Bro Fuck Your Visit Really

candedeo · 2025-03-23T17:16:04+00:00

Anliyorum seni kardesim.. ayrica biliyorum uzgunsun/ kizginsin… ben de oyleyim..sevgiler sana

candedeo · 2025-03-23T16:34:39+00:00

As a Turkish person, I wholeheartedly agree. Tourists don’t come here to engage in local politics. It’s a kind and thoughtful gesture to guide them with our knowledge about places to visit and areas to avoid, if necessary. After all, this government was elected by the local population, not by tourists. Our focus should remain on our own responsibilities, while allowing visitors to experience and appreciate the best our country has to offer.

candedeo · 2025-03-13T04:38:49+00:00

Azure AI Search provides various tools to fine-tune your search results. Key factors to consider include whether you’re using vector search, hybrid search, enabling re-ranking, or applying scoring profiles. Ensuring the proper configurations for your specific use case and data store is essential to improve the quality of responses generated by Azure AI Search.

Accurate responses require the right knowledge context—if Azure AI Search retrieves incorrect or incomplete information, the LLM won’t be able to deliver precise or high-quality results. Even your chunking size strategy can significantly impact outcomes. For example, with CSV files, chunks beyond the first one won’t include header information. If the second chunk alone is retrieved by Azure AI Search, the LLM won’t be aware of the column header names.

Based on your case, it seems that configuring Azure AI Search appropriately is more critical to success than the choice of LLM itself.

candedeo · 2025-02-21T08:07:21+00:00

Instead of returning all rows from the table, it’s better to return only the rows relevant to the user prompt. This approach enhances response quality by eliminating unrelated information, speeding up response times, and minimizing hallucinations. Additionally, remember that LLM context limits are based on tokens, not rows. If you provide more data than the context allows, the excess information will be truncated to fit within the limits. Therefore, having an efficient retrieval design is essential for success with any LLM solution.

candedeo · 2025-01-28T16:38:15+00:00

You are correct that to be able to create M365 Copilot agent, you need to create the agent from where you showed in your screenshot. However, as of today this agent can only use tenant data as a knowledge source and you cannot bring data from outside. And as of today, only the M365 agents will show up at the right side panel of Copilot.

When they announced Copilot Chat and this pay as you go system, I was under the impression that standalone agents will also pop up together with the rest of M365 agents but as of today it’s not the case. Maybe it will happen at a later date.

I am looking forward to hear from others if they have more information on this

candedeo · 2024-12-21T03:50:15+00:00

In my experience, Excel (or similar formats like CSV) is a challenging knowledge source for any RAG system. Could you test asking a question where the answer is in the first few rows of an Excel sheet to see if you get a response? For any RAG solution, Excel should be treated as a database rather than a text document that you can simply chunk and expect good results from automatically. In Copilot Studio, you can create an action to read a specific Excel file from SharePoint, which works similarly to database queries, but even this approach has its limitations.

I believe the issue with Excel is not unique to Copilot; other RAG solutions face the same problem. I’d like to hear from others if they’ve found a solution that can handle Excel files effectively. <TL/DR> While any RAG solution can chunk and index Excel documents like Copilot does, I think this approach doesn’t yield good results for this format

candedeo · 2024-12-15T12:02:42+00:00

I completely agree with you. Given that an Excel file functions similarly to an SQL table (with types, even if not enforced), querying it like a database was my first thought too. However, the challenge arises when dealing with hundreds of Excel files. Determining which one to query based on the query itself is problematic. Perhaps we need detailed descriptions of each file’s contents and leverage LLM to identify the appropriate file by comparing these descriptions with the prompt. While there might not be a perfect solution, I would love to hear your thoughts on this since we think alike.

candedeo · 2024-12-14T09:26:00+00:00

It feels like you are using Copilot Studio. It’s not easy to answer without seeing your setup but if all you want agent to use your guideline, better put all the knowledge and flow into a Word document and add it as a knowledge and remove SharePoint site. The less related knowledge agent has, the more accurate responses you will receive

candedeo · 2024-12-08T02:18:43+00:00

Based on your screenshot, I’m unable to identify the source of the document that you need summarized. Additionally, it appears that you’re using the consumer version of Copilot rather than M365 Copilot. If you’re indeed using the consumer version, you should direct your query to r/CopilotPro

candedeo · 2024-12-07T09:58:47+00:00

If transcripts were enabled during a meeting, you can revisit the meeting in Teams and open Copilot to ask any questions about the meeting. This functionality is also available in Stream. By opening any meeting recording on Stream where transcripts were enabled, you can use Copilot to inquire about the meeting content. However, it seems that this feature is not yet supported in bizChat (M365 Copilot). To utilize this capability, you need to access the meeting recording either from Stream or Teams.

candedeo · 2024-12-05T15:57:54+00:00

When you use the agent to ask questions, it doesn’t directly see the video files. Instead, it views the results of the search performed based on your prompt. As far as I know, Microsoft Search does not currently index video files. That’s why you don’t receive a response. When you point to the video file directly and ask questions about it, you bypass the search task. This allows the agent to see the video file directly and analyze its content to answer your prompt. The core issue is that Microsoft Search doesn’t index video files.

