Spaces:
Running
Running
File size: 2,250 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 |
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"OPENAI_KEY = \"sk-XXX\""
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Use ChatOpenAI\n",
"\n",
"Set you `OPENAI_API_KEY` environment variable."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from manifest import Manifest\n",
"from manifest.connections.client_pool import ClientConnection\n",
"\n",
"openai_chat = ClientConnection(\n",
" client_name=\"openaichat\",\n",
" client_connection=OPENAI_KEY,\n",
" engine=\"gpt-3.5-turbo\"\n",
")\n",
"\n",
"manifest = Manifest(client_pool=[openai_chat])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"manifest_iterator = manifest.run(\"Tell me a story about a fat cat.\\n\\nOnce upon a time\", max_tokens=200, stream=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"\n",
"cur_line_length = 0\n",
"# Iterate over stream\n",
"for res in manifest_iterator:\n",
" sys.stdout.write(res)\n",
" cur_line_length += len(res)\n",
" if cur_line_length > 80:\n",
" sys.stdout.write(\"\\n\")\n",
" cur_line_length = 0"
]
}
],
"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
}
|