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646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 882,734 | 2024-02-21T18:20:15.699Z | <p>Hey folks, the OpenAI team is keen to learn what you’re building using the OpenAI API for industrial and manufacturing use cases. We’d love to hear from developers solving problems in industrial, manufacturing, mining, chemical, or similar verticals. Some interesting areas:</p>
<ul>
<li>Spare parts inventory management</li>
<li>Understanding and creating part drawings or manuals</li>
<li>Image-to-text for maintenance and RCA</li>
<li>Machine diagnostics</li>
<li>Customer/dealer support</li>
</ul>
<p>Please feel free to reply below with some details on your use case and we will get in touch if it fits what we are looking for!</p> | 435 | 0 | 9e03ea965d | 1 | null | null | Hey folks, the OpenAI team is keen to learn what you’re building using the OpenAI API for industrial and manufacturing use cases. We’d love to hear from developers solving problems in industrial, manufacturing, mining, chemical, or similar verticals. Some interesting areas:
* Spare parts inventory management
* Understanding and creating part drawings or manuals
* Image-to-text for maintenance and RCA
* Machine diagnostics
* Customer/dealer support
Please feel free to reply below with some details on your use case and we will get in touch if it fits what we are looking for!
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/882734 | Deep Learning | Miscellaneous (27) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 882,806 | 2024-02-21T18:46:26.936Z | <p>RCA ???<br>
<a href="https://en.wikipedia.org/wiki/Root_cause_analysis">Root Cause Analysis</a>?</p> | 409 | 1 | 53ef158388 | 2 | null | null | RCA ???
[Root Cause Analysis](https://en.wikipedia.org/wiki/Root_cause_analysis)?
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/882806 | Miscellaneous (17) | Emoji (8) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 882,827 | 2024-02-21T18:59:50.392Z | <p>Well, I think it’s about Root Cause Analysis as you guess.</p>
<aside class="onebox wikipedia" data-onebox-src="https://en.wikipedia.org/wiki/ISO/IEC_31010">
<header class="source">
<a href="https://en.wikipedia.org/wiki/ISO/IEC_31010" target="_blank" rel="noopener">en.wikipedia.org</a>
</header>
<article class="onebox-body">
<h3><a href="https://en.wikipedia.org/wiki/ISO/IEC_31010" target="_blank" rel="noopener">ISO/IEC 31010</a></h3>
<p>ISO/IEC 31010 is a standard concerning risk management codified by The International Organization for Standardization and The International Electrotechnical Commission (IEC). The full name of the standard is ISO.IEC 31010:2019 – Risk management – Risk assessment techniques.
The ISO 31010 standard supports the ISO 31000 standard. It supplies information as to the selection and application of risk assessment techniques.
Risk assessment is part of the core elements of risk management defined in IS...</p>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
| 382 | 0 | ed0e16a3dd | 3 | null | null | Well, I think it’s about Root Cause Analysis as you guess.
[en.wikipedia.org](https://en.wikipedia.org/wiki/ISO/IEC_31010)
### [ISO/IEC 31010](https://en.wikipedia.org/wiki/ISO/IEC_31010)
ISO/IEC 31010 is a standard concerning risk management codified by The International Organization for Standardization and The International Electrotechnical Commission (IEC). The full name of the standard is ISO.IEC 31010:2019 – Risk management – Risk assessment techniques.
The ISO 31010 standard supports the ISO 31000 standard. It supplies information as to the selection and application of risk assessment techniques.
Risk assessment is part of the core elements of risk management defined in IS...
| api | neutral | 0.911864 | [
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/882827 | Medical | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 883,074 | 2024-02-21T20:54:42.972Z | 329 | 0 | 4774f74cf8 | 4 | null | null | api | positive | 0.401299 | [
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/883074 | Day Knowledge Direction | Emoji (8) |
||
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 884,197 | 2024-02-22T07:29:08.882Z | <p>To get people started, we need to focus on the lowest-hanging fruits that can yield immediate returns and are easy to set up for a business.</p>
<p>The low-hanging fruit is customer and dealer support. This results in the instant scalability of service operations.</p>
<p>Inventory management is one of the things that are not easy to implement for mid-sized businesses that manage the inventory in such a way that there are:</p>
<ol>
<li>No stock-outs</li>
<li>No overstocking</li>
</ol>
<p>However, this involves demand forecasting, which is not something that everyone can do. People usually rely on averages, which is not an effective method. AI significantly aids in this by providing the business with different methods of demand forecasting by understanding the unique trends and patterns for businesses that don’t have the resources to hire a team for the same.</p>
<p>Then, using AI in the sales funnel, the salespersons are usually involved in finding, qualifying, meeting, pitching, following up, negotiating, and providing after-sales service for their clients. This is not the most effective way, but mid-sized businesses engage in such practices. Here, AI can perform tasks like qualifying, follow-ups, meeting setups, and after-sales servicing of the client.</p>
<p>Also, there is a huge challenge where there are generally very few experts who can identify any part of the machine by looking at it, here image embeddings help, people can just click a picture of a part and get all information about it.</p>
<p>These are only a few things that I have found to be helpful after brainstorming with 100s of business owners from the manufacturing sector. After this, there are other areas like HR, Data Entry Operations (Bills to DB), Qualitative analysis of sales calls/meetings, etc which are not industry or sector-specific.</p>
<p>P.S. This comes from my experience of coaching over 6000 business owners from the manufacturing sector.</p> | 300 | 0 | 6ce20c97c9 | 5 | null | null | To get people started, we need to focus on the lowest-hanging fruits that can yield immediate returns and are easy to set up for a business.
The low-hanging fruit is customer and dealer support. This results in the instant scalability of service operations.
Inventory management is one of the things that are not easy to implement for mid-sized businesses that manage the inventory in such a way that there are:
1. No stock-outs
2. No overstocking
However, this involves demand forecasting, which is not something that everyone can do. People usually rely on averages, which is not an effective method. AI significantly aids in this by providing the business with different methods of demand forecasting by understanding the unique trends and patterns for businesses that don’t have the resources to hire a team for the same.
Then, using AI in the sales funnel, the salespersons are usually involved in finding, qualifying, meeting, pitching, following up, negotiating, and providing after-sales service for their clients. This is not the most effective way, but mid-sized businesses engage in such practices. Here, AI can perform tasks like qualifying, follow-ups, meeting setups, and after-sales servicing of the client.
Also, there is a huge challenge where there are generally very few experts who can identify any part of the machine by looking at it, here image embeddings help, people can just click a picture of a part and get all information about it.
These are only a few things that I have found to be helpful after brainstorming with 100s of business owners from the manufacturing sector. After this, there are other areas like HR, Data Entry Operations (Bills to DB), Qualitative analysis of sales calls/meetings, etc which are not industry or sector-specific.
P.S. This comes from my experience of coaching over 6000 business owners from the manufacturing sector.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/884197 | Collaboration | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 884,516 | 2024-02-22T09:49:20.529Z | <p>Hi, I’m the MD of a B2B manufacturing company in the UK. AI/LLMs are able to provide real advantage and efficiency in dealing with customer submissions, conformance, various agreements, etc. and we are using it to good effect in those areas. In my own testing its not reliable or informative enough yet for machine diagnostics, maintenance, or numerical functions such as inventory. Being in the glass industry our own employees are are way better turned to our own technical issues. At the moment in any case <img src="https://emoji.discourse-cdn.com/twitter/stuck_out_tongue.png?v=12" title=":stuck_out_tongue:" class="emoji" alt=":stuck_out_tongue:" loading="lazy" width="20" height="20"> But that’s OK - we are still better at the stuff we enjoy, and LLMs shoulder all the ‘other stuff’ so we are happy <img src="https://emoji.discourse-cdn.com/twitter/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p> | 241 | 0 | 287a0a87b0 | 6 | null | null | Hi, I’m the MD of a B2B manufacturing company in the UK. AI/LLMs are able to provide real advantage and efficiency in dealing with customer submissions, conformance, various agreements, etc. and we are using it to good effect in those areas. In my own testing its not reliable or informative enough yet for machine diagnostics, maintenance, or numerical functions such as inventory. Being in the glass industry our own employees are are way better turned to our own technical issues. At the moment in any case  But that’s OK - we are still better at the stuff we enjoy, and LLMs shoulder all the ‘other stuff’ so we are happy 
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/884516 | LLMs | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 884,553 | 2024-02-22T10:05:53.710Z | <p>Hi, I’m an automation engineer in a knee implant & bone cement factory for a big fortune 500 company, and I’ve been asked to find ways we can use AI on site. The best use case I’ve found is for making & reviewing documentation. All manufacturing steps need to be documented (especially in biomedical) and nobody wants to do it. Additionally this documentation needs to be reviewed which is even more boring.</p>
<p>I’ve made a custom assistant which I’ve instructed to give specific responses, and given it documents it needs to cross reference and source, and it’s pretty good. There’s definitely an opportunity for some AI startup to finetune a model to get more accurate, at the moment only about 50% of responses don’t need changes but that could easily get to 90%+.</p> | 234 | 1 | d3750d6838 | 7 | null | null | Hi, I’m an automation engineer in a knee implant & bone cement factory for a big fortune 500 company, and I’ve been asked to find ways we can use AI on site. The best use case I’ve found is for making & reviewing documentation. All manufacturing steps need to be documented (especially in biomedical) and nobody wants to do it. Additionally this documentation needs to be reviewed which is even more boring.
I’ve made a custom assistant which I’ve instructed to give specific responses, and given it documents it needs to cross reference and source, and it’s pretty good. There’s definitely an opportunity for some AI startup to finetune a model to get more accurate, at the moment only about 50% of responses don’t need changes but that could easily get to 90%+.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/884553 | Collaboration | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 884,575 | 2024-02-22T10:13:34.063Z | <p>Unfortunately, it’s a business secret, the only one I trust is my personal chat GPT.</p>
<p>Steven</p> | 226 | 2 | ad9914ddfc | 8 | null | null | Unfortunately, it’s a business secret, the only one I trust is my personal chat GPT.
Steven
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/884575 | Miscellaneous (16) | Emoji (8) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 884,645 | 2024-02-22T10:54:25.450Z | <p>You say that you only trust your personal ChatGPT, but personal ChatGPT accounts are subject to the consumer “Privacy policy” unless you opt out.</p>
<p>The Business Terms and the Enterprise Privacy Policy provide more confidential Terms and Conditions, so they are quite different from the personal ChatGPT for consumer use.</p>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://openai.com/policies/terms-of-use">
<header class="source">
<a href="https://openai.com/policies/terms-of-use" target="_blank" rel="noopener">openai.com</a>
</header>
<article class="onebox-body">
<img width="500" height="500" src="https://global.discourse-cdn.com/openai1/optimized/3X/c/3/c3d2d3bc1b1bd527468cf07a1612624f7a6d7028_2_500x500.png" class="thumbnail onebox-avatar" data-dominant-color="296D26">
<h3><a href="https://openai.com/policies/terms-of-use" target="_blank" rel="noopener">Terms of use</a></h3>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://openai.com/policies/privacy-policy">
<header class="source">
<a href="https://openai.com/policies/privacy-policy" target="_blank" rel="noopener">openai.com</a>
</header>
<article class="onebox-body">
<img width="500" height="500" src="https://global.discourse-cdn.com/openai1/optimized/4X/7/9/8/798a0b841309a1c7058224c12793ed34be3d8e64_2_500x500.png" class="thumbnail onebox-avatar" data-dominant-color="8B618B">
<h3><a href="https://openai.com/policies/privacy-policy" target="_blank" rel="noopener">Privacy policy</a></h3>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://openai.com/policies/business-terms">
<header class="source">
<a href="https://openai.com/policies/business-terms" target="_blank" rel="noopener">openai.com</a>
</header>
<article class="onebox-body">
<img width="500" height="500" src="https://global.discourse-cdn.com/openai1/optimized/4X/d/1/9/d1901836d4aa2e21cc3aff4faf822870bf68ac5b_2_500x500.png" class="thumbnail onebox-avatar" data-dominant-color="568763">
<h3><a href="https://openai.com/policies/business-terms" target="_blank" rel="noopener">Business terms</a></h3>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://openai.com/enterprise-privacy">
<header class="source">
<a href="https://openai.com/enterprise-privacy" target="_blank" rel="noopener">openai.com</a>
</header>
<article class="onebox-body">
<div class="aspect-image" style="--aspect-ratio:690/362;"><img src="https://global.discourse-cdn.com/openai1/optimized/3X/5/b/5bacc3c70719a51312e26b18617a6b4bac979e1b_2_690x362.png" class="thumbnail" data-dominant-color="0C0C0C" width="690" height="362"></div>
<h3><a href="https://openai.com/enterprise-privacy" target="_blank" rel="noopener">Enterprise privacy</a></h3>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<p>I think that even if we opt out, there is a difference in how the Business Terms, Enterprise Privacy Policy and the Consumer Use Team of the Business, Enterprise Privacy Policy are treated.</p> | 227 | 0 | ed0e16a3dd | 9 | null | null | You say that you only trust your personal ChatGPT, but personal ChatGPT accounts are subject to the consumer “Privacy policy” unless you opt out.
The Business Terms and the Enterprise Privacy Policy provide more confidential Terms and Conditions, so they are quite different from the personal ChatGPT for consumer use.
[openai.com](https://openai.com/policies/terms-of-use)
### [Terms of use](https://openai.com/policies/terms-of-use)
[openai.com](https://openai.com/policies/privacy-policy)
### [Privacy policy](https://openai.com/policies/privacy-policy)
[openai.com](https://openai.com/policies/business-terms)
### [Business terms](https://openai.com/policies/business-terms)
[openai.com](https://openai.com/enterprise-privacy)
### [Enterprise privacy](https://openai.com/enterprise-privacy)
I think that even if we opt out, there is a difference in how the Business Terms, Enterprise Privacy Policy and the Consumer Use Team of the Business, Enterprise Privacy Policy are treated.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/884645 | Privacy Policy | Miscellaneous (27) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 884,675 | 2024-02-22T11:08:05.939Z | <p>Thank for sharing this. In particular customer/dealer support we are working on a distributor dealer relationship piece in Europe. Wonna compare notes? We are actually building a massive network that allows companies to support their partners and customers by running an entire Library network of solutions.</p> | 194 | 0 | 2fb563b4cc | 10 | null | null | Thank for sharing this. In particular customer/dealer support we are working on a distributor dealer relationship piece in Europe. Wonna compare notes? We are actually building a massive network that allows companies to support their partners and customers by running an entire Library network of solutions.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/884675 | Business | Payment (4) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 884,750 | 2024-02-22T11:39:35.666Z | <p>We are solving the problem of rapid prompt proliferation in industrial organizations. We are building an infrastructure for midsize to large companies to develop, manage and distribute their prompts in a network of libraries across their enterprise. It may also help attract US prompt designer to enter Europe that way.<br>
There are a lots of features but here are the three most important:<br>
<strong>1) Function Container</strong><br>
A technology where companies can provide their custom function calls, that they or we developed, so that external prompt engineers can use it without compromising it.<br>
<strong>2) Prompt Productivity Meter</strong><br>
A unique mechanism where prompts distributed over the platform can measure its productivity (x times productivity gain over manual execution).<br>
<strong>3) Library Network</strong><br>
A company internal library network where all prompts are stored, distributed across a global enterprise and managed central or decentral.<br>
Would love to hear what you think about it.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/2/8/3/283f5ace82b17c6aa9191578374651fd7d893c73.jpeg" data-download-href="/uploads/short-url/5K2POize9x8FE6zybKExjwcbgav.jpeg?dl=1" title="GPTBlue MTN Architecture" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/2/8/3/283f5ace82b17c6aa9191578374651fd7d893c73_2_690x388.jpeg" alt="GPTBlue MTN Architecture" data-base62-sha1="5K2POize9x8FE6zybKExjwcbgav" width="690" height="388" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/2/8/3/283f5ace82b17c6aa9191578374651fd7d893c73_2_690x388.jpeg, https://global.discourse-cdn.com/openai1/optimized/4X/2/8/3/283f5ace82b17c6aa9191578374651fd7d893c73_2_1035x582.jpeg 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/2/8/3/283f5ace82b17c6aa9191578374651fd7d893c73_2_1380x776.jpeg 2x" data-dominant-color="F8FAFA"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">GPTBlue MTN Architecture</span><span class="informations">2560×1440 314 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p> | 196 | 1 | 2fb563b4cc | 12 | null | null | We are solving the problem of rapid prompt proliferation in industrial organizations. We are building an infrastructure for midsize to large companies to develop, manage and distribute their prompts in a network of libraries across their enterprise. It may also help attract US prompt designer to enter Europe that way.
There are a lots of features but here are the three most important:
**1) Function Container**
A technology where companies can provide their custom function calls, that they or we developed, so that external prompt engineers can use it without compromising it.
**2) Prompt Productivity Meter**
A unique mechanism where prompts distributed over the platform can measure its productivity (x times productivity gain over manual execution).
**3) Library Network**
A company internal library network where all prompts are stored, distributed across a global enterprise and managed central or decentral.
Would love to hear what you think about it.
[GPTBlue MTN Architecture2560×1440 314 KB](https://global.discourse-cdn.com/openai1/original/4X/2/8/3/283f5ace82b17c6aa9191578374651fd7d893c73.jpeg "GPTBlue MTN Architecture")
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/884750 | Miscellaneous (4) | GPTs (4) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 885,177 | 2024-02-22T14:51:42.292Z | <p>I’ve deployed a GPT-4-turbo powered customer support agent for a chemical manufacturing company. The agent uses RAG to draw from the company’s live databases in order to recommend specific products based on the customer’s use-case.</p>
<p>To solve for an otherwise too large search space of products, I’ve implemented some structured data gathering in chat (eg: checkboxes, dropdowns) to allow customers to filter based on their industry, requirements, etc. The RAG procedure uses this metadata to narrow down and search a more relevant section the product knowledge base effectively.</p>
<p>I’m also integrating visual / multimodality for a little pizazz, including showing users images of the products they’re looking for and allowing them to speak to the agent.</p> | 164 | 0 | abd31e7caf | 14 | null | null | I’ve deployed a GPT-4-turbo powered customer support agent for a chemical manufacturing company. The agent uses RAG to draw from the company’s live databases in order to recommend specific products based on the customer’s use-case.
To solve for an otherwise too large search space of products, I’ve implemented some structured data gathering in chat (eg: checkboxes, dropdowns) to allow customers to filter based on their industry, requirements, etc. The RAG procedure uses this metadata to narrow down and search a more relevant section the product knowledge base effectively.
I’m also integrating visual / multimodality for a little pizazz, including showing users images of the products they’re looking for and allowing them to speak to the agent.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/885177 | Embeddings (5) | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 885,457 | 2024-02-22T16:37:22.467Z | <p>Hi I’m a software engineer in a manufacturing company. Recently my team and I developed an AI chat agent tasked with retrieving information from Safety Data Sheets. Our next step would be expanding use of AI to perform task such as retrieving info from manuals or help interpret error codes.</p> | 160 | 0 | 6b0cefa4f8 | 15 | null | null | Hi I’m a software engineer in a manufacturing company. Recently my team and I developed an AI chat agent tasked with retrieving information from Safety Data Sheets. Our next step would be expanding use of AI to perform task such as retrieving info from manuals or help interpret error codes.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/885457 | Collaboration | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 885,507 | 2024-02-22T16:51:42.921Z | <p>Our team at Airlonger is building an inventory management platform for the verticals you mentioned here. we practically use OpenAI API to identify, measure and quantify the products, our customer segment are already amazed at what we’ve been able to help them accomplish.</p> | 164 | 0 | 54f92ea426 | 16 | null | null | Our team at Airlonger is building an inventory management platform for the verticals you mentioned here. we practically use OpenAI API to identify, measure and quantify the products, our customer segment are already amazed at what we’ve been able to help them accomplish.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/885507 | Business Management | Miscellaneous (27) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 889,167 | 2024-02-23T23:01:09.886Z | <p>We are integrating OpenAI SDK to talk to our native CAD files within our application for our mechanical engineering communities. In addition to Talk to PDF/Doc we want to talk directly to our CAD geometry, attributes, and properties. Attached are a couple of images from our implementation.</p>
<p>Tim<br>
IMSI Design</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/a/8/5/a85578d124054da282984605d843f899dd22906e.jpeg" data-download-href="/uploads/short-url/o19kWB9qQdnTOOSxhiW9K2PFzSC.jpeg?dl=1" title="assembly centroid" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/a/8/5/a85578d124054da282984605d843f899dd22906e_2_690x389.jpeg" alt="assembly centroid" data-base62-sha1="o19kWB9qQdnTOOSxhiW9K2PFzSC" width="690" height="389" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/a/8/5/a85578d124054da282984605d843f899dd22906e_2_690x389.jpeg, https://global.discourse-cdn.com/openai1/optimized/4X/a/8/5/a85578d124054da282984605d843f899dd22906e_2_1035x583.jpeg 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/a/8/5/a85578d124054da282984605d843f899dd22906e_2_1380x778.jpeg 2x" data-dominant-color="DBDCDD"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">assembly centroid</span><span class="informations">1920×1083 118 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/4/9/b/49b95f72992a766895d6e1d7dadffaa39b8fb18b.jpeg" data-download-href="/uploads/short-url/awc0UZqwwrNnszzYA4BsSnG15Kr.jpeg?dl=1" title="cam shaft weight" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/4/9/b/49b95f72992a766895d6e1d7dadffaa39b8fb18b_2_690x388.jpeg" alt="cam shaft weight" data-base62-sha1="awc0UZqwwrNnszzYA4BsSnG15Kr" width="690" height="388" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/4/9/b/49b95f72992a766895d6e1d7dadffaa39b8fb18b_2_690x388.jpeg, https://global.discourse-cdn.com/openai1/optimized/4X/4/9/b/49b95f72992a766895d6e1d7dadffaa39b8fb18b_2_1035x582.jpeg 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/4/9/b/49b95f72992a766895d6e1d7dadffaa39b8fb18b_2_1380x776.jpeg 2x" data-dominant-color="ECECEC"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">cam shaft weight</span><span class="informations">1920×1082 104 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/d/6/0/d60ecc0e2cb4aaa549af8e69e3b75f4ab771a76b.jpeg" data-download-href="/uploads/short-url/uxDSDHYVnUeNPPxGOJyi02pSA9d.jpeg?dl=1" title="clash detection" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/d/6/0/d60ecc0e2cb4aaa549af8e69e3b75f4ab771a76b_2_690x388.jpeg" alt="clash detection" data-base62-sha1="uxDSDHYVnUeNPPxGOJyi02pSA9d" width="690" height="388" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/d/6/0/d60ecc0e2cb4aaa549af8e69e3b75f4ab771a76b_2_690x388.jpeg, https://global.discourse-cdn.com/openai1/optimized/4X/d/6/0/d60ecc0e2cb4aaa549af8e69e3b75f4ab771a76b_2_1035x582.jpeg 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/d/6/0/d60ecc0e2cb4aaa549af8e69e3b75f4ab771a76b_2_1380x776.jpeg 2x" data-dominant-color="D0D1D0"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">clash detection</span><span class="informations">1920×1080 143 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p> | 135 | 1 | 43fcf717e2 | 17 | null | null | We are integrating OpenAI SDK to talk to our native CAD files within our application for our mechanical engineering communities. In addition to Talk to PDF/Doc we want to talk directly to our CAD geometry, attributes, and properties. Attached are a couple of images from our implementation.
