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aiwrite.py 8.00 KB
一键复制 编辑 原始数据 按行查看 历史
qiangshushu 提交于 2024-01-31 11:00 . 写作助手,文生图替换模型
import json
import re
from time import sleep
import requests
from flask import Flask, Response, stream_with_context, request
from flask_cors import CORS, cross_origin
app = Flask(__name__)
CORS(app)
@app.route('/aiwrite', methods=['POST'])
@cross_origin()
def process_request():
try:
# Check the request content type to ensure it is "application/json"
if request.headers.get('Content-Type') != 'application/json':
return json.dump({"msg": "Bad Request", "response": 500, "results":"Unsupported Media Type"},ensure_ascii = False)
data = request.get_json()
# Check if 'input' and 'prompt' are provided
if 'input' not in data:
return json.dumps({"msg": "Bad Request", "response": 500, "results":"没有input参数"},ensure_ascii = False)
elif 'prompt' not in data:
return json.dumps({"msg": "Bad Request", "response": 500, "results":"没有prompt参数"},ensure_ascii = False)
input_text = data['input']
prompt = data['prompt']
if 'stream' not in data:
stream = False
else:
stream = data.get('stream')
remind = ""
if 'remind' in data:
remind = data.get('remind')
# Get 'rewrite_style' if provided, otherwise set to None
rewrite_key = {0:"通用改写",1:"新闻记者",2:"动漫主播",3:"学生"}
rewrite_style = ""
try:
rewrite_code = data.get('rewrite_style')
rewrite_style=rewrite_key.get(rewrite_code)
except:
print("wu")
prompt_message = ""
# Generate the prompt based on the input, prompt, and rewrite_style
if prompt == 1:
prompt_message = f"主题是:{input_text}。请根据指定的主题返回内容提纲。"
elif prompt == 2:
prompt_message = f"主题是:{input_text}。请根据指定的主题写一篇文章,字数在500字以上。"
elif prompt == 3:
prompt_message = f"以下为内容开头:{input_text}。以与提供的上下文一致的方式继续用中文写一篇文章。"
elif prompt == 4:
if remind == "":
prompt_message = f"文章为:{input_text}。请对这篇文章进行润色,使其表达更加准确,内容更加精美。"
else:
prompt_message = f"文章为:{input_text}。要求为:{remind}。请根据要求对这篇文章进行润色,使其表达更加准确,内容更加精美。"
elif prompt == 5:
if rewrite_style != "":
if remind == "":
prompt_message = f"文章全文改写。文章全文为:{input_text}。请以{rewrite_style}的口吻将该文章改写。"
else:
prompt_message = f"文章全文改写。文章全文为:{input_text}。改写要求为:{remind}。请根据要求以{rewrite_style}的口吻将该文章进行改写。"
else:
if remind == "":
prompt_message = f"文章全文改写。文章全文为:{input_text}。请将以上文本进行改写。"
else:
prompt_message = f"文章全文改写。文章全文为:{input_text}。改写要求为:{remind}。请根据要求将该文章进行改写。"
print(prompt_message)
else:
return json.dumps({"msg": "Invalid prompt value", "response": 500, "result":"please choose prompt value 0-5"},ensure_ascii = False)
# Here you can implement the logic to generate the appropriate response based on the request parameters.
# For simplicity, we'll just echo the input parameters.
print(prompt_message)
url = 'http://10.211.25.28:3000/v1/chat/completions' # 替换为你的目标 URL
# 定义要发送的数据(可以是字典、JSON 等格式)
data = {
"model": "SparkDesk",
"messages": [
{
"role": "user",
"content": prompt_message
}
],
"temperature": 0.7,
"top_p": 1,
"max_tokens": 4096,
"stop": [
"string"
],
"user": "pdmi"
}
headers = {
"Content-Type": "application/json",
"Authorization": "Bearer sk-9aKmaj8vpFGB9OlRCdFaA7Dc352a40158d9578Bc29A0Ac6e"
}
response = requests.post(url, json=data, headers=headers) # 使用 JSON 格式发送数据
if stream:
data = {
"model": "SparkDesk",
"messages": [
{
"role": "user",
"content": prompt_message
}
],
"temperature": 0.7,
"top_p": 1,
"max_tokens": 4096,
"stop": [
"string"
],
"user": "pdmi",
"stream": True,
}
response = requests.post(url, json=data, headers=headers)
#pattern = r'data:\s*(\{.*?"id"\s*:\s*"[^"]*"\s*,\s*"model"\s*:\s*"[^"]*"\s*,\s*"choices"\s*:\s*\[.*?\]\s*\})'
pattern = r'data:\s*({.*?"id"\s*:\s*"[^"]*"\s*,\s*"object"\s*:\s*"[^"]*"\s*,\s*"created"\s*:\s*\d+\s*,\s*"model"\s*:\s*"[^"]*"\s*,\s*"choices"\s*:\s*\[.*?\]\s*})'
def generate_data():
partial_data = ""
for chunk in response.iter_content(chunk_size=1024):
if chunk:
try:
# 将数据块解码为字符串
chunk_str = chunk.decode("utf8", 'ignore')
#print(chunk_str)
except UnicodeDecodeError as e:
# 处理无法解码的数据块,可以选择跳过或记录错误
print(f"UnicodeDecodeError: {e}")
continue
#
# # 将数据块追加到暂存字符串
partial_data += chunk_str
match = re.search(pattern, partial_data)
# 查找是否有完整的 JSON 数据
while match:
_, data_block, partial_data = re.split(pattern, partial_data, maxsplit=1)
match = re.search(pattern, partial_data)
json_block = json.loads(data_block)
choices = json_block.get("choices", [])
try:
content = choices[0]['delta']['content']
except:
content = ""
yield content + "\n"
sleep(0.1)
if response.status_code == 200:
return Response(stream_with_context(generate_data()), mimetype='text/event-stream')
else:
return json.dumps({"msg": "error", "response": 400, "results": response.text}, ensure_ascii=False)
response_content = ""
# 检查响应状态码
if response.status_code == 200:
# 解析响应内容
response_data = response.json() # 如果服务器返回 JSON 数据
response_content = response_data['choices'][0]['message']['content']
print(response_content)
else:
return json.dumps({"msg": "error", "response": 400, "results": response.text}, ensure_ascii=False)
return json.dumps({"msg": "ok", "response": 200, "results": response_content}, ensure_ascii=False)
except Exception as e:
print(e)
return json.dumps({"msg": "Internal Server Error", "response": 500, "results": "请重试"},ensure_ascii = False)
if __name__ == "__main__":
app.run(host='0.0.0.0', port=9000)
Python
1
https://gitee.com/renith/langchain-ChatGLM.git
git@gitee.com:renith/langchain-ChatGLM.git
renith
langchain-ChatGLM
langchain-ChatGLM
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