langchain-ai / langchain-aws-template Goto Github PK
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License: Other
Build Generative AI applications with Langchain on AWS
License: Other
To avoid timeouts and improve the user experience responses should be streamed using the streaming feature in Langchain and combined with WebSocket APIs
Add a Retrieval Augmented Generation (RAG) template that can connect to external knowledge sources.
I occasionally get a the following error on completions:
KeyError: 'message'
Here's the stack:
File ".../langchain_aws/chat_models/bedrock.py", line 361, in _generate
for chunk in self._stream(messages, stop, run_manager, **kwargs):
File ".../langchain_aws/chat_models/bedrock.py", line 339, in _stream
for chunk in self._prepare_input_and_invoke_stream(
File ".../langchain_aws/llms/bedrock.py", line 653, in _prepare_input_and_invoke_stream
for chunk in LLMInputOutputAdapter.prepare_output_stream(
File ".../langchain_aws/llms/bedrock.py", line 239, in prepare_output_stream
chunk_obj[output_key]
Here are my langchain versions:
langchain 0.1.20
langchain-anthropic 0.1.11
langchain-aws 0.1.3
langchain-community 0.0.38
langchain-core 0.1.52
langchain-experimental 0.0.58
langchain-text-splitters 0.0.1
langgraph 0.0.48
Python version: Python 3.11.6
Model Id: anthropic.claude-3-sonnet-20240229-v1:0
The error is intermittent. It appears to be an issue with the response that Bedrock is generating.
I am getting this error
0
Chat with AI
0
hello
KeyError: 'session_id'
Traceback:
File "/Users/rupeshti/anaconda3/lib/python3.11/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 541, in _run_script
exec(code, module.__dict__)
File "/Users/rupeshti/workdir/gitbox/langchain-aws-template-main/service/webapp/app.py", line 123, in <module>
write_chat_message(a, q)
File "/Users/rupeshti/workdir/gitbox/langchain-aws-template-main/service/webapp/app.py", line 114, in write_chat_message
st.session_state['session_id'] = md['answer']['session_id']
~~~~~~~~~~~~^^^^^^^^^^^^^^
Made with [Streamlit](http://streamlit.io/)
Many developers will need a front-end login/authentication that integrates with the back-end. One option is Amplify authentication, but the downside is it requires a Javascript front-end. To do so we could look to making a Typescript front-end folder that branches off of the mckaywrigely/chatbot-ui project.
Amplify Auth has the added benefit of allowing developers to identify which user is currently accessing the front-end allowing them to customize the chatbot with multiple features such as: allowing a user to access previous conversations in the left-hand menu and ensuring a user only has access to their own data.
Another benefit of the mckaywrigely/chatbot-ui project front-end is we can add further features later on such as allowing a user to select certain tools (similar to GPT Plugins).
cdk deploy in the service blows up with some permissions errors
Full stack trace:
12:51:25 PM | CREATE_FAILED | AWS::Lambda::Function | LangChainHandlerDD6FD44B
Resource handler returned message: "User: arn:aws:sts::942747732415:assumed-role/cdk-hnb659fds-cfn-exec-role-9
42747732415-us-west-2/AWSCloudFormation is not authorized to perform: lambda:GetLayerVersion on resource: arn:
aws:lambda:us-east-1:177933569100:layer:AWS-Parameters-and-Secrets-Lambda-Extension:4 because no resource-base
d policy allows the lambda:GetLayerVersion action (Service: Lambda, Status Code: 403, Request ID: 64ab8809-cc5
4-49d2-996f-1b96c387404e)" (RequestToken: d53c00f6-d230-3dde-73bb-942b56d31849, HandlerErrorCode: AccessDenied
)
❌ LangChainApp failed: Error: The stack named LangChainApp failed creation, it may need to be manually deleted from the AWS console: ROLLBACK_COMPLETE: Resource handler returned message: "User: arn:aws:sts::942747732415:assumed-role/cdk-hnb659fds-cfn-exec-role-942747732415-us-west-2/AWSCloudFormation is not authorized to perform: lambda:GetLayerVersion on resource: arn:aws:lambda:us-east-1:177933569100:layer:AWS-Parameters-and-Secrets-Lambda-Extension:4 because no resource-based policy allows the lambda:GetLayerVersion action (Service: Lambda, Status Code: 403, Request ID: 64ab8809-cc54-49d2-996f-1b96c387404e)" (RequestToken: d53c00f6-d230-3dde-73bb-942b56d31849, HandlerErrorCode: AccessDenied)
