UHRS
Hi all, I'm Alex and new to this space, Im currently working on the uhrs platform, was looking at a way to contact the admin and found through. I have experience in Ai of self driven cars and human robots from a common vendor, Remotasks. Id be greatful if I get a welcome and a small introduction of this space and what you guys talk about...Thanks in advance .
Adding searching SharePoint pages to chatbot (page contents not uploaded files)
Hi , I am new to Azure bot frameworks and Cognitive Services and am working on creating a chatbot to signpost staff to various in-house services. I have created a QnA bot using the QnA maker but I want to extend the bot to be able to search our SharePoint Intranet and link users to appropriate entries on our site. These are not files but SharePoint web pages. Assuming this is possible, what is the best way of achieving this?
RAG / Vector Database best practices for CoPilot Studio
I have been working with Microsoft Gen AI LLM tools (Azure OpenAI Studio and CoPilot Studio) for building a custom 'agent' for answering questions about a set of company internal documents. It seems like RAG is the best approach and fine-tuning would be overkill. In support of RAG with a vector database I would like to understand best practices. It isn't clear to me if manually uploading files to the CoPilot within CoPilot studio does effective preprocessing of the documents (e.g. tables) and chunking or not. And, if it adds embeddings for words not in the pre-trained LLMs embeddings vocabulary. I am looking for the best practice on an ongoing basis for automating the updates (add,update,delete) to the RAG content on an ongoing basis for multiple additional customized LLMs with different sets of documents. It seems like that leveraging open source technology like "langchain" might be a way to achieve consistent results for LLMs that might be updated on a regular basis with RAG content. Is that advised? Or are there Microsoft tools that might be better for automating content updates? Also, there is a choice of what vector database to use, posgrestsql, Cosmos DB (Mongo), etc. Which are supported and recommended for Copilot studio. Thanks in advance for any guidance!Demystifying Error in Microsoft Designer "Image Couldn't Be Generated"
The error message on Microsoft Designer : "Images couldn't be generated. Something may have triggered Microsoft Responsible AI guidelines" suggests that there might be an issue related to Microsoft's Responsible AI guidelines while attempting to generate images using a Microsoft tool or service. Review Documentation: Check the official documentation or user guides related to the specific Microsoft tool or service you are using. Look for any guidelines or restrictions related to image generation and Responsible AI practices. Check AI Guidelines Compliance: Ensure that your use of the tool aligns with Microsoft's Responsible AI guidelines. Microsoft may have specific requirements or restrictions in place to promote ethical and responsible AI usage. Contact Support: If you cannot find a solution in the documentation or online forums, consider reaching out to Microsoft support for assistance. They may provide insights into the specific issue and guide you on how to proceed. Update Software: Ensure that you are using the latest version of the Microsoft tool or service. Software updates often include bug fixes and improvements that may address issues related to AI guidelines. Check for Service Status: Sometimes, issues may be related to temporary service disruptions or maintenance. Check the status of the Microsoft service you are using to see if there are any reported issues. Community Forums: Look for discussions on Microsoft's community forums. Other users may have experienced similar issues, and there might be community-driven solutions or insights. Provide Feedback: If you are using a preview or beta version of a tool, consider providing feedback to Microsoft. They may appreciate insights into user experiences and potential issues.Innovate with Azure AI Studio AMA: Unleashing Generative AI for Enterprise Solutions
Join us for an AMA on Azure AI Studio next week, December 14 at 9AM PT! Check out the link below for more details: Innovate with Azure AI Studio AMA: Unleashing Generative AI for Enterprise Solutions - Microsoft Community Hub
GenAI based Project Management
Phase 1 We wanted to develop a Gen AI solution for Project Management activities like below. Can anyone guide us or help how we can start? We are in the learning phase of Gen AI with MS learn materials & video courses. Effort estimation based on task description and technology Creating tasks/subtasks/comments in the ERP project module Assign the developer/resources based on the skill required Monitor the progress of projects & tasks Taking follow-up with the developer for particular tasks through task updates, Teams chat & Teams call. Create a project progress report and share it with the respective customer through email. Make the Teams call with the developer and discuss the progress/challenges (One to one call & group call) Attend customer meeting calls, prepare meeting notes and share them with all the participants. Make the phone call (VOIP) to employees/developers/customers/contractors for the project/task update. Attending customer calls/ Team calls to understand the requirements and create a project scope document.Issue: Deploying a Model using Azure Machine Learning Service