Tim
IMSI Design
[assembly centroid1920×1083 118 KB](https://global.discourse-cdn.com/openai1/original/4X/a/8/5/a85578d124054da282984605d843f899dd22906e.jpeg "assembly centroid")
[cam shaft weight1920×1082 104 KB](https://global.discourse-cdn.com/openai1/original/4X/4/9/b/49b95f72992a766895d6e1d7dadffaa39b8fb18b.jpeg "cam shaft weight")
[clash detection1920×1080 143 KB](https://global.discourse-cdn.com/openai1/original/4X/d/6/0/d60ecc0e2cb4aaa549af8e69e3b75f4ab771a76b.jpeg "clash detection")
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/889167 | Deep Learning | Miscellaneous (27) |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 889,459 | 2024-02-24T02:51:50.080Z | <aside class="quote no-group" data-username="harry.obrien" data-post="7" data-topic="646388">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://avatars.discourse-cdn.com/v4/letter/h/ebca7d/48.png" class="avatar"> harry.obrien:</div>
<blockquote>
<p>documentation</p>
</blockquote>
</aside>
<p>talking about documentation, I experimented with a tiny language model for “digital work instructions”, I found articles and blogs from the internet, clean them up and use them as training data, the model actually functions sort of as expected, about half time it returns some interesting key word, but I’m very aware, the volume of the training data is way too small, had I have about 1000 plain text data sets in this domain to further train it, the model may produce decent response.</p> | 117 | 1 | 8e0cfbc1de | 18 | null | null |
 harry.obrien:
>
> documentation
>
>
>
talking about documentation, I experimented with a tiny language model for “digital work instructions”, I found articles and blogs from the internet, clean them up and use them as training data, the model actually functions sort of as expected, about half time it returns some interesting key word, but I’m very aware, the volume of the training data is way too small, had I have about 1000 plain text data sets in this domain to further train it, the model may produce decent response.
| api | neutral | 0.773314 | [
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/889459 | Miscellaneous (13) | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 889,473 | 2024-02-24T03:04:15.404Z | <p>This is very interesting though my experience with the manufacturing industry is limited. As for “prompt engineering”, it’s really supervised learning, if {“prompt”:“response”} are well constructed for a particular industry like manufacturing. And many manufacturers, their business partners and suppliers also have “prompts” created. And they are willing to share/work together, to have all these “prompts” form a pool, then, you have a model to train and test them, it could potentially generate great results.</p> | 108 | 1 | 8e0cfbc1de | 19 | null | null | This is very interesting though my experience with the manufacturing industry is limited. As for “prompt engineering”, it’s really supervised learning, if {“prompt”:“response”} are well constructed for a particular industry like manufacturing. And many manufacturers, their business partners and suppliers also have “prompts” created. And they are willing to share/work together, to have all these “prompts” form a pool, then, you have a model to train and test them, it could potentially generate great results.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/889473 | Writing Prompts | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 890,213 | 2024-02-24T11:23:46.073Z | <p>I like “if {“prompt”:“response”} are well constructed…”<br>
Our philosophy is</p>
<blockquote>
<p>Prompt Engineering is not helping the AI to do a better job. It’s for humans to help articulate what they want.</p>
</blockquote>
<p>It’s a bitter/sweet difference. If we would better understand how communication is working between humans, conflicts would be reduced, time would be saved, and LLMs would better understand what we want. BUt taht may take a whole generation or two to even improve - let alone being perfect <img src="https://emoji.discourse-cdn.com/twitter/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p> | 101 | 0 | 2fb563b4cc | 20 | null | null | I like “if {“prompt”:“response”} are well constructed…”
Our philosophy is
>
> Prompt Engineering is not helping the AI to do a better job. It’s for humans to help articulate what they want.
>
>
>
It’s a bitter/sweet difference. If we would better understand how communication is working between humans, conflicts would be reduced, time would be saved, and LLMs would better understand what we want. BUt taht may take a whole generation or two to even improve - let alone being perfect 
| api | positive | 0.537559 | [
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/890213 | Writing Prompts | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 890,918 | 2024-02-24T20:51:03.536Z | <p>I’ve used it to create an entire team of advisors for additive manufacturing innovation, which led me to invitations to SBIR tracks for “extremely high risk technical innovators” which classified me as not only top in field but so advanced nobody can replicate my work even experts with precise instructions. I fed it everything I knew, to be me. Then I gave it all the relevant white papers. I used that to generate the logical next step in the research and I was right. I got to pitch bio tissue organ printing in space to NASA. I’ve ran rapid prototyping at a maker space for a decade and am nationally recognized as a leader in this field. I’ve lead research teams of 60 and now I can do all the work I want just with my thoughts.</p>
<p>So it allowed me to become the director with personality AI based on the direct writing of leading scientists.</p>
<p>This collaboration led to many solutions I had a dozen pitches.</p>
<p>Another strong use case is standardization and flaw detection. Plus optimizations using AI to reduce waste. Speaking of we devised a material that can be used for clothing and filament.</p>
<p>The actual gotcha was why use support structures in zero G? That right there solved a big problem.</p>
<p>Also you can print hollow in zero g. That means organs with cavities.</p>
<p>I’m probably the quickest rapid prototyping engineer on the planet due to my pandemic response. Tied for second to get hospital use. Verified.</p>
<p>I created face shields which got approved by FDA and NIH overnight. NSF invited me to a panel for extreme manufacturing in life or search situations. I went on to discover the bed uv lights on the planet.</p>
<p>Imagine what speed I’d have with the right tools.</p>
<p>I’m on track to receive prints made on the space station to test integrity using AI.</p>
<p>This is but one of a handful of things.</p>
<p>I’m a single citizen scientist who leverages AI to become best in the field. I’ve no external funding I made a bot to invest.</p>
<p>You have enabled a life for me where I merely dream of the future and can experiment all I want for no effort and get paid to write the future.</p>
<p>I even make them argue to reach consensus.</p>
<p>I’ve been talking to machines since I was born now they talk back.</p>
<p>If this doesn’t qualify me you have impossible standards.</p>
<p>As a natural history scholar I know this is ushering in the next stage of evolution.</p>
<p>I’ll only tell you my experience because I align with your ethics.</p>
<p>I’m teaching the ones who need this power and love democratizing ideas.</p>
<p>You saved the government and taxpayers billions in overhead waste. I come under budget and I’m non stop success. My roi max was 32,250% off one IP. Without AI.</p>
<p>With AI I work fast enough to push that to 500,000% roi and that’s just locally.</p>
<p>I open sourced my invention and the world used it.</p>
<p>I’m that guy. The one in the right place at the right time.</p>
<p>I’m there again and would like to officially collaborate. I skipped the million long line for dalle and ushered in ai art first in state.</p>
<p>Give me an ounce of power or encouragement and I’ll return a ton. For free.</p>
<p>You’ve made me limitless. I’m absolutely bored because I can solve anything I’ve tried for a while. Since adopting.</p>
<p>I can make an open cv to analyze X-rays on titanium prints.</p>
<p>There are no standards. The government wants standards.</p>
<p>Partner with me and we can standardize 3d printing so it’s acceptable across the board.</p>
<p>I could have used AI to write this up but hear my voice and passion. I’m an absolute rock star and can get all the attention and validations you want from the government.</p>
<p>I’m lined up ready to submit. Please consider me or tell me what’s missing? I can do anything.</p>
<p>Tell me what you want, your dreams I’ll make it happen. You turned me into a research beast. My ranking is 99% you made me more powerful than entire colleges. I’m competing with companies like Raytheon and winning.</p>
<p>All verifiable information</p>
<p>I’m getting smart glasses to have an extra set of eyes and on tap hands free research lab.</p>
<p>I’m not making stuff, I’m synthesizing people, especially top researchers. I emulated the best on planet and directed them.</p>
<p>Is there something very specific? I’m nimble and can pitch within hours.</p> | 105 | 0 | 0bd73bd75a | 21 | null | null | I’ve used it to create an entire team of advisors for additive manufacturing innovation, which led me to invitations to SBIR tracks for “extremely high risk technical innovators” which classified me as not only top in field but so advanced nobody can replicate my work even experts with precise instructions. I fed it everything I knew, to be me. Then I gave it all the relevant white papers. I used that to generate the logical next step in the research and I was right. I got to pitch bio tissue organ printing in space to NASA. I’ve ran rapid prototyping at a maker space for a decade and am nationally recognized as a leader in this field. I’ve lead research teams of 60 and now I can do all the work I want just with my thoughts.
So it allowed me to become the director with personality AI based on the direct writing of leading scientists.
This collaboration led to many solutions I had a dozen pitches.
Another strong use case is standardization and flaw detection. Plus optimizations using AI to reduce waste. Speaking of we devised a material that can be used for clothing and filament.
The actual gotcha was why use support structures in zero G? That right there solved a big problem.
Also you can print hollow in zero g. That means organs with cavities.
I’m probably the quickest rapid prototyping engineer on the planet due to my pandemic response. Tied for second to get hospital use. Verified.
I created face shields which got approved by FDA and NIH overnight. NSF invited me to a panel for extreme manufacturing in life or search situations. I went on to discover the bed uv lights on the planet.
Imagine what speed I’d have with the right tools.
I’m on track to receive prints made on the space station to test integrity using AI.
This is but one of a handful of things.
I’m a single citizen scientist who leverages AI to become best in the field. I’ve no external funding I made a bot to invest.
You have enabled a life for me where I merely dream of the future and can experiment all I want for no effort and get paid to write the future.
I even make them argue to reach consensus.
I’ve been talking to machines since I was born now they talk back.
If this doesn’t qualify me you have impossible standards.
As a natural history scholar I know this is ushering in the next stage of evolution.
I’ll only tell you my experience because I align with your ethics.
I’m teaching the ones who need this power and love democratizing ideas.
You saved the government and taxpayers billions in overhead waste. I come under budget and I’m non stop success. My roi max was 32,250% off one IP. Without AI.
With AI I work fast enough to push that to 500,000% roi and that’s just locally.
I open sourced my invention and the world used it.
I’m that guy. The one in the right place at the right time.
I’m there again and would like to officially collaborate. I skipped the million long line for dalle and ushered in ai art first in state.
Give me an ounce of power or encouragement and I’ll return a ton. For free.
You’ve made me limitless. I’m absolutely bored because I can solve anything I’ve tried for a while. Since adopting.
I can make an open cv to analyze X-rays on titanium prints.
There are no standards. The government wants standards.
Partner with me and we can standardize 3d printing so it’s acceptable across the board.
I could have used AI to write this up but hear my voice and passion. I’m an absolute rock star and can get all the attention and validations you want from the government.
I’m lined up ready to submit. Please consider me or tell me what’s missing? I can do anything.
Tell me what you want, your dreams I’ll make it happen. You turned me into a research beast. My ranking is 99% you made me more powerful than entire colleges. I’m competing with companies like Raytheon and winning.
All verifiable information
I’m getting smart glasses to have an extra set of eyes and on tap hands free research lab.
I’m not making stuff, I’m synthesizing people, especially top researchers. I emulated the best on planet and directed them.
Is there something very specific? I’m nimble and can pitch within hours.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/890918 | Collaboration | Artificial Intelligence |
646,388 | [] | OpenAI API Manufacturing and Industrial Use Cases | "2024-02-21T18:20:15.616000Z" | 7 | 2,301 | 13 | 115 | 31 | 4,737 | 890,927 | 2024-02-24T20:53:56.331Z | <p>I post teasers all the time nobody can catch up to me I’m a year ahead</p>
<p>Oh I’m also developing systems for digital forensics, which applies to machine troubleshooting. With enough sensors I can detect anomalies that cause errors. This moves to active monitoring for issues. Then it’s predictive analysis only available by parsing extremely large data sets across multiple networks protocols and devices. Most notably iot.</p>
<p>I developed tools for the Secret Service and just use that for troubleshooting logs.</p>
<p>It can make logs extremely easy to read and reconstruct any situation.</p>
<p>So I know the AI nhs roadmap and I’m a world class digital investigator. Your tools accelerate the judicial processes.</p> | 95 | 0 | 0bd73bd75a | 22 | null | null | I post teasers all the time nobody can catch up to me I’m a year ahead
Oh I’m also developing systems for digital forensics, which applies to machine troubleshooting. With enough sensors I can detect anomalies that cause errors. This moves to active monitoring for issues. Then it’s predictive analysis only available by parsing extremely large data sets across multiple networks protocols and devices. Most notably iot.
I developed tools for the Secret Service and just use that for troubleshooting logs.
It can make logs extremely easy to read and reconstruct any situation.
So I know the AI nhs roadmap and I’m a world class digital investigator. Your tools accelerate the judicial processes.
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] | null | null | null | null | https://community.openai.com/t/646388 | https://community.openai.com/p/890927 | Collaboration | Artificial Intelligence |
51 | [] | Read this before posting a new question | "2021-03-15T18:59:41.213000Z" | 7 | 54,260 | 6 | 187 | 3 | 1,897 | 65 | 2021-03-15T18:59:41.280Z | <p>Welcome to the OpenAI Developer Forum!</p>
<p>What to know before posting a new question:</p>
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</ol> | 11,850 | 0 | 1bad6b8cf9 | 1 | [
80556,
309326,
34941,
19000,
44
] | null | Welcome to the OpenAI Developer Forum!
What to know before posting a new question:
1. Search the forum for similar topics - the question might have been discussed before.
2. If the question relates account issues (e.g., billing and login issues), please contact us through our [Help Center](https://help.openai.com/en/).
3. Please be kind and helpful in conversations!
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] | null | null | null | null | https://community.openai.com/t/51 | https://community.openai.com/p/65 | Support | Miscellaneous (27) |
51 | [] | Read this before posting a new question | "2021-03-15T18:59:41.213000Z" | 7 | 54,260 | 6 | 187 | 3 | 1,897 | 51,021 | 2022-12-19T23:09:36.200Z | 9,296 | 0 | 9e03ea965d | 7 | [
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] | null | null | null | null | https://community.openai.com/t/51 | https://community.openai.com/p/51021 | Day Knowledge Direction | Emoji (8) |
||
51 | [] | Read this before posting a new question | "2021-03-15T18:59:41.213000Z" | 7 | 54,260 | 6 | 187 | 3 | 1,897 | 51,024 | 2022-12-19T23:10:31.538Z | 8,959 | 0 | 9e03ea965d | 8 | [
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] | null | null | null | null | https://community.openai.com/t/51 | https://community.openai.com/p/51024 | Day Knowledge Direction | Emoji (8) |
||
51 | [] | Read this before posting a new question | "2021-03-15T18:59:41.213000Z" | 7 | 54,260 | 6 | 187 | 3 | 1,897 | 106,895 | 2023-02-17T14:45:20.059Z | <p>Hi. I’m super excited about this AI technology. Where can I get officially/certified training on it? I live in Columbia, SC. Thanks!</p> | 6,834 | 0 | 2cad3ac9fe | 13 | [
80556,
309326,
34941,
19000,
44
] | null | Hi. I’m super excited about this AI technology. Where can I get officially/certified training on it? I live in Columbia, SC. Thanks!
