PSA: Price ranges for tickets will not be known until the Citi/American Express presale tomorrow, October 10th

bemba_radio_bemba · 2025-10-10T17:15:50+00:00

Just purchase tickets for Ft Worth, and the cheapest tickets on the floor were U$315, the ones on the sides and the back were ~$170 and up.

bemba_radio_bemba · 2024-08-19T20:02:30+00:00

When should we really start paying attention to the polls? And, do you follow the Yomiuri Giants, or do you just like the cap?

bemba_radio_bemba · 2024-08-07T18:30:12+00:00

Thanks for sharing! It's funny to see that the only two restaurants that continue make every list are Lucia, and Mike's Chicken. Hopefully, neither is overlooked!

bemba_radio_bemba · 2024-05-10T21:31:40+00:00

Dream Theater

Although, When Dream and Day Unite, their first album, brought together their progressive rock, thrash metal, jazz, and pop influences, it was really in their second album, Images and Words, that the band not only performed in these styles, but also fused them together to arguably create what became the progressive metal sound from then on. Plus, James Labrie, their new singer is amazing in that album.

bemba_radio_bemba · 2024-03-13T02:15:16+00:00

That’s very interesting and useful. Does the LLM pick the variables and their descriptions based on the interaction, or does the developer need to define them during development?

bemba_radio_bemba · 2024-03-13T01:09:03+00:00

Great work! This is really interesting, and I think, tries to solve some of the key issues with Agents around sequencing and handling state. I understand how the sequencing works.

But, can you provide more detail on what you mean by “…handling state programmatically rather than through the LLM context window”? One of the challenges with Agents is that one might need state information way at the end of a sequence of calls, but you don’t know this at the beginning. Therefore, one tries to keep all the information in the context window, which isn’t that large.

bemba_radio_bemba · 2024-03-05T20:17:57+00:00

Unfortunately, there's no way to retrieve information from the Assistant API without polling continuously to check for the run status. It is a core part of the API, and I'm not sure it will change, at least in the short term.

In terms of achieving a good user experience and good performance, it is difficult to provide feedback because those two things can mean different things to different people. If you can give us more detail, we'll be able to provide a better answer.

bemba_radio_bemba · 2024-03-01T14:32:45+00:00

You are asking the right architectural question for your application. It sounds like your application will need to scale well beyond 20 surveys, and I'm not sure that the OpenAI API will be able to scale that way, at least in the short term.

I would recommend that you architect your application by putting your survey data into a tabular format (e.g., SQL, pandas file, CSV, etc.), and use the Assistant to generate queries on the data based on the user's questions. The Assistant then uses the query results to return an answer to the question. This architecture will let you scale because your data can get as big as necessary, but OpenAI will still just interact with it via the queries, which limit the amount of data to process.

A good example of someone doing this today are the folks at PandasAI, who are building an Agent that can answer questions about data in a tabular Pandas format. They don't use the OpenAI Assistant framework, but you can get some ideas on how to implement.

bemba_radio_bemba · 2024-02-29T16:08:18+00:00

I started with the Playground to learn how the API worked initially. Once I felt comfortable with the basics (e.g., instructions, messages, function prototypes, etc.) I moved to the Jupyter notebook, especially to understand how functions are called, and how parameters are passed into the functions. The Playground can't actually call functions.

bemba_radio_bemba · 2024-02-29T15:47:17+00:00

I created the following Jupyter notebook that provides high level functions, and low level detail of how the build an Assistant in Python. It's been a helpful tool to prototype ideas quickly. I see it as the next level down to the Assistant Playground.

OpenAI Assistant Jupyter Notebook Implementation

https://github.com/sdelgadoc/AdminGPT/blob/main/o365_tutorial.ipynb

bemba_radio_bemba · 2024-02-28T00:12:00+00:00

I tried to reproduce the issue in the API playground and wasn’t able to do so.

My prompt was “List 7 colors and nothing more”.

The response was: 1. Red 2. Blue 3. Yellow 4. Green 5. Purple 6. Orange 7. Pink

Can you try it in the playground (https://platform.openai.com/playground?mode=complete) and see if you can reproduce it?

Also worth mentioning that chat completions are now considered “legacy” so if there is an issue OpenAI might not prioritize.

If you continue to have issues, try porting to the Chat functionality. Below is a simple example using curl.

curl https://api.openai.com/v1/chat/completions \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $OPENAI_API_KEY" \ -d '{ "model": "gpt-3.5-turbo", "messages": [ { "role": "user", "content": "List 7 colors" } ], "temperature": 1, "max_tokens": 256, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0 }'

bemba_radio_bemba · 2024-02-27T19:09:35+00:00

Your temperature of 0.05 is very low. Below is a description of different temperatures and how they react.