Hi All, I created a classifier model using Azure Machine Learning service, after successfully registering a model i built the correct environment for container instance providing scoring file, environment file and configuration file Unfortunately when I am deploying my solution it's giving me the error, however here is my deployment service logs to get more details: **service Logs** 2020-02-07T06:21:10,612616835+00:00 - rsyslog/run 2020-02-07T06:21:10,616528746+00:00 - iot-server/run 2020-02-07T06:21:10,617958751+00:00 - gunicorn/run 2020-02-07T06:21:10,627065178+00:00 - nginx/run EdgeHubConnectionString and IOTEDGE_IOTHUBHOSTNAME are not set. Exiting... 2020-02-07T06:21:11,108893523+00:00 - iot-server/finish 1 0 2020-02-07T06:21:11,116794547+00:00 - Exit code 1 is normal. Not restarting iot-server. Starting gunicorn 19.9.0 Listening at: http://127.0.0.1:31311 (12) Using worker: sync worker timeout is set to 300 Booting worker with pid: 45 Initializing logger Starting up app insights client Starting up request id generator Starting up app insight hooks Invoking user's init function 2020-02-07 06:21:15,494 | azureml.core.run | DEBUG | Could not load run context RunEnvironmentException: Message: Could not load a submitted run, if outside of an execution context, use experiment.start_logging to initialize an azureml.core.Run. InnerException None ErrorResponse { "error": { "message": "Could not load a submitted run, if outside of an execution context, use experiment.start_logging to initialize an azureml.core.Run." } }, switching offline: False 2020-02-07 06:21:15,495 | azureml.core.run | DEBUG | Could not load the run context and allow_offline set to False 2020-02-07 06:21:15,495 | azureml.core.model | DEBUG | Checking root for demo_Model.pkl because candidate dir azureml-models had 1 nodes: azureml-models/demomodel/8/demo_Model.pkl User's init function failed Encountered Exception Traceback (most recent call last): File "/var/azureml-server/aml_blueprint.py", line 163, in register main.init() File "/var/azureml-app/main.py", line 88, in init driver_module.init() File "score.py", line 13, in init model_path = Model.get_model_path('demo_Model.pkl') File "/opt/miniconda/lib/python3.6/site-packages/azureml/core/model.py", line 697, in get_model_path return Model._get_model_path_local(model_name, version) File "/opt/miniconda/lib/python3.6/site-packages/azureml/core/model.py", line 718, in _get_model_path_local return Model._get_model_path_local_from_root(model_name) File "/opt/miniconda/lib/python3.6/site-packages/azureml/core/model.py", line 761, in _get_model_path_local_from_root "set logging level to DEBUG.".format(candidate_model_path)) azureml.exceptions._azureml_exception.ModelNotFoundException: ModelNotFoundException: Message: Model not found in cache or in root at ./demo_Model.pkl. For more info,set logging level to DEBUG. InnerException None ErrorResponse { "error": { "message": "Model not found in cache or in root at ./demo_Model.pkl. For more info,set logging level to DEBUG." } } /opt/miniconda/lib/python3.6/site-packages/sklearn/externals/joblib/__init__.py:15: FutureWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+. warnings.warn(msg, category=FutureWarning) Worker exiting (pid: 45) Shutting down: Master Reason: Worker failed to boot. 2020-02-07T06:21:15,663509630+00:00 - gunicorn/finish 3 0 2020-02-07T06:21:15,664398433+00:00 - Exit code 3 is not normal. Killing image. **Error** Running.............................................................................................................................................................................................................................................. TimedOut ERROR - Service deployment polling reached non-successful terminal state, current service state: Unhealthy More information can be found using '.get_logs()' Error: { "code": "DeploymentTimedOut", "statusCode": 504, "message": "The deployment operation polling has TimedOut. The service creation is taking longer than our normal time. We are still trying to achieve the desired state for the web service. Please check the webservice state for the current webservice health. From SDK you can run print(service.state) to know the current state of the webservice." } ERROR - Service deployment polling reached non-successful terminal state, current service state: Unhealthy More information can be found using '.get_logs()' Error: { "code": "DeploymentTimedOut", "statusCode": 504, "message": "The deployment operation polling has TimedOut. The service creation is taking longer than our normal time. We are still trying to achieve the desired state for the web service. Please check the webservice state for the current webservice health. From SDK you can run print(service.state) to know the current state of the webservice." } --------------------------------------------------------------------------- WebserviceException Traceback (most recent call last) ~/anaconda3_501/lib/python3.6/site-packages/azureml/core/webservice/webservice.py in wait_for_deployment(self, show_output) 530 'Error:\n' --> 531 '{}'.format(self.state, logs_response, error_response), logger=module_logger) 532 print('{} service creation operation finished, operation "{}"'.format(self._webservice_type, WebserviceException: WebserviceException: Message: Service deployment polling reached non-successful