final

launch.py

@@ -1,4 +1,5 @@
 from modules import launch_utils
+import nltk
 
 args = launch_utils.args
 python = launch_utils.python
@@ -41,6 +42,13 @@ def main():
     if args.test_server:
         configure_for_tests()
 
+
+    # 下载nltk资源（仅需运行一次）
+    print("Downloading nltk data...")
+    nltk.download('punkt')
+    nltk.download('averaged_perceptron_tagger')
+    nltk.download('stopwords')
+
     start()
 
 

modules/api/api.py

@@ -1,21 +1,29 @@
 import base64
 import io
-import os
 import time
 import datetime
 import uvicorn
 import ipaddress
 import requests
+import logging
+from openai import AsyncOpenAI
 import gradio as gr
 from threading import Lock
 from io import BytesIO
+from starlette.middleware.base import BaseHTTPMiddleware
 from fastapi import APIRouter, Depends, FastAPI, Request, Response
 from fastapi.security import HTTPBasic, HTTPBasicCredentials
 from fastapi.exceptions import HTTPException
 from fastapi.responses import JSONResponse
 from fastapi.encoders import jsonable_encoder
 from secrets import compare_digest
 
+import nltk
+from nltk.corpus import stopwords
+from nltk.tokenize import word_tokenize
+from deep_translator import GoogleTranslator
+
+
 import modules.shared as shared
 from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart, shared_items, script_callbacks, infotext_utils, sd_models, sd_schedulers
 from modules.api import models
@@ -133,67 +141,39 @@ def encode_pil_to_base64(image):
 
 
 def api_middleware(app: FastAPI):
-    rich_available = False
-    try:
-        if os.environ.get('WEBUI_RICH_EXCEPTIONS', None) is not None:
-            import anyio  # importing just so it can be placed on silent list
-            import starlette  # importing just so it can be placed on silent list
-            from rich.console import Console
-            console = Console()
-            rich_available = True
-    except Exception:
-        pass
-
-    @app.middleware("http")
-    async def log_and_time(req: Request, call_next):
-        ts = time.time()
-        res: Response = await call_next(req)
-        duration = str(round(time.time() - ts, 4))
-        res.headers["X-Process-Time"] = duration
-        endpoint = req.scope.get('path', 'err')
-        if shared.cmd_opts.api_log and endpoint.startswith('/sdapi'):
-            print('API {t} {code} {prot}/{ver} {method} {endpoint} {cli} {duration}'.format(
-                t=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f"),
-                code=res.status_code,
-                ver=req.scope.get('http_version', '0.0'),
-                cli=req.scope.get('client', ('0:0.0.0', 0))[0],
-                prot=req.scope.get('scheme', 'err'),
-                method=req.scope.get('method', 'err'),
-                endpoint=endpoint,
-                duration=duration,
-            ))
-        return res
-
-    def handle_exception(request: Request, e: Exception):
-        err = {
-            "error": type(e).__name__,
-            "detail": vars(e).get('detail', ''),
-            "body": vars(e).get('body', ''),
-            "errors": str(e),
-        }
-        if not isinstance(e, HTTPException):  # do not print backtrace on known httpexceptions
-            message = f"API error: {request.method}: {request.url} {err}"
-            if rich_available:
-                print(message)
-                console.print_exception(show_locals=True, max_frames=2, extra_lines=1, suppress=[anyio, starlette], word_wrap=False, width=min([console.width, 200]))
-            else:
-                errors.report(message, exc_info=True)
-        return JSONResponse(status_code=vars(e).get('status_code', 500), content=jsonable_encoder(err))
-
-    @app.middleware("http")
-    async def exception_handling(request: Request, call_next):
-        try:
-            return await call_next(request)
-        except Exception as e:
-            return handle_exception(request, e)
-
-    @app.exception_handler(Exception)
-    async def fastapi_exception_handler(request: Request, e: Exception):
-        return handle_exception(request, e)
+    # try:
+    #     if os.environ.get('WEBUI_RICH_EXCEPTIONS', None) is not None:
+    #         import anyio  # importing just so it can be placed on silent list
+    #         import starlette  # importing just so it can be placed on silent list
+    #         from rich.console import Console
+    #         console = Console()
+    #         rich_available = True
+    # except Exception:
+    #     pass
+    class LoggingMiddleware(BaseHTTPMiddleware):
+        async def dispatch(self, req: Request, call_next):
+            ts = time.time()
+            res: Response = await call_next(req)
+            duration = str(round(time.time() - ts, 4))
+            res.headers["X-Process-Time"] = duration
+            endpoint = req.scope.get('path', 'err')
+            if shared.cmd_opts.api_log and endpoint.startswith('/sdapi'):
+                print('API {t} {code} {prot}/{ver} {method} {endpoint} {cli} {duration}'.format(
+                    t=datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f"),
+                    code=res.status_code,
+                    ver=req.scope.get('http_version', '0.0'),
+                    cli=req.scope.get('client', ('0:0.0.0', 0))[0],
+                    prot=req.scope.get('scheme', 'err'),
+                    method=req.scope.get('method', 'err'),
+                    endpoint=endpoint,
+                    duration=duration,
+                ))
+            return res
+
+    # fastapi 自带了 exception handler
+    # 不再需要自定义
+    app.add_middleware(LoggingMiddleware)
 