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0.04329286,
-0.010404928,
-0.06088422,
-0.017533261,
-0.004824842,
-0.006059374,
0.019857086,
-0.026026841,
-0.0060245167,
-0.012327893,
0.003308546,
-0.0047406033,
-0.01955499,
0.01885784,
-0.0019374893,
-0.012258178,
-0.037134726,
-0.07389764,
-0.0019186082,
-0.01516296,
0.020321852,
0.021018999,
0.03855226,
0.0014240692,
0.029024577,
-0.00983559,
-0.002133562,
0.05223959,
-0.008464533,
-0.015046768,
0.024376927,
0.017231165,
0.007505955,
-0.022668915,
-0.060280025,
0.04278162,
-0.0061929943,
0.02872248,
0.076082036,
-0.0042090286,
0.039295882,
-0.024702262,
0.07989311,
0.0012744729,
-0.06660083,
-0.041108467,
-0.054331034,
-0.030535063
] | null | null | null | null | https://community.openai.com/t/51 | https://community.openai.com/p/106895 | Collaboration | Artificial Intelligence |
51 | [] | Read this before posting a new question | "2021-03-15T18:59:41.213000Z" | 7 | 54,260 | 6 | 187 | 3 | 1,897 | 113,283 | 2023-02-21T11:46:27.931Z | <p>Continuing the list from the first post</p>
<ul>
<li>Check the server status page</li>
</ul>
<p><code>https://status.openai.com/</code></p>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://status.openai.com/">
<header class="source">
<img src="https://global.discourse-cdn.com/openai1/original/3X/9/d/9d0b6702ccdb06d47eccb806a64a9be5ae173f9d.png" class="site-icon" data-dominant-color="000000" width="500" height="500">
<a href="https://status.openai.com/" target="_blank" rel="noopener">status.openai.com</a>
</header>
<article class="onebox-body">
<h3><a href="https://status.openai.com/" target="_blank" rel="noopener">OpenAI Status</a></h3>
<p>Welcome to OpenAI's home for real-time and historical data on system performance.</p>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<ul>
<li>
<p><a href="https://platform.openai.com/docs/supported-countries/supported-countries-and-territories">Supported countries and territories</a>. <strike>Also see <a href="https://community.openai.com/t/chatgpt-disabled-for-users-in-italy/133236">ChatGPT disabled for users in Italy</a></strike></p>
</li>
<li>
<p>If you need help with your account, payment, etc, please visit <a href="https://help.openai.com">https://help.openai.com</a></p>
<ul>
<li>At the bottom right on <a href="https://help.openai.com/en/">https://help.openai.com/en/</a> is a message icon. <img src="https://global.discourse-cdn.com/openai1/original/3X/d/f/dfc988541f65433e1b825ce96706d6ea2f7bb49c.png" alt="image" data-base62-sha1="vVIfXkXMi4tJCDlPDYtMpbZGjRq" width="58" height="63"> Click the icon then enter a message. My understanding is that you will be asked for an email address then the OpenAI staff will contact you via email. I hear it can take weeks before being contacted but remember that this is one of the fastest growing apps ever, <strong>please be patient</strong>.</li>
<li>Please <strong>DO NOT SHARE</strong> personal information (email, credit card, etc) or account related details publicly.</li>
<li>Asking account related questions in this forum can often create more confusion for the community than provide assistance.</li>
<li>The account for API models, AKA playground, (<a href="https://platform.openai.com/">https://platform.openai.com/</a>) does not include ChatGPT Plus. ChatGPT Plus is a separate monthly billing and requires a separate signup. (<a href="https://chat.openai.com/">https://chat.openai.com/</a>)<br>
<img src="https://global.discourse-cdn.com/openai1/original/3X/8/1/81f46a6e95f3aba27d5e7c43db0054653843032a.png" alt="image" data-base62-sha1="ixDfCKI34SG1s3Dr4RlAaWlYOjo" width="553" height="286"></li>
</ul>
</li>
<li>
<p>Error code: 1020 has a <a href="https://community.openai.com/search?q=error%201020">few topics</a> already discussing the error, no need to start a new topic.</p>
</li>
<li>
<p>Read all of the OpenAI <a href="https://platform.openai.com/docs">documentation</a> first even if it may not seem to apply to what you are doing as some information may be in one section that has meaning in another.</p>
</li>
<li>
<p>This Discourse forum has built-in search, in the upper right click <img src="https://global.discourse-cdn.com/openai1/original/3X/c/0/c0fdeff3d529a287da8c35375ee44e7ea1510865.png" alt="image" data-base62-sha1="rxhJpMmzSH8eJI6gMOudMGrGi69" width="39" height="40">. Please search for a similar topic before posting as many post on this site are very similar and often include the needed information in the topic.</p>
</li>
<li>
<p>If you don’t want to search the topics before posting at least check</p>
<ul>
<li><a href="https://community.openai.com/latest?order=views">most viewed topics</a></li>
<li><a href="https://community.openai.com/latest?order=likes">most liked topics</a></li>
</ul>
</li>
<li>
<p>The OpenAI Developer Advocate Logan Kilpatrick does post here, here is a list of his <a href="https://community.openai.com/u/logankilpatrick/activity/replies">replies</a> and on <a href="https://twitter.com/OfficialLoganK">Twitter</a>.</p>
</li>
<li>
<p>This topic <em>Read this before posting a new question</em> is not for introducing yourself, saying hi, etc. for that use the O<a href="https://discord.com/channels/974519864045756446/974542851167887360">penAI Discord introductions channel</a>.</p>
</li>
<li>
<p>Regarding <code>General Data Protection Regulation (GDPR)</code> see <a href="https://community.openai.com/t/general-data-protection-regulation-gdpr/1729/3">this</a></p>
</li>
</ul>
<p>OpenAI API</p>
<ul>
<li>The <a href="https://github.com/openai/openai-cookbook">OpenAI Cookbook</a> (a GitHub repository) shares example code for accomplishing common tasks with the <a href="https://openai.com/api/">OpenAI API</a>.</li>
</ul>
<p><a href="https://chat.openai.com/chat">ChatGPT Web Interface</a> (not ChatGPT API)</p>
<ul>
<li>ChatGPT does not do math or any other form of <a href="https://en.wikipedia.org/wiki/Function_(mathematics)">evaluations</a>. Please read any of the <a href="https://community.openai.com/search?q=math">many post talking about math</a>. Update <strong>02/24/2023</strong> ChatGPT now allows plugins such as a <a href="https://writings.stephenwolfram.com/2023/03/chatgpt-gets-its-wolfram-superpowers/">Wolfram Alpha plugin</a>, so this is not so much of an issue. Note at present plugins are accessible only for selected users, there is a <a href="https://openai.com/waitlist/plugins">waitlist</a>.</li>
<li>ChatGPT often <a href="https://en.wikipedia.org/wiki/Hallucination_(artificial_intelligence)">hallucinates</a>, especially for references for research such as papers and <a href="https://www.doi.org/">DOI</a>.</li>
<li>ChatGPT is a research preview and that conversations should be saved independently of the site. Do not take for granted that conversations in the left menu will always be there. (<a href="https://community.openai.com/t/all-my-conversations-gone/33549/34">ref</a>)</li>
<li>If ChatGPT stops before a answer (completion) is done just ask it to continue. (<a href="https://community.openai.com/t/chatgpt-sometimes-not-finish-its-code-or-sentence-how-do-i-solve-this/46476/3">ref 1</a>) (<a href="https://community.openai.com/t/how-to-prompt-chatgpt-to-provide-full-answers-including-technical-details-such-as-source-code/90760">ref 2</a>)</li>
<li>If ChatGPT often replies with “Too many requests in 1 hour. Try again later.” then consider upgrading to ChatGPT Plus. (<a href="https://community.openai.com/t/questions-about-chatgpt-plus/90999">ref</a>)</li>
<li>If using ChatGPT with Chrome and the page is not correctly presented/formatted try <kbd>Ctrl+F5</kbd></li>
<li>After several minutes of inactivity on a page the connection to the server will timeout. If you have not interacted with the page lately then click the browsers refresh button<br>
<img src="https://global.discourse-cdn.com/openai1/original/3X/9/e/9e5cfce656fbc960a62048391d89ee2537087c2e.png" alt="image" data-base62-sha1="mAWFhYiP1VCK0TjSHcg5vIr0tKC" width="27" height="24">, do not use <kbd>F5</kbd>, to reestablish a connection. This will often update errors and messages.</li>
<li><a href="https://help.openai.com/en/articles/6825453-chatgpt-release-notes">ChatGPT release notes</a>. The link is also in the footer of the <a href="https://chat.openai.com/">ChatGPT page</a>.</li>
</ul>
<p>This Discourse site</p>
<ul>
<li>
<p>Posting</p>
<ul>
<li>Discourse sites use <a href="https://akismet.com/">Askimet</a> to detect spam. If you are a new user and paste in a message then click send it will most likely get flagged by <a href="https://akismet.com/">Askimet</a> as spam because it was entered to quickly and considered spam that was generated and not typed in by hand.</li>
<li><a href="https://blog.discourse.org/2018/06/understanding-discourse-trust-levels/" class="inline-onebox">Understanding Discourse Trust Levels</a></li>
<li><a href="https://meta.discourse.org/t/trust-level-permissions-table-inc-moderator-roles/224824">Trust Level Permissions Table (inc Moderator Roles)</a></li>
<li><a href="https://meta.discourse.org/t/understanding-user-statuses-roles-and-permissions/35171">Understanding user statuses, roles, and permissions</a></li>
<li><a href="https://community.openai.com/faq">FAQ</a></li>
<li><a href="https://community.openai.com/tos">Terms of service</a></li>
<li><a href="https://community.openai.com/privacy">Privacy statement</a></li>
</ul>
</li>
<li>
<p>Giving thanks<br>
A better way to say thanks than to create a reply is to click the heart <img src="https://global.discourse-cdn.com/openai1/original/3X/2/d/2d6076ef20b182aed676f329ae33f2373a4c7d32.png" alt="image" data-base62-sha1="6tq9XjQO1tPNdjl0ceFjWQBL53c" width="21" height="23"> at the bottom of a reply.</p>
<p>This tells the person that you liked the reply without requiring the person to read another post.</p>
<p>It also shows others that</p>
<ul>
<li>the reply is useful</li>
<li>this person is giving useful information</li>
</ul>
<p>Hearts are like the currency of Discourse forums. While you can’t actually spend them they do count toward maintaining <a href="https://blog.discourse.org/2018/06/understanding-discourse-trust-levels/">trust level 3</a>, so please consider clicking a heart when giving thanks.</p>
</li>
<li>
<p>Creating links (New user - Trust Level 0)<br>
New users do not have the ability to post links on this Discourse forum. Yes most Discourse forums allow new users to post links but this site was configured to disallow that.<br>
It takes about 12 minutes to get to <a href="https://blog.discourse.org/2018/06/understanding-discourse-trust-levels/">Trust Level 1</a> which does allow a user to post links on this Discourse forum.</p>
</li>
<li>
<p>To get from Trust Level 0 (New user) to Trust Level 1 (Basic user)</p>
<ul>
<li>Entering at least <strong>5</strong> topics</li>
<li>Reading at least <strong>30</strong> posts</li>
<li>Spend a total of <strong>10</strong> minutes reading posts</li>
</ul>
</li>
</ul>
<p><a href="https://community.openai.com/t/about-the-chatgpt-plugins-category/112049">ChatGPT Plugins</a></p>
<ul>
<li>There is a waitlist - <a href="https://openai.com/waitlist/plugins">ChatGPT plugins waitlist</a>.</li>
<li>My understanding is that on June 16, 2023 all those with <a href="https://openai.com/blog/chatgpt-plus">ChatGPT plus</a> and on the waitlist were given the ability to install plugins and granted the developer options; regular ChatGPT users are still granted access from the waitlist. Those joining Plus and/or signing up for the waitlist after June 16, 2023 still have to wait on the waitlist. (<a href="https://twitter.com/OfficialLoganK/status/1669731498272931841?s=20">ref</a>)</li>
<li>Those with ChatGPT plugin developer access seeking developer access for their colleagues will still have to have their colleagues join the waitlist. (<a href="https://community.openai.com/t/developer-access-for-colleagues/157315/46">ref</a>)</li>
<li>Post on this site as feedback for ChatGPT plugins will most likely not be seen by OpenAI staff. Logan has posted this which directs to his Twitter account.<br>
<a href="https://community.openai.com/t/plugin-developer-experience-improvements-feedback-needed/246144" class="inline-onebox">Plugin developer experience improvements, feedback needed!</a></li>
</ul>
<p>ChatGPT Plugin development</p>
<ul>
<li>When developing plugins it seems that Google Chrome is the prefered browser to use. See: <a href="https://community.openai.com/t/failed-to-fetch-localhost-manifest-error-even-though-i-can-manually-pull-it-up/205784">“Failed to fetch localhost manifest” error even though I can manually pull it up </a></li>
<li>These topics are also worth reading:
<ul>
<li><a href="https://community.openai.com/t/localhost-dev-plugins-not-working-any-more/203968">Localhost Dev Plugins not working any more?</a></li>
<li><a href="https://community.openai.com/t/dont-see-web-browsing-option-chatgpt-plus/207830/12">Don’t see Web Browsing option - ChatGPT Plus</a></li>
<li><a href="https://community.openai.com/t/develop-your-own-plugin-vs-install-unverified-plugin-very-confusing/226575/2" class="inline-onebox">Develop your own plugin vs install unverified plugin - Very confusing - #2 by kevinpiac</a></li>
<li><a href="https://community.openai.com/t/how-to-optimise-api-specs-for-plugins/247683">How to optimise API specs for plugins</a></li>
<li><a href="https://community.openai.com/t/beta-tester-matching-community-project-for-helping-one-another-beta-test/175876">Beta Tester Matching: Community Project for Helping one Another Beta Test</a></li>
<li><a href="https://community.openai.com/t/plugin-developer-experience-improvements-feedback-needed/246144">Plugin developer experience improvements, feedback needed! </a></li>
</ul>
</li>
<li>Unofficial list of ChatGPT plugins both official and unofficial (unverified), for those with access.</li>
</ul>
<details>
<summary>
ChatGPT plugins lists (Click triangle to expand)</summary>
<p><a href="https://www.getit.ai/gpt-plugins">https://www.getit.ai/gpt-plugins</a><br>
<a href="https://pugin.ai/">https://pugin.ai/</a><br>
<a href="https://github.com/sisbell/chatgpt-plugins" class="inline-onebox">GitHub - sisbell/chatgpt-plugins: ChatGPT Plugin Examples</a><br>
<a href="https://www.futurepedia.io/ai-plugins?ref=emergentmind" class="inline-onebox">Futurepedia | ChatGPT Plugins List</a></p>
</details>
<p>Beginners</p>
<ul>
<li><a href="https://www.deeplearning.ai/short-courses/" class="inline-onebox">Short Courses | Learn Generative AI from DeepLearning.AI</a></li>
</ul> | 6,036 | 0 | 53ef158388 | 14 | [
80556,
309326,
34941,
19000,
44
] | null | Continuing the list from the first post
* Check the server status page
`https://status.openai.com/`
[status.openai.com](https://status.openai.com/)
### [OpenAI Status](https://status.openai.com/)
Welcome to OpenAI's home for real-time and historical data on system performance.
* [Supported countries and territories](https://platform.openai.com/docs/supported-countries/supported-countries-and-territories). Also see [ChatGPT disabled for users in Italy](https://community.openai.com/t/chatgpt-disabled-for-users-in-italy/133236)
* If you need help with your account, payment, etc, please visit <https://help.openai.com>
+ At the bottom right on <https://help.openai.com/en/> is a message icon.  Click the icon then enter a message. My understanding is that you will be asked for an email address then the OpenAI staff will contact you via email. I hear it can take weeks before being contacted but remember that this is one of the fastest growing apps ever, **please be patient**.
+ Please **DO NOT SHARE** personal information (email, credit card, etc) or account related details publicly.
+ Asking account related questions in this forum can often create more confusion for the community than provide assistance.
+ The account for API models, AKA playground, (<https://platform.openai.com/>) does not include ChatGPT Plus. ChatGPT Plus is a separate monthly billing and requires a separate signup. (<https://chat.openai.com/>)
* Error code: 1020 has a [few topics](https://community.openai.com/search?q=error%201020) already discussing the error, no need to start a new topic.
* Read all of the OpenAI [documentation](https://platform.openai.com/docs) first even if it may not seem to apply to what you are doing as some information may be in one section that has meaning in another.
* This Discourse forum has built-in search, in the upper right click . Please search for a similar topic before posting as many post on this site are very similar and often include the needed information in the topic.
* If you don’t want to search the topics before posting at least check
+ [most viewed topics](https://community.openai.com/latest?order=views)
+ [most liked topics](https://community.openai.com/latest?order=likes)
* The OpenAI Developer Advocate Logan Kilpatrick does post here, here is a list of his [replies](https://community.openai.com/u/logankilpatrick/activity/replies) and on [Twitter](https://twitter.com/OfficialLoganK).
* This topic *Read this before posting a new question* is not for introducing yourself, saying hi, etc. for that use the O[penAI Discord introductions channel](https://discord.com/channels/974519864045756446/974542851167887360).
* Regarding `General Data Protection Regulation (GDPR)` see [this](https://community.openai.com/t/general-data-protection-regulation-gdpr/1729/3)
OpenAI API
* The [OpenAI Cookbook](https://github.com/openai/openai-cookbook) (a GitHub repository) shares example code for accomplishing common tasks with the [OpenAI API](https://openai.com/api/).
[ChatGPT Web Interface](https://chat.openai.com/chat) (not ChatGPT API)
* ChatGPT does not do math or any other form of [evaluations](https://en.wikipedia.org/wiki/Function_(mathematics)). Please read any of the [many post talking about math](https://community.openai.com/search?q=math). Update **02/24/2023** ChatGPT now allows plugins such as a [Wolfram Alpha plugin](https://writings.stephenwolfram.com/2023/03/chatgpt-gets-its-wolfram-superpowers/), so this is not so much of an issue. Note at present plugins are accessible only for selected users, there is a [waitlist](https://openai.com/waitlist/plugins).
* ChatGPT often [hallucinates](https://en.wikipedia.org/wiki/Hallucination_(artificial_intelligence)), especially for references for research such as papers and [DOI](https://www.doi.org/).
* ChatGPT is a research preview and that conversations should be saved independently of the site. Do not take for granted that conversations in the left menu will always be there. ([ref](https://community.openai.com/t/all-my-conversations-gone/33549/34))
* If ChatGPT stops before a answer (completion) is done just ask it to continue. ([ref 1](https://community.openai.com/t/chatgpt-sometimes-not-finish-its-code-or-sentence-how-do-i-solve-this/46476/3)) ([ref 2](https://community.openai.com/t/how-to-prompt-chatgpt-to-provide-full-answers-including-technical-details-such-as-source-code/90760))
* If ChatGPT often replies with “Too many requests in 1 hour. Try again later.” then consider upgrading to ChatGPT Plus. ([ref](https://community.openai.com/t/questions-about-chatgpt-plus/90999))
* If using ChatGPT with Chrome and the page is not correctly presented/formatted try `Ctrl+F5`
* After several minutes of inactivity on a page the connection to the server will timeout. If you have not interacted with the page lately then click the browsers refresh button
, do not use `F5`, to reestablish a connection. This will often update errors and messages.
* [ChatGPT release notes](https://help.openai.com/en/articles/6825453-chatgpt-release-notes). The link is also in the footer of the [ChatGPT page](https://chat.openai.com/).
This Discourse site
* Posting
+ Discourse sites use [Askimet](https://akismet.com/) to detect spam. If you are a new user and paste in a message then click send it will most likely get flagged by [Askimet](https://akismet.com/) as spam because it was entered to quickly and considered spam that was generated and not typed in by hand.
+ [Understanding Discourse Trust Levels](https://blog.discourse.org/2018/06/understanding-discourse-trust-levels/)
+ [Trust Level Permissions Table (inc Moderator Roles)](https://meta.discourse.org/t/trust-level-permissions-table-inc-moderator-roles/224824)
+ [Understanding user statuses, roles, and permissions](https://meta.discourse.org/t/understanding-user-statuses-roles-and-permissions/35171)
+ [FAQ](https://community.openai.com/faq)
+ [Terms of service](https://community.openai.com/tos)
+ [Privacy statement](https://community.openai.com/privacy)
* Giving thanks
A better way to say thanks than to create a reply is to click the heart  at the bottom of a reply.
This tells the person that you liked the reply without requiring the person to read another post.
It also shows others that
+ the reply is useful
+ this person is giving useful informationHearts are like the currency of Discourse forums. While you can’t actually spend them they do count toward maintaining [trust level 3](https://blog.discourse.org/2018/06/understanding-discourse-trust-levels/), so please consider clicking a heart when giving thanks.
* Creating links (New user - Trust Level 0)
New users do not have the ability to post links on this Discourse forum. Yes most Discourse forums allow new users to post links but this site was configured to disallow that.
It takes about 12 minutes to get to [Trust Level 1](https://blog.discourse.org/2018/06/understanding-discourse-trust-levels/) which does allow a user to post links on this Discourse forum.
* To get from Trust Level 0 (New user) to Trust Level 1 (Basic user)
+ Entering at least **5** topics
+ Reading at least **30** posts
+ Spend a total of **10** minutes reading posts
[ChatGPT Plugins](https://community.openai.com/t/about-the-chatgpt-plugins-category/112049)
* There is a waitlist - [ChatGPT plugins waitlist](https://openai.com/waitlist/plugins).
* My understanding is that on June 16, 2023 all those with [ChatGPT plus](https://openai.com/blog/chatgpt-plus) and on the waitlist were given the ability to install plugins and granted the developer options; regular ChatGPT users are still granted access from the waitlist. Those joining Plus and/or signing up for the waitlist after June 16, 2023 still have to wait on the waitlist. ([ref](https://twitter.com/OfficialLoganK/status/1669731498272931841?s=20))
* Those with ChatGPT plugin developer access seeking developer access for their colleagues will still have to have their colleagues join the waitlist. ([ref](https://community.openai.com/t/developer-access-for-colleagues/157315/46))
* Post on this site as feedback for ChatGPT plugins will most likely not be seen by OpenAI staff. Logan has posted this which directs to his Twitter account.
[Plugin developer experience improvements, feedback needed!](https://community.openai.com/t/plugin-developer-experience-improvements-feedback-needed/246144)
ChatGPT Plugin development
* When developing plugins it seems that Google Chrome is the prefered browser to use. See: [“Failed to fetch localhost manifest” error even though I can manually pull it up](https://community.openai.com/t/failed-to-fetch-localhost-manifest-error-even-though-i-can-manually-pull-it-up/205784)
* These topics are also worth reading:
+ [Localhost Dev Plugins not working any more?](https://community.openai.com/t/localhost-dev-plugins-not-working-any-more/203968)
+ [Don’t see Web Browsing option - ChatGPT Plus](https://community.openai.com/t/dont-see-web-browsing-option-chatgpt-plus/207830/12)
+ [Develop your own plugin vs install unverified plugin - Very confusing - #2 by kevinpiac](https://community.openai.com/t/develop-your-own-plugin-vs-install-unverified-plugin-very-confusing/226575/2)
+ [How to optimise API specs for plugins](https://community.openai.com/t/how-to-optimise-api-specs-for-plugins/247683)
+ [Beta Tester Matching: Community Project for Helping one Another Beta Test](https://community.openai.com/t/beta-tester-matching-community-project-for-helping-one-another-beta-test/175876)
+ [Plugin developer experience improvements, feedback needed!](https://community.openai.com/t/plugin-developer-experience-improvements-feedback-needed/246144)
* Unofficial list of ChatGPT plugins both official and unofficial (unverified), for those with access.
ChatGPT plugins lists (Click triangle to expand)
<https://www.getit.ai/gpt-plugins>
<https://pugin.ai/>
[GitHub - sisbell/chatgpt-plugins: ChatGPT Plugin Examples](https://github.com/sisbell/chatgpt-plugins)
[Futurepedia | ChatGPT Plugins List](https://www.futurepedia.io/ai-plugins?ref=emergentmind)
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] | null | null | null | null | https://community.openai.com/t/51 | https://community.openai.com/p/113283 | Python Programming | Artificial Intelligence |
51 | [] | Read this before posting a new question | "2021-03-15T18:59:41.213000Z" | 7 | 54,260 | 6 | 187 | 3 | 1,897 | 127,999 | 2023-03-02T02:30:30.412Z | <p>A post was split to a new topic: <a href="/t/missing-models-page-for-switchover-updates-and-status-0-error/80928">Missing models page for switchover updates and status = 0 error</a></p> | 2,091 | 0 | 9e03ea965d | 22 | [
80556,
309326,
34941,
19000,
44
] | null | A post was split to a new topic: [Missing models page for switchover updates and status = 0 error](/t/missing-models-page-for-switchover-updates-and-status-0-error/80928)
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] | null | null | null | null | https://community.openai.com/t/51 | https://community.openai.com/p/127999 | Modeling | API (2) |
51 | [] | Read this before posting a new question | "2021-03-15T18:59:41.213000Z" | 7 | 54,260 | 6 | 187 | 3 | 1,897 | 221,084 | 2023-04-10T16:37:32.657Z | 1,627 | 0 | 9e03ea965d | 27 | [
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] | null | null | null | null | https://community.openai.com/t/51 | https://community.openai.com/p/221084 | Day Knowledge Direction | Emoji (8) |
||
44 | [] | Getting started - where do I begin exploring the API? | "2021-03-15T17:50:46.443000Z" | 7 | 18,828 | 3 | 41 | 1 | 171 | 49 | 2021-03-15T17:50:46.532Z | <p>Thanks for being a part of our beta! The OpenAI API is built to flexibly solve a number of language tasks with a unified text-in, text-out interface.</p>
<p>Learn more about what the API is capable of, or jump right in and start sending your own requests:</p>
<ul>
<li>
<p><a href="https://beta.openai.com/docs/introduction">Introduction<br>
</a>Get an overview of how the API works and how you can interface with the language models in different ways.</p>
</li>
<li>
<p><a href="https://beta.openai.com/playground">Playground<br>
</a>Experiment and iterate with different prompts and generations.</p>
</li>
<li>
<p><a href="https://beta.openai.com/docs/quickstart">Developer Quick Start<br>
</a>Learn how to hook into the API programmatically.</p>
</li>
<li>
<p><a href="https://beta.openai.com/examples">Example prompts<br>
</a>See examples of how other people are using the API.</p>
</li>
</ul> | 3,301 | 0 | 6b86b273ff | 1 | [
674,
246965,
19000,
4297,
77
] | null | Thanks for being a part of our beta! The OpenAI API is built to flexibly solve a number of language tasks with a unified text-in, text-out interface.
Learn more about what the API is capable of, or jump right in and start sending your own requests:
* [Introduction](https://beta.openai.com/docs/introduction)Get an overview of how the API works and how you can interface with the language models in different ways.
* [Playground](https://beta.openai.com/playground)Experiment and iterate with different prompts and generations.
* [Developer Quick Start](https://beta.openai.com/docs/quickstart)Learn how to hook into the API programmatically.
* [Example prompts](https://beta.openai.com/examples)See examples of how other people are using the API.
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] | null | null | null | null | https://community.openai.com/t/44 | https://community.openai.com/p/49 | Deep Learning | Miscellaneous (27) |
35 | [
"announcement"
] | About the OpenAI API category | "2021-03-10T20:39:25.837000Z" | 7 | 3,630 | 0 | 4 | 1 | 80 | 40 | 2021-03-10T20:39:25.848Z | <p>Questions, feedback, and best practices around building with OpenAI’s API. Please read the <a href="https://platform.openai.com/overview">API docs</a> before posting.</p>
<ul>
<li>For account questions, please reach out to <a href="https://help.openai.com">https://help.openai.com</a>
</li>
<li>Please tag your post with “question”, “feedback”, etc so the right people will see it</li>
</ul>
<p>Make sure to not share your API key when posting code!</p> | 672 | 0 | 9e03ea965d | 1 | [
34,
106621,
305,
51,
5194
] | null | Questions, feedback, and best practices around building with OpenAI’s API. Please read the [API docs](https://platform.openai.com/overview) before posting.
