第一个增强版上线

flask_drop_rewrite_request.py

@@ -302,7 +302,7 @@ def pre_sentence_ulit(sentence):
     '''
     sentence = str(sentence).strip()
     if_change = True
-    if len(sentence) > 7:
+    if len(sentence) > 9:
         text = "You are a helpful assistant.\n\nUser:改写下面这句话，要求意思接近但是改动幅度比较大，字数只能多不能少:\n{}\nAssistant:".format(sentence)
     else:
         text = "You are a helpful assistant.\n\nUser:下面词不做任何变化:\n{}\nAssistant:".format(sentence)
@@ -322,6 +322,8 @@ def pre_sentence_ulit(sentence):
 
 
 def main(texts: dict):
+    if texts == {"1": "0"}:
+        9/0
     text_list = paragraph_test(texts)
 
     text_info = []
@@ -421,11 +423,17 @@ def classify():  # 调用模型，设置最大batch_size
         if text_type == 'focus':
             texts_list = main(texts)
         elif text_type == 'chapter':
-            texts_list = main(texts)
+            try:
+                texts_list = main(texts)
+            except:
+                texts_list = []
         else:
             texts_list = []
+        if texts_list != []:
+            return_text = {"texts": texts_list, "probabilities": None, "status_code": 200}
+        else:
+            return_text = {"texts": texts_list, "probabilities": None, "status_code": 400}
 
-        return_text = {"texts": texts_list, "probabilities": None, "status_code": 200}
         load_result_path = "./new_data_logs/{}.json".format(query_id)
 
         print("query_id: ", query_id)

flask_predict_batch_mistral.py

@@ -279,13 +279,12 @@ def main(texts: dict):
     for i, output in enumerate(outputs):
         index = output.request_id
         generated_text = output.outputs[0].text
-        generated_text = pre_sentence_ulit(generated_text)
         generated_text_list[int(index)] = generated_text
 
 
     for i in range(len(text_list)):
         if len(text_list[i][0]) > 7:
-            continue
+            generated_text_list[i] = pre_sentence_ulit(generated_text_list[i])
         else:
             generated_text_list[i] = text_list[i][0]
 

flask_predict_mistral_vllm.py

@@ -1,3 +1,5 @@
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = "2"
 import flask
 from transformers import pipeline
 import redis
@@ -5,6 +7,9 @@ import uuid
 import json
 from threading import Thread
 import time
+import requests
+from flask import request
+from vllm import LLM, SamplingParams
 
 app = flask.Flask(__name__)
 pool = redis.ConnectionPool(host='localhost', port=63179, max_connections=100, db=5, password="zhicheng123*")
@@ -29,34 +34,33 @@ def mistral_vllm_models(texts):
         generated_text = output.outputs[0].text
         generated_text_list[int(index)] = generated_text
 
+    return generated_text_list
 
-def classify(batch_size):  # 调用模型，设置最大batch_size
+
+def classify():  # 调用模型，设置最大batch_size
     while True:
-        texts = []
-        query_ids = []
         if redis_.llen(db_key_query) == 0:  # 若队列中没有元素就继续获取
             continue
-        for i in range(min(redis_.llen(db_key_query), batch_size)):
+        else:
             query = redis_.lpop(db_key_query).decode('UTF-8')  # 获取query的text
-            query_ids.append(json.loads(query)['id'])
-            texts.append(json.loads(query)['text'])  # 拼接若干text 为batch
+            query_ids = json.loads(query)['id']
+            texts = json.loads(query)['texts']  # 拼接若干text 为batch
         result = mistral_vllm_models(texts)  # 调用模型
-        for (id_, res) in zip(query_ids, result):
-            res['score'] = str(res['score'])
-            redis_.set(id_, json.dumps(res))  # 将模型结果送回队列
+        print(result)
+        redis_.set(query_ids, json.dumps(result))  # 将模型结果送回队列
 
 
 @app.route("/predict", methods=["POST"])
 def handle_query():
-    text = flask.request.form['text']  # 获取用户query中的文本 例如"I love you"
+    texts = request.json["texts"]  # 获取用户query中的文本 例如"I love you"
     id_ = str(uuid.uuid1())  # 为query生成唯一标识
-    d = {'id': id_, 'text': text}  # 绑定文本和query id
+    d = {'id': id_, 'texts': texts}  # 绑定文本和query id
     redis_.rpush(db_key_query, json.dumps(d))  # 加入redis
     while True:
         result = redis_.get(id_)  # 获取该query的模型结果
         if result is not None:
             redis_.delete(id_)
-            result_text = {'code': "200", 'data': result.decode('UTF-8')}
+            result_text = {'code': "200", 'resilt': json.loads(result.decode('UTF-8'))}
             break
     return flask.jsonify(result_text)  # 返回结果
 
@@ -64,4 +68,4 @@ def handle_query():
 if __name__ == "__main__":
     t = Thread(target=classify)
     t.start()
-    app.run(debug=False, host='127.0.0.1', port=9000)
+    app.run(debug=False, host='0.0.0.0', port=14010)

redis_check_uuid_mistral.py

@@ -44,9 +44,10 @@ def handle_query():
         with open(result_path, encoding='utf8') as f1:
             # 加载文件的对象
             result_dict = json.load(f1)
+        code = result_dict["status_code"]
         texts = result_dict["texts"]
         probabilities = result_dict["probabilities"]
-        result_text = {'code': 200, 'text': texts, 'probabilities': probabilities}
+        result_text = {'code': code, 'text': texts, 'probabilities': probabilities}
     else:
         querying_list = list(redis_.smembers("querying"))
         querying_set = set()
@@ -84,4 +85,4 @@ def handle_query():
 
 
 if __name__ == "__main__":
-    app.run(debug=False, host='0.0.0.0', port=14003)
+    app.run(debug=False, host='0.0.0.0', port=14005)