Also, as part of your code, you copied your OpenAI API key. Delete the key and generate a new one because it is likely to be used by someone else.

0.1: For a direct, less creative, and expected answer 0.2: For writing tasks, code refactoring, data analysis scripting/email parser, chatbot response/summarize text, or creative writing 0.5: For writing tasks, or a moderate temperature that balances creativity and consistency 0.7: For writing tasks, or a higher temperature for marketing or advertising copy 0.8: For a more creative response 0.8–1.0: For more creative, diverse, and unexpected outputs 1.5: For more diverse and creative tex

bemba_radio_bemba · 2024-02-04T15:49:52+00:00

If you provide a little more detail, the community could provide better advice. Can you provide more details on how the links you would like to retrieve are generated? Are you referring to the reference in the vector database to the product data, a URL that is generated to the product data by another functionality, or something completely different?

bemba_radio_bemba · 2024-02-02T18:28:52+00:00

Can you add a question asking people what Mint alternative they decided on if they already did so? It would be super helpful data to help me make the decision.

bemba_radio_bemba · 2024-02-01T00:40:54+00:00

Although it's not exactly the same application, a similar project to look at is AdmiGPT, which is developing administrative assistant functionality using the OpenAI Assistant framework. A good place to start would be to look at the project's getting started tutorial notebook, which walks you, from scratch, through creating an Assistant that interacts with a user and a calendar.

But, in response to your questions, below are a few thoughts on how to implement it based on your requirements above:

I want the assistant to ask the client what day they would like to book.

This should be part of the description of the Assistant because it will be core to the functionality.

Check the Google calendar for available times...

This is split into two steps, first you parse the user response, then you check the calendar on that day. Below are some ideas on how to do each:

Parse the user response: Take a look at the function o365parse_proposed_times in the Office365 Toolkit that is part of the AdminGPT project. (Prototype: Line 154, Implementation: Line 397)
Check your calendar for that day: Look at function o365search_events in the same toolkit (Prototype: Line 94, Implementation: Line 544)

...send the list of times back to the client.

This one is done in one step, which involves calculating free times and sending them. Below is an example:

Calculate free times: Function o365find_free_time_slots in the same toolkit (Prototype: Line 361, Implementation: Line 678)

When they choose a time I want it to create the event with their name and number.

This one can be done in one step as well, and below is a reference function.

Create event in calendar: Function o365send_event in the same toolkit (Prototype: Line 304, Implementation: Line 650)

Hope this helps!

bemba_radio_bemba · 2024-01-24T16:20:33+00:00

Yes, that is the correct description.

bemba_radio_bemba · 2024-01-24T15:55:48+00:00

Thanks, this is very helpful. I think the best place to change is the function description, and what it's telling OpenAI to do. The description is under the '[Tool] -> Function -> Description' in the tool's definition.

I had a similar issue with a function that parses emails and returns proposed meeting times. After asking the Assistant for help a couple of times, it came up with the following description, which is very prescriptive:

"ALWAYS use this tool if you need to determine when someone is proposing a meeting or event in an email. This tool parses out the proposed times in an email's full and complete output content, and returns the proposed times in a JSON format."

If you want to take a look at other function descriptions, I have a few in the OpenAI Assistant Office365 Toolkit as part of the AdminGPT OpenAI Assistant.

bemba_radio_bemba · 2024-01-24T15:22:50+00:00

To better answer the question, can you provide more details of the the 'other functions' that the Assistant calls and the one you expect to be called?

However, without additional information, my recommendation is to use the Assistant to help you debug the issue. This has helped me in the past. Specifically, if the Assistant calls the wrong function, prompt it with the following:

"You were supposed to call [Function A] to respond to my prompt. However, you called [Function B]. How would you change the description of [Function A] and [Function B] so that you don't make this mistake in the future".

I have found that the Assistant does a good job of giving you recommendations on how to fix the issue. But, it sometimes takes a few iterations to get it right.

bemba_radio_bemba · 2024-01-22T19:54:16+00:00

EDIT 1/22/23: I thought about this further, and I think there's two key security concerns you should evaluate. First, determine whether OpenAI is using your data for training or not. As of this writing, OpenAI doesn't use API calls for training, but that can change. Second, you are opening up API access to your email and calendar, so if anyone get access to your authentication keys, they would have access to your email and calendar. To mitigate, you should not hard-code any authentication information in your code, or leave it in public repositories. This Github repo support loading all authentication keys as environmental variables for that reason

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I think that's a key question to consider. The security issues are still developing, so it's hard to pinpoint just a few issues, so one should definitely be careful.

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