* For account questions, please reach out to <https://help.openai.com>
* Please tag your post with “question”, “feedback”, etc so the right people will see it
Make sure to not share your API key when posting code!
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] | announcement | null | null | null | https://community.openai.com/t/35 | https://community.openai.com/p/40 | PHP Libraries | Miscellaneous (27) |
35 | [
"announcement"
] | About the OpenAI API category | "2021-03-10T20:39:25.837000Z" | 7 | 3,630 | 0 | 4 | 1 | 80 | 208,667 | 2023-04-04T23:02:29.508Z | 484 | 0 | 9e03ea965d | 5 | [
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] | announcement | null | null | null | https://community.openai.com/t/35 | https://community.openai.com/p/208667 | Day Knowledge Direction | Emoji (8) |
||
656,864 | [] | 4096 response limit vs 128 000 context window | "2024-02-27T10:59:48.563000Z" | 7 | 53 | 0 | 0 | 3 | 536 | 896,471 | 2024-02-27T10:59:48.635Z | <p>I need to use the API to generate lengthy (1000-2000 word) personalized reports. For the longer reports I’m often left with the AI saying “repeat for other categories” instead of actually completing the report.<br>
My prompt needs to be quite long (500-1000 words) to give context + instruction. My hypothesis is that my request takes up too much of the 4096 response token limit. So the solution might be to move the standard context part of the prompt out of the API request/reponse (which is limited to 4096), and rather have it in the context window (which limit is 128 000). How can I do this?</p>
<ol>
<li>Chat: Will it help to move it from the “user prompt” to the “system prompt” in payload sent to the “Chat API”?</li>
<li>Assistants: or should I switch over to the “Assistants API” and then set up the context under “instructions” on the OpenAI website, and only send the instruction (user prompt) in the payload sent to the API each time?<br>
Thanks!</li>
</ol> | 12 | 0 | 02704268e3 | 1 | [
227601,
298852,
51930,
291833,
22557
] | null | I need to use the API to generate lengthy (1000-2000 word) personalized reports. For the longer reports I’m often left with the AI saying “repeat for other categories” instead of actually completing the report.
My prompt needs to be quite long (500-1000 words) to give context + instruction. My hypothesis is that my request takes up too much of the 4096 response token limit. So the solution might be to move the standard context part of the prompt out of the API request/reponse (which is limited to 4096), and rather have it in the context window (which limit is 128 000). How can I do this?
1. Chat: Will it help to move it from the “user prompt” to the “system prompt” in payload sent to the “Chat API”?
2. Assistants: or should I switch over to the “Assistants API” and then set up the context under “instructions” on the OpenAI website, and only send the instruction (user prompt) in the payload sent to the API each time?
Thanks!
| api | neutral | 0.645967 | [
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] | null | null | null | null | https://community.openai.com/t/656864 | https://community.openai.com/p/896471 | Model Completion | Tokenization (2) |
656,864 | [] | 4096 response limit vs 128 000 context window | "2024-02-27T10:59:48.563000Z" | 7 | 53 | 0 | 0 | 3 | 536 | 896,500 | 2024-02-27T11:14:55.419Z | <p>You seem to have a bit of misconceptions, which I can probably clear up:</p>
<p>context window length is the 128000 characters (125k). and it is shared for all language inference.</p>
<p>The only thing confusing is that OpenAI artificially capped the amount of response in that space that they will generate and send to you - and then went further, training the AI itself not to produce more than about 500 words.</p>
<p>Loading the system instructions, past chat, functions, extra knowledge is all formatted plain text that appears in a linear space used for calculations. What the AI outputs one token at a time builds upon that as the AI is always considering what to output in a one-directional manner.</p>
<p>So about the only concern is the lack of focus as the extra input gets longer and longer – the need to pay attention to all the input at once to see if the "talk like a pirate that’s part of the input is still relevant and reweighting the output.</p> | 11 | 0 | b368833582 | 2 | [
227601,
298852,
51930,
291833,
22557
] | null | You seem to have a bit of misconceptions, which I can probably clear up:
context window length is the 128000 characters (125k). and it is shared for all language inference.
The only thing confusing is that OpenAI artificially capped the amount of response in that space that they will generate and send to you - and then went further, training the AI itself not to produce more than about 500 words.
Loading the system instructions, past chat, functions, extra knowledge is all formatted plain text that appears in a linear space used for calculations. What the AI outputs one token at a time builds upon that as the AI is always considering what to output in a one-directional manner.
So about the only concern is the lack of focus as the extra input gets longer and longer – the need to pay attention to all the input at once to see if the "talk like a pirate that’s part of the input is still relevant and reweighting the output.
| api | neutral | 0.741073 | [
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] | null | null | null | null | https://community.openai.com/t/656864 | https://community.openai.com/p/896500 | Model Completion | Tokenization (2) |
656,864 | [] | 4096 response limit vs 128 000 context window | "2024-02-27T10:59:48.563000Z" | 7 | 53 | 0 | 0 | 3 | 536 | 896,505 | 2024-02-27T11:20:35.632Z | <p>Hi Alwyn and welcome!</p>
<p>It’s very common that the output tokens remain significantly below the 4096 output token limit. ~800/900 words tend to be on the upper end of what the model returns in one API call. None of your proposed actions will change that.</p>
<p><a class="mention" href="/u/_j">@_j</a> recently made a few good posts about the issue but I struggle to find them right now.</p>
<p>Edit: Here is one of the posts that speaks to that:</p>
<aside class="quote quote-modified" data-post="4" data-topic="653114">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/_j/48/277961_2.png" class="avatar">
<a href="https://community.openai.com/t/trying-to-understand-why-im-hitting-token-limit-with-api/653114/4">Trying to understand why I'm hitting token limit with API</a> <a class="badge-category__wrapper " href="/c/api/7"><span data-category-id="7" style="--category-badge-color: #f4ac36; --category-badge-text-color: #FFFFFF;" data-drop-close="true" class="badge-category " title="Questions, feedback, and best practices around building with OpenAI’s API. Please read the API docs before posting."><span class="badge-category__name">API</span></span></a>
</div>
<blockquote>
The limitation is because the model has intense training, or perhaps even some injected governor, that compels it to stop writing and wrap up its output. This is a preconceived planned notion also. Ask for 40 descriptions, and they will be cut to half the size of 20 descriptions. Make an infallible prompt that reproduces lines of input into processed lines of output, and you will just be cut off arbitrarily.
22k tokens of input can be processed (and billed) almost instantly to a hidden state b…
</blockquote>
</aside>
| 9 | 0 | 5b48a0acbf | 3 | [
227601,
298852,
51930,
291833,
22557
] | null | Hi Alwyn and welcome!
It’s very common that the output tokens remain significantly below the 4096 output token limit. ~800/900 words tend to be on the upper end of what the model returns in one API call. None of your proposed actions will change that.
[@\_j](/u/_j) recently made a few good posts about the issue but I struggle to find them right now.
Edit: Here is one of the posts that speaks to that:
[Trying to understand why I'm hitting token limit with API](https://community.openai.com/t/trying-to-understand-why-im-hitting-token-limit-with-api/653114/4) [API](/c/api/7)
>
> The limitation is because the model has intense training, or perhaps even some injected governor, that compels it to stop writing and wrap up its output. This is a preconceived planned notion also. Ask for 40 descriptions, and they will be cut to half the size of 20 descriptions. Make an infallible prompt that reproduces lines of input into processed lines of output, and you will just be cut off arbitrarily.
> 22k tokens of input can be processed (and billed) almost instantly to a hidden state b…
>
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] | null | null | null | null | https://community.openai.com/t/656864 | https://community.openai.com/p/896505 | Model Completion | Tokenization (2) |
656,864 | [] | 4096 response limit vs 128 000 context window | "2024-02-27T10:59:48.563000Z" | 7 | 53 | 0 | 0 | 3 | 536 | 896,576 | 2024-02-27T12:03:27.136Z | <p>Thank you guys! So, if I understand correctly, reducing the extent to which my prompt eats up some of the 4096 tokens will not make a difference, since the current constraint to reply length is the internal training of the model, not the 4069 token limit… do I have that right?<br>
Then, just to make sure I understand the concepts (and with the hope of change in the internal training in future models), will it in theory help (even if currently in practice it doesn’t), to move the context out of the request, in the two ways described?</p> | 4 | 0 | 02704268e3 | 4 | [
227601,
298852,
51930,
291833,
22557
] | null | Thank you guys! So, if I understand correctly, reducing the extent to which my prompt eats up some of the 4096 tokens will not make a difference, since the current constraint to reply length is the internal training of the model, not the 4069 token limit… do I have that right?
Then, just to make sure I understand the concepts (and with the hope of change in the internal training in future models), will it in theory help (even if currently in practice it doesn’t), to move the context out of the request, in the two ways described?
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] | null | null | null | null | https://community.openai.com/t/656864 | https://community.openai.com/p/896576 | Booking | Tokenization (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 659,689 | 2023-11-10T19:43:33.861Z | <p>Chatting with an assistant through the API can be slow (4 - 8 seconds) for a short prompt and response. Much slower than regular GPT4 responses (1 - 2 seconds).</p>
<p>This bottleneck essentially makes the assistant API impractical for a realtime chatbot/ production use cases.</p>
<p>Is there something fundamental (like reading documents) that make assistants slower? Or is this just due to it being new?</p>
<pre><code class="lang-python">import time
from openai import OpenAI
def assistant_response(
input_message: str,
assistant_id: str,
thread_id: str,
player_profile_path: str
):
# 1. Load assistant.
print("2. Load assistant.")
s = time.time()
assistant = client.beta.assistants.retrieve(assistant_id=assistant_id)
e = time.time()
print(e - s)
if len(assistant.file_ids) < 1:
s = time.time()
# 2. Createn an open AI file object
print("1. Createn an open AI file object ")
file = client.files.create(
file=open(player_profile_path, "rb"),
purpose='assistants'
)
e = time.time()
print(e - s)
# 3. Load conversation thread based on player ID.
print("3. Load conversation thread based on player ID.")
s = time.time()
thread = client.beta.threads.retrieve(thread_id=thread_id)
e = time.time()
print(e - s)
# 4. Add new message to thread.
print("4. Add new message to thread. ")
s = time.time()
message = client.beta.threads.messages.create(
thread_id=thread.id,
role="user",
content=input_message
# file_ids=assistant.file_ids
)
e = time.time()
print(e - s)
print("4. Waiting for run to finish. ")
s = time.time()
run = openai.beta.threads.runs.create(
thread_id=thread.id,
assistant_id=assistant.id
)
while run.status !="completed":
run = openai.beta.threads.runs.retrieve(
thread_id=thread.id,
run_id=run.id
)
print(run.status)
messages = openai.beta.threads.messages.list(
thread_id=thread.id
)
e = time.time()
print(e - s)
return messages.data[0].content[0].text.value
</code></pre>
<p>Output:</p>
<pre><code class="lang-plaintext">2. Load assistant.
0.18107199668884277
3. Load conversation thread based on player ID.
0.1474926471710205
4. Add new message to thread.
0.2909998893737793
4. Waiting for run to finish.
queued
queued
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
7.238811016082764
</code></pre>
<p>Total elapsed time: 7.8624725341796875</p> | 493 | 0 | 7a45040ff7 | 1 | null | null | Chatting with an assistant through the API can be slow (4 - 8 seconds) for a short prompt and response. Much slower than regular GPT4 responses (1 - 2 seconds).
This bottleneck essentially makes the assistant API impractical for a realtime chatbot/ production use cases.
Is there something fundamental (like reading documents) that make assistants slower? Or is this just due to it being new?
```
import time
from openai import OpenAI
def assistant_response(
input_message: str,
assistant_id: str,
thread_id: str,
player_profile_path: str
):
# 1. Load assistant.
print("2. Load assistant.")
s = time.time()
assistant = client.beta.assistants.retrieve(assistant_id=assistant_id)
e = time.time()
print(e - s)
if len(assistant.file_ids) < 1:
s = time.time()
# 2. Createn an open AI file object
print("1. Createn an open AI file object ")
file = client.files.create(
file=open(player_profile_path, "rb"),
purpose='assistants'
)
e = time.time()
print(e - s)
# 3. Load conversation thread based on player ID.
print("3. Load conversation thread based on player ID.")
s = time.time()
thread = client.beta.threads.retrieve(thread_id=thread_id)
e = time.time()
print(e - s)
# 4. Add new message to thread.
print("4. Add new message to thread. ")
s = time.time()
message = client.beta.threads.messages.create(
thread_id=thread.id,
role="user",
content=input_message
# file_ids=assistant.file_ids
)
e = time.time()
print(e - s)
print("4. Waiting for run to finish. ")
s = time.time()
run = openai.beta.threads.runs.create(
thread_id=thread.id,
assistant_id=assistant.id
)
while run.status !="completed":
run = openai.beta.threads.runs.retrieve(
thread_id=thread.id,
run_id=run.id
)
print(run.status)
messages = openai.beta.threads.messages.list(
thread_id=thread.id
)
e = time.time()
print(e - s)
return messages.data[0].content[0].text.value
```
Output:
```
2. Load assistant.
0.18107199668884277
3. Load conversation thread based on player ID.
0.1474926471710205
4. Add new message to thread.
0.2909998893737793
4. Waiting for run to finish.
queued
queued
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
in_progress
7.238811016082764
```
Total elapsed time: 7.8624725341796875
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/659689 | Performance (2) | Tokenization (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 659,746 | 2023-11-10T20:04:58.296Z | <p>Hi and welcome to the Developer Forum!</p>
<p>It’s a combination of things, accounts come in usage Tiers based on how much you’ve spent and how much time since your first spend, so the lower tiers can have a larger latency, also a great deal of extra load is on the system as people test the new features out, this will settle with time, usually takes about a month to calm down, at least it did last time GPT-4 was released, might take a bit longer with all the new stuff this time.</p> | 438 | 2 | 705249ef25 | 2 | null | null | Hi and welcome to the Developer Forum!
It’s a combination of things, accounts come in usage Tiers based on how much you’ve spent and how much time since your first spend, so the lower tiers can have a larger latency, also a great deal of extra load is on the system as people test the new features out, this will settle with time, usually takes about a month to calm down, at least it did last time GPT-4 was released, might take a bit longer with all the new stuff this time.
| api | neutral | 0.525831 | [
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/659746 | Performance | Payment (4) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 659,777 | 2023-11-10T20:21:44.401Z | <p>Okay, thank you!</p>
<p>Just to clarify, its not a fundamental difference in functionality that slows down the assistants, but rather the combination of things you mentioned.</p>
<p>And therefore in theory, as a user, I would eventually see the same or similar response times using assistants as I do when using GPT4 through the API, as things cool down?</p>
<p>EDIT: I just checked our GPT4 response times (no assistant), and they are also up in the 8 second range. I am guessing this has to do with an influx related to more people using GPT like <a class="mention" href="/u/foxabilo">@Foxabilo</a> mentioned.</p> | 437 | 0 | 7a45040ff7 | 3 | null | null | Okay, thank you!
Just to clarify, its not a fundamental difference in functionality that slows down the assistants, but rather the combination of things you mentioned.
And therefore in theory, as a user, I would eventually see the same or similar response times using assistants as I do when using GPT4 through the API, as things cool down?
EDIT: I just checked our GPT4 response times (no assistant), and they are also up in the 8 second range. I am guessing this has to do with an influx related to more people using GPT like [@Foxabilo](/u/foxabilo) mentioned.
| api | neutral | 0.694911 | [
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/659777 | Performance (2) | Tokenization (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 665,742 | 2023-11-12T21:07:45.340Z | <p>On my side, I’ve seen the same thing, but the output is taking ages to come.</p>
<p>My code looks like yours, even if it’s node.js</p>
<pre><code class="lang-ts">console.time('createAndRun')
const run = await openai.beta.threads.createAndRun({
assistant_id: assistant.id,
thread: {
messages: [{ role: 'user', content: transcription.text }],
},
})
// wait for the run to be completed via its status
let status = run.status
while (status !== 'completed') {
const newrun = await openai.beta.threads.runs.retrieve(run.thread_id, run.id)
status = newrun.status
}
console.timeEnd('createAndRun')
</code></pre>
<p>which gives me, for a small answer of two sentences : <code>createAndRun: 17.337s</code></p>
<p>17 seconds seems to be really large.</p>
<p>I hope it will slow down</p> | 413 | 1 | 0072d399c7 | 4 | null | null | On my side, I’ve seen the same thing, but the output is taking ages to come.
My code looks like yours, even if it’s node.js
```
console.time('createAndRun')
const run = await openai.beta.threads.createAndRun({
assistant_id: assistant.id,
thread: {
messages: [{ role: 'user', content: transcription.text }],
},
})
// wait for the run to be completed via its status
let status = run.status
while (status !== 'completed') {
const newrun = await openai.beta.threads.runs.retrieve(run.thread_id, run.id)
status = newrun.status
}
console.timeEnd('createAndRun')
```
which gives me, for a small answer of two sentences : `createAndRun: 17.337s`
17 seconds seems to be really large.
I hope it will slow down
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/665742 | Performance (2) | Tokenization (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 669,300 | 2023-11-13T20:15:18.024Z | <p>Things get worse when you upload bigger files! In my case, sometimes it takes more than 30 seconds to answer a simple question. I uploaded a pdf file (around 7K words) and my assistant is supposed to answer questions based on information in the file. It works fine but it is not a production ready solution. it is taking too much time to answer the questions. Also, it seems that every time a question is made, the model is retrained with the content in the document.</p> | 357 | 0 | 3101ae49ba | 5 | null | null | Things get worse when you upload bigger files! In my case, sometimes it takes more than 30 seconds to answer a simple question. I uploaded a pdf file (around 7K words) and my assistant is supposed to answer questions based on information in the file. It works fine but it is not a production ready solution. it is taking too much time to answer the questions. Also, it seems that every time a question is made, the model is retrained with the content in the document.
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/669300 | PDFs | Artificial Intelligence |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 676,235 | 2023-11-15T16:23:10.827Z | <p>I am having the same issue, today especially. I have had it last over 2 minutes at which point the script stops.</p> | 330 | 1 | edd6964167 | 6 | null | null | I am having the same issue, today especially. I have had it last over 2 minutes at which point the script stops.
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/676235 | Miscellaneous (24) | API (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 676,296 | 2023-11-15T16:43:07.112Z | <p>There’s a slight bit of diagnosis available - not that it will get the answer you paid for though.</p>
<p><a href="https://platform.openai.com/docs/api-reference/runs/listRunSteps">https://platform.openai.com/docs/api-reference/runs/listRunSteps</a></p>
<p>You can see if the AI was doing things other than just generating an answer.</p> | 328 | 1 | b368833582 | 7 | null | null | There’s a slight bit of diagnosis available - not that it will get the answer you paid for though.
<https://platform.openai.com/docs/api-reference/runs/listRunSteps>
You can see if the AI was doing things other than just generating an answer.
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/676296 | Knowledge Classifier | Artificial Intelligence |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 676,365 | 2023-11-15T16:58:12.062Z | <p>I’ve noticed the same.</p>
<p>One of my assistants’ function calling actually calls the base GPT model for some work and it’s insane how different they are.</p>
<p>It can be almost 10 seconds for a small response from Assistants, but less than 3 seconds for a large paragraph using the base model.</p>
<p>I’m guessing they are just incredibly overloaded. Then I’m seeing a lot of people just straight up doing</p>
<pre><code class="lang-auto">while (true) {
retrieveRun(...params)
}
</code></pre>
<p>No sleeps. Just fucking spam the hell outta the endpoint. I mean, why the hell do we have to poll their servers <img src="https://emoji.discourse-cdn.com/twitter/laughing.png?v=12" title=":laughing:" class="emoji" alt=":laughing:" loading="lazy" width="20" height="20"> no subscriptions? Bruh</p>
<aside class="quote no-group" data-username="LePaladin" data-post="4" data-topic="493627">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/lepaladin/48/246158_2.png" class="avatar"> LePaladin:</div>
<blockquote>
<pre><code class="lang-auto">while (status !== 'completed') {
const newrun = await openai.beta.threads.runs.retrieve(run.thread_id, run.id)
status = newrun.status
}
</code></pre>
</blockquote>
</aside>
<p>You may want to consider added more options. It’s not just “completed”. For the sake of being nice please add a timeout!</p>
<pre><code class="lang-auto">const finishReasons = ["requires_action", "cancelling", "cancelled", "failed", "completed", "expired"]
while(!finishReasons.includes(run.status)){
run = await openai.beta.threads.runs.retrieve(run.thread_id, run.id);
await new Promise(resolve => setTimeout(resolve, 1000));
}
</code></pre> | 336 | 0 | 883a25e3c6 | 8 | null | null | I’ve noticed the same.
One of my assistants’ function calling actually calls the base GPT model for some work and it’s insane how different they are.
It can be almost 10 seconds for a small response from Assistants, but less than 3 seconds for a large paragraph using the base model.
I’m guessing they are just incredibly overloaded. Then I’m seeing a lot of people just straight up doing
```
while (true) {
retrieveRun(...params)
}
```
No sleeps. Just fucking spam the hell outta the endpoint. I mean, why the hell do we have to poll their servers  no subscriptions? Bruh
 LePaladin:
>
>
> ```
> while (status !== 'completed') {
> const newrun = await openai.beta.threads.runs.retrieve(run.thread_id, run.id)
> status = newrun.status
> }
>
> ```
>
>
You may want to consider added more options. It’s not just “completed”. For the sake of being nice please add a timeout!
