File size: 3,797 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
{
 "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": [
    "AZURE_KEY = \"API_KEY::URL\"\n",
    "OPENAI_KEY = \"sk-XXX\""
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Use Azure and OpenAI models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from manifest import Manifest\n",
    "from manifest.connections.client_pool import ClientConnection\n",
    "from pathlib import Path\n",
    "\n",
    "cache_path = Path(\"manifest.db\")\n",
    "if cache_path.exists():\n",
    "    cache_path.unlink()\n",
    "\n",
    "\n",
    "azure = ClientConnection(\n",
    "    client_name=\"azureopenai\",\n",
    "    client_connection=AZURE_KEY,\n",
    "    engine=\"text-davinci-003\",\n",
    ")\n",
    "\n",
    "manifest = Manifest(client_pool=[azure], \n",
    "    cache_name=\"sqlite\",\n",
    "    cache_connection=\"manifest.db\"\n",
    ")\n",
    "\n",
    "\n",
    "openai = ClientConnection(\n",
    "    client_name=\"openai\",\n",
    "    client_connection=OPENAI_KEY,\n",
    "    engine=\"text-davinci-003\",\n",
    ")\n",
    "\n",
    "manifest_openai_nocache = Manifest(client_pool=[openai])\n",
    "\n",
    "manifest_openai = Manifest(client_pool=[openai], \n",
    "    cache_name=\"sqlite\",\n",
    "    cache_connection=\"manifest.db\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Show caches are the same\n",
    "text = \"What is the meaning of life?\"\n",
    "res = manifest.run(text, max_tokens=100, temperature=0.7, return_response=True)\n",
    "print(res.get_response())\n",
    "print(res.is_cached())\n",
    "res2 = manifest_openai.run(text, max_tokens=100, temperature=0.7, return_response=True)\n",
    "print(res2.is_cached())\n",
    "\n",
    "assert res2.get_response() == res.get_response()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "azure_chat = ClientConnection(\n",
    "    client_name=\"azureopenaichat\",\n",
    "    client_connection=AZURE_KEY,\n",
    "    engine=\"gpt-3.5-turbo\",\n",
    ")\n",
    "\n",
    "manifest = Manifest(client_pool=[azure_chat])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(manifest.run(\"What do you think is the best food?\", max_tokens=100))\n",
    "\n",
    "chat_dict = [\n",
    "    {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
    "    {\"role\": \"user\", \"content\": \"Who won the world series in 2020?\"},\n",
    "    {\"role\": \"assistant\", \"content\": \"The Los Angeles Dodgers won the World Series in 2020.\"},\n",
    "    {\"role\": \"user\", \"content\": \"Where was it played?\"}\n",
    "]\n",
    "print(manifest.run(chat_dict, max_tokens=100))"
   ]
  }
 ],
 "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
}