默认embbedding模型出现问题 ：TypeError: 'NoneType' object is not iterable

[lcj1069864078]

我在指定了了本地的大模型路径之后，使用MetaGPT的默认嵌入模型会报错：
Traceback (most recent call last):
File "/mnt/d/MetaGPT-main/MetaGPT-main/examples/mytest.py", line 28, in
asyncio.run(main())
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/asyncio/runners.py", line 190, in run
return runner.run(main)
^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/asyncio/base_events.py", line 654, in run_until_complete
return future.result()
^^^^^^^^^^^^^^^
File "/mnt/d/MetaGPT-main/MetaGPT-main/examples/mytest.py", line 23, in main
engine = SimpleEngine.from_docs(input_files=[DOC_PATH])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/d/MetaGPT-main/MetaGPT-main/metagpt/rag/engines/simple.py", line 128, in from_docs
return cls._from_nodes(
^^^^^^^^^^^^^^^^
File "/mnt/d/MetaGPT-main/MetaGPT-main/metagpt/rag/engines/simple.py", line 301, in _from_nodes
retriever = get_retriever(configs=retriever_configs, nodes=nodes, embed_model=embed_model)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/d/MetaGPT-main/MetaGPT-main/metagpt/rag/factories/retriever.py", line 69, in get_retriever
return self._create_default(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/d/MetaGPT-main/MetaGPT-main/metagpt/rag/factories/retriever.py", line 76, in _create_default
index = self._extract_index(None, **kwargs) or self._build_default_index(**kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/mnt/d/MetaGPT-main/MetaGPT-main/metagpt/rag/factories/retriever.py", line 117, in _build_default_index
index = VectorStoreIndex(
^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/indices/vector_store/base.py", line 74, in init
super().init(
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/indices/base.py", line 91, in init
index_struct = self.build_index_from_nodes(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/indices/vector_store/base.py", line 307, in build_index_from_nodes
return self._build_index_from_nodes(nodes, **insert_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/indices/vector_store/base.py", line 279, in _build_index_from_nodes
self._add_nodes_to_index(
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/indices/vector_store/base.py", line 232, in _add_nodes_to_index
nodes_batch = self._get_node_with_embedding(nodes_batch, show_progress)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/indices/vector_store/base.py", line 140, in _get_node_with_embedding
id_to_embed_map = embed_nodes(
^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/indices/utils.py", line 138, in embed_nodes
new_embeddings = embed_model.get_text_embedding_batch(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/core/base/embeddings/base.py", line 255, in get_text_embedding_batch
embeddings = self._get_text_embeddings(cur_batch)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/embeddings/openai/base.py", line 419, in _get_text_embeddings
return get_embeddings(
^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/tenacity/init.py", line 289, in wrapped_f
return self(f, *args, **kw)
^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/tenacity/init.py", line 379, in call
do = self.iter(retry_state=retry_state)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/tenacity/init.py", line 314, in iter
return fut.result()
^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/concurrent/futures/_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/concurrent/futures/_base.py", line 401, in __get_result
raise self._exception
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/tenacity/init.py", line 382, in call
result = fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/llama_index/embeddings/openai/base.py", line 180, in get_embeddings
data = client.embeddings.create(input=list_of_text, model=engine, **kwargs).data
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/openai/resources/embeddings.py", line 114, in create
return self._post(
^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/openai/_base_client.py", line 1271, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/openai/_base_client.py", line 942, in request
return self._request(
^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/openai/_base_client.py", line 1048, in _request
return self._process_response(
^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/openai/_base_client.py", line 1147, in _process_response
return api_response.parse()
^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/openai/_response.py", line 318, in parse
parsed = self._options.post_parser(parsed)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/lcj1069/anaconda3/envs/MetaGPT4/lib/python3.11/site-packages/openai/resources/embeddings.py", line 102, in parser
for embedding in obj.data:
TypeError: 'NoneType' object is not iterable
ERROR conda.cli.main_run:execute(124): conda run python /mnt/d/MetaGPT-main/MetaGPT-main/examples/mytest.py failed. (See above for error)

我自己认为是因为网络原因无法访问openai的embedding模型，但是我查阅了MetaGPT文档中支持的其他embedding模型，发现大多数embedding模型与MetaGPT的运行环境不相适配，请问你们有更好的访问openai的方法或者有其他支持MetaGPT可本地部署的embedding模型吗？

[seehi]

1. 可以用下面代码验证embedding服务是否正常：

from llama_index.embeddings.openai import OpenAIEmbedding


embedding = OpenAIEmbedding(api_base="YOUR_API_BASE", api_key="YOUR_API_KEY")
print(embedding.get_text_embedding("hello world"))

2. 当前可通过配置设置的embedding模型，可查看：配置embedding
3. llamaindex支持的所有模型也是都支持，from_docs函数有个embed_model参数