> For the complete documentation index, see [llms.txt](https://ultrasafe.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ultrasafe.gitbook.io/docs/workspaces.md). # Workspaces On The Platform, a workspace encompasses a set of accounts with defined permissions and roles. Creating a workspace for your team provides the ability to: 1. **Administer access controls and manage associated costs** 2. **Facilitate the sharing of fine-tuned models among team members** ### Important Creating an API key within your organization’s workspace and using it to develop a fine-tuned model grants access to this model for all team members with the appropriate permissions. This approach ensures that the model is readily available and usable by authorized users across your team. ### Set up a workspace. Upon first joining The Platform, you have the option to either create a new workspace or join an existing one. To establish a new workspace, click on “Create workspace” and follow the setup instructions.

If you are already logged into The Platform, you can create or join a workspace by clicking on your name in the bottom left corner and then selecting “Create or join workspace.

Whether for personal use or your organization, you can set up a workspace.

### Switch Workspaces You can toggle between your personal workspace and your organization’s workspace.

### Add Members to Your Organization To invite members, go to “Workspace - Members” and select “Invite a new member.”

### Prompting Capabilities Creating prompts will be the first step on your journey to using Ultrasafe AI models. It is crucial to create well-crafted prompts to ensure optimal responses from Ultrasafe models. You will learn how to prompt using four different methods in this guide: * Classification * Summarization * Personalization * Evaluation ### Classification[](https://docs.mistral.ai/guides/prompting_capabilities/#classification) Ultrasafe AI models can easily categorize text into distinct classes. Imagine a virtual assistant for an e-commerce platform: we can set up predefined categories within the prompt and then guide Ultrasafe AI models to classify the customer’s inquiry into the correct category. In the following example, when presented with the customer inquiry, Ultrasafe AI models correctly categorizes it as "country support": | User | I am inquiring about the availability of your cards in the EU, as I am a resident of France and am interested in using your cards. | | --------- | ---------------------------------------------------------------------------------------------------------------------------------- | | Assistant | country support | Prompt (Arrow dropdown) : |

You are a bank customer service bot. Your task is to assess customer intent and categorize customer inquiry after <<<>>> into one of the following predefined categories:

card arrival

change pin

exchange rate

country support

cancel transfer

charge dispute

If the text doesn't fit into any of the above categories, classify it as:

customer service

You will only respond with the category. Do not include the word "Category". Do not provide explanations or notes.

####

Here are some examples:

Inquiry: How do I know if I will get my card, or if it is lost? I am concerned about the delivery process and would like to ensure that I will receive my card as expected. Could you please provide information about the tracking process for my card, or confirm if there are any indicators to identify if the card has been lost during delivery?

Category: card arrival

Inquiry: I am planning an international trip to Paris and would like to inquire about the current exchange rates for Euros as well as any associated fees for foreign transactions.

Category: exchange rate

Inquiry: What countries are getting support? I will be traveling and living abroad for an extended period of time, specifically in France and Germany, and would appreciate any information regarding compatibility and functionality in these regions.

Category: country support

Inquiry: Can I get help starting my computer? I am having difficulty starting my computer,and would appreciate your expertise in helping me troubleshoot the issue.

Category: customer service

###

<<<

Inquiry: {insert inquiry text here}

>>>

| | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | #### **Strategies we used** * Few-shot learning: This method involves giving a few examples in the prompts, and the LLM can produce corresponding outputs based on the examples. few-shot learning improves model performance, especially when the task is difficult or we wish to have the model respond in a particular way. * Delimiter: Different sections of the text are separated by delimiters like ###, <<< >>>. Our example used ### for examples and <<<>>> for customer inquiries. * Role playing: When the LLM receives a role (e.g., "You are an e-commerce customer service bot"), it provides personal context and often enhances performance. ### Summarization[](https://docs.mistral.ai/guides/prompting_capabilities/#summarization) The ability of LLMs to understand and generate natural language means that summarizing is a common task for them. As an example, here is a prompt for generating interesting questions and summarizing an essay. Prompt (Arrow dropdown) : |

You are a commentator. Your task is to write a report on an essay.

When presented with the essay, come up with interesting questions to ask, and answer each question.

Afterward, combine all the information and write a report in the markdown format.

# Essay:

{essay}

# Instructions:

## Summarize:

In clear and concise language, summarize the key points and themes presented in the essay.

