- 参考文档
https://creative.chat/
1.调用AI大模型API
1.1文心一言
https://console.bce.baidu.com/qianfan/ais/console/applicationConsole/application
- 创建应用：https://console.bce.baidu.com/qianfan/ais/console/applicationConsole/application
- 示例代码：https://console.bce.baidu.com/tools/?_=1692863460488#/api?product=QIANFAN&project=千帆大模型平台&parent=鉴权认证机制&api=oauth%2F2.0%2Ftoken&method=post
import requests
import jsonAPI_KEY = "CUJRwLhCHA8hQapnaAQsIGPR"
SECRET_KEY = "L1yYhbcZCId5iMQQsBnVXkjNOdzBAH2O"def main():url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-speed-128k?access_token=" + get_access_token()payload = json.dumps({"system":"你是一个生活AI。对人的作息，休闲，工作，学习，娱乐，饮食，运动，健康，心理，社交，教育，娱乐知识很精通","messages": [{"role": "user","content": "您叫什么名字"},]})headers = {'Content-Type': 'application/json'}response = requests.request("POST", url, headers=headers, data=payload)print(response.text)def get_access_token():"""使用 AK，SK 生成鉴权签名（Access Token）:return: access_token，或是None(如果错误)"""url = "https://aip.baidubce.com/oauth/2.0/token"params = {"grant_type": "client_credentials", "client_id": API_KEY, "client_secret": SECRET_KEY}return str(requests.post(url, params=params).json().get("access_token"))if __name__ == '__main__':main()
2大模型部署fastapi
2.1 文心一言
- app.py
from fastapi import FastAPI
from uvicorn import run
from Config.modules import modulesapp = FastAPI()# 自动加载模块路由
for module_name, module_path in modules.items():module = __import__(module_path, fromlist=['router'])app.include_router(module.router)if __name__ == '__main__':run(app, host='0.0.0.0', port=1888)- config/modules.py
modules = {'Demo': 'Extension.Demo.route','LLM': 'Extension.LLM.route',
}- LLM/setting.py
Erniebot_API_KEY = "CUJRwLhCHA8hQapnaAQsIGPR"
Erniebot_SECRET_KEY"L1yYhbcZCId5iMQQsBnVXkjNOdzBAH2"
Qwen_API_KEY = ""
ChatGPT_API_KEY = ""
- LLM/llm_erniebot.py
import requests
import json
from Extension.LLM.setting import Erniebot_API_KEY, Erniebot_SECRET_KEYdef erniebot(text, ai_name, ai_role):url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-speed-128k?access_token=" + get_access_token()payload = json.dumps({"system": ai_name+' '+ai_role,"messages": [{"role": "user","content": text}],# 如果设置为False，AI可能会使用搜索功能来查找最新的信息或解决特定的查询，从而提供更准确、更及时的信息。"disable_search": False,# 如果设置为True，AI在提供信息时会尝试包含引用来源，比如网页链接、书籍引用等，这有助于验证信息的准确性和来源。"enable_citation": True,})headers = {'Content-Type': 'application/json'}response = requests.request("POST", url, headers=headers, data=payload)data = json.loads(response.text)usage = data['usage']result = {"reply": data['result'],"prompt_tokens": usage['prompt_tokens'],"completion_tokens": usage['completion_tokens'],"total_tokens": usage['total_tokens']}return resultdef get_access_token():"""使用 AK，SK 生成鉴权签名（Access Token）:return: access_token，或是None(如果错误)"""API_KEY = Erniebot_API_KEYSECRET_KEY = Erniebot_SECRET_KEYurl = "https://aip.baidubce.com/oauth/2.0/token"params = {"grant_type": "client_credentials","client_id": API_KEY, "client_secret": SECRET_KEY}return str(requests.post(url, params=params).json().get("access_token"))
2.2通义千问
-
API KEY：https://dashscope.console.aliyun.com/apiKey
-
示例代码：https://help.aliyun.com/zh/dashscope/developer-reference/quick-start#014863e0459zq
import random
from http import HTTPStatus
import dashscope
dashscope.api_key = "sk-3f7cd2b89a894c3e9a115f83d37c8afe"def call_with_messages():messages = [{'role': 'system', 'content': '你是一个健康AI。你是一个健康专家，对人的作息，饮食，健身，营养，医学等健康方面的知识，非常精通。'},{'role': 'user', 'content': '你叫什么名字'}]response = dashscope.Generation.call("qwen-turbo",messages=messages,# set the random seed, optional, default to 1234 if not setseed=random.randint(1, 10000),# set the result to be "message" format.result_format='message',)if response.status_code == HTTPStatus.OK:print(response)else:print('Request id: %s, Status code: %s, error code: %s, error message: %s' % (response.request_id, response.status_code,response.code, response.message))if __name__ == '__main__':call_with_messages()
- LLM/llm_qwen.py
import random
import dashscope
from Extension.LLM.setting import Qwen_API_KEYdashscope.api_key = Qwen_API_KEYdef qwen(text, ai_name, ai_role):messages = [{'role': 'system', 'content': ai_name+' '+ai_role},{'role': 'user', 'content': text}]response = dashscope.Generation.call("qwen-turbo",messages=messages,# set the random seed, optional, default to 1234 if not setseed=random.randint(1, 10000),# set the result to be "message" format.result_format='message',)usage = response.usagedata = response.output.choicesresult = {"reply": data[0].message.content,"prompt_tokens": usage.input_tokens,"completion_tokens": usage.output_tokens,"total_tokens": usage.total_tokens}return result2.3windows部署AI大模型
2.31Windows部署通义千问
-
https://lmstudio.ai/
-
https://www.modelscope.cn/models/qwen/Qwen2-7B-Instruct-GGUF/summary
2.32Windows部署Llama 3
- https://lmstudio.ai/
- https://www.modelscope.cn/models/ModelM/Llama-3-8b-zh-gguf/summary
2.33Windows部署Stable Diffusion
- https://pan.quark.cn/s/2c832199b09b
- https://www.bilibili.com/video/BV1iM4y1y7oA
