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HuangHai 4 months ago
parent 7a5f225571
commit 3f8ea34c24
5 changed files with 248 additions and 66 deletions
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108
AI/WxMini/Start.py
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@ -1,5 +1,6 @@
import asyncio
import logging
import re
import time
import uuid
from contextlib import asynccontextmanager
@ -11,6 +12,7 @@ from fastapi.security import OAuth2PasswordBearer
from jose import JWTError, jwt
from openai import AsyncOpenAI
from passlib.context import CryptContext
from starlette.responses import StreamingResponse
from WxMini.Milvus.Config.MulvusConfig import *
from WxMini.Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
@ -402,7 +404,8 @@ async def get_risk_chat_logs(
offset = (page - 1) * page_size
# 调用 get_chat_logs_by_risk_flag 方法
logs, total = await get_chat_logs_by_risk_flag(app.state.mysql_pool, risk_flag,current_user["person_id"], offset, page_size)
logs, total = await get_chat_logs_by_risk_flag(app.state.mysql_pool, risk_flag, current_user["person_id"], offset,
page_size)
if not logs:
return {
"success": False,
@ -425,7 +428,6 @@ async def get_risk_chat_logs(
}
# 获取风险统计接口
@app.get("/aichat/chat_logs_summary")
async def chat_logs_summary(
@ -484,6 +486,7 @@ async def chat_logs_summary(
}
}
# 获取上传OSS的授权Token
@app.get("/aichat/get_oss_upload_token")
async def get_oss_upload_token(current_user: dict = Depends(get_current_user)):
@ -504,6 +507,107 @@ async def get_oss_upload_token(current_user: dict = Depends(get_current_user)):
}
async def is_text_dominant(image_url):
"""
判断图片是否主要是文字内容
:param image_url: 图片 URL
:return: True（主要是文字） / False（主要是物体/场景）
"""
completion = await client.chat.completions.create(
model="qwen-vl-ocr",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": image_url,
"min_pixels": 28 * 28 * 4,
"max_pixels": 28 * 28 * 1280
},
{"type": "text", "text": "Read all the text in the image."},
]
}
],
stream=False
)
text = completion.choices[0].message.content
# 判断是否只有英文和数字
if re.match(r'^[A-Za-z0-9\s]+$', text):
print("识别到的内容只有英文和数字，可能是无意义的字符，调用识别内容功能。")
return False
return True
async def recognize_text(image_url):
"""
识别图片中的文字，流式输出
"""
completion = await client.chat.completions.create(
model="qwen-vl-ocr",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": image_url,
"min_pixels": 28 * 28 * 4,
"max_pixels": 28 * 28 * 1280
},
{"type": "text", "text": "Read all the text in the image."},
]
}
],
stream=True
)
async for chunk in completion:
if chunk.choices[0].delta.content is not None:
for char in chunk.choices[0].delta.content:
if char != ' ':
yield char
time.sleep(0.1)
async def recognize_content(image_url):
"""
识别图片中的内容，流式输出
"""
completion = await client.chat.completions.create(
model="qwen-vl-plus",
messages=[{"role": "user", "content": [
{"type": "text", "text": "这是什么"},
{"type": "image_url", "image_url": {"url": image_url}}
]}],
stream=True
)
async for chunk in completion:
if chunk.choices[0].delta.content is not None:
for char in chunk.choices[0].delta.content:
yield char
time.sleep(0.1)
@app.get("/aichat/process_image")
async def process_image(image_url: str, current_user: dict = Depends(get_current_user)):
logger.info(f"current_user:{current_user['login_name']}")
"""
处理图片，自动判断调用哪个功能
:param image_url: 图片 URL
:return: 流式输出结果
"""
try:
if await is_text_dominant(image_url):
print("检测到图片主要是文字内容，开始识别文字：")
return StreamingResponse(recognize_text(image_url), media_type="text/plain")
else:
print("检测到图片主要是物体/场景，开始识别内容：")
return StreamingResponse(recognize_content(image_url), media_type="text/plain")
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
# 运行 FastAPI 应用
if __name__ == "__main__":
import uvicorn

16
AI/WxMini/Test/OCR1_Image_Recognition.py
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@ -1,3 +1,4 @@
import time
from openai import OpenAI
from WxMini.Milvus.Config.MulvusConfig import *
@ -5,6 +6,8 @@ client = OpenAI(
api_key=MODEL_API_KEY,
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
image_url = "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg"
completion = client.chat.completions.create(
model="qwen-vl-ocr",
messages=[
@ -13,7 +16,7 @@ completion = client.chat.completions.create(
"content": [
{
"type": "image_url",
"image_url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg",
"image_url": image_url,
"min_pixels": 28 * 28 * 4,
"max_pixels": 28 * 28 * 1280
},
@ -22,12 +25,17 @@ completion = client.chat.completions.create(
]
}
],
stream=True)
stream=True
)
full_content = ""
print("流式输出内容为：")
for chunk in completion:
if chunk.choices[0].delta.content is None:
continue
# 遍历每个字符并逐个输出
for char in chunk.choices[0].delta.content:
if char!=' ':
print(char, end="", flush=True) # 逐个输出字符，不换行
time.sleep(0.1) # 控制输出速度
full_content += chunk.choices[0].delta.content
print(chunk.choices[0].delta.content)
print(f"完整内容为：{full_content}")