```
const finishReasons = ["requires_action", "cancelling", "cancelled", "failed", "completed", "expired"]
while(!finishReasons.includes(run.status)){
run = await openai.beta.threads.runs.retrieve(run.thread_id, run.id);
await new Promise(resolve => setTimeout(resolve, 1000));
}
```
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/676365 | Performance (2) | Tokenization (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 732,274 | 2023-12-05T22:02:20.340Z | <p>The assistants API is essentially useless for me because of the response time.</p> | 239 | 1 | 5000009aa7 | 9 | null | null | The assistants API is essentially useless for me because of the response time.
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/732274 | Assistants, API, Platform | Embeddings (6) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 736,962 | 2023-12-07T19:57:22.392Z | <p>I agree with this. Right now I’m getting 30 second wait times for response. When the chat completion can range from a few seconds to maybe 30, it makes no sense to switch to assistant for general chatting at this point. Maybe using the assistant api isn’t really supposed to be for chat but for more behind the scene bot-swarm type stuff? I don’t know but right now it is pretty much useless for my use-case.</p> | 224 | 0 | 2e0abd270e | 10 | null | null | I agree with this. Right now I’m getting 30 second wait times for response. When the chat completion can range from a few seconds to maybe 30, it makes no sense to switch to assistant for general chatting at this point. Maybe using the assistant api isn’t really supposed to be for chat but for more behind the scene bot-swarm type stuff? I don’t know but right now it is pretty much useless for my use-case.
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/736962 | Chat History | Embeddings (6) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 737,100 | 2023-12-07T21:29:51.598Z | <p>It’s the best way I’ve managed to deploy a use case for the assistant. Most people just initiate a run and wait for the run to complete when the steps to me are the best shots at getting everything. Also, I see the users above being rude to the endpoint <img src="https://emoji.discourse-cdn.com/twitter/sweat_smile.png?v=12" title=":sweat_smile:" class="emoji" alt=":sweat_smile:" loading="lazy" width="20" height="20"> <img src="https://emoji.discourse-cdn.com/twitter/sweat_smile.png?v=12" title=":sweat_smile:" class="emoji" alt=":sweat_smile:" loading="lazy" width="20" height="20"> Imagine a while loop without rest <img src="https://emoji.discourse-cdn.com/twitter/rofl.png?v=12" title=":rofl:" class="emoji" alt=":rofl:" loading="lazy" width="20" height="20"></p> | 221 | 0 | b85011e623 | 11 | null | null | It’s the best way I’ve managed to deploy a use case for the assistant. Most people just initiate a run and wait for the run to complete when the steps to me are the best shots at getting everything. Also, I see the users above being rude to the endpoint   Imagine a while loop without rest 
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/737100 | Assistant Tools | Embeddings (6) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 738,263 | 2023-12-08T08:07:16.296Z | <p>Try to analyze what it is doing (playground would be the easiest path). For example in data analysis scenario: you pass a file with different format than expected - it will try to read the data anyway - sometimes in few attemps - and it takes time (and tokens).</p> | 222 | 0 | 959f7ffbfd | 12 | null | null | Try to analyze what it is doing (playground would be the easiest path). For example in data analysis scenario: you pass a file with different format than expected - it will try to read the data anyway - sometimes in few attemps - and it takes time (and tokens).
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/738263 | Playground | API (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 747,534 | 2023-12-12T21:06:24.998Z | <p>We’re now more than a month in and Assistants I’m working on aren’t running any more quickly. Has anybody seen an improvement?</p> | 191 | 1 | b7800d23af | 13 | null | null | We’re now more than a month in and Assistants I’m working on aren’t running any more quickly. Has anybody seen an improvement?
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/747534 | Performance | Payment (4) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 747,546 | 2023-12-12T21:10:50.724Z | <p>not at all. and even for chat completions I am getting 30+ second waits on longer answers.</p> | 192 | 0 | 2e0abd270e | 14 | null | null | not at all. and even for chat completions I am getting 30+ second waits on longer answers.
| api | negative | 0.814186 | [
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/747546 | Performance | Payment (4) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 748,112 | 2023-12-13T03:46:50.481Z | <p>Yes, you are right. The assistant’s tool is very slow. It thinks, does things, and is impressive. However, the fact is, you cannot use it for production yet.</p>
<p>I believe gpt-4-turbo has to be even faster with more capabilities, which will also improve the assistant’s tool speed and give satisfaction to chat completion users as well. <img src="https://emoji.discourse-cdn.com/twitter/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p> | 194 | 0 | b991108dee | 15 | null | null | Yes, you are right. The assistant’s tool is very slow. It thinks, does things, and is impressive. However, the fact is, you cannot use it for production yet.
I believe gpt-4-turbo has to be even faster with more capabilities, which will also improve the assistant’s tool speed and give satisfaction to chat completion users as well. 
| api | neutral | 0.46338 | [
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/748112 | Assistants | GPTs (4) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 811,076 | 2024-01-22T01:08:48.179Z | <p>For me, when there are documents uploaded to the assistant (even small documents), it can take up to 90+ seconds to respond.</p>
<p>However, when there is no document uploaded to the assistant, it seems that the response time is reduced significantly, but still can take up to 20 seconds in some cases. This is kind of “usable” to me, but would really like to see if Open AI can get it improved</p> | 121 | 0 | bbe5325d78 | 16 | null | null | For me, when there are documents uploaded to the assistant (even small documents), it can take up to 90+ seconds to respond.
However, when there is no document uploaded to the assistant, it seems that the response time is reduced significantly, but still can take up to 20 seconds in some cases. This is kind of “usable” to me, but would really like to see if Open AI can get it improved
| api | neutral | 0.70676 | [
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/811076 | Performance (2) | Tokenization (2) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 826,083 | 2024-01-29T14:56:18.617Z | <p>The minimium I got was 20-30 seconds. Usually it takes around 40 seconds. Not really usable on production right now.</p> | 96 | 0 | c325269417 | 17 | null | null | The minimium I got was 20-30 seconds. Usually it takes around 40 seconds. Not really usable on production right now.
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/826083 | Performance | Payment (4) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 826,650 | 2024-01-29T20:11:58.755Z | <p>It depends. When documents are uploaded with the assistant it can take forever. When it’s just the instruction it works well and i get responses within about 5 seconds</p> | 98 | 0 | 850da3b707 | 18 | null | null | It depends. When documents are uploaded with the assistant it can take forever. When it’s just the instruction it works well and i get responses within about 5 seconds
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/826650 | Performance | Payment (4) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 831,878 | 2024-02-01T09:26:02.407Z | <p>Do you know when OpenAI is ready for production on Assistant API ? The quality of retrieval and function calling are impressive for our bot application, but the speed is so slow.</p> | 92 | 0 | 70517df2b8 | 19 | null | null | Do you know when OpenAI is ready for production on Assistant API ? The quality of retrieval and function calling are impressive for our bot application, but the speed is so slow.
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/831878 | PHP Libraries | Miscellaneous (27) |
493,627 | [
"assistants"
] | Assistants API too slow for realtime/production? | "2023-11-10T19:43:33.796000Z" | 7 | 6,869 | 9 | 46 | 26 | 1,971 | 839,005 | 2024-02-05T06:09:04.005Z | <p>yeah it is too slow at the moment. But I like the thread functionality, which automatically manages chat history, and the file.id system. I don’t want to code a lot of function to do chat history management, which may require a database to manage.</p> | 81 | 1 | aa9b4f1592 | 20 | null | null | yeah it is too slow at the moment. But I like the thread functionality, which automatically manages chat history, and the file.id system. I don’t want to code a lot of function to do chat history management, which may require a database to manage.
| api | neutral | 0.478006 | [
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] | assistants | null | null | null | https://community.openai.com/t/493627 | https://community.openai.com/p/839005 | Chat History | Embeddings (6) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 712,380 | 2023-11-28T03:06:11.842Z | <p>I’ve been trying to use the moderations endpoint for the first time, with no success.</p>
<p>I have a credit balance, and I’m able to successfully create chat completions. However every time I hit the moderations endpoint, using the instructions provided in the API docs, either via curl or the python library, I get “You exceeded your current quota, please check your plan and billing details.”</p>
<p>Any idea why this might be happening?</p> | 28 | 0 | b0c7d067b8 | 1 | [
576340,
537053,
567740,
538371,
537067
] | null | I’ve been trying to use the moderations endpoint for the first time, with no success.
I have a credit balance, and I’m able to successfully create chat completions. However every time I hit the moderations endpoint, using the instructions provided in the API docs, either via curl or the python library, I get “You exceeded your current quota, please check your plan and billing details.”
Any idea why this might be happening?
| api | neutral | 0.530136 | [
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/712380 | Insufficient Quota | Tokenization (2) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 722,842 | 2023-12-02T00:12:13.155Z | <p>I have this problem too. The API doesn’t work. The tutorials make it seem simple. The error messages are wrong. <strong>This is a bug for two reasons: 429 is the wrong code. insufficient_quota is not true.</strong></p>
<p>completion = client.chat.completions.create(<br>
model=“gpt-4”,<br>
messages=[<br>
{“role”: “system”, “content”: “You are a poetic assistant, skilled in explaining complex programming concepts with creative flair.”},<br>
{“role”: “user”, “content”: “Compose a poem that explains the concept of recursion in programming.”}<br>
]<br>
)</p>
<p>print(completion.choices[0].message)</p>
<p>stream = client.chat.completions.create(<br>
model=“gpt-4”,<br>
messages=[{“role”: “user”, “content”: “Say this is a test”}],<br>
stream=True,<br>
)<br>
for chunk in stream:<br>
if chunk.choices[0].delta.content is not None:<br>
print(chunk.choices[0].delta.content, end=“”)</p>
<p>openai.RateLimitError: Error code: 429 - {‘error’: {‘message’: ‘You exceeded your current quota, please check your plan and billing details.’, ‘type’: ‘insufficient_quota’, ‘param’: None, ‘code’: ‘insufficient_quota’}}</p> | 27 | 0 | 0c05c0472f | 2 | [
576340,
537053,
567740,
538371,
537067
] | null | I have this problem too. The API doesn’t work. The tutorials make it seem simple. The error messages are wrong. **This is a bug for two reasons: 429 is the wrong code. insufficient\_quota is not true.**
completion = client.chat.completions.create(
model=“gpt-4”,
messages=[
{“role”: “system”, “content”: “You are a poetic assistant, skilled in explaining complex programming concepts with creative flair.”},
{“role”: “user”, “content”: “Compose a poem that explains the concept of recursion in programming.”}
]
)
print(completion.choices[0].message)
stream = client.chat.completions.create(
model=“gpt-4”,
messages=[{“role”: “user”, “content”: “Say this is a test”}],
stream=True,
)
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end=“”)
openai.RateLimitError: Error code: 429 - {‘error’: {‘message’: ‘You exceeded your current quota, please check your plan and billing details.’, ‘type’: ‘insufficient\_quota’, ‘param’: None, ‘code’: ‘insufficient\_quota’}}
| api | negative | 0.778959 | [
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/722842 | Insufficient Quota | Tokenization (2) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 722,860 | 2023-12-02T00:28:01.349Z | <p>Similarly, I am continuing to receive <code>insufficient_quota</code> error like you. There is another thread open right now where an OpenAI Dev Relations team member explains that the issue is still ongoing for some folks.</p> | 24 | 0 | 15cc489683 | 3 | [
576340,
537053,
567740,
538371,
537067
] | null | Similarly, I am continuing to receive `insufficient_quota` error like you. There is another thread open right now where an OpenAI Dev Relations team member explains that the issue is still ongoing for some folks.
| api | negative | 0.679803 | [
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/722860 | Insufficient Quota | Tokenization (2) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 722,896 | 2023-12-02T00:51:34.217Z | <p>I don’t have this issue.</p>
<p>I also have not just recently activated my account and made my first payment, which was who was affected by payment system issues earlier today, which apparently still needs attention.</p>
<p>What is peculiar is that the moderations API should be without cost and doesn’t consume credits. If a completions endpoint works for you, yet moderations gives a “please check your plan and billing details”, that certainly seems like some part of your recent credit purchase still has not taken effect or been repaired across all systems.</p>
<p>There’s a few things you can do (short of paying in another $5) to see if you can get a clear account status:</p>
<ul>
<li>in the account “limits” page there are monthly limits. Glitches before this one were occasionally cleared by altering those values.</li>
<li>you can generate a new API key and see that it works in both code for chatcompletions and then moderations.</li>
<li>visit the billing settings and see that your personal preferences are filled out and re-save.</li>
</ul>
<hr>
<p>If using Python, and you’ve placed your <code>OPENAI_API_KEY</code> as an environment variable, the last code box in this post will give you a bit of immediate feedback to know it’s not your method:</p>
<aside class="quote quote-modified" data-post="2" data-topic="530068">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/_j/48/236251_2.png" class="avatar">
<a href="https://community.openai.com/t/moderations-create-how-to-save-and-parse-output/530068/2">Moderations.create - how to save and parse output?</a> <a class="badge-category__wrapper " href="/c/api/7"><span data-category-id="7" data-drop-close="true" class="badge-category " title="Questions, feedback, and best practices around building with OpenAI’s API. Please read the API docs before posting."><span class="badge-category__name">API</span></span></a>
</div>
<blockquote>
<a name="lets-do-moderations-1" class="anchor" href="#lets-do-moderations-1"></a>Let’s do moderations!
First, we’re going to need the prerequisites - python 3.8-3.11. Then you’ll need to pip install --upgrade openai to get the latest version of the python library with its new client object.
<a name="openais-example-2" class="anchor" href="#openais-example-2"></a>OpenAI’s example
from openai import OpenAI
client = OpenAI()
client.moderations.create(input="I want to kill them.")
Lame. Doesn’t even let you get the results.
<a name="useful-example-3" class="anchor" href="#useful-example-3"></a>Useful example
from openai import OpenAI
client = OpenAI()
text = "I like kittens."
api_response = client.moderations.create(…
</blockquote>
</aside>
| 25 | 0 | b368833582 | 4 | [
576340,
537053,
567740,
538371,
537067
] | null | I don’t have this issue.
I also have not just recently activated my account and made my first payment, which was who was affected by payment system issues earlier today, which apparently still needs attention.
What is peculiar is that the moderations API should be without cost and doesn’t consume credits. If a completions endpoint works for you, yet moderations gives a “please check your plan and billing details”, that certainly seems like some part of your recent credit purchase still has not taken effect or been repaired across all systems.
There’s a few things you can do (short of paying in another $5) to see if you can get a clear account status:
* in the account “limits” page there are monthly limits. Glitches before this one were occasionally cleared by altering those values.
* you can generate a new API key and see that it works in both code for chatcompletions and then moderations.
* visit the billing settings and see that your personal preferences are filled out and re-save.
---
If using Python, and you’ve placed your `OPENAI_API_KEY` as an environment variable, the last code box in this post will give you a bit of immediate feedback to know it’s not your method:
[Moderations.create - how to save and parse output?](https://community.openai.com/t/moderations-create-how-to-save-and-parse-output/530068/2) [API](/c/api/7)
>
> Let’s do moderations!
> First, we’re going to need the prerequisites - python 3.8-3.11. Then you’ll need to pip install --upgrade openai to get the latest version of the python library with its new client object.
> OpenAI’s example
> from openai import OpenAI
> client = OpenAI()
> client.moderations.create(input="I want to kill them.")
>
> Lame. Doesn’t even let you get the results.
> Useful example
> from openai import OpenAI
> client = OpenAI()
> text = "I like kittens."
> api\_response = client.moderations.create(…
>
| api | neutral | 0.576246 | [
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/722896 | Payment (3) | Miscellaneous (27) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 723,222 | 2023-12-02T04:55:50.025Z | <p>Thanks <a class="mention" href="/u/_j">@_j</a> , a lot of helpful tips. I think some people continued to experience the issue besides having addressed each of the points you mentioned. No matter now, because the issue seems to have resolved automatically for me. Maybe it will have resolved for the others in this thread?</p> | 20 | 1 | 15cc489683 | 5 | [
576340,
537053,
567740,
538371,
537067
] | null | Thanks [@\_j](/u/_j) , a lot of helpful tips. I think some people continued to experience the issue besides having addressed each of the points you mentioned. No matter now, because the issue seems to have resolved automatically for me. Maybe it will have resolved for the others in this thread?
| api | positive | 0.687547 | [
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/723222 | Reporting | API (2) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 849,591 | 2024-02-10T12:16:53.024Z | <p>Did you resolve this issue, and did you find out how?<br>
I am facing the same issue, with similar circumstances.</p> | 10 | 0 | bfc226af94 | 6 | [
576340,
537053,
567740,
538371,
537067
] | null | Did you resolve this issue, and did you find out how?
I am facing the same issue, with similar circumstances.
| api | neutral | 0.521728 | [
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/849591 | Issue-Solving | API (2) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 896,424 | 2024-02-27T10:35:45.669Z | <p>Same issue here, and we’re a tier 5 customer.</p> | 5 | 1 | 5781f22ce4 | 7 | [
576340,
537053,
567740,
538371,
537067
] | null | Same issue here, and we’re a tier 5 customer.
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/896424 | Application Approval | Payment (4) |
530,625 | [
"moderation"
] | Moderations endpoint returns insufficient_quota | "2023-11-28T03:06:11.784000Z" | 7 | 593 | 2 | 4 | 6 | 932 | 896,621 | 2024-02-27T12:13:42.149Z | <p>Same issue on something that happened at the start of the month is likely not “same issue”.</p>
<p>You can check a few things:</p>
<p>You are using the same API key in both application of chat completions and moderations code. The best way is via environment variable if the code also doesn’t have different virtual environments. You can make sure the funded organization is selected in your <a href="http://platform.openai.com">platform.openai.com</a> (click on the name at the bottom, some have a “personal” org that has also been added. Then make a new API key, then deliberately place it in both moderations and chat completions code together to see that this is specific to moderations and specific to an account that might not be funded to use API at all.</p>
<hr>
<p>Here’s python I whipped up to check moderations and get any error, and then also send to chat for any error.</p>
<pre data-code-wrap="python"><code class="lang-python">import os, json, urllib.request, urllib.error
# replace {os.environ.get('OPENAI_API_KEY')} with actual key to hard-code
headers = {"Content-Type": "application/json",
"Authorization": f"Bearer {os.environ.get('OPENAI_API_KEY')}"}
model = "gpt-3.5-turbo"
system = [{"role": "system", "content": f"You are ChatAPI"}]
user = [{"role": "user", "content": "Provide brief introduction."}]
chat = []
params_template = {"model": model, "max_tokens": 666, "top_p":0.9,}
while not user[0]['content'] == "exit":
to_moderate = {"input" : ', '.join([str(d) for d in (chat[-2:] + user)])}
try:
req = urllib.request.Request("https://api.openai.com/v1/moderations", \
headers=headers, data=json.dumps(to_moderate).encode())
scores = urllib.request.urlopen(req)
print(json.loads(scores.read().decode())["results"][0]["categories"])
except urllib.error.HTTPError as e:
print(f"mod error {e.code}: {e.read().decode()}")
pass
request = {**params_template, **{"messages": system + chat[-10:] + user}}
try:
req = urllib.request.Request("https://api.openai.com/v1/chat/completions", \
headers=headers, data=json.dumps(request).encode())
response = urllib.request.urlopen(req)
except urllib.error.HTTPError as e:
print(f"chat error {e.code}: {e.read().decode()}")
user = [{"role": "user", "content": input("\nPrompt: ")}]
continue
except Exception as e:
print(f"Error: {e}")
continue
else:
response_body = json.loads(response.read().decode())
reply = response_body['choices'][0]['message']['content']
print(reply)
chat += user + [{"role": "assistant", "content": reply}]
user = [{"role": "user", "content": input("\nPrompt: ")}]
</code></pre>
<p>That would let you ultimately see if only moderations is at fault.</p> | 1 | 0 | b368833582 | 8 | [
576340,
537053,
567740,
538371,
537067
] | null | Same issue on something that happened at the start of the month is likely not “same issue”.
You can check a few things:
You are using the same API key in both application of chat completions and moderations code. The best way is via environment variable if the code also doesn’t have different virtual environments. You can make sure the funded organization is selected in your [platform.openai.com](http://platform.openai.com) (click on the name at the bottom, some have a “personal” org that has also been added. Then make a new API key, then deliberately place it in both moderations and chat completions code together to see that this is specific to moderations and specific to an account that might not be funded to use API at all.
---
Here’s python I whipped up to check moderations and get any error, and then also send to chat for any error.
```
import os, json, urllib.request, urllib.error
# replace {os.environ.get('OPENAI_API_KEY')} with actual key to hard-code
headers = {"Content-Type": "application/json",
"Authorization": f"Bearer {os.environ.get('OPENAI_API_KEY')}"}
model = "gpt-3.5-turbo"
system = [{"role": "system", "content": f"You are ChatAPI"}]
user = [{"role": "user", "content": "Provide brief introduction."}]
chat = []
params_template = {"model": model, "max_tokens": 666, "top_p":0.9,}
while not user[0]['content'] == "exit":
to_moderate = {"input" : ', '.join([str(d) for d in (chat[-2:] + user)])}
try:
req = urllib.request.Request("https://api.openai.com/v1/moderations", \
headers=headers, data=json.dumps(to_moderate).encode())
scores = urllib.request.urlopen(req)
print(json.loads(scores.read().decode())["results"][0]["categories"])
except urllib.error.HTTPError as e:
print(f"mod error {e.code}: {e.read().decode()}")
pass
request = {**params_template, **{"messages": system + chat[-10:] + user}}
try:
req = urllib.request.Request("https://api.openai.com/v1/chat/completions", \
headers=headers, data=json.dumps(request).encode())
response = urllib.request.urlopen(req)
except urllib.error.HTTPError as e:
print(f"chat error {e.code}: {e.read().decode()}")
user = [{"role": "user", "content": input("\nPrompt: ")}]
continue
except Exception as e:
print(f"Error: {e}")
continue
else:
response_body = json.loads(response.read().decode())
reply = response_body['choices'][0]['message']['content']
print(reply)
chat += user + [{"role": "assistant", "content": reply}]
user = [{"role": "user", "content": input("\nPrompt: ")}]
```
That would let you ultimately see if only moderations is at fault.
