dustyposa / rasa_ch_faq Goto Github PK
View Code? Open in Web Editor NEW用 rasa 实现 rasa demo 机器人,有一些惊奇的功能,faq,图谱,多轮等
License: MIT License
用 rasa 实现 rasa demo 机器人,有一些惊奇的功能,faq,图谱,多轮等
License: MIT License
我使用了您开源出来的前端项目,另外我没有使用 npm 部署前端服务, 而是直接使用了您给出的命令行: --cors "*" 加载了这个前端文件。但是我有一个问题:
还请您不吝赐教。期待得到您的回复,我的 VX:18336304089
如果您愿意提供帮助,我愿意有偿获得您的指导与帮助。
你好,我想问一下,rasa3.0如何实现图片的上传。
想到一个加一个吧。
运行rasa train时报错,报错信息如下:
Traceback (most recent call last):
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/transformers/modeling_tf_utils.py", line 1232, in from_pretrained
missing_keys, unexpected_keys = load_tf_weights(model, resolved_archive_file)
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/transformers/modeling_tf_utils.py", line 459, in load_tf_weights
with h5py.File(resolved_archive_file, "r") as f:
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/h5py/_hl/files.py", line 406, in init
fid = make_fid(name, mode, userblock_size,
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/h5py/_hl/files.py", line 173, in make_fid
fid = h5f.open(name, flags, fapl=fapl)
File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "h5py/h5f.pyx", line 88, in h5py.h5f.open
OSError: Unable to open file (file signature not found)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/anaconda3/envs/rasa/bin/rasa", line 8, in
sys.exit(main())
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/main.py", line 117, in main
cmdline_arguments.func(cmdline_arguments)
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/cli/train.py", line 59, in
train_parser.set_defaults(func=lambda args: run_training(args, can_exit=True))
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/cli/train.py", line 91, in run_training
training_result = train_all(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/api.py", line 109, in train
return rasa.utils.common.run_in_loop(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/utils/common.py", line 296, in run_in_loop
result = loop.run_until_complete(f)
File "uvloop/loop.pyx", line 1456, in uvloop.loop.Loop.run_until_complete
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/model_training.py", line 108, in train_async
return await _train_async_internal(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/model_training.py", line 289, in _train_async_internal
await _do_training(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/model_training.py", line 335, in _do_training
model_path = await _train_nlu_with_validated_data(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/model_training.py", line 759, in _train_nlu_with_validated_data
await rasa.nlu.train.train(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/nlu/train.py", line 97, in train
trainer = Trainer(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/nlu/model.py", line 167, in init
self.pipeline = self._build_pipeline(cfg, component_builder)
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/nlu/model.py", line 178, in _build_pipeline
component = component_builder.create_component(component_cfg, cfg)
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/nlu/components.py", line 938, in create_component
component = registry.create_component_by_config(component_config, cfg)
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/nlu/registry.py", line 193, in create_component_by_config
return component_class.create(component_config, config)
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/nlu/featurizers/dense_featurizer/lm_featurizer.py", line 105, in create
return cls(component_config, hf_transformers_loaded=hf_transformers_loaded)
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/rasa/nlu/featurizers/dense_featurizer/lm_featurizer.py", line 88, in init
self._load_model_instance(skip_model_load)
File "/Users/wenhk/Downloads/rasa_ch_faq/compoments/nlu/featurizer/lm_featurizer.py", line 83, in _load_model_instance
self.model = model_class_dict[self.model_name].from_pretrained(
File "/Users/anaconda3/envs/rasa/lib/python3.8/site-packages/transformers/modeling_tf_utils.py", line 1234, in from_pretrained
raise OSError(
OSError: Unable to load weights from h5 file. If you tried to load a TF 2.0 model from a PyTorch checkpoint, please set from_pt=True.
请问这是什么问题?
多轮对话确定一个推荐,怎么实现?
人:你好
AI:你好
人:我要找大学
AI:你什么学历
人:高中
AI:你什么年龄
人:18岁
AI:你想读什么专业
人:计算机
AI:你想再什么地区
人:北京
AI:推荐你北京大学
如果要实现多轮条件合并才能推出结果,怎么实现呢?
[root@localhost rasa_ch_faq]# rasa train
-bash: rasa: 未找到命令
大佬 执行rasa命令提示这个是啥情况
Some layers from the model checkpoint at pre_models were not used when initializing TFBertModel: ['mlm___cls', 'nsp___cls']
除了几个yml文件,其他要改动的地方是不是很多呢?
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.