at FullCloudFormationDeployment.monitorDeployment (/Users/jmannix/.volta/tools/image/packages/aws-cdk/lib/node_modules/aws-cdk/lib/index.js:397:10236)
at processTicksAndRejections (node:internal/process/task_queues:96:5)
at async deployStack2 (/Users/jmannix/.volta/tools/image/packages/aws-cdk/lib/node_modules/aws-cdk/lib/index.js:400:145739)
at async /Users/jmannix/.volta/tools/image/packages/aws-cdk/lib/node_modules/aws-cdk/lib/index.js:400:128776
at async run (/Users/jmannix/.volta/tools/image/packages/aws-cdk/lib/node_modules/aws-cdk/lib/index.js:400:126782)
❌ Deployment failed: Error: Stack Deployments Failed: Error: The stack named LangChainApp failed creation, it may need to be manually deleted from the AWS console: ROLLBACK_COMPLETE: Resource handler returned message: "User: arn:aws:sts::942747732415:assumed-role/cdk-hnb659fds-cfn-exec-role-942747732415-us-west-2/AWSCloudFormation is not authorized to perform: lambda:GetLayerVersion on resource: arn:aws:lambda:us-east-1:177933569100:layer:AWS-Parameters-and-Secrets-Lambda-Extension:4 because no resource-based policy allows the lambda:GetLayerVersion action (Service: Lambda, Status Code: 403, Request ID: 64ab8809-cc54-49d2-996f-1b96c387404e)" (RequestToken: d53c00f6-d230-3dde-73bb-942b56d31849, HandlerErrorCode: AccessDenied)
at deployStacks (/Users/jmannix/.volta/tools/image/packages/aws-cdk/lib/node_modules/aws-cdk/lib/index.js:400:129083)
at processTicksAndRejections (node:internal/process/task_queues:96:5)
at async CdkToolkit.deploy (/Users/jmannix/.volta/tools/image/packages/aws-cdk/lib/node_modules/aws-cdk/lib/index.js:400:147788)
at async exec4 (/Users/jmannix/.volta/tools/image/packages/aws-cdk/lib/node_modules/aws-cdk/lib/index.js:455:51984)
Stack Deployments Failed: Error: The stack named LangChainApp failed creation, it may need to be manually deleted from the AWS console: ROLLBACK_COMPLETE: Resource handler returned message: "User: arn:aws:sts::942747732415:assumed-role/cdk-hnb659fds-cfn-exec-role-942747732415-us-west-2/AWSCloudFormation is not authorized to perform: lambda:GetLayerVersion on resource: arn:aws:lambda:us-east-1:177933569100:layer:AWS-Parameters-and-Secrets-Lambda-Extension:4 because no resource-based policy allows the lambda:GetLayerVersion action (Service: Lambda, Status Code: 403, Request ID: 64ab8809-cc54-49d2-996f-1b96c387404e)" (RequestToken: d53c00f6-d230-3dde-73bb-942b56d31849, HandlerErrorCode: AccessDenied)
Langflow is a web interface to experiment and prototype langchain pipelines.
https://pypi.org/project/langflow/
In Jupyter Notebook (jupyter notebook has docker).
Instructions : 5, 6, 7
langflow-ai/langflow#310
Got struck after installing. Both local and network links giving "This site can’t be reached"
Tried both with local and network ip adding /proxy/3000. Didn't work.
pip install langflow
in sagemaker studio is exiting with the error below. Langflow not getting installed.
Update the LangChain version to the current version 0.0.193
.
The AWS Secret needs to include 2 keys, the second slack-bot-token
needs taken from the Slack App page in Slack after the app is configured. README should be updated to walk users through this.
I think this issue is related to aws secrets manager not setup correctly, according to this issue.
I followed this instruction to set up my aws secrets (and I made sure that it was set up in the same region as my lambda & api):
Expected secret name is api-keys
openai key is expected to be stored with openai-api-key
key
but I still got Status:502;Internal server error...
here is a log file:
Any help is appreciated!
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