.empty:\n", + " other_total_requests = other_projects['num_model_requests'].sum()\n", + " \n", + " plt.figure(figsize=(10, 8))\n", + " plt.pie(\n", + " other_projects['num_model_requests'], \n", + " labels=other_projects['project_id'], \n", + " autopct=lambda p: f'{p:.1f}%\\n({int(p * other_total_requests / 100):,})',\n", + " startangle=140,\n", + " textprops={'fontsize': 10}\n", + " )\n", + " plt.title('Breakdown of \"Other\" Projects by Model Requests', fontsize=14)\n", + " plt.axis('equal') # Equal aspect ratio ensures pie chart is circular.\n", + " plt.tight_layout()\n", + " plt.show()\n", + " else:\n", + " print(\"Total model requests is zero. Pie chart will not be rendered.\")\n", + "else:\n", + " print(\"No grouped data available for pie chart.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Costs API Example\n", + "\n", + "In this section, we'll work with the OpenAI Costs API to retrieve and visualize cost data. Similar to the completions data, we'll:\n", + "- Call the Costs API to get aggregated cost data.\n", + "- Parse the JSON response into a pandas DataFrame.\n", + "- Visualize costs grouped by line item using a bar chart." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Costs data retrieved successfully!\n" + ] + } + ], + "source": [ + "# Calculate start time: n days ago from now\n", + "days_ago = 30\n", + "start_time = int(time.time()) - (days_ago * 24 * 60 * 60)\n", + "\n", + "# Define the Costs API endpoint\n", + "costs_url = \"https://api.openai.com/v1/organization/costs\"\n", + "\n", + "# Initialize an empty list to store all data\n", + "all_costs_data = []\n", + "\n", + "# Initialize pagination cursor\n", + "page_cursor = None\n", + "\n", + "# Loop to handle pagination\n", + "while True:\n", + " costs_params = {\n", + " \"start_time\": start_time, # Required: Start time (Unix seconds)\n", + " \"bucket_width\": \"1d\", # Optional: Currently only '1d' is supported\n", + " \"limit\": 30, # Optional: Number of buckets to return\n", + " }\n", + "\n", + " if page_cursor:\n", + " costs_params[\"page\"] = page_cursor\n", + "\n", + " costs_response = requests.get(costs_url, headers=headers, params=costs_params)\n", + "\n", + " if costs_response.status_code == 200:\n", + " costs_json = costs_response.json()\n", + " all_costs_data.extend(costs_json.get(\"data\", []))\n", + "\n", + " page_cursor = costs_json.get(\"next_page\")\n", + " if not page_cursor:\n", + " break\n", + " else:\n", + " print(f\"Error: {costs_response.status_code}\")\n", + " break\n", + "\n", + "if all_costs_data:\n", + " print(\"Costs data retrieved successfully!\")\n", + "else:\n", + " print(\"No costs data found.\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parse the Costs API Response and Create a DataFrame\n", + "\n", + "We will now parse the JSON data from the Costs API, extract relevant fields, and create a pandas DataFrame for further analysis.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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start_timeend_timeamount_valuecurrencyline_itemproject_idstart_datetimeend_datetime
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" + ], + "text/plain": [ + " start_time end_time amount_value currency line_item project_id \\\n", + "0 1734307200 1734393600 55.358578 usd None None \n", + "1 1734393600 1734480000 0.000110 usd None None \n", + "2 1734480000 1734566400 0.016204 usd None None \n", + "3 1734566400 1734652800 2.121425 usd None None \n", + "4 1734652800 1734739200 3.771420 usd None None \n", + "\n", + " start_datetime end_datetime \n", + "0 2024-12-16 2024-12-17 \n", + "1 2024-12-17 2024-12-18 \n", + "2 2024-12-18 2024-12-19 \n", + "3 2024-12-19 2024-12-20 \n", + "4 2024-12-20 2024-12-21 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Initialize a list to hold parsed cost records\n", + "cost_records = []\n", + "\n", + "# Extract bucketed cost data from all_costs_data\n", + "for bucket in all_costs_data:\n", + " start_time = bucket.get(\"start_time\")\n", + " end_time = bucket.get(\"end_time\")\n", + " for result in bucket.get(\"results\", []):\n", + " cost_records.append({\n", + " \"start_time\": start_time,\n", + " \"end_time\": end_time,\n", + " \"amount_value\": result.get(\"amount\", {}).get(\"value\", 0),\n", + " \"currency\": result.get(\"amount\", {}).get(\"currency\", \"usd\"),\n", + " \"line_item\": result.get(\"line_item\"),\n", + " \"project_id\": result.get(\"project_id\")\n", + " })\n", + "\n", + "# Create a DataFrame from the cost records\n", + "cost_df = pd.DataFrame(cost_records)\n", + "\n", + "# Convert Unix timestamps to datetime for readability\n", + "cost_df['start_datetime'] = pd.to_datetime(cost_df['start_time'], unit='s')\n", + "cost_df['end_datetime'] = pd.to_datetime(cost_df['end_time'], unit='s')\n", + "\n", + "# Display the first few rows of the DataFrame\n", + "cost_df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualize Costs by Line Item\n", + "\n", + "We'll create a bar chart to visualize the total costs aggregated by line item. This helps identify which categories (e.g., models or other services) contribute most to the expenses.