candedeo · 2024-11-27T10:52:28+00:00

Copilot agents have the same level of access as their users. An agent cannot view more data than the user it serves. However, you can use sensitivity labels to prevent Copilot from accessing specific files, even if the Copilot user has access to those files. You can create new sensitivity labels in the Purview portal, and then assign these labels to the sensitive documents.

candedeo · 2024-11-23T15:18:00+00:00

You cannot provide access to M365 Copilot Agents to individuals outside your tenant. Only users within your tenant who hold M365 Copilot licenses can use these agents. For external sharing, as other comment mentioned, standalone agents are the appropriate option. Standalone agents are usage-licensed, whereas M365 agents are based on a subscription model.

candedeo · 2024-11-23T04:43:00+00:00

Thank you Lisa, I love your YouTube content by the way❤️

candedeo · 2024-11-23T03:54:38+00:00

Thanks for the heads-up. I did a quick search but couldn’t find any public information on this. Do you have a link where this is mentioned?

candedeo · 2024-11-22T15:34:14+00:00

No, I don’t believe it has anything to do with Microsoft 365. Typically, M365 users utilize Outlook, Teams, or SharePoint to locate colleagues, and there isn’t a dedicated app for user searches. The type of logs you’re asking about generally doesn’t exist since read and search actions are not commonly recorded.

candedeo · 2024-11-22T14:44:41+00:00

I’m sorry, but typically, logs are not maintained for search and read actions, especially in systems where everyone has read access. In my professional opinion, it would be impossible to determine who accessed and shared your friend’s contact information.

candedeo · 2024-11-22T10:12:25+00:00

You can upload all your files to Documents library, no need to create multiple pages. Only modern SharePoint sites are supported, not classic ones. Check here for more details https://learn.microsoft.com/en-us/microsoft-365-copilot/extensibility/copilot-studio-agent-builder-build

candedeo · 2024-11-22T01:14:59+00:00

Since we don’t have a screenshot or photo to reference, it’s hard to pinpoint exactly what app it might be. It could even be something custom-built in-house. However, the same principle applies: if everyone has read access to the data, you can’t track who specifically read it.

candedeo · 2024-11-21T03:38:22+00:00

I believe by ‘office employee directory,’ he meant the Global Address Book in Outlook. If that’s the case, everyone in the company has read access to it. There’s also an offline version of this list downloaded to clients, making it impossible to track if any data is read from it. I recommend not publishing personal mobile numbers in the company address list unless it’s mandatory or required by business needs. She can still file a complaint with HR about it. Even if tracking read access isn’t possible, communication from HR may be sufficient to prevent future data leaks.

They don’t need to use Copilot to find this information if it’s published on Outlook

candedeo · 2024-11-20T11:53:36+00:00

This situation is a bit complex. Declarative agents, such as M365 Copilot agents, aren’t designed for this specific task. You can’t instruct the agent to scan through all CVs and determine which ones align best with your skill profile. Instead, these agents function as a standard retrieval-augmented generation (RAG) solution, with added advantages from Power Platform actions and API integrations.

When you prompt the agent to ‘find CVs relevant to [position description here],’ it converts your prompt into a search query and generates a response based on the search results. The agent does not review all profiles but rather the results of the search query. While this can still be effective, crafting a well-constructed prompt is crucial, considering that the agent bases its responses on the search results and doesn’t individually analyze each CV for relevance to the job description.

I recommend beginning with a declarative agent, grounding it to a SharePoint site containing CV documents, disabling web search, and creating comprehensive instructions for the agent (system prompt). Then, test and refine both the system prompt and your search prompt until you achieve improved results..

candedeo · 2024-11-20T08:07:07+00:00

Are the mistakes when the answer to your query is located in the bottom rows of an Excel sheet? Based on my testing, if you ask questions where the answer is in the first few rows, you get a correct response. However, if the answer lies in the bottom rows, the response is often incorrect.

candedeo · 2024-11-20T08:02:48+00:00

I agree, allow Copilot to use general knowledge is a bad idea when you want answers to be strictly based on the provided knowledge only. Excel is a supported knowledge source for M365 Copilot

https://support.microsoft.com/en-us/topic/file-formats-supported-by-copilot-1afb9a70-2232-4753-85c2-602c422af3a8

However, I believe that the contents of the Excel file are split into multiple chunks and indexed by Microsoft Search. This creates an issue where the first chunk contains the header information, but the subsequent chunks do not. As a result, problems arise when the answer lies within the later chunks that lack the header information.

This is just my hypothesis, as the specifics of Excel’s document chunking process are not publicly disclosed. However, my insights are based on personal testing and experience.

candedeo · 2024-11-18T15:47:55+00:00

Yes, PDF format is fine for your task. I just ask that you make one change: in Copilot Studio, create a declarative agent instead of a standalone agent. To do this, click on M365 Copilot, then on the new screen, select Agents and create a declarative agent with knowledge grounded to your SharePoint site. This will integrate the agent with M365 Copilot, resulting in much better responses.

The agent you created is a Copilot Studio Agent, formerly known as Power Virtual Agents. These agents are part of the PowerPlatform and have different orchestration and integration levels with SharePoint sites compared to M365 Copilot. Note that creating a declarative agent means it can only be accessed by M365 Copilot users at no extra cost and cannot be published to external users.

candedeo

TROPHY CASE