Spaces:
Running
Running
File size: 5,414 Bytes
b247dc4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 |
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"OPENAI_KEY1 = \"sk-XXX\"\n",
"OPENAI_KEY2 = \"sk-XX\""
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Use OpenAI\n",
"\n",
"Set you `OPENAI_API_KEY` environment variable."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from manifest import Manifest\n",
"from manifest.connections.client_pool import ClientConnection\n",
"\n",
"openai_ada = ClientConnection(\n",
" client_name=\"openai\",\n",
" client_connection=OPENAI_KEY1,\n",
" engine=\"text-ada-001\"\n",
")\n",
"\n",
"openai_curie = ClientConnection(\n",
" client_name=\"openai\",\n",
" client_connection=OPENAI_KEY2,\n",
" engine=\"text-curie-001\"\n",
")\n",
"\n",
"manifest = Manifest(client_pool=[openai_ada, openai_curie], client_pool_schedule=\"round_robin\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0\n",
"I am a model.\n",
"1\n",
"I am a MacBook Pro with a retina\n"
]
}
],
"source": [
"res = manifest.run(\"What model are you?\", temperature=0.0)\n",
"print(manifest.client_pool.current_client_id)\n",
"print(res)\n",
"res = manifest.run(\"What model are you?\", temperature=0.0)\n",
"print(manifest.client_pool.current_client_id)\n",
"print(res)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## With Async"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"import nest_asyncio\n",
"# This is required for asyncio.run(...) to work in Jupyter notebooks.\n",
"nest_asyncio.apply()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"from manifest import Manifest\n",
"from manifest.connections.client_pool import ClientConnection\n",
"\n",
"openai_ada = ClientConnection(\n",
" client_name=\"openai\",\n",
" client_connection=OPENAI_KEY1,\n",
" engine=\"text-ada-001\"\n",
")\n",
"\n",
"openai_babbage = ClientConnection(\n",
" client_name=\"openai\",\n",
" client_connection=OPENAI_KEY2,\n",
" engine=\"text-babbage-001\"\n",
")\n",
"\n",
"openai_curie = ClientConnection(\n",
" client_name=\"openai\",\n",
" client_connection=OPENAI_KEY2,\n",
" engine=\"text-curie-001\"\n",
")\n",
"\n",
"manifest = Manifest(client_pool=[openai_ada, openai_babbage, openai_curie], client_pool_schedule=\"round_robin\")\n",
"manifest_single_client = Manifest(client_pool=[openai_babbage])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"For loop: 128.68\n",
"Running with async single client\n",
"Running 1 tasks across all clients.\n",
"Async loop: 4.02\n",
"Running with async two clients but not chunking\n",
"Running 1 tasks across all clients.\n",
"Async loop: 3.92\n",
"Running with async two clients and chunk size\n",
"Running 20 tasks across all clients.\n",
"Async loop: 1.44\n"
]
}
],
"source": [
"import time\n",
"import asyncio\n",
"\n",
"prompts = [f\"Tell me something interesting about {i}\" for i in range(400)]\n",
"st = time.time()\n",
"for pmt in prompts:\n",
" _ = manifest_single_client.run(pmt, max_tokens=30)\n",
"print(f\"For loop: {time.time() - st :.2f}\")\n",
"\n",
"print(\"Running with async single client\")\n",
"st = time.time()\n",
"_ = asyncio.run(manifest_single_client.arun_batch(prompts, max_tokens=30, chunk_size=-1))\n",
"print(f\"Async loop: {time.time() - st :.2f}\")\n",
"\n",
"print(\"Running with async two clients but not chunking\")\n",
"st = time.time()\n",
"_ = asyncio.run(manifest.arun_batch(prompts, max_tokens=30, chunk_size=-1))\n",
"print(f\"Async loop: {time.time() - st :.2f}\")\n",
"\n",
"print(\"Running with async two clients and chunk size\")\n",
"st = time.time()\n",
"_ = asyncio.run(manifest.arun_batch(prompts, max_tokens=30, chunk_size=20))\n",
"print(f\"Async loop: {time.time() - st :.2f}\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "manifest",
"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": "3.10.4"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "fddffe4ac3b9f00470127629076101c1b5f38ecb1e7358b567d19305425e9491"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|