From 05891fcfc06c88b9097cc03b422d2e42e0784eb0 Mon Sep 17 00:00:00 2001 From: Lorenzo Drudi Date: Sat, 27 Apr 2024 15:44:59 +0200 Subject: [PATCH] fix(docs): fix demo nb. --- demo.ipynb | 52 +++++++++++++--------------------- openai_cost_logger/__init__.py | 2 +- setup.py | 2 +- 3 files changed, 21 insertions(+), 35 deletions(-) diff --git a/demo.ipynb b/demo.ipynb index 0d330ee..aca82d4 100644 --- a/demo.ipynb +++ b/demo.ipynb @@ -2,18 +2,9 @@ "cells": [ { "cell_type": "code", - "execution_count": 76, + "execution_count": 1, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "The autoreload extension is already loaded. To reload it, use:\n", - " %reload_ext autoreload\n" - ] - } - ], + "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" @@ -28,7 +19,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -75,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -129,29 +120,24 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "import os\n", - "import sys\n", - "import openai\n", - "import pathlib\n", - "\n", - "# Add the src directory to the path\n", - "sys.path.insert(0, str(pathlib.Path('src')))" + "import openai" ] }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "imported openai_cost_logger\n" + "imported openai-cost-logger\n" ] } ], @@ -171,7 +157,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -191,7 +177,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -212,7 +198,7 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -226,7 +212,7 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -250,7 +236,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -286,14 +272,14 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Total cost: 3e-05 (USD)\n" + "Total cost: 4.4e-05 (USD)\n" ] } ], @@ -304,14 +290,14 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "gpt-3.5-turbo-0125: 2.8e-05 (USD)\n", + "gpt-3.5-turbo-0125: 4.2e-05 (USD)\n", "text-embedding-ada-002: 2e-06 (USD)\n" ] } @@ -323,12 +309,12 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] diff --git a/openai_cost_logger/__init__.py b/openai_cost_logger/__init__.py index e511bd8..4a243e6 100644 --- a/openai_cost_logger/__init__.py +++ b/openai_cost_logger/__init__.py @@ -2,4 +2,4 @@ from .constants import MODELS_COST, DEFAULT_LOG_PATH from .openai_cost_logger_viz import OpenAICostLoggerViz from .openai_cost_logger_utils import OpenAICostLoggerUtils -print('imported openai_cost_logger') \ No newline at end of file +print('imported openai-cost-logger') \ No newline at end of file diff --git a/setup.py b/setup.py index 797e609..548984d 100644 --- a/setup.py +++ b/setup.py @@ -4,7 +4,7 @@ with open('README.rst') as f: long_description = f.read() -version_number = '0.3.0' +version_number = '0.3.1' setup( name='openai-cost-logger',