26
AI/WxMini/Test/OCR1_Image_Recognition_Stream.py
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@ -1,26 +0,0 @@
from openai import OpenAI
from WxMini.Milvus.Config.MulvusConfig import *
client = OpenAI(
api_key=MODEL_API_KEY,
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
completion = client.chat.completions.create(
model="qwen-vl-ocr",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg",
"min_pixels": 28 * 28 * 4,
"max_pixels": 28 * 28 * 1280
},
# 为保证识别效果，目前模型内部会统一使用"Read all the text in the image."进行识别，用户输入的文本不会生效。
{"type": "text", "text": "Read all the text in the image."},
]
}
])
print(completion.choices[0].message.content)

109
AI/WxMini/Test/TestAutoSelect.py
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@ -0,0 +1,109 @@
import re
import time
from openai import OpenAI
from WxMini.Milvus.Config.MulvusConfig import *
client = OpenAI(
api_key=MODEL_API_KEY,
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
def is_text_dominant(image_url):
"""
判断图片是否主要是文字内容
:param image_url: 图片 URL
:return: True（主要是文字） / False（主要是物体/场景）
"""
completion = client.chat.completions.create(
model="qwen-vl-ocr",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": image_url,
"min_pixels": 28 * 28 * 4,
"max_pixels": 28 * 28 * 1280
},
{"type": "text", "text": "Read all the text in the image."},
]
}
],
stream=False
)
text = completion.choices[0].message.content
# 判断条件
# 1、有汉字出现就是文字
# 2、如果是英文，但是识别出来的内容只有英文，认为是文字
# 判断是否只有英文和数字
if re.match(r'^[A-Za-z0-9\s]+$', text):
print("识别到的内容只有英文和数字，可能是无意义的字符，调用识别内容功能。")
return False
return True
def recognize_text(image_url):
"""
识别图片中的文字
"""
completion = client.chat.completions.create(
model="qwen-vl-ocr",
messages=[
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": image_url,
"min_pixels": 28 * 28 * 4,
"max_pixels": 28 * 28 * 1280
},
{"type": "text", "text": "Read all the text in the image."},
]
}
],
stream=True
)
print("流式输出内容为：")
for chunk in completion:
if chunk.choices[0].delta.content is not None:
for char in chunk.choices[0].delta.content:
if char != ' ':
print(char, end="", flush=True)
time.sleep(0.1)
def recognize_content(image_url):
"""
识别图片中的内容
"""
completion = client.chat.completions.create(
model="qwen-vl-plus",
messages=[{"role": "user", "content": [
{"type": "text", "text": "这是什么"},
{"type": "image_url", "image_url": {"url": image_url}}
]}],
stream=True
)
print("流式输出结果：")
for chunk in completion:
if chunk.choices[0].delta.content is not None:
for char in chunk.choices[0].delta.content:
print(char, end="", flush=True)
time.sleep(0.1)
def process_image(image_url):
"""
处理图片，自动判断调用哪个功能
"""
if is_text_dominant(image_url):
print("检测到图片主要是文字内容，开始识别文字：")
recognize_text(image_url)
else:
print("检测到图片主要是物体/场景，开始识别内容：")
recognize_content(image_url)
# 示例调用
#image_url = "https://ylt.oss-cn-hangzhou.aliyuncs.com/Temp/james.png"
image_url = "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg"
process_image(image_url)

45
AI/WxMini/Test/X1_ReadImage.py
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@ -1,4 +1,4 @@
import json
import time # 导入 time 模块
from openai import OpenAI
from WxMini.Milvus.Config.MulvusConfig import *
@ -6,37 +6,24 @@ client = OpenAI(
api_key=MODEL_API_KEY,
base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
)
# 一盆花
# photo_url = 'https://ylt.oss-cn-hangzhou.aliyuncs.com/Temp/mudan.jpg'
# 狗与女主人
# photo_url = "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"
# 哪吒
# photo_url = 'https://ylt.oss-cn-hangzhou.aliyuncs.com/Temp/nezha.jpg'
# 锅包肉
# photo_url = 'https://ylt.oss-cn-hangzhou.aliyuncs.com/Temp/gbr.jpg'
# 儿童看图说话
# photo_url = 'https://ylt.oss-cn-hangzhou.aliyuncs.com/Temp/xiaoxiong.jpg'
# 詹姆斯与库里
photo_url='https://ylt.oss-cn-hangzhou.aliyuncs.com/Temp/james.png'
# 图片 URL
image_url = 'https://ylt.oss-cn-hangzhou.aliyuncs.com/Temp/james.png'
# 创建流式请求
completion = client.chat.completions.create(
model="qwen-vl-plus",
# 此处以qwen-vl-plus为例，可按需更换模型名称。模型列表：https://help.aliyun.com/zh/model-studio/getting-started/models
model="qwen-vl-plus", # 使用 qwen-vl-plus 模型
messages=[{"role": "user", "content": [
{"type": "text", "text": "这是什么"},
{"type": "image_url",
"image_url": {"url": photo_url}}
]}]
{"type": "image_url", "image_url": {"url": image_url}}
]}],
stream=True # 启用流式输出
)
json_data = completion.model_dump_json()
# 解析 JSON 数据
data = json.loads(json_data)
# 提取 content 内容
content = data['choices'][0]['message']['content']
# 打印 content
print(content)
# 流式输出结果
print("流式输出结果：")
for chunk in completion:
if chunk.choices[0].delta.content is not None:
for char in chunk.choices[0].delta.content: # 逐个字符输出
print(char, end="", flush=True) # 逐个字符输出，不换行
time.sleep(0.1) # 控制输出速度，延迟 0.1 秒
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