terminal state, current service state: Unhealthy More information can be found using '.get_logs()' Error: { "code": "DeploymentTimedOut", "statusCode": 504, "message": "The deployment operation polling has TimedOut. The service creation is taking longer than our normal time. We are still trying to achieve the desired state for the web service. Please check the webservice state for the current webservice health. From SDK you can run print(service.state) to know the current state of the webservice." } InnerException None ErrorResponse { "error": { "message": "Service deployment polling reached non-successful terminal state, current service state: Unhealthy\nMore information can be found using '.get_logs()'\nError:\n{\n \"code\": \"DeploymentTimedOut\",\n \"statusCode\": 504,\n \"message\": \"The deployment operation polling has TimedOut. The service creation is taking longer than our normal time. We are still trying to achieve the desired state for the web service. Please check the webservice state for the current webservice health. From SDK you can run print(service.state) to know the current state of the webservice.\"\n}" } } During handling of the above exception, another exception occurred: WebserviceException Traceback (most recent call last) <timed exec> in <module> ~/anaconda3_501/lib/python3.6/site-packages/azureml/core/webservice/webservice.py in wait_for_deployment(self, show_output) 538 'Current state is {}'.format(self.state), logger=module_logger) 539 else: --> 540 raise WebserviceException(e.message, logger=module_logger) 541 542 def _wait_for_operation_to_complete(self, show_output): WebserviceException: WebserviceException: Message: Service deployment polling reached non-successful terminal state, current service state: Unhealthy More information can be found using '.get_logs()' Error: { "code": "DeploymentTimedOut", "statusCode": 504, "message": "The deployment operation polling has TimedOut. The service creation is taking longer than our normal time. We are still trying to achieve the desired state for the web service. Please check the webservice state for the current webservice health. From SDK you can run print(service.state) to know the current state of the webservice." } InnerException None ErrorResponse { "error": { "message": "Service deployment polling reached non-successful terminal state, current service state: Unhealthy\nMore information can be found using '.get_logs()'\nError:\n{\n \"code\": \"DeploymentTimedOut\",\n \"statusCode\": 504,\n \"message\": \"The deployment operation polling has TimedOut. The service creation is taking longer than our normal time. We are still trying to achieve the desired state for the web service. Please check the webservice state for the current webservice health. From SDK you can run print(service.state) to know the current state of the webservice.\"\n}" } } That's how my webservice code look like: %%time from azureml.core.webservice import Webservice from azureml.core.model import Model from azureml.core.model import InferenceConfig from azureml.core.environment import Environment myenv = Environment.from_conda_specification(name="myenv", file_path="myenv.yml") inference_config = InferenceConfig(entry_script="score.py", environment=myenv) service = Model.deploy(workspace=ws, name='myimage', models=[model], inference_config=inference_config, deployment_config=aciconfig) service.wait_for_deployment(show_output=True) can anyone tell me what it actually means? How can i solve this? Thanks AhmadHow can i contact UHRS team
I'm writing to express my concern about my recent inability to access UHRS. When I attempted to log in, I received a message stating that I was blocked from working in UHRS due to a failed login attempt. While I was informed by someone that it may have been due to the quality of my work, I am unsure of the exact reasons for this blockage, as my work has been of high quality and I have not received any warnings or notifications to suggest otherwise. I would appreciate it if you could help me reactivate my account so that I can continue working. If there is any further information that I can provide to assist in this process, please let me know. Thank you for your attention to this matter.Copilot for Autonomous Agents
I'm doing some remarkable things with Copilot in a browser - pushing it to its limits. However, I would like to build autonomous AI agents in Python on Mac or PC and wonder if Microsoft is thinking about this? Even if I could automate the browser with API calls, that would give me the power I need to build some amazing Copilot-powered applications. If any Desktop Copilot Product Manager wants to reach out to me, please do! I will be happy to show some of the innovations I'm building with Copilot.
Flow - Trigger mail on SharePoint Library Column
Hi All I'm busy building a simple Contract Management System in sharepoint where i store all my supplier contracts in one place and now im trying to trigger a mail notification based on the notice period to send me a mail\team notification that the contract is about to expire. I created a Library in SharPoint and added a few custom columns to the library to specify a few things namely : Contract Name Start Date End Date Notice Period Contract Owner Now my question is how do I do the flow part that will send the notifications ? Please guide me what to use in flow to get the desired result here. Many Thanks Janus