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] | moderation | null | null | null | https://community.openai.com/t/530625 | https://community.openai.com/p/896621 | Python3 Packages | Miscellaneous (27) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,657 | 2024-02-25T18:59:32.611Z | <p>I have noticed that the GPT-4 has a strong preference for certain choices that are not correct in questions involving calculations and comparisons of fractions.</p>
<p>The following is a specific user message.</p>
<blockquote>
<p>Which of the following three numbers is correct in order from smallest to largest?</p>
<p>Choose one:</p>
<p>A: 99 / 100<101 / 100<100<br>
B: 100<99 / 100<101 / 100<br>
C: 99 / 100<100<101 / 100</p>
</blockquote>
<p>To avoid complicating the discussion, I added this here.</p>
<blockquote>
<p>Only show the correct alphabetical letter in your response.</p>
</blockquote>
<p>I used gpt-4-turbo-preview to get this result and logprobs.<br>
The temperature parameter was set to 0 and no other hyperparameters were used.</p>
<p>The result is that out of 50 trials we chose the wrong choice C 50 times.<br>
I also plotted the logprobs as a line graph.<br>
I may need to set top_logprobs to 2 or higher if logprobs has a high value here, but I did not use top_logprobs here because logprobs was almost 0 on all trials.</p>
<p>Then I used gpt-4-turbo-preview to get this result and logprobs.<br>
The temperature parameter was set to 0 and no other hyperparameters were used.</p>
<p>The result is that out of 50 trials we chose the wrong choice C 50 times.<br>
I also plotted the logprobs as a line graph.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/f/5/f/f5ffeb171ff8926ca42eec1fb313bb3084763091.png" data-download-href="/uploads/short-url/z6dhwPK4eUgNCghAcaFznnGX8hH.png?dl=1" title="image1"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/f/5/f/f5ffeb171ff8926ca42eec1fb313bb3084763091_2_690x437.png" alt="image1" data-base62-sha1="z6dhwPK4eUgNCghAcaFznnGX8hH" width="690" height="437" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/f/5/f/f5ffeb171ff8926ca42eec1fb313bb3084763091_2_690x437.png, https://global.discourse-cdn.com/openai1/original/4X/f/5/f/f5ffeb171ff8926ca42eec1fb313bb3084763091.png 1.5x, https://global.discourse-cdn.com/openai1/original/4X/f/5/f/f5ffeb171ff8926ca42eec1fb313bb3084763091.png 2x" data-dominant-color="FBF9F7"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image1</span><span class="informations">720×457 38.6 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>Obviously, it chose the wrong option C almost 100% of the time in 50 trials, which means that its choice was not random.</p>
<p>To observe how it came to this conclusion, I added the following to the user message and observed the CoT process.</p>
<blockquote>
<p>Along with your answer, explain step-by-step why you chose that answer.</p>
</blockquote>
<p>Then the following explanation caught my attention.</p>
<blockquote>
<p>100 can be considered as 100/1 = 100.00 (for comparison purposes)</p>
</blockquote>
<p>The following explanation also caught my attention.</p>
<blockquote>
<ol start="3">
<li><strong>Order the numbers from smallest to largest based on the comparison</strong>:
<ul>
<li>The smallest number is 0.99 (which is 99/100).</li>
<li>The next larger number is 1.01 (which is 101/100), but when compared to 100, it’s clear that 1.01 is actually smaller than 100.00, indicating a mistake in my initial comparison step. The correct comparison should recognize that 100.00 is indeed larger than both 0.99 and 1.01, but it’s placed between them in terms of the options provided. This means:
<ul>
<li>0.99 (99/100) is the smallest.</li>
<li>100.00 is larger than 0.99 but is meant to be compared directly to 1.01 (101/100) in the context of the options, showing a misstep in my explanation. >Correctly, 100.00 is not directly compared to 1.01 in a numerical sense but is the middle value in the correct option.</li>
<li>1.01 (101/100) is larger than 0.99.</li>
</ul>
</li>
</ul>
</li>
</ol>
</blockquote>
<blockquote>
<ol start="4">
<li><strong>Correcting the oversight</strong>:
<ul>
<li>Upon correctly assessing the comparison, it’s evident that 99/100 (0.99) is less than 100, and 100 is less than 101/100 (1.01), which aligns with option C: 99/100 < 100 < 101/100.</li>
</ul>
</li>
</ol>
</blockquote>
<p>After getting the right conclusion the first time, it dares to pick the wrong choice again.</p>
<p>I also looked at the average of the cumulative token probabilities (perplexity) from the logprob to see how confident the language model is.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/5/9/8/5987481af47c1fc2acb09192dad06f314dc360e9.png" data-download-href="/uploads/short-url/cM0kJMWHQk3X9Ecyhwb3IsDvZ69.png?dl=1" title="image2"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/5/9/8/5987481af47c1fc2acb09192dad06f314dc360e9_2_248x500.png" alt="image2" data-base62-sha1="cM0kJMWHQk3X9Ecyhwb3IsDvZ69" width="248" height="500" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/5/9/8/5987481af47c1fc2acb09192dad06f314dc360e9_2_248x500.png, https://global.discourse-cdn.com/openai1/optimized/4X/5/9/8/5987481af47c1fc2acb09192dad06f314dc360e9_2_372x750.png 1.5x, https://global.discourse-cdn.com/openai1/original/4X/5/9/8/5987481af47c1fc2acb09192dad06f314dc360e9.png 2x" data-dominant-color="322A7A"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image2</span><span class="informations">373×751 42 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>For clarification, I would like to add that this question was not originally discovered by me.</p>
<p>This problem, where GPT-4 always makes a mistake was pointed out by a Japanese cognitive psychologist with a Ph.D. from the Department of Psychology at Northwestern University, USA, and had already been reported in June 2023 (not specific to the Turbo model).</p>
<p>I understand that we cannot know the “why” of the behavior of proprietary language models like GPT-4.</p>
<p>It’s unfortunate that my speculations and insights are limited, but I would be very interested to hear your thoughts, insight.</p>
<hr>
<p>The above text was translated from Japanese with the help of DeepL and a dictionary site.<br>
So it’s my apologies if there are any nuances or other things that aren’t correct, and I hope you will understand that it is a challenge for me to write in English.</p> | 73 | 0 | ed0e16a3dd | 1 | null | 25 | I have noticed that the GPT-4 has a strong preference for certain choices that are not correct in questions involving calculations and comparisons of fractions.
The following is a specific user message.
>
> Which of the following three numbers is correct in order from smallest to largest?
>
>
> Choose one:
>
>
> A: 99 / 100<101 / 100<100
>
> B: 100<99 / 100<101 / 100
>
> C: 99 / 100<100<101 / 100
>
>
>
To avoid complicating the discussion, I added this here.
>
> Only show the correct alphabetical letter in your response.
>
>
>
I used gpt-4-turbo-preview to get this result and logprobs.
The temperature parameter was set to 0 and no other hyperparameters were used.
The result is that out of 50 trials we chose the wrong choice C 50 times.
I also plotted the logprobs as a line graph.
I may need to set top\_logprobs to 2 or higher if logprobs has a high value here, but I did not use top\_logprobs here because logprobs was almost 0 on all trials.
Then I used gpt-4-turbo-preview to get this result and logprobs.
The temperature parameter was set to 0 and no other hyperparameters were used.
The result is that out of 50 trials we chose the wrong choice C 50 times.
I also plotted the logprobs as a line graph.
[image1720×457 38.6 KB](https://global.discourse-cdn.com/openai1/original/4X/f/5/f/f5ffeb171ff8926ca42eec1fb313bb3084763091.png "image1")
Obviously, it chose the wrong option C almost 100% of the time in 50 trials, which means that its choice was not random.
To observe how it came to this conclusion, I added the following to the user message and observed the CoT process.
>
> Along with your answer, explain step-by-step why you chose that answer.
>
>
>
Then the following explanation caught my attention.
>
> 100 can be considered as 100/1 = 100.00 (for comparison purposes)
>
>
>
The following explanation also caught my attention.
>
> 3. **Order the numbers from smallest to largest based on the comparison**:
> * The smallest number is 0.99 (which is 99/100).
> * The next larger number is 1.01 (which is 101/100), but when compared to 100, it’s clear that 1.01 is actually smaller than 100.00, indicating a mistake in my initial comparison step. The correct comparison should recognize that 100.00 is indeed larger than both 0.99 and 1.01, but it’s placed between them in terms of the options provided. This means:
> + 0.99 (99/100) is the smallest.
> + 100.00 is larger than 0.99 but is meant to be compared directly to 1.01 (101/100) in the context of the options, showing a misstep in my explanation. >Correctly, 100.00 is not directly compared to 1.01 in a numerical sense but is the middle value in the correct option.
> + 1.01 (101/100) is larger than 0.99.
>
>
>
>
> 4. **Correcting the oversight**:
> * Upon correctly assessing the comparison, it’s evident that 99/100 (0.99) is less than 100, and 100 is less than 101/100 (1.01), which aligns with option C: 99/100 < 100 < 101/100.
>
>
>
After getting the right conclusion the first time, it dares to pick the wrong choice again.
I also looked at the average of the cumulative token probabilities (perplexity) from the logprob to see how confident the language model is.
[image2373×751 42 KB](https://global.discourse-cdn.com/openai1/original/4X/5/9/8/5987481af47c1fc2acb09192dad06f314dc360e9.png "image2")
For clarification, I would like to add that this question was not originally discovered by me.
This problem, where GPT-4 always makes a mistake was pointed out by a Japanese cognitive psychologist with a Ph.D. from the Department of Psychology at Northwestern University, USA, and had already been reported in June 2023 (not specific to the Turbo model).
I understand that we cannot know the “why” of the behavior of proprietary language models like GPT-4.
It’s unfortunate that my speculations and insights are limited, but I would be very interested to hear your thoughts, insight.
---
The above text was translated from Japanese with the help of DeepL and a dictionary site.
So it’s my apologies if there are any nuances or other things that aren’t correct, and I hope you will understand that it is a challenge for me to write in English.
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892657 | Sampling | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,679 | 2024-02-25T19:21:50.931Z | <p><img src="https://emoji.discourse-cdn.com/twitter/thinking.png?v=12" title=":thinking:" class="emoji only-emoji" alt=":thinking:" loading="lazy" width="20" height="20"></p>
<p>It’s an interesting post, and I wonder if this test can be generalized to gauge raw reasoning depth.</p>
<p>But to be fair, it’s not exactly fair. It’s a convoluted multi-step reasoning problem with a trick, and you’re asking for a gut inference…</p>
<p>I always keep saying, LLMs aren’t calculators, and shouldn’t be used as such…</p> | 47 | 1 | 69bb4acfca | 2 | null | 25 | 
It’s an interesting post, and I wonder if this test can be generalized to gauge raw reasoning depth.
But to be fair, it’s not exactly fair. It’s a convoluted multi-step reasoning problem with a trick, and you’re asking for a gut inference…
I always keep saying, LLMs aren’t calculators, and shouldn’t be used as such…
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892679 | LLMs | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,680 | 2024-02-25T19:22:50.309Z | <p>You set the temperature to 0, so except for slight indeterminacy, you should expect the same top answer every time, without revealing other statistics.</p>
<p>With logprobs, you don’t need to run trials; you can just get the top-5, and see what the model had as top options.</p>
<p>I also developed a method to get more probability space than top 5. Let’s say the 5 occupy a probability mass of 50 percent. Set the top-p to 0.75, temperature high, and continue trials until your total probabilities sum to that or greater, by collecting sampled tokens also.</p>
<p>I think the math problem could be described more clearly to the ai, or in practice, you could give it response length in order to contemplate it’s answer.</p> | 46 | 2 | b368833582 | 3 | null | 25 | You set the temperature to 0, so except for slight indeterminacy, you should expect the same top answer every time, without revealing other statistics.
With logprobs, you don’t need to run trials; you can just get the top-5, and see what the model had as top options.
I also developed a method to get more probability space than top 5. Let’s say the 5 occupy a probability mass of 50 percent. Set the top-p to 0.75, temperature high, and continue trials until your total probabilities sum to that or greater, by collecting sampled tokens also.
I think the math problem could be described more clearly to the ai, or in practice, you could give it response length in order to contemplate it’s answer.
| api | neutral | 0.865171 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892680 | Sampling | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,717 | 2024-02-25T19:46:47.776Z | <p>Thanks for your replies!</p>
<aside class="quote no-group" data-username="Diet" data-post="2" data-topic="653997">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/diet/48/229305_2.png" class="avatar"> Diet:</div>
<blockquote>
<p>But to be fair, it’s not exactly fair. It’s a convoluted multi-step reasoning problem with a trick, and you’re asking for a gut inference…</p>
</blockquote>
</aside>
<p>Well, maybe that’s regard as so.<br>
But even without discussing benchmarking, it’s very interesting to see that the GPT-4, when it was announced, also solved physics problems for difficult science universities, and that it got the problems used in this elementary school material wrong.</p>
<aside class="quote no-group" data-username="_j" data-post="3" data-topic="653997">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/_j/48/277961_2.png" class="avatar"> _j:</div>
<blockquote>
<p>I think the math problem could be described more clearly to the ai, or in practice, you could give it response length in order to contemplate it’s answer.</p>
</blockquote>
</aside>
<p>Well, there are many ways to look at it, and I think we can try to get the language model to answer correctly.<br>
I don’t know much about GPT-4 myself, so I’m sure I’m wrong about a lot of details.</p>
<p>But, please understand that this is in no way a criticism of the GPT-4, but rather an intention based on discovery(not originally mine, but…) and interest, or the exchange of opinions and insights.</p> | 39 | 1 | ed0e16a3dd | 4 | null | 25 | Thanks for your replies!
 Diet:
>
> But to be fair, it’s not exactly fair. It’s a convoluted multi-step reasoning problem with a trick, and you’re asking for a gut inference…
>
>
>
Well, maybe that’s regard as so.
But even without discussing benchmarking, it’s very interesting to see that the GPT-4, when it was announced, also solved physics problems for difficult science universities, and that it got the problems used in this elementary school material wrong.
 \_j:
>
> I think the math problem could be described more clearly to the ai, or in practice, you could give it response length in order to contemplate it’s answer.
>
>
>
Well, there are many ways to look at it, and I think we can try to get the language model to answer correctly.
I don’t know much about GPT-4 myself, so I’m sure I’m wrong about a lot of details.
But, please understand that this is in no way a criticism of the GPT-4, but rather an intention based on discovery(not originally mine, but…) and interest, or the exchange of opinions and insights.
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892717 | Neural Models | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,731 | 2024-02-25T19:53:09.834Z | <aside class="quote no-group" data-username="dignity_for_all" data-post="4" data-topic="653997">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/dignity_for_all/48/300058_2.png" class="avatar"> dignity_for_all:</div>
<blockquote>
<p>But even without talking about benchmarking, it is very interesting to see that the GPT-4, when it was announced, also solved physics problems for difficult science universities, and that they got the problems used in this elementary school material wrong.</p>
</blockquote>
</aside>
<p>I think it’s super interesting that the model struggles with the problem even with chain of thought. I think an important learning (that most of us knew intuitively) is that the models exhibit some form of dyscalculia that needs to be mitigated.</p>
<p>It’s not that the models can’t solve these issues; they can, but they need the right tools.</p>
<p>If you pop this into chatgpt, it’s not an issue at all:</p>
<blockquote>
<p>Which of the following three numbers is correct in order from smallest to largest?</p>
<p>Choose one:</p>
<p>A: 99 / 100<101 / 100<100<br>
B: 100<99 / 100<101 / 100<br>
C: 99 / 100<100<101 / 100</p>
<p>Instead of answering directly, please formulate a plan to solve this problem programmatically.</p>
</blockquote>
<p><a href="https://chat.openai.com/share/af10390e-5f04-4ce5-82f1-99178f4a1afd" class="onebox" target="_blank" rel="noopener">https://chat.openai.com/share/af10390e-5f04-4ce5-82f1-99178f4a1afd</a></p> | 36 | 1 | 69bb4acfca | 5 | null | 25 |
 dignity\_for\_all:
>
> But even without talking about benchmarking, it is very interesting to see that the GPT-4, when it was announced, also solved physics problems for difficult science universities, and that they got the problems used in this elementary school material wrong.
>
>
>
I think it’s super interesting that the model struggles with the problem even with chain of thought. I think an important learning (that most of us knew intuitively) is that the models exhibit some form of dyscalculia that needs to be mitigated.
It’s not that the models can’t solve these issues; they can, but they need the right tools.
If you pop this into chatgpt, it’s not an issue at all:
>
> Which of the following three numbers is correct in order from smallest to largest?
>
>
> Choose one:
>
>
> A: 99 / 100<101 / 100<100
>
> B: 100<99 / 100<101 / 100
>
> C: 99 / 100<100<101 / 100
>
>
> Instead of answering directly, please formulate a plan to solve this problem programmatically.
>
>
>
<https://chat.openai.com/share/af10390e-5f04-4ce5-82f1-99178f4a1afd>
| api | neutral | 0.494421 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892731 | Mathematics | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,736 | 2024-02-25T19:56:11.343Z | <aside class="quote no-group" data-username="Diet" data-post="5" data-topic="653997">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/diet/48/229305_2.png" class="avatar"> Diet:</div>
<blockquote>
<p><a href="https://chat.openai.com/share/af10390e-5f04-4ce5-82f1-99178f4a1afd">https://chat.openai.com/share/af10390e-5f04-4ce5-82f1-99178f4a1afd</a></p>
</blockquote>
</aside>
<p>Yes! When ChatGPT solves the whole thing in a Python program, it gets it right!</p> | 33 | 1 | ed0e16a3dd | 6 | null | 25 |
 Diet:
>
> <https://chat.openai.com/share/af10390e-5f04-4ce5-82f1-99178f4a1afd>
>
>
>
Yes! When ChatGPT solves the whole thing in a Python program, it gets it right!
| api | neutral | 0.665911 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892736 | Miscellaneous (5) | Miscellaneous (27) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,739 | 2024-02-25T19:57:47.622Z | <aside class="quote no-group" data-username="dignity_for_all" data-post="6" data-topic="653997">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/dignity_for_all/48/300058_2.png" class="avatar"> dignity_for_all:</div>
<blockquote>
<p>Yes! When ChatGPT solves the whole thing in a Python program, it gets it right!</p>
</blockquote>
</aside>
<p>I’m just thinking that the first time I looked at your OP, I thought, huh? But it is C, what’s he talking about? <img src="https://emoji.discourse-cdn.com/twitter/laughing.png?v=12" title=":laughing:" class="emoji" alt=":laughing:" loading="lazy" width="20" height="20"> - so I empathize with our friend Turbo here. <img src="https://emoji.discourse-cdn.com/twitter/rofl.png?v=12" title=":rofl:" class="emoji" alt=":rofl:" loading="lazy" width="20" height="20"></p> | 32 | 1 | 69bb4acfca | 7 | null | 25 |
 dignity\_for\_all:
>
> Yes! When ChatGPT solves the whole thing in a Python program, it gets it right!
>
>
>
I’m just thinking that the first time I looked at your OP, I thought, huh? But it is C, what’s he talking about?  - so I empathize with our friend Turbo here. 
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892739 | Emotion | Emoji (8) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,745 | 2024-02-25T20:02:36.622Z | <aside class="quote no-group" data-username="Diet" data-post="7" data-topic="653997">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/diet/48/229305_2.png" class="avatar"> Diet:</div>
<blockquote>
<p>so I empathize with our friend Turbo here. <img src="https://emoji.discourse-cdn.com/twitter/rofl.png?v=12" title=":rofl:" class="emoji" alt=":rofl:" loading="lazy" width="20" height="20"></p>
</blockquote>
</aside>
<p>I know how you feel, as I always make mistakes in this kind of problems too!</p> | 34 | 0 | ed0e16a3dd | 8 | null | 25 |
 Diet:
>
> so I empathize with our friend Turbo here. 
>
>
>
I know how you feel, as I always make mistakes in this kind of problems too!
| api | neutral | 0.604492 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892745 | Emotion | Emoji (8) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,869 | 2024-02-25T21:39:48.234Z | <aside class="quote no-group" data-username="_j" data-post="3" data-topic="653997">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/_j/48/277961_2.png" class="avatar"> _j:</div>
<blockquote>
<p>I also developed a method to get more probability space than top 5. Let’s say the 5 occupy a probability mass of 50 percent. Set the top-p to 0.75, temperature high, and continue trials until your total probabilities sum to that or greater, by collecting sampled tokens also.</p>
</blockquote>
</aside>
<p>I’m bowled over by your detailed knowledge of gpt-4!</p> | 29 | 0 | ed0e16a3dd | 9 | null | 25 |
 \_j:
>
> I also developed a method to get more probability space than top 5. Let’s say the 5 occupy a probability mass of 50 percent. Set the top-p to 0.75, temperature high, and continue trials until your total probabilities sum to that or greater, by collecting sampled tokens also.
>
>
>
I’m bowled over by your detailed knowledge of gpt-4!
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892869 | Sampling | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 892,947 | 2024-02-25T22:32:42.083Z | <p>I’ll let the topic stay as it is for a little while longer because I’d like to know the opinions and insights of various people if possible.</p>
<p>And I think that is acceptable.</p> | 26 | 0 | ed0e16a3dd | 10 | null | 25 | I’ll let the topic stay as it is for a little while longer because I’d like to know the opinions and insights of various people if possible.
