feat: ai生成图片
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91
callback.py
91
callback.py
@@ -11,6 +11,26 @@ import time
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from transformers import AutoTokenizer, AutoModel
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from transformers import AutoTokenizer, AutoModel
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import uvicorn, json, datetime
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import uvicorn, json, datetime
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import torch
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import torch
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import json
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import base64
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import requests
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def submit_post(url: str, data: dict):
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"""
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Submit a POST request to the given URL with the given data.
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"""
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return requests.post(url, data=json.dumps(data))
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def save_encoded_image(b64_image: str, output_path: str):
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"""
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Save the given image to the given output path.
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"""
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with open(output_path, "wb") as image_file:
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image_file.write(base64.b64decode(b64_image))
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DEVICE = "cuda"
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DEVICE = "cuda"
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DEVICE_ID = "0"
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DEVICE_ID = "0"
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@@ -86,7 +106,7 @@ async def create_item(request: Request):
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return answer
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return answer
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# 通过网址发送闪信
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# AI智能对话
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@app.post("/callback")
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@app.post("/callback")
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async def callback(
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async def callback(
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# item: Item,
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# item: Item,
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@@ -137,6 +157,75 @@ async def callback(
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headers = {"Content-Type": "application/json"}
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headers = {"Content-Type": "application/json"}
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return JSONResponse(content=content, headers=headers)
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return JSONResponse(content=content, headers=headers)
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# AI生成图片
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@app.post("/img")
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async def img(
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# item: Item,
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# inputArguments: Union[str, None] = None,
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query=Body(None),
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appid: Union[str, None] = Header(default=None),
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bid: Union[str, None] = Header(default=None),
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requestid: Union[str, None] = Header(default=None),
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uid: Union[str, None] = Header(default=None),
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):
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print('query',query)
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print('query[query]',query["query"])
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# 获取请求参数
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global model, tokenizer
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# time.sleep(10)
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# print("item", item)
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history = [] #默认空数组
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prompt=''
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max_length=None
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top_p=None
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temperature=None
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try:
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query = unquote(query["query"], "utf-8")
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# 判断有没有'/img'标识符
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if ('/img' in query):
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query=query.replace('/img', '')
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prompt=query
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txt2img_url = 'http://127.0.0.1:7861/sdapi/v1/txt2img'
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data = {'prompt': prompt}
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res = submit_post(txt2img_url, data)
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# 以时间戳命名
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now = datetime.datetime.now()
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save_encoded_image(res.json()['images'][0], f'img/{now}.png')
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response=f'http://aiimg.yidooplanet.com/{now}.png'
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else:
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prompt = query #问题
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# 请求ai模型
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response, history = model.chat(tokenizer,
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prompt,
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history=history,
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max_length=max_length if max_length else 2048,
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top_p=top_p if top_p else 0.7,
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temperature=temperature if temperature else 0.95)
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except:
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prompt = ""
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# log日志
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# now = datetime.datetime.now()
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# time = now.strftime("%Y-%m-%d %H:%M:%S")
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# log = "[" + time + "] " + '", prompt:"' + prompt + '", response:"' + repr(response) + '"'
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# print(log)
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content = {
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"answer": response,
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"answer_type": "text",
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}
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headers = {"Content-Type": "application/json"}
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return JSONResponse(content=content, headers=headers)
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if __name__ == '__main__':
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if __name__ == '__main__':
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tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b-int4", trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b-int4", trust_remote_code=True)
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model = AutoModel.from_pretrained("THUDM/chatglm2-6b-int4", trust_remote_code=True).cuda()
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model = AutoModel.from_pretrained("THUDM/chatglm2-6b-int4", trust_remote_code=True).cuda()
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