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Using locally, version 0.1.16 with the config in the code.
>>> import mem0
>>> mem0.__version__
'0.1.16'
import os
os.environ['AWS_REGION'] = "my-region"
os.environ['AWS_ACCESS_KEY']="my-key"
os.environ['AWS_SECRET_ACCESS_KEY']="my-secret"
config = {
"llm": {
"provider": "aws_bedrock",
"config": {
"model": "arn:aws:bedrock:ap-south-1::foundation-model/anthropic.claude-3-sonnet-20240229-v1:0",
"temperature": 0.2,
"max_tokens": 1500,
}
},
"vector_store": {
"provider": "qdrant",
"config": {
"url": "my-url",
"api_key": "my-key"
}
},
"embedder": {
"provider": "huggingface"
}
}
m = Memory.from_config(config)
# 1. Add: Store a memory from any unstructured text
result = m.add("I am working on improving my tennis skills. Suggest some online courses.", user_id="me", metadata={"category": "hobbies"})
Running it locally, when using AWS bedrock anthropic, I am getting the following error.
File "/Users/neeraj/Code/t-mem0/main.py", line 33, in <module>
result = m.add("I am working on improving my tennis skills. Suggest some online courses.", user_id="neeraj", metadata={"category": "hobbies"})
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/neeraj/Code/t-mem0/lib/python3.12/site-packages/mem0/memory/main.py", line 109, in add
vector_store_result = future1.result()
^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/[email protected]/3.12.6/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 449, in result
return self.__get_result()
^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/Cellar/[email protected]/3.12.6/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/_base.py", line 401, in __get_result
raise self._exception
File "/opt/homebrew/Cellar/[email protected]/3.12.6/Frameworks/Python.framework/Versions/3.12/lib/python3.12/concurrent/futures/thread.py", line 58, in run
result = self.fn(*self.args, **self.kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/neeraj/Code/t-mem0/lib/python3.12/site-packages/mem0/memory/main.py", line 136, in _add_to_vector_store
response = self.llm.generate_response(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: AWSBedrockLLM.generate_response() got an unexpected keyword argument 'response_format'
The error looks to be because AWSBedrockLLM has the following signature
🐛 Describe the bug
Using locally, version 0.1.16 with the config in the code.
Running it locally, when using AWS bedrock anthropic, I am getting the following error.
The error looks to be because
AWSBedrockLLM
has the following signatureThis looks to be a very basic miss. Am I doing something wrong, or is
AWSBedrockLLM
not widely used ?The text was updated successfully, but these errors were encountered: