#2025/7/14 #优化获取最新数据代码 #优化预警提示语

shidong

2025-07-14 fa78e5b5e03e40431e6c4404c6ecb00b8de81be3

 qwen_thread.py

@@ -41,6 +41,7 @@
                torch_dtype=torch.float16

            ).eval()
            model = model.to(f"cuda:{config.get('cuda')}")
            self.model_pool.append(model)

        # 共享的处理器 (线程安全)
@@ -93,12 +94,13 @@
                    risk_description = self.image_rule_chat_with_detail(filedata, res['waning_value'], ragurl,rag_mode,max_tokens)
                    # 生成处理建议
                    suggestion = self.image_rule_chat_suggestion(filedata, res['waning_value'], ragurl,rag_mode,max_tokens)
                    self.logger.info(
                        f"{res['video_point_id']}执行完毕：{res['id']}:是否预警{is_waning},安全隐患：{risk_description}\n处理建议：{suggestion}")
            else:
                is_desc = 3

            # 数据组
            data = {
                "id": res['id'],
                "event_level_id": res['event_level_id'],  # event_level_id
                "event_level_name": res['event_level_name'],  # event_level_id
                "rule_id": res["rule_id"],
@@ -122,9 +124,9 @@
                "suggestion": suggestion,
                "knowledge_id": res['knowledge_id']
            }

            self.collection.delete(f"id == {res['id']}")
            # 保存到milvus
            image_id = self.collection.upsert(data).primary_keys
            image_id = self.collection.insert(data).primary_keys
            data = {
                "id": str(image_id[0]),
                "video_point_id": res['video_point_id'],
@@ -171,8 +173,8 @@
                return_tensors="pt",
            )
            inputs = inputs.to(model.device)
            with torch.inference_mode():
                outputs = model.generate(**inputs,max_new_tokens=100)
            with torch.inference_mode(),torch.cuda.amp.autocast():
                outputs = model.generate(**inputs,max_new_tokens=200)
            generated_ids = outputs[:, len(inputs.input_ids[0]):]
            image_text = self.processor.batch_decode(
                generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=True
@@ -218,7 +220,7 @@
    def image_rule_chat(self, image_des,rule_text, ragurl, rag_mode,max_tokens):
        try:
            content = (
                f"图片描述内容为：\n{image_des}\n规则内容：\n{rule_text}。\n请验证图片描述中是否有符合规则的内容，不进行推理和think。返回结果格式为[xxx符合的规则id]，如果没有返回[]")
                f"图片描述内容为：\n{image_des}\n规则内容：\n{rule_text}。\n请验证图片描述中是否有不符合规则的内容，不进行推理和think。返回结果格式为[xxx符合的规则id]，如果没有返回[]")
            #self.logger.info(len(content))
            search_data = {
                "prompt": "",