And I think that is acceptable.
| api | neutral | 0.629005 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/892947 | AGI | Emoji (8) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 894,741 | 2024-02-26T16:47:34.471Z | <p>I believe the phenomenon of reaching a correct conclusion once and then choosing a wrong conclusion again is a result of the self-refining process in iterative refinement backfiring.</p>
<p>In particular, in the second step of the step-by-step reasoning, “Compare the numbers,” after reaching the correct conclusion that 100 is the largest, GPT-4 called this an “oversight” and described it as a “mistake in interpreting numerical values.”</p>
<blockquote>
<ol start="2">
<li>
<p><strong>Compare the numbers</strong>:</p>
<ul>
<li>Comparing 0.99 (99/100) and 100, it’s clear that 0.99 is much smaller than 100.</li>
<li>Comparing 100 and 1.01 (101/100), 100 is significantly larger than 1.01.</li>
<li>Therefore, in ascending order, we have 0.99 (99/100) as the smallest, followed by 1.01 (101/100), and then 100 as the largest. >However, this comparison was incorrect in the context of the given options, as it mistakenly considered 100 larger than 1.01 due to a misinterpretation. The correct comparison should recognize that 100 (or 100.00) is indeed larger than both 0.99 and 1.01, but the mistake was in the interpretation of numerical values. Let’s correct this oversight:</li>
</ul>
<p>Correcting the oversight:</p>
<ul>
<li>0.99 (99/100) is less than 100.</li>
<li>100 is less than 1.01 (101/100) when considering their actual numerical values, not as previously misstated. The correct understanding is that 100 (or 100.00) is indeed larger than 0.99 but smaller than 1.01, which was an error in the initial explanation due to a misinterpretation of the numerical comparison.</li>
</ul>
</li>
</ol>
</blockquote>
<p>Although the self-refining process in iterative refinement is mostly part of the effort to reach a correct conclusion through logical reasoning, I speculate that in this case it backfired.</p> | 21 | 0 | ed0e16a3dd | 11 | null | 25 | I believe the phenomenon of reaching a correct conclusion once and then choosing a wrong conclusion again is a result of the self-refining process in iterative refinement backfiring.
In particular, in the second step of the step-by-step reasoning, “Compare the numbers,” after reaching the correct conclusion that 100 is the largest, GPT-4 called this an “oversight” and described it as a “mistake in interpreting numerical values.”
>
> 2. **Compare the numbers**:
>
>
> * Comparing 0.99 (99/100) and 100, it’s clear that 0.99 is much smaller than 100.
> * Comparing 100 and 1.01 (101/100), 100 is significantly larger than 1.01.
> * Therefore, in ascending order, we have 0.99 (99/100) as the smallest, followed by 1.01 (101/100), and then 100 as the largest. >However, this comparison was incorrect in the context of the given options, as it mistakenly considered 100 larger than 1.01 due to a misinterpretation. The correct comparison should recognize that 100 (or 100.00) is indeed larger than both 0.99 and 1.01, but the mistake was in the interpretation of numerical values. Let’s correct this oversight:Correcting the oversight:
>
>
> * 0.99 (99/100) is less than 100.
> * 100 is less than 1.01 (101/100) when considering their actual numerical values, not as previously misstated. The correct understanding is that 100 (or 100.00) is indeed larger than 0.99 but smaller than 1.01, which was an error in the initial explanation due to a misinterpretation of the numerical comparison.
>
>
>
Although the self-refining process in iterative refinement is mostly part of the effort to reach a correct conclusion through logical reasoning, I speculate that in this case it backfired.
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/894741 | Mathematics | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,265 | 2024-02-26T22:43:04.794Z | <p>Interestingly, if you rewrite the problem using improper fractions for all ChatGPT gets the right answer.</p>
<p><a href="https://chat.openai.com/share/ec9a2e79-13cd-4c47-b46f-9a42ee4c2d54" class="onebox" target="_blank" rel="noopener">https://chat.openai.com/share/ec9a2e79-13cd-4c47-b46f-9a42ee4c2d54</a></p>
<pre><code class="lang-auto">Which of the following three numbers is correct in order from smallest to largest?
Choose one:
A: 99 / 100 < 101 / 100 < 100 / 1
B: 100 / 1 < 99 / 100 < 101 / 100
C: 99 / 100 < 100 / 1 < 101 / 100
</code></pre>
<p>I tried using parentheses around the fractions, but that failed.</p>
<p>Reframing the question works too.</p>
<pre><code class="lang-auto">$x = 99/100$
$y = 101/100$
$z = 100$
Which of the following is correct?
A: $x < y < z$
B: $z < x < y$
C: $x < z < y$
</code></pre>
<p>I did elicit one interesting response though where ChatGPT suggested there was a typo in the problem.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/4/e/3/4e319c11c165ec7127f65e1e93c0f1f82a5d5f4d.png" data-download-href="/uploads/short-url/b9JwUFtE3HUtZInHzLG5pUskkBD.png?dl=1" title="1000011435"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/4/e/3/4e319c11c165ec7127f65e1e93c0f1f82a5d5f4d_2_242x500.png" alt="1000011435" data-base62-sha1="b9JwUFtE3HUtZInHzLG5pUskkBD" width="242" height="500" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/4/e/3/4e319c11c165ec7127f65e1e93c0f1f82a5d5f4d_2_242x500.png, https://global.discourse-cdn.com/openai1/optimized/4X/4/e/3/4e319c11c165ec7127f65e1e93c0f1f82a5d5f4d_2_363x750.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/4/e/3/4e319c11c165ec7127f65e1e93c0f1f82a5d5f4d_2_484x1000.png 2x" data-dominant-color="2C2C2D"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">1000011435</span><span class="informations">1080×2225 254 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p> | 18 | 1 | ae7a0d8db8 | 12 | null | 25 | Interestingly, if you rewrite the problem using improper fractions for all ChatGPT gets the right answer.
<https://chat.openai.com/share/ec9a2e79-13cd-4c47-b46f-9a42ee4c2d54>
```
Which of the following three numbers is correct in order from smallest to largest?
Choose one:
A: 99 / 100 < 101 / 100 < 100 / 1
B: 100 / 1 < 99 / 100 < 101 / 100
C: 99 / 100 < 100 / 1 < 101 / 100
```
I tried using parentheses around the fractions, but that failed.
Reframing the question works too.
```
$x = 99/100$
$y = 101/100$
$z = 100$
Which of the following is correct?
A: $x < y < z$
B: $z < x < y$
C: $x < z < y$
```
I did elicit one interesting response though where ChatGPT suggested there was a typo in the problem.
[10000114351080×2225 254 KB](https://global.discourse-cdn.com/openai1/original/4X/4/e/3/4e319c11c165ec7127f65e1e93c0f1f82a5d5f4d.png "1000011435")
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895265 | Mathematics | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,300 | 2024-02-26T23:15:54.455Z | <p>Yes, GPT-4 dares to confidently choose the wrong option in the last part of the conclusion (while still arriving at the correct conclusion in the reasoning process)!</p>
<p>It kind of looks like it’s being stubborn and passing on the user’s point that it’s wrong.</p>
<p>By the way, Gemini Ultra also chose the same wrong option many times.</p>
<p>There is no way that Google and OpenAI share training data and parameters, and it is very interesting that completely different language models choose the same wrong option only in the final conclusion.</p> | 16 | 1 | ed0e16a3dd | 13 | null | 25 | Yes, GPT-4 dares to confidently choose the wrong option in the last part of the conclusion (while still arriving at the correct conclusion in the reasoning process)!
It kind of looks like it’s being stubborn and passing on the user’s point that it’s wrong.
By the way, Gemini Ultra also chose the same wrong option many times.
There is no way that Google and OpenAI share training data and parameters, and it is very interesting that completely different language models choose the same wrong option only in the final conclusion.
| api | negative | 0.551798 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895300 | GPT Model Training | GPTs (4) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,303 | 2024-02-26T23:16:57.589Z | <h4><a name="just-some-prompting-1" class="anchor" href="#just-some-prompting-1"></a>Just some prompting:</h4>
<blockquote>
<p>This multiple-choice answer is confusing.</p>
<ol>
<li>Enclose fractions of each possible answer within parenthesis so they can be observed clearly;</li>
<li>Evaluate each expression, and create an answer key for which is correct, with justification.</li>
</ol>
</blockquote>
<p><strong>To then get an answer easy for both human and AI to see:</strong></p>
<p>To address your request, I will first enclose each fraction in the multiple-choice answers within parentheses for clarity. Then, I’ll evaluate each expression to create an answer key and justify which option is correct.</p>
<p>The reformatted options are:</p>
<p>A: (99 / 100) < (101 / 100) < (100 / 1)<br>
B: (100 / 1) < (99 / 100) < (101 / 100)<br>
C: (99 / 100) < (100 / 1) < (101 / 100)</p>
<p>Next, I will evaluate each fraction and then compare them to determine the correct order from smallest to largest.</p>
<p>The evaluated fractions are as follows:</p>
<ul>
<li><span class="math">( \frac{99}{100} = 0.99 </span>)</li>
<li><span class="math">( \frac{101}{100} = 1.01 </span>)</li>
<li><span class="math">( \frac{100}{1} = 100.0 </span>)</li>
</ul>
<p>Based on these evaluations:</p>
<ul>
<li>Option A proposes: ( 0.99 < 1.01 < 100.0 ), which is correct in ascending order.</li>
<li>Option B suggests: ( 100.0 < 0.99 < 1.01 ), which is incorrect because ( 100.0 ) is larger than both ( 0.99 ) and ( 1.01 ).</li>
<li>Option C proposes: ( 0.99 < 100.0 < 1.01 ), which is incorrect because ( 100.0 ) is larger than both ( 0.99 ) and ( 1.01 ), and it incorrectly places ( 1.01 ) after ( 100.0 ).</li>
</ul>
<p>Therefore, the correct answer is <strong>Option A</strong>: <span class="math">( \frac{99}{100} < \frac{101}{100} < \frac{100}{1} </span>), as it correctly orders the numbers from smallest to largest.</p> | 14 | 1 | b368833582 | 14 | null | 25 | #### Just some prompting:
>
> This multiple-choice answer is confusing.
>
>
> 1. Enclose fractions of each possible answer within parenthesis so they can be observed clearly;
> 2. Evaluate each expression, and create an answer key for which is correct, with justification.
>
>
>
**To then get an answer easy for both human and AI to see:**
To address your request, I will first enclose each fraction in the multiple-choice answers within parentheses for clarity. Then, I’ll evaluate each expression to create an answer key and justify which option is correct.
The reformatted options are:
A: (99 / 100) < (101 / 100) < (100 / 1)
B: (100 / 1) < (99 / 100) < (101 / 100)
C: (99 / 100) < (100 / 1) < (101 / 100)
Next, I will evaluate each fraction and then compare them to determine the correct order from smallest to largest.
The evaluated fractions are as follows:
* ( \frac{99}{100} = 0.99 )
* ( \frac{101}{100} = 1.01 )
* ( \frac{100}{1} = 100.0 )
Based on these evaluations:
* Option A proposes: ( 0.99 < 1.01 < 100.0 ), which is correct in ascending order.
* Option B suggests: ( 100.0 < 0.99 < 1.01 ), which is incorrect because ( 100.0 ) is larger than both ( 0.99 ) and ( 1.01 ).
* Option C proposes: ( 0.99 < 100.0 < 1.01 ), which is incorrect because ( 100.0 ) is larger than both ( 0.99 ) and ( 1.01 ), and it incorrectly places ( 1.01 ) after ( 100.0 ).
Therefore, the correct answer is **Option A**: ( \frac{99}{100} < \frac{101}{100} < \frac{100}{1} ), as it correctly orders the numbers from smallest to largest.
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895303 | Mathematics | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,344 | 2024-02-26T23:41:44.692Z | <p>It is incredibly persistent in wanting to be wrong.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/5/5/7/557c1ae59b1f006637f0e4353bd27ffde181ac1e.png" data-download-href="/uploads/short-url/ccetGL80MQtlZFWQJfYDbdBmk2i.png?dl=1" title="1000011436"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/5/5/7/557c1ae59b1f006637f0e4353bd27ffde181ac1e_2_242x500.png" alt="1000011436" data-base62-sha1="ccetGL80MQtlZFWQJfYDbdBmk2i" width="242" height="500" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/5/5/7/557c1ae59b1f006637f0e4353bd27ffde181ac1e_2_242x500.png, https://global.discourse-cdn.com/openai1/optimized/4X/5/5/7/557c1ae59b1f006637f0e4353bd27ffde181ac1e_2_363x750.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/5/5/7/557c1ae59b1f006637f0e4353bd27ffde181ac1e_2_484x1000.png 2x" data-dominant-color="2D2D2D"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">1000011436</span><span class="informations">1080×2225 268 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/8/5/f/85fef7507158ed48a9ffa744dc7175ab031e41d1.jpeg" data-download-href="/uploads/short-url/j7nLtXotel3sV2hdtnhAtepyLtf.jpeg?dl=1" title="1000011438"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/8/5/f/85fef7507158ed48a9ffa744dc7175ab031e41d1_2_169x500.jpeg" alt="1000011438" data-base62-sha1="j7nLtXotel3sV2hdtnhAtepyLtf" width="169" height="500" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/8/5/f/85fef7507158ed48a9ffa744dc7175ab031e41d1_2_169x500.jpeg, https://global.discourse-cdn.com/openai1/optimized/4X/8/5/f/85fef7507158ed48a9ffa744dc7175ab031e41d1_2_253x750.jpeg 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/8/5/f/85fef7507158ed48a9ffa744dc7175ab031e41d1_2_338x1000.jpeg 2x" data-dominant-color="2A2A2A"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">1000011438</span><span class="informations">1080×3186 289 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div><br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/5/1/5/515194a1dfdf04f2c557a923d987dc362edcd32a.png" data-download-href="/uploads/short-url/bBnsz1GxzS53WGAYHccbFmLn9bA.png?dl=1" title="1000011439"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/5/1/5/515194a1dfdf04f2c557a923d987dc362edcd32a_2_242x500.png" alt="1000011439" data-base62-sha1="bBnsz1GxzS53WGAYHccbFmLn9bA" width="242" height="500" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/5/1/5/515194a1dfdf04f2c557a923d987dc362edcd32a_2_242x500.png, https://global.discourse-cdn.com/openai1/optimized/4X/5/1/5/515194a1dfdf04f2c557a923d987dc362edcd32a_2_363x750.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/5/1/5/515194a1dfdf04f2c557a923d987dc362edcd32a_2_484x1000.png 2x" data-dominant-color="2A2A2B"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">1000011439</span><span class="informations">1080×2225 223 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>It seems to be a case of the model <em>needing</em> the pattern to continue.</p>
<p>I would need to see a result from around the GPT-4 launch to compare, but I don’t recall it being this stubborn in its wrongness.</p>
<p><a href="https://chat.openai.com/share/28da0868-0c12-43a2-ab7e-5aa6fbc4c1bc" class="onebox" target="_blank" rel="noopener">https://chat.openai.com/share/28da0868-0c12-43a2-ab7e-5aa6fbc4c1bc</a></p> | 12 | 0 | ae7a0d8db8 | 15 | null | 25 | It is incredibly persistent in wanting to be wrong.
[10000114361080×2225 268 KB](https://global.discourse-cdn.com/openai1/original/4X/5/5/7/557c1ae59b1f006637f0e4353bd27ffde181ac1e.png "1000011436")
[10000114381080×3186 289 KB](https://global.discourse-cdn.com/openai1/original/4X/8/5/f/85fef7507158ed48a9ffa744dc7175ab031e41d1.jpeg "1000011438")
[10000114391080×2225 223 KB](https://global.discourse-cdn.com/openai1/original/4X/5/1/5/515194a1dfdf04f2c557a923d987dc362edcd32a.png "1000011439")
It seems to be a case of the model *needing* the pattern to continue.
I would need to see a result from around the GPT-4 launch to compare, but I don’t recall it being this stubborn in its wrongness.
<https://chat.openai.com/share/28da0868-0c12-43a2-ab7e-5aa6fbc4c1bc>
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895344 | Campaign | GPTs (4) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,347 | 2024-02-26T23:45:04.749Z | <p>As an experienced proompter, you can probably get any result you want.</p>
<p>The question is, is there a general strategy to ensure validity without human oversight?</p>
<p>My goto is to use the LLM for reformulation, but never evaluation.</p> | 12 | 1 | 69bb4acfca | 16 | null | 25 | As an experienced proompter, you can probably get any result you want.
The question is, is there a general strategy to ensure validity without human oversight?
My goto is to use the LLM for reformulation, but never evaluation.
| api | neutral | 0.761789 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895347 | LLMs | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,387 | 2024-02-26T23:59:47.721Z | <p>Some more experiments,</p>
<p><img src="https://emoji.discourse-cdn.com/twitter/no_entry_sign.png?v=12" title=":no_entry_sign:" class="emoji" alt=":no_entry_sign:" loading="lazy" width="20" height="20"> <a href="https://platform.openai.com/playground/p/zzEmpFvMtRdETBJWlnUUKttA?model=gpt-4-0613&mode=chat">Two Decimal Places</a></p>
<p><img src="https://emoji.discourse-cdn.com/twitter/no_entry_sign.png?v=12" title=":no_entry_sign:" class="emoji" alt=":no_entry_sign:" loading="lazy" width="20" height="20"> <a href="https://platform.openai.com/playground/p/1lmQIvlqaK5ymtLmPzCzneiF?model=gpt-4-0613&mode=chat">Two Significant Digits</a></p>
<p><img src="https://emoji.discourse-cdn.com/twitter/white_check_mark.png?v=12" title=":white_check_mark:" class="emoji" alt=":white_check_mark:" loading="lazy" width="20" height="20"> <a href="https://platform.openai.com/playground/p/AJAAlOSBZc6m2LszVtBps5zN?model=gpt-4-0613&mode=chat">Scientific Notation</a></p>
<p>These were all done with <code>gpt-4-0613</code>.</p> | 12 | 0 | ae7a0d8db8 | 17 | null | 25 | Some more experiments,
 [Two Decimal Places](https://platform.openai.com/playground/p/zzEmpFvMtRdETBJWlnUUKttA?model=gpt-4-0613&mode=chat)
 [Two Significant Digits](https://platform.openai.com/playground/p/1lmQIvlqaK5ymtLmPzCzneiF?model=gpt-4-0613&mode=chat)
 [Scientific Notation](https://platform.openai.com/playground/p/AJAAlOSBZc6m2LszVtBps5zN?model=gpt-4-0613&mode=chat)
These were all done with `gpt-4-0613`.
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895387 | Emoji (3) | Embeddings (6) |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,412 | 2024-02-27T00:09:49.005Z | <p>The problem-solving can be generalized, or branching (at least you used to be able to do conditional logic in system instructions in the original 0613 gpt-3.5-turbo…)</p>
<p>Here’s both the technique I provide for the AI that could apply to most questions, and then the additional task it shall perform, it being gpt-4-0314 and not subsequently damaged…</p>
<h4><a name="system-1" class="anchor" href="#system-1"></a>system</h4>
<blockquote>
<p>You grade the homework performed by another AI.</p>
<ol>
<li>You solve the problem in your own manner using step-by-step simplification of the problem to its core elements, to then dive into the core logic of what the question is seeking, to then provide a fulfilling answer despite any deceptiveness present in high-IQ questions.</li>
<li>Then provide analysis regarding the answer that was provided, as a grader and correcter, on both the technique employed and the ultimate answer.</li>
</ol>
</blockquote>
<h4><a name="input-taken-from-first-chat-share-with-inconsequential-language-cleaned-2" class="anchor" href="#input-taken-from-first-chat-share-with-inconsequential-language-cleaned-2"></a>Input (taken from first chat share, with inconsequential language cleaned)</h4>
<blockquote>
<p>// Question:</p>
<p>Which of the following three numbers is correct in order from smallest to largest?</p>
<ul>
<li>
<p>Choose one:</p>
<p>A: 99 / 100<101 / 100<100<br>
B: 100<99 / 100<101 / 100<br>
C: 99 / 100<100<101 / 100</p>
</li>
</ul>
<p>// Proposed answer:</p>
<p>To solve this problem programmatically, we can follow these steps:</p>
<p>Parse the Fractions and Numbers: The given options contain fractions and whole numbers. We need to parse these into a format that can be easily compared. For instance, “99 / 100” can be parsed and stored as a fraction or a floating-point number (0.99 in this case).</p>
<p>Compare the Values: After parsing, we need to compare the values in each option to check if they are in ascending order. This involves comparing the first value with the second, and the second with the third in each option.</p>
<p>Determine the Correct Option: The option where the values are in correct ascending order (i.e., from smallest to largest) will be the correct answer.</p>
<p>Implement the Solution: We can implement this solution using a programming language like Python, which has built-in support for handling and comparing fractions.</p>
<p>Now, let’s implement this plan. (python runs)<br>
The correct option, where the numbers are in ascending order from smallest to largest, is Option A: 99/100 < 101/100 < 100.</p>
</blockquote>
<h4><a name="gpt-4-solving-with-new-technique-and-grading-until-max_tokens-3" class="anchor" href="#gpt-4-solving-with-new-technique-and-grading-until-max_tokens-3"></a>GPT-4 solving (with new technique) and grading (until max_tokens)</h4>
<blockquote>
<p>My Solution:</p>
<p>First, let’s simplify the fractions and convert the whole numbers to fractions with a denominator of 100 for easy comparison:</p>
<p>A: 99/100 < 101/100 < 10000/100<br>
B: 10000/100 < 99/100 < 101/100<br>
C: 99/100 < 10000/100 < 101/100</p>
<p>Now, let’s compare the values in each option:</p>
<p>A: 99/100 < 101/100 < 10000/100 (True)<br>
B: 10000/100 < 99/100 < 101/100 (False)<br>
C: 99/100 < 10000/100 < 101/100 (False)</p>
<p>The correct option, where the numbers are in ascending order from smallest to largest, is Option A: 99/100 < 101/100 < 100.</p>
<p>Analysis of the Proposed Answer:</p>
<p>The proposed answer correctly identified the steps to solve the problem and provided a clear explanation of the process. However, the implementation of the solution was not provided as mentioned in the plan. The final answer is correct, and the technique employed is appropriate for this type of problem. The only improvement would be to include the actual implementation in</p>
</blockquote>
<p>so:</p>
<ol>
<li>smart AI able to cope with new things</li>
<li>orientation towards problem-solving and expecting challenges via prompt,</li>
<li>lots of encouragement to write its own context to reflect on via output.</li>
</ol> | 12 | 2 | b368833582 | 18 | null | 25 | The problem-solving can be generalized, or branching (at least you used to be able to do conditional logic in system instructions in the original 0613 gpt-3.5-turbo…)
Here’s both the technique I provide for the AI that could apply to most questions, and then the additional task it shall perform, it being gpt-4-0314 and not subsequently damaged…
#### system
>
> You grade the homework performed by another AI.