## Interesting Questions:

Generate three distinct and thought-provoking questions that can be asked about the content of the essay. For each question:

- After "Q: ", describe the problem

- After "A: ", provide a detailed explanation of the problem addressed in the question.

- Enclose the ultimate answer in <>.

## Write a report

Using the essay summary and the answers to the interesting questions, create a comprehensive report in Markdown format.

| | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | #### **Strategies we used:**[****](https://docs.mistral.ai/guides/prompting_capabilities/#strategies-we-used-1) * Step-by-step instructions: As a result of using chain-of-thought prompting, LLMs are able to approach complex problems by using intermediate reasoning steps. By breaking complex problems down into simpler and smaller steps, it is often easier for us to solve them as well as debug and inspect the behavior of our models. The task is broken down into three steps: summarize, generate interesting questions, and write the report. By doing so, the language is able to think through each step of the report and generate a comprehensive report at the end. * Example generation: The LLMs can generate examples with explanations and steps that automatically guide reasoning and understanding. To illustrate this point, we ask the LLM to come up with three questions and to provide detailed explanations for each of them. * Output formatting: If we wish to request that LLM output in a particular format, we can specifically request "write a report in the Markdown format". ### Personalization[](https://docs.mistral.ai/guides/prompting_capabilities/#personalization) LLMS can provide content tailored to individual users, which makes them excellent at personalization tasks. Our example illustrates how personalized email responses can be created to address questions from customers. | User |

Dear mortgage lender,

What's your 30-year fixed-rate APR, how is it compared to the 15-year fixed rate?

Regards,

Anna

| | --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Assistant |

Dear Anna,

Thank you for your inquiry regarding our fixed-rate mortgage options. Our current 30-year fixed-rate interest rate is 6.403% with an Annual Percentage Rate (APR) of 6.484%. In comparison, our 15-year fixed-rate interest rate is 5.705% with an APR of 5.848%.

As you can see, the 15-year fixed-rate option has a lower interest rate and APR compared to the 30-year fixed-rate option. This means that you would pay less in interest over the life of the loan if you choose the 15-year option. However, the monthly payments would be higher due to the shorter loan term.

Please let us know if you have any other questions or if we can assist you further in choosing the best mortgage option for your needs.

Best regards,
Lender Customer Support

| Prompt (Arrow dropdown) : |

You are a mortgage lender customer service bot, and your task is to create personalized email responses to address customer questions. Answer the customer's inquiry using the provided facts below. Ensure that your response is clear, concise, and directly addresses the customer's question. Address the customer in a friendly and professional manner. Sign the email with "Lender Customer Support."

# Facts

30-year fixed-rate: interest rate 6.403%, APR 6.484%

20-year fixed-rate: interest rate 6.329%, APR 6.429%

15-year fixed-rate: interest rate 5.705%, APR 5.848%

10-year fixed-rate: interest rate 5.500%, APR 5.720%

7-year ARM: interest rate 7.011%, APR 7.660%

5-year ARM: interest rate 6.880%, APR 7.754%

3-year ARM: interest rate 6.125%, APR 7.204%

30-year fixed-rate FHA: interest rate 5.527%, APR 6.316%

30-year fixed-rate VA: interest rate 5.684%, APR 6.062%

# Email

{insert customer email here}


Assistant	{ "Summaries": [ { "Summary": "The author discusses their early experiences with programming and writing, starting with writing short stories and programming on an IBM 1401 in 9th grade. They then moved on to working with microcomputers, building their own from a Heathkit, and eventually convincing their father to buy a TRS-80 in 1980. They wrote simple games, a program to predict rocket flight trajectories, and a word processor.", "Confidence": 0.9 }, { "Summary": "The author began college as a philosophy major, but found it to be unfulfilling and switched to AI. They were inspired by a novel and a PBS documentary, as well as the potential for AI to create intelligent machines like those in the novel. Despite this excitement, they eventually realized that the traditional approach to AI was flawed and shifted their focus to Lisp.", "Confidence": 0.85 }, { "Summary": "The author briefly worked at Interleaf, where they found that their Lisp skills were highly valued. They eventually left Interleaf to return to RISD, but continued to work as a freelance Lisp hacker. While at RISD, they started painting still lives in their bedroom at night, which led to them applying to art schools and eventually attending the Accademia di Belli Arti in Florence.", "Confidence": 0.9 } ] }

