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gpt cache cookbook

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ishaan-jaff 2023-08-27 10:33:07 -07:00
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"# Using GPT Cache x LiteLLM\n",
"- Cut costs 10x, improve speed 100x"
],
"metadata": {
"id": "kBwDrphDDEoO"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "_K_4auSgCSjg"
},
"outputs": [],
"source": [
"!pip install litellm gptcache"
]
},
{
"cell_type": "markdown",
"source": [
"# Usage\n",
"* use `from litellm.cache import completion`\n",
"* Init GPT Cache using the following lines:\n",
"```python\n",
"from gptcache import cache\n",
"cache.init()\n",
"cache.set_openai_key()\n",
"```"
],
"metadata": {
"id": "DlZ22IfmDR5L"
}
},
{
"cell_type": "markdown",
"source": [
"## With OpenAI"
],
"metadata": {
"id": "js80pW9PC1KQ"
}
},
{
"cell_type": "code",
"source": [
"from gptcache import cache\n",
"import os\n",
"from litellm.cache import completion # import completion from litellm.cache\n",
"import time\n",
"\n",
"# Set your .env keys\n",
"os.environ['OPENAI_API_KEY'] = \"\"\n",
"\n",
"##### GPT Cache Init\n",
"cache.init()\n",
"cache.set_openai_key()\n",
"#### End of GPT Cache Init\n",
"\n",
"question = \"what's LiteLLM\"\n",
"for _ in range(2):\n",
" start_time = time.time()\n",
" response = completion(\n",
" model='gpt-3.5-turbo',\n",
" messages=[\n",
" {\n",
" 'role': 'user',\n",
" 'content': question\n",
" }\n",
" ],\n",
" )\n",
" print(f'Question: {question}')\n",
" print(\"Time consuming: {:.2f}s\".format(time.time() - start_time))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "24a-mg1OCWe1",
"outputId": "36130cb6-9bd6-4bc6-8405-b6e19a1e9357"
},
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"start to install package: redis\n",
"successfully installed package: redis\n",
"start to install package: redis_om\n",
"successfully installed package: redis_om\n",
"Question: what's LiteLLM\n",
"Time consuming: 1.18s\n",
"Question: what's LiteLLM\n",
"Time consuming: 0.00s\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## With Cohere"
],
"metadata": {
"id": "xXPtHamPCy73"
}
},
{
"cell_type": "code",
"source": [
"from gptcache import cache\n",
"import os\n",
"from litellm.cache import completion # import completion from litellm.cache\n",
"import time\n",
"\n",
"# Set your .env keys\n",
"os.environ['COHERE_API_KEY'] = \"\"\n",
"\n",
"##### GPT Cache Init\n",
"cache.init()\n",
"cache.set_openai_key()\n",
"#### End of GPT Cache Init\n",
"\n",
"question = \"what's LiteLLM Github\"\n",
"for _ in range(2):\n",
" start_time = time.time()\n",
" response = completion(\n",
" model='gpt-3.5-turbo',\n",
" messages=[\n",
" {\n",
" 'role': 'user',\n",
" 'content': question\n",
" }\n",
" ],\n",
" )\n",
" print(f'Question: {question}')\n",
" print(\"Time consuming: {:.2f}s\".format(time.time() - start_time))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "goRtiiAlChRW",
"outputId": "47f473da-5560-4d6f-d9ef-525ff8e60758"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Question: what's LiteLLM Github\n",
"Time consuming: 1.58s\n",
"Question: what's LiteLLM Github\n",
"Time consuming: 0.00s\n"
]
}
]
}
]
}