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kkdai/devday2023.ipynb

Created November 8, 2023 16:04
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devday2023.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import pickle\n",
"import requests\n",
"import json\n",
"from dotenv import load_dotenv\n",
"\n",
"# Laden Sie die Umgebungsvariablen aus der .env-Datei\n",
"load_dotenv()\n",
"\n",
"openai_api_key = os.environ.get(\"OPENAI_API_KEY\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def get_completion(messages, model=\"gpt-3.5-turbo\", temperature=0, max_tokens=300):\n",
" payload = { \"model\": model, \"temperature\": temperature, \"messages\": messages, \"max_tokens\": max_tokens }\n",
" headers = { \"Authorization\": f'Bearer {openai_api_key}', \"Content-Type\": \"application/json\" }\n",
" response = requests.post('https://api.openai.com/v1/chat/completions', headers = headers, data = json.dumps(payload) )\n",
" obj = json.loads(response.text)\n",
" if response.status_code == 200 :\n",
" return obj[\"choices\"][0][\"message\"][\"content\"]\n",
" else :\n",
" return obj[\"error\"]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"import json\n",
"from pprint import pp"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# GPT-4V API\n",
"\n",
"content 參數變成 hash 惹，超簡單"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"messages = [\n",
" { \"role\": \"user\", \"content\": [\n",
" {\n",
" \"type\": \"image_url\",\n",
" \"image_url\": \"https://ccmsassets.ithome.com.tw/2023/7/27/8bc15cdc-bb93-431c-9b26-542704d88df9.png\",\n",
" },\n",
" { \"type\": \"text\", \"text\": \"能根據照片資訊猜測哪裡拍的嗎？\" }\n",
" ] }\n",
"]\n",
"\n",
"get_completion(messages, model=\"gpt-4-vision-preview\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip show openai"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Assistants API with retriever"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 0. 上傳檔案"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# 找個範例檔案 https://report.nat.gov.tw/ReportFront/ReportDetail/detail?sysId=C11201557\n",
"!wget -O 'C11201717_1.pdf' https://report.nat.gov.tw/ReportFront/PageSystem/reportFileDownload/C11201717/001"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data = { \"purpose\": \"assistants\" }\n",
"f = open('C11201717_1.pdf', 'rb')\n",
"files = [(\"file\", (\"C11201717_1.pdf\", f, \"application/octet-stream\"))]\n",
"\n",
"headers = { \"Authorization\": f'Bearer {openai_api_key}', \"OpenAI-Beta\": \"assistants=v1\" }\n",
"response = requests.post(f\"https://api.openai.com/v1/files\", headers = headers, data = data, files = files )\n",
"f_obj = json.loads(response.text)\n",
"\n",
"print(f_obj)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"f_obj['id']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1. 建立 assistant with retriever (這時 OpenAI 才跑檔案索引)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"payload = { \"model\": \"gpt-4-1106-preview\", \"name\": \"evan-rag\", \"tools\": [{\"type\": \"retrieval\"}],\n",
" \"instructions\": \"You are a customer support chatbot. Use your knowledge base to best respond to customer queries.\",\n",
" \"file_ids\": [f_obj['id']] }\n",
"headers = { \"Authorization\": f'Bearer {openai_api_key}', \"Content-Type\": \"application/json\", \"OpenAI-Beta\": \"assistants=v1\" }\n",
"response = requests.post('https://api.openai.com/v1/assistants', headers = headers, data = json.dumps(payload) )\n",
"ass_obj = json.loads(response.text)\n",
"\n",
"print(ass_obj)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. 初次建立 thread 對話"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"payload = { \"messages\": [ { \"role\": \"user\", \"content\": \"請問和 Pentera 的會晤討論了什麼?\"} ] }\n",
"headers = { \"Authorization\": f'Bearer {openai_api_key}', \"Content-Type\": \"application/json\", \"OpenAI-Beta\": \"assistants=v1\" }\n",
"response = requests.post('https://api.openai.com/v1/threads', headers = headers, data = json.dumps(payload) )\n",
"th_obj = json.loads(response.text)\n",
"\n",
"print(th_obj)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3. 執行 run，產生 AI 回覆"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"assistant_id = ass_obj['id']\n",
"thread_id = th_obj['id']\n",
"\n",
"payload = { \"assistant_id\": assistant_id }\n",
"headers = { \"Authorization\": f'Bearer {openai_api_key}', \"Content-Type\": \"application/json\", \"OpenAI-Beta\": \"assistants=v1\" }\n",
"response = requests.post(f\"https://api.openai.com/v1/threads/{thread_id}/runs\", headers = headers, data = json.dumps(payload) )\n",
"run_obj = json.loads(response.text)\n",
"\n",
"print(run_obj)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 5. 查看目前 messages"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"headers = { \"Authorization\": f'Bearer {openai_api_key}', \"Content-Type\": \"application/json\", \"OpenAI-Beta\": \"assistants=v1\" }\n",
"response = requests.get(f\"https://api.openai.com/v1/threads/{thread_id}/messages\", headers = headers )\n",
"ret_obj = json.loads(response.text)\n",
"\n",
"pp(ret_obj)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 可繼續加 message 到 thread 中，繼續 run 對話"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"payload = { \"role\": \"user\", \"content\": \"和 Chain Reaction 談了什麼?\" }\n",
"headers = { \"Authorization\": f'Bearer {openai_api_key}', \"Content-Type\": \"application/json\", \"OpenAI-Beta\": \"assistants=v1\" }\n",
"response = requests.post(f\"https://api.openai.com/v1/threads/{thread_id}/messages\", headers = headers, data = json.dumps(payload) )\n",
"obj = json.loads(response.text)\n",
"\n",
"print(obj)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.10.11"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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