Assistant

{

"Summaries": [

{

"Summary": "The author discusses their early experiences with programming and writing, starting with writing short stories and programming on an IBM 1401 in 9th grade. They then moved on to working with microcomputers, building their own from a Heathkit, and eventually convincing their father to buy a TRS-80 in 1980. They wrote simple games, a program to predict rocket flight trajectories, and a word processor.",

"Confidence": 0.9

{

"Summary": "The author began college as a philosophy major, but found it to be unfulfilling and switched to AI. They were inspired by a novel and a PBS documentary, as well as the potential for AI to create intelligent machines like those in the novel. Despite this excitement, they eventually realized that the traditional approach to AI was flawed and shifted their focus to Lisp.",

"Confidence": 0.85

{

"Summary": "The author briefly worked at Interleaf, where they found that their Lisp skills were highly valued. They eventually left Interleaf to return to RISD, but continued to work as a freelance Lisp hacker. While at RISD, they started painting still lives in their bedroom at night, which led to them applying to art schools and eventually attending the Accademia di Belli Arti in Florence.",

"Confidence": 0.9

}

]

}

Prompt (Arrow dropdown) : |

You are a summarization system that can provide summaries with associated confidence scores.

In clear and concise language, provide three short summaries of the following essay, along with their confidence scores.

You will only respond with a JSON object with the key Summary and Confidence. Do not provide explanations.

# Essay:

{insert essay text here}


Assistant	Summary 1: The essay discusses the author's experiences with writing and programming before college, his initial struggles with learning Fortran on an IBM 1401, and the shift towards microcomputers that led to his interest in AI. He also touches on his decision to pursue a degree in AI and the disillusionment he felt when he realized that AI as practiced at the time was a hoax. Summary 2: The author tells the story of his journey into programming, starting with writing short stories before discovering the world of computers. He describes his early experiences with an IBM 1401 and how it was like a mini Bond villain's lair. He also talks about his fascination with microcomputers and how it led him to learn Lisp and become interested in AI. However, he eventually became disillusioned with AI and decided to focus on Lisp instead. Summary 3: The essay recounts the author's experiences with writing and programming before college, including his early attempts at writing short stories and his struggles with learning to program on an IBM 1401. He discusses how the arrival of microcomputers changed everything and sparked his interest in AI. However, he eventually realized that AI, as practiced at the time, was a hoax, and he turned his attention to Lisp. He also touches on his decision to pursue a degree in AI despite his disillusionment with the field. Evaluation: I believe that Summary 1 is the best summary because it provides a clear and concise overview of the author's experiences with writing and programming before college, the shift towards microcomputers, and his eventual disillusionment with AI. It covers the key points of the essay without getting bogged down in unnecessary details. Summary 2 is also good, but it focuses more on the author's early experiences with computers and less on his later experiences with AI. Summary 3 is the weakest summary because it does not capture the full scope of the author's experiences and does not mention his decision to pursue a degree in AI despite his disillusionment with the field.

Assistant

Summary 1: The essay discusses the author's experiences with writing and programming before college, his initial struggles with learning Fortran on an IBM 1401, and the shift towards microcomputers that led to his interest in AI. He also touches on his decision to pursue a degree in AI and the disillusionment he felt when he realized that AI as practiced at the time was a hoax.

Summary 2: The author tells the story of his journey into programming, starting with writing short stories before discovering the world of computers. He describes his early experiences with an IBM 1401 and how it was like a mini Bond villain's lair. He also talks about his fascination with microcomputers and how it led him to learn Lisp and become interested in AI. However, he eventually became disillusioned with AI and decided to focus on Lisp instead.

Summary 3: The essay recounts the author's experiences with writing and programming before college, including his early attempts at writing short stories and his struggles with learning to program on an IBM 1401. He discusses how the arrival of microcomputers changed everything and sparked his interest in AI. However, he eventually realized that AI, as practiced at the time, was a hoax, and he turned his attention to Lisp. He also touches on his decision to pursue a degree in AI despite his disillusionment with the field.

Evaluation: I believe that Summary 1 is the best summary because it provides a clear and concise overview of the author's experiences with writing and programming before college, the shift towards microcomputers, and his eventual disillusionment with AI. It covers the key points of the essay without getting bogged down in unnecessary details. Summary 2 is also good, but it focuses more on the author's early experiences with computers and less on his later experiences with AI. Summary 3 is the weakest summary because it does not capture the full scope of the author's experiences and does not mention his decision to pursue a degree in AI despite his disillusionment with the field.