-    @app.exception_handler(HTTPException)
-    async def http_exception_handler(request: Request, e: HTTPException):
-        return handle_exception(request, e)
 
 
 class Api:
@@ -244,6 +224,7 @@ def __init__(self, app: FastAPI, queue_lock: Lock):
         self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)
         self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=list[models.ScriptInfo])
         self.add_api_route("/sdapi/v1/extensions", self.get_extensions_list, methods=["GET"], response_model=list[models.ExtensionItem])
+        self.add_api_route("/nlp/v1/nature2prompt", self.nature2prompt, methods=["POST"], response_model=models.Nature2PromptResponse)
 
         if shared.cmd_opts.api_server_stop:
             self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
@@ -429,6 +410,67 @@ def get_field_value(field, params):
 
         return params
 
+    def extract_nouns(self, sentence):
+        # 分词
+        words = word_tokenize(sentence)
+
+        # 词性标注
+        pos_tagged = nltk.pos_tag(words)
+
+        # 提取名词（NN, NNS, NNP, NNPS）
+        nouns = [word for word, pos in pos_tagged if pos in ['NN', 'NNS', 'NNP', 'NNPS']]
+
+        return nouns
+
+    async def nature2prompt(self, nature2promptreq: models.Nature2PromptRequest):
+        client = AsyncOpenAI()
+
+        n2p_logger = logging.getLogger(__name__)
+
+        input_to_bot = nature2promptreq
+        chat_completion = await client.chat.completions.create(
+            messages=[
+                {
+                    "role": "system",
+                    "content": "现在我需要你提取出几个关键词概括我给你的句子，例如 '海上生明月' 对应 '海上' 和 '明月'。注意，仅返回关键词，不要返回其他内容。",
+                },
+                # {"role": "assistant",
+                #  "content":" ",},
+                {"role": "user",
+                 "content":input_to_bot.text,}
+                # {"role": "assistant",
+                #  "content":" ",},
+            ],
+
+            model="gpt-3.5-turbo",
+        )
+        return_to_bot2 = chat_completion.choices[0].message.content
+
+
+        n2p_logger.info(f"返回: {return_to_bot2}")
+        translated = GoogleTranslator(source='auto', target='en').translate(return_to_bot2)  # output -> Weiter so, du bist großartig
+        n2p_logger.info(f"翻译后：{translated}")
+        # 确保你已经安装了nltk库。如果没有安装，请运行以下命令：
+
+
+
+        # 移动到了 launch.py 脚本中，只需要启动时候调用
+        # 下载nltk资源（仅需运行一次）
+        # nltk.download('punkt')
+        # nltk.download('averaged_perceptron_tagger')
+        # nltk.download('stopwords')
+
+        # 示例句子
+        sentence = translated
+        n2p_logger.info(f"sentence: {sentence}")
+        printnon = ''
+        # 提取名词
+        nouns = self.extract_nouns(sentence)
+        for item in nouns:
+          printnon += (item +", ")
+        print("过滤后的名词词表:",printnon)
+        return models.Nature2PromptResponse(filtered_nouns=printnon)
+
     def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
         task_id = txt2imgreq.force_task_id or create_task_id("txt2img")
 

modules/api/models.py

@@ -131,6 +131,12 @@ def generate_model(self):
     ]
 ).generate_model()
 
+class Nature2PromptRequest(BaseModel):
+    text: str
+
+class Nature2PromptResponse(BaseModel):
+    filtered_nouns: str
+
 class TextToImageResponse(BaseModel):
     images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
     parameters: dict

requirements.txt

@@ -30,4 +30,8 @@ torch
 torchdiffeq
 torchsde
 transformers==4.30.2
-pillow-avif-plugin==1.4.3
+pillow-avif-plugin==1.4.3
+
+openai
+nltk
+deep_translator