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if not cost_df.empty:\n", + " # Ensure datetime conversion for 'start_datetime' column\n", + " if 'start_datetime' not in cost_df.columns or not pd.api.types.is_datetime64_any_dtype(cost_df['start_datetime']):\n", + " cost_df['start_datetime'] = pd.to_datetime(cost_df['start_time'], unit='s', errors='coerce')\n", + "\n", + " # Create a new column for just the date part of 'start_datetime'\n", + " cost_df['date'] = cost_df['start_datetime'].dt.date\n", + " \n", + " # Group by date and sum the amounts\n", + " cost_per_day = cost_df.groupby('date')['amount_value'].sum().reset_index()\n", + " \n", + " # Plot the data\n", + " plt.figure(figsize=(12, 6))\n", + " plt.bar(cost_per_day['date'], cost_per_day['amount_value'], width=0.6, color='skyblue', alpha=0.8)\n", + " plt.xlabel('Date')\n", + " plt.ylabel('Total Cost (USD)')\n", + " plt.title('Total Cost per Day (Last 30 Days)')\n", + " plt.xticks(rotation=45, ha='right')\n", + " plt.tight_layout()\n", + " plt.show()\n", + "else:\n", + " print(\"No cost data available to plot.\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Additional Visualizations (Optional)\n", + "\n", + "You can extend this notebook with more visualizations for both the Completions and Costs APIs. For example:\n", + "\n", + "**Completions API:**\n", + "- Group by user, project, or model to see which ones consume the most tokens.\n", + "- Create line plots for time series analysis of token usage over days or hours.\n", + "- Use pie charts to visualize distribution of tokens across models, users, or projects.\n", + "- Experiment with different `group_by` parameters (e.g., `[\"model\", \"user_id\"]`) to gain deeper insights.\n", + "\n", + "**Costs API:**\n", + "- Group by project or line item to identify spending patterns.\n", + "- Create line or bar charts to visualize daily cost trends.\n", + "- Use pie charts to show how costs are distributed across projects, services, or line items.\n", + "- Try various `group_by` options (e.g., `[\"project_id\"]`, `[\"line_item\"]`) for granular analysis.\n", + "\n", + "Experiment with different parameters and visualization techniques using `pandas` and `matplotlib` (or libraries like Plotly/Bokeh) to gain deeper insights, and consider integrating these visualizations into interactive dashboards for real-time monitoring.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Integrating with Third-Party Dashboarding Platforms\n", + "\n", + "To bring OpenAI usage and cost data into external dashboarding tools like Tableau, Power BI, or custom platforms (e.g., Plotly Dash, Bokeh), follow these steps:\n", + "\n", + "1. **Data Collection & Preparation:**\n", + " - Use Python scripts to regularly fetch data from the Completions and Costs APIs.\n", + " - Process and aggregate the data with pandas, then store it in a database, data warehouse, or export it as CSV/JSON files.\n", + "\n", + "2. **Connecting to a Dashboard:**\n", + " - **BI Tools (Tableau, Power BI):**\n", + " - Connect directly to the prepared data source (SQL database, CSV files, or web APIs).\n", + " - Use built-in connectors to schedule data refreshes, ensuring dashboards always display current information.\n", + " - **Custom Dashboards (Plotly Dash, Bokeh):**\n", + " - Embed API calls and data processing into the dashboard code.\n", + " - Build interactive visual components that automatically update as new data is fetched.\n", + "\n", + "3. **Real-Time & Automated Updates:**\n", + " - Schedule scripts using cron jobs, task schedulers, or workflow tools (e.g., Apache Airflow) to refresh data periodically.\n", + " - Implement webhooks or streaming APIs (if available) for near real-time data updates.\n", + "\n", + "By integrating API data into third-party platforms, you can create interactive, real-time dashboards that combine OpenAI metrics with other business data, offering comprehensive insights and automated monitoring.\n" + ] + } + ], + "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": "3.13.0" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/registry.yaml b/registry.yaml index 6af129f2f5..18f358facc 100644 --- a/registry.yaml +++ b/registry.yaml @@ -1778,3 +1778,12 @@ - colin-jarvis tags: - guardrails + +- title: How to use the Usage API and Cost API to monitor your OpenAI usage + path: examples/completions_usage_api.ipynb + date: 2025-01-14 + authors: + - MW-OAI + tags: + - usage-api + - cost-api