Prompt (Arrow dropdown) : |

You are given an essay text and need to provide summaries and evaluate them.

# Essay:

{insert essay text here}

Step 1: In this step, provide three short summaries of the given essay. Each summary should be clear, concise, and capture the key points of the speech. Aim for around 2-3 sentences for each summary.

Step 2: Evaluate the three summaries from Step 1 and rate which one you believe is the best. Explain your choice by pointing out specific reasons such as clarity, completeness, and relevance to the speech content.


Assistant	Summary 1: The author writes about their experiences with programming and writing before college. They started programming using Fortran on an IBM 1401 and wrote short stories. They later got into AI, but became disillusioned with it while in graduate school. The author then turned their focus to Lisp, eventually writing a book about it called "On Lisp". They also tried pursuing art, but found it difficult to make a living from it. Summary 2: The author describes their experiences with programming in college and later in the workforce. They learned Lisp while in college, which expanded their concept of what a program could do. After graduation, the author worked at Interleaf, a company that made document creation software. They also did some consulting and writing on the side, eventually writing a book called "On Lisp". The author enjoyed working at Interleaf, but found that the Lisp they used was just a thin layer on top of a larger C cake. Summary 3: The author tells the story of their early experiences with programming and writing. They started writing short stories before college, but they were not very good. The first programs they wrote were on an IBM 1401 using Fortran. In college, they got into AI, but found it disappointing. The author then turned their focus to Lisp, which they found to be more interesting. They also tried pursuing art, but found it difficult to make a living from it. The author eventually wrote a book called "On Lisp" and worked at Interleaf, a company that made document creation software. They enjoyed their time at Interleaf, but found that the Lisp they used was just a thin layer on top of a larger C cake.

Assistant

Summary 1: The author writes about their experiences with programming and writing before college. They started programming using Fortran on an IBM 1401 and wrote short stories. They later got into AI, but became disillusioned with it while in graduate school. The author then turned their focus to Lisp, eventually writing a book about it called "On Lisp". They also tried pursuing art, but found it difficult to make a living from it.

Summary 2: The author describes their experiences with programming in college and later in the workforce. They learned Lisp while in college, which expanded their concept of what a program could do. After graduation, the author worked at Interleaf, a company that made document creation software. They also did some consulting and writing on the side, eventually writing a book called "On Lisp". The author enjoyed working at Interleaf, but found that the Lisp they used was just a thin layer on top of a larger C cake.

Summary 3: The author tells the story of their early experiences with programming and writing. They started writing short stories before college, but they were not very good. The first programs they wrote were on an IBM 1401 using Fortran. In college, they got into AI, but found it disappointing. The author then turned their focus to Lisp, which they found to be more interesting. They also tried pursuing art, but found it difficult to make a living from it. The author eventually wrote a book called "On Lisp" and worked at Interleaf, a company that made document creation software. They enjoyed their time at Interleaf, but found that the Lisp they used was just a thin layer on top of a larger C cake.

Prompt (Arrow dropdown) : |

Provide three short summaries of the given essay. Each summary should be clear, concise, and capture the key points of the essay.

Aim for around 2-3 sentences for each summary.

# essay:

{insert essay text here}


Assistant	Summary 3 provides the most complete and accurate summary of the essay. It covers the author's experiences with writing and programming before college, their disappointment with AI in college, and their eventual focus on Lisp and work at Interleaf. Summary 1 is missing some key details, such as the author's work at Interleaf and their writing of "On Lisp". Summary 2 focuses too much on the author's time at Interleaf and neglects their early experiences with writing and programming before college. Overall, Summary 3 is the best choice as it is the most complete and accurate summary of the essay.

Assistant

Summary 3 provides the most complete and accurate summary of the essay. It covers the author's experiences with writing and programming before college, their disappointment with AI in college, and their eventual focus on Lisp and work at Interleaf. Summary 1 is missing some key details, such as the author's work at Interleaf and their writing of "On Lisp". Summary 2 focuses too much on the author's time at Interleaf and neglects their early experiences with writing and programming before college. Overall, Summary 3 is the best choice as it is the most complete and accurate summary of the essay.

Prompt (Arrow dropdown) : |

You are given an essay and three summaries of the essay. Evaluate the three summaries and rate which one you believe is the best.

Explain your choice by pointing out specific reasons such as clarity, completeness, and relevance to the essay content.

# Essay:

{insert essay text here}

# Summaries

{insert the previous output}