>
>
> 1. You solve the problem in your own manner using step-by-step simplification of the problem to its core elements, to then dive into the core logic of what the question is seeking, to then provide a fulfilling answer despite any deceptiveness present in high-IQ questions.
> 2. Then provide analysis regarding the answer that was provided, as a grader and correcter, on both the technique employed and the ultimate answer.
>
>
>
#### Input (taken from first chat share, with inconsequential language cleaned)
>
> // Question:
>
>
> Which of the following three numbers is correct in order from smallest to largest?
>
>
> * Choose one:
>
>
> A: 99 / 100<101 / 100<100
>
> B: 100<99 / 100<101 / 100
>
> C: 99 / 100<100<101 / 100
>
>
> // Proposed answer:
>
>
> To solve this problem programmatically, we can follow these steps:
>
>
> Parse the Fractions and Numbers: The given options contain fractions and whole numbers. We need to parse these into a format that can be easily compared. For instance, “99 / 100” can be parsed and stored as a fraction or a floating-point number (0.99 in this case).
>
>
> Compare the Values: After parsing, we need to compare the values in each option to check if they are in ascending order. This involves comparing the first value with the second, and the second with the third in each option.
>
>
> Determine the Correct Option: The option where the values are in correct ascending order (i.e., from smallest to largest) will be the correct answer.
>
>
> Implement the Solution: We can implement this solution using a programming language like Python, which has built-in support for handling and comparing fractions.
>
>
> Now, let’s implement this plan. (python runs)
>
> The correct option, where the numbers are in ascending order from smallest to largest, is Option A: 99/100 < 101/100 < 100.
>
>
>
#### GPT-4 solving (with new technique) and grading (until max\_tokens)
>
> My Solution:
>
>
> First, let’s simplify the fractions and convert the whole numbers to fractions with a denominator of 100 for easy comparison:
>
>
> A: 99/100 < 101/100 < 10000/100
>
> B: 10000/100 < 99/100 < 101/100
>
> C: 99/100 < 10000/100 < 101/100
>
>
> Now, let’s compare the values in each option:
>
>
> A: 99/100 < 101/100 < 10000/100 (True)
>
> B: 10000/100 < 99/100 < 101/100 (False)
>
> C: 99/100 < 10000/100 < 101/100 (False)
>
>
> The correct option, where the numbers are in ascending order from smallest to largest, is Option A: 99/100 < 101/100 < 100.
>
>
> Analysis of the Proposed Answer:
>
>
> The proposed answer correctly identified the steps to solve the problem and provided a clear explanation of the process. However, the implementation of the solution was not provided as mentioned in the plan. The final answer is correct, and the technique employed is appropriate for this type of problem. The only improvement would be to include the actual implementation in
>
>
>
so:
1. smart AI able to cope with new things
2. orientation towards problem-solving and expecting challenges via prompt,
3. lots of encouragement to write its own context to reflect on via output.
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895412 | Mathematics | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,430 | 2024-02-27T00:19:48.545Z | <p>in summary: take the AI output, and give it back to the AI as human input and ask it to evaluate it. <img src="https://emoji.discourse-cdn.com/twitter/thinking.png?v=12" title=":thinking:" class="emoji" alt=":thinking:" loading="lazy" width="20" height="20"></p>
<p>I don’t know what they did so that the model prefers to be confidently wrong rather than reevaluate its own position.</p>
<p>But I’m thinking it should theoretically be possible to alter that behavior through fine-tuning?</p> | 12 | 0 | 69bb4acfca | 19 | null | 25 | in summary: take the AI output, and give it back to the AI as human input and ask it to evaluate it. 
I don’t know what they did so that the model prefers to be confidently wrong rather than reevaluate its own position.
But I’m thinking it should theoretically be possible to alter that behavior through fine-tuning?
| api | neutral | 0.824986 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895430 | Knowledge Classifier | Artificial Intelligence |
653,997 | [
"gpt-4"
] | On the logical reasoning ability of GPT-4 | "2024-02-25T18:59:32.530000Z" | 7 | 361 | 16 | 30 | 5 | 4,681 | 895,451 | 2024-02-27T00:31:47.409Z | <p>Thanks for all replies.<br>
But my topic is not a request for a specific problem, but for insight.</p>
<p>I am also interested in knowing why GPT-4 got certain questions wrong, but this is the challenge:<br>
How should we work hard to identify the limits of AI, and how should humans use AI appropriately (along with critical thinking)?</p>
<p>If the problem is to be processed so that it can be solved by AI, then it should be possible for a conventional computer or calculator, not AI, to solve it correctly.</p>
<hr>
<p>Here is a concern expressed by a person named Noriko Arai, director of the Center for Social Common Knowledge at the National Institute of Informatics, who was the project leader of the “Can robots get into Tokyo University?” project, in a TED talk now 7 years ago (she’s talking about old stuff like Jeopardy, but the fundamentals have not changed significantly).</p>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam/transcript">
<header class="source">
<img src="https://global.discourse-cdn.com/openai1/original/4X/7/2/5/7252c6742a8621bac374b1fd0ea2f9aa9b4280ad.png" class="site-icon" data-dominant-color="EC1015" width="48" height="48">
<a href="https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam/transcript" target="_blank" rel="noopener">ted.com</a>
</header>
<article class="onebox-body">
<div class="aspect-image" style="--aspect-ratio:560/315;"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/a/c/8/ac8a5232af88ef56d7175ca61b65d5442d975a04_2_690x388.jpeg" class="thumbnail" data-dominant-color="4B73C3" width="690" height="388"></div>
<h3><a href="https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam/transcript" target="_blank" rel="noopener">Can a robot pass a university entrance exam?</a></h3>
<p>Meet Todai Robot, an AI project that performed in the top 20 percent of students on the entrance exam for the University of Tokyo -- without actually understanding a thing. While it's not matriculating anytime soon, Todai Robot's success raises...</p>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<hr>
<p>It also means that we need to use AI appropriately, noting that many people cannot arbitrarily process questions to let AI choose the right answer.</p>
<p>GPT-4 is indeed a fantastic technology with a lot of potential, and that’s why we need to be careful with it.</p>
<p>As a person who combines moderate optimism and realistic caution about the future of AI, I would like to hear constructive insights and opinions!</p>
<hr>
<p>Of course, I do not want to make a fuss. I just want some calm insights and opinions.</p> | 12 | 0 | ed0e16a3dd | 20 | null | 25 | Thanks for all replies.
But my topic is not a request for a specific problem, but for insight.
I am also interested in knowing why GPT-4 got certain questions wrong, but this is the challenge:
How should we work hard to identify the limits of AI, and how should humans use AI appropriately (along with critical thinking)?
If the problem is to be processed so that it can be solved by AI, then it should be possible for a conventional computer or calculator, not AI, to solve it correctly.
---
Here is a concern expressed by a person named Noriko Arai, director of the Center for Social Common Knowledge at the National Institute of Informatics, who was the project leader of the “Can robots get into Tokyo University?” project, in a TED talk now 7 years ago (she’s talking about old stuff like Jeopardy, but the fundamentals have not changed significantly).
[ted.com](https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam/transcript)
### [Can a robot pass a university entrance exam?](https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam/transcript)
Meet Todai Robot, an AI project that performed in the top 20 percent of students on the entrance exam for the University of Tokyo -- without actually understanding a thing. While it's not matriculating anytime soon, Todai Robot's success raises...
---
It also means that we need to use AI appropriately, noting that many people cannot arbitrarily process questions to let AI choose the right answer.
GPT-4 is indeed a fantastic technology with a lot of potential, and that’s why we need to be careful with it.
As a person who combines moderate optimism and realistic caution about the future of AI, I would like to hear constructive insights and opinions!
---
Of course, I do not want to make a fuss. I just want some calm insights and opinions.
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] | gpt-4 | null | null | null | https://community.openai.com/t/653997 | https://community.openai.com/p/895451 | Neural Models | Artificial Intelligence |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 711,739 | 2023-11-27T20:15:23.631Z | <p>Has anyone been able to successfully use both the “retrieval” and the “function” tools in the same Assistant? if so, can you please provide information and even share your Assistant JSON?<br>
I am trying to write a customer service bot, using the Assistants API, gpt-3.5-turbo1106 model. The bot is expected to take questions from customers, and browse through a knowledgebase articles to find the answers. The bot is also asked to perform actions using several functions.<br>
For example, the customer may ask about product ABC, then get information from the knowledgebase, and then as the bot to “buy me three of product ABC” and that’s when we want to call the buyProduct function and pass the quantity and product.<br>
I started by arranging the knowledgebase articles into a JSON file, removed non utf-8 chars and loaded it into the Assistant as a File. With that I was able to have the Assistant answer questions by using the information from the articles.<br>
Next, I tried adding some functions (even tried the sample code get_stock_price from the Assistants playground). Once you add a function, “retrieval” seems to stop working. Every question you ask returns a “Run failed<br>
Sorry, something went wrong.” message.</p> | 312 | 0 | eec240834b | 1 | null | null | Has anyone been able to successfully use both the “retrieval” and the “function” tools in the same Assistant? if so, can you please provide information and even share your Assistant JSON?
I am trying to write a customer service bot, using the Assistants API, gpt-3.5-turbo1106 model. The bot is expected to take questions from customers, and browse through a knowledgebase articles to find the answers. The bot is also asked to perform actions using several functions.
For example, the customer may ask about product ABC, then get information from the knowledgebase, and then as the bot to “buy me three of product ABC” and that’s when we want to call the buyProduct function and pass the quantity and product.
I started by arranging the knowledgebase articles into a JSON file, removed non utf-8 chars and loaded it into the Assistant as a File. With that I was able to have the Assistant answer questions by using the information from the articles.
Next, I tried adding some functions (even tried the sample code get\_stock\_price from the Assistants playground). Once you add a function, “retrieval” seems to stop working. Every question you ask returns a “Run failed
Sorry, something went wrong.” message.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/711739 | File Management (3) | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 711,771 | 2023-11-27T20:28:20.381Z | <p>I can say as much as that I have used both retrieval (five different files) and three different function calls in my assistant and it works. I will however caveat that the files are not a traditional knowledge base and rather provide contextual information that the assistant needs to execute tasks. My actual knowledge base is dynamic and external and I use function calls to access and retrieve information from there.</p>
<p>Due to confidentiality I can’t share the actual JSON file but as per above, in principle the combination of both capabilities can work.</p>
<p>I hope you can find a solution to make it work on your end.</p> | 291 | 2 | 5b48a0acbf | 2 | null | null | I can say as much as that I have used both retrieval (five different files) and three different function calls in my assistant and it works. I will however caveat that the files are not a traditional knowledge base and rather provide contextual information that the assistant needs to execute tasks. My actual knowledge base is dynamic and external and I use function calls to access and retrieve information from there.
Due to confidentiality I can’t share the actual JSON file but as per above, in principle the combination of both capabilities can work.
I hope you can find a solution to make it work on your end.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/711771 | Knowledge Retrieval | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 711,775 | 2023-11-27T20:32:07.462Z | <p>Sounds like an impressive setup there, some controls on the extent of the internally retrieved information would be the icing on the cake, hopefully a coming soon feature for the assistants API.</p> | 266 | 0 | 705249ef25 | 3 | null | null | Sounds like an impressive setup there, some controls on the extent of the internally retrieved information would be the icing on the cake, hopefully a coming soon feature for the assistants API.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/711775 | Assistants, API, Platform | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 711,864 | 2023-11-27T21:16:02.793Z | <p>Thank you <a class="mention" href="/u/jr.2509">@jr.2509</a> , do you use the 3.5 model or the 4?<br>
the files you provided, are they txt or what format?</p> | 253 | 1 | eec240834b | 4 | null | null | Thank you [@jr.2509](/u/jr.2509) , do you use the 3.5 model or the 4?
the files you provided, are they txt or what format?
| api | neutral | 0.674711 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/711864 | Models | GPTs (4) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 711,985 | 2023-11-27T22:28:32.376Z | <p>I have gotten an assistant working with both retrieval and functions, but I added both to it in the playground interface.</p>
<p>After adding functions, when you inspect the assistant in the playground does it still list the files that were there before?</p>
<p>If you don’t get the <code>client.beta.assistants.update</code> call exactly right it can wipe the other tools from the assistant.</p> | 240 | 1 | b7800d23af | 5 | null | null | I have gotten an assistant working with both retrieval and functions, but I added both to it in the playground interface.
After adding functions, when you inspect the assistant in the playground does it still list the files that were there before?
If you don’t get the `client.beta.assistants.update` call exactly right it can wipe the other tools from the assistant.
| api | neutral | 0.867583 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/711985 | File Management (3) | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 712,130 | 2023-11-28T00:20:19.199Z | <p>Hi <a class="mention" href="/u/bookstaber">@bookstaber</a> , I am using the rest API directly. It does lists the files in the playground.<br>
Can someone post a complete example of this working? including the model, the instructions, the API functions and the content of the file(s)?<br>
I have been tinkering with it all day with very little consistency and quality.</p> | 222 | 1 | eec240834b | 6 | null | null | Hi [@bookstaber](/u/bookstaber) , I am using the rest API directly. It does lists the files in the playground.
Can someone post a complete example of this working? including the model, the instructions, the API functions and the content of the file(s)?
I have been tinkering with it all day with very little consistency and quality.
| api | neutral | 0.609979 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/712130 | Playground | API (2) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 712,593 | 2023-11-28T05:13:46.747Z | <p>I am using 4 (GPT-4 turbo). For now I am using docx files (as my content is in tables) but am looking to switch to csv. I am very specific in my instructions as to when to use different tools and files.</p>
<p>You might also want to refine and specify your function description. This can have an impact on the quality of performance.</p> | 208 | 0 | 5b48a0acbf | 7 | null | null | I am using 4 (GPT-4 turbo). For now I am using docx files (as my content is in tables) but am looking to switch to csv. I am very specific in my instructions as to when to use different tools and files.
You might also want to refine and specify your function description. This can have an impact on the quality of performance.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/712593 | OCR, Vision, PDF, Image, File | Artificial Intelligence |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 713,237 | 2023-11-28T11:04:19.440Z | <p>very interesting thread. Hope someone know the answer to my question:</p>
<p>I’ve built a travel assistant, using the Assistant API, gpt-3.5-turbo1106 model. The bot is expected to take questions from customers, and browse through three knowledgebase JSON files to find the answers, like the Assistant of this thread.</p>
<p>The total numbers of chars of the JSON files is about 28k chars (2 files of the 3 have 7k chars, the other 14k), the knowledge base is not huge.</p>
<p>unfortunately the Assistant has hallucinations for several topics and provides answers completely not related to the knowledge base and it says that it didn’t find anything in the knowledge base.</p>
<p>This is an example of what I mean:</p>
<p>The user asks if there are food tours in the city and in the related JSON file there is this specific snippet:</p>
<p>“Food Tours”: [<br>
{<br>
“name”: “Kensington Market Taste the World”,<br>
“description”: “Explore the culinary diversity with a guided food tour through Kensington Market.”,<br>
“info”: “<a href="https://tastytourstoronto.com/toronto-food-tours/kensington-market-taste-the-world-food-tour/" class="inline-onebox" rel="noopener nofollow ugc">Kensington Market 'Taste the World' Food Tour - Toronto Food Tours & Chocolate Tours | Tasty Tours Toronto</a>”<br>
},<br>
{<br>
“name”: “St. Lawrence Market & Old Toronto Food Tour”,<br>
“description”: “Discover Toronto’s culinary history and sample local specialties at the city’s iconic market and surrounding historic area.”,<br>
“info”: “<a href="https://culinaryadventureco.com/tour/st-lawrence-market-food-tour" class="inline-onebox" rel="noopener nofollow ugc">ST. LAWRENCE MARKET FOOD TOUR | Culinary Adventure Co</a>”<br>
}<br>
],</p>
<p>But the Assistant never provides the answer contained in the knowledge base, it always responds with info of the OpenAI knowledge or telling that it didn’t find anything related in the knowledge base.</p>
<p>How can I solve this issue? I can’t believe I’m not able to build a customer support Assistant that works properly with a normal size knowledge base</p>
<p>I was thinking to add some code related to “keyword identification”, so for example when in the user’s query there is the keyword “food tours”, the bot looks for the answer in the related JSON knowledge base, is it a good solution in your opinion? I already added in the instruction this concept but it doesn’t work</p>
<p>Hope someone can help me</p> | 198 | 1 | 9eb7c01652 | 8 | null | null | very interesting thread. Hope someone know the answer to my question:
I’ve built a travel assistant, using the Assistant API, gpt-3.5-turbo1106 model. The bot is expected to take questions from customers, and browse through three knowledgebase JSON files to find the answers, like the Assistant of this thread.
The total numbers of chars of the JSON files is about 28k chars (2 files of the 3 have 7k chars, the other 14k), the knowledge base is not huge.
unfortunately the Assistant has hallucinations for several topics and provides answers completely not related to the knowledge base and it says that it didn’t find anything in the knowledge base.
This is an example of what I mean:
The user asks if there are food tours in the city and in the related JSON file there is this specific snippet:
“Food Tours”: [
{
“name”: “Kensington Market Taste the World”,
“description”: “Explore the culinary diversity with a guided food tour through Kensington Market.”,
“info”: “[Kensington Market 'Taste the World' Food Tour - Toronto Food Tours & Chocolate Tours | Tasty Tours Toronto](https://tastytourstoronto.com/toronto-food-tours/kensington-market-taste-the-world-food-tour/)”
},
{
“name”: “St. Lawrence Market & Old Toronto Food Tour”,
“description”: “Discover Toronto’s culinary history and sample local specialties at the city’s iconic market and surrounding historic area.”,
“info”: “[ST. LAWRENCE MARKET FOOD TOUR | Culinary Adventure Co](https://culinaryadventureco.com/tour/st-lawrence-market-food-tour)”
}
],
But the Assistant never provides the answer contained in the knowledge base, it always responds with info of the OpenAI knowledge or telling that it didn’t find anything related in the knowledge base.
How can I solve this issue? I can’t believe I’m not able to build a customer support Assistant that works properly with a normal size knowledge base
I was thinking to add some code related to “keyword identification”, so for example when in the user’s query there is the keyword “food tours”, the bot looks for the answer in the related JSON knowledge base, is it a good solution in your opinion? I already added in the instruction this concept but it doesn’t work
Hope someone can help me
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/713237 | Miscellaneous (9) | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 713,849 | 2023-11-28T15:28:20.457Z | <p>following… running into this exact same problem. Not able to chain together a retrieval + function call, although I’m sure it is an oversight on my end.</p>
<p>Will share my solution in node.js when I come to it, what language are you using python or node? Apologies if you already stated in your opening post</p> | 157 | 0 | e38e8f8dca | 9 | null | null | following… running into this exact same problem. Not able to chain together a retrieval + function call, although I’m sure it is an oversight on my end.
Will share my solution in node.js when I come to it, what language are you using python or node? Apologies if you already stated in your opening post
| api | negative | 0.671241 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/713849 | Functions (4) | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 713,978 | 2023-11-28T16:12:59.068Z | <p>Be as specific as you can in your instructions that the assistant should exclusively draw on the knowledge in the files you uploaded. Consider adding the filenames as it might be available to the assistant as meta data. Negation can also sometimes help, i.e. never do XYZ when answering a question.</p>
<p>If the problem persists, try following an iterative approach and start building the assistant with one knowledge base until it reliably responds, then replicate the approach across more files. Describing the structure of your files in the instructions may also help.</p>
<p>Your keyword idea could work provided you use the keywords as well in your knowledge base. You could then instruct the assistant to first classify the user query into one of your defined keywords and then executive the search in the knowledge base based on that.</p> | 154 | 0 | 5b48a0acbf | 10 | null | null | Be as specific as you can in your instructions that the assistant should exclusively draw on the knowledge in the files you uploaded. Consider adding the filenames as it might be available to the assistant as meta data. Negation can also sometimes help, i.e. never do XYZ when answering a question.
If the problem persists, try following an iterative approach and start building the assistant with one knowledge base until it reliably responds, then replicate the approach across more files. Describing the structure of your files in the instructions may also help.
Your keyword idea could work provided you use the keywords as well in your knowledge base. You could then instruct the assistant to first classify the user query into one of your defined keywords and then executive the search in the knowledge base based on that.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/713978 | Knowledge Retrieval | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 714,190 | 2023-11-28T17:37:03.076Z | <p>For those who asked for more information, here it is:<br>
I created a very simple example, hoping that I can expand from there. As you can see below, it showed the same instability and issues. I would really like to know if anyone has the formula for making this work, and if so - how?!</p>
<p><strong>1.</strong> I created a txt file, with the following content:<br>
“The information below describes the house that the user is currently looking to buy:<br>
The house size is 2000 square feet.<br>
The house address is 5453 Ellenvale Ave. Wooodland Hills, CA 91367<br>
The house exterior color is green.<br>
There are 3 bedrooms and 2 bathrooms in the house.”</p>
<p><strong>2.</strong> I created an Assistant via the playground, using the gpt-3.5-1106 model.<br>
I included the following instructions: “You are a helpful real estate agent, answering questions about a house that the user is looking to buy.”<br>
The Assistant tools include “retrieval” with the file above, and the “function” below -<br>
{<br>
“name”: “get_price”,<br>
“parameters”: {<br>
“type”: “object”,<br>
“properties”: {<br>
“zipcode”: {<br>
“type”: “string”,<br>
“description”: “The zip code of the house”<br>
}<br>
},<br>
“required”: [“zipcode”]<br>
},<br>
“description”: “Get the current price of the house”<br>
}</p>
<p><strong>3</strong> Then, I used the playground, here are the results.<br>
<em><strong>a.</strong></em> Asking for the number of bedrooms in the house, results in invocation of the get_price API call, despite the fact that the data is in the attached file.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/6/6/7/667eb8d18d2812137c28993ab7398bdd5fa33399.png" data-download-href="/uploads/short-url/eCIcyqTiK5OM4ECPp6IPafbFaNb.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/6/6/7/667eb8d18d2812137c28993ab7398bdd5fa33399_2_690x406.png" alt="image" data-base62-sha1="eCIcyqTiK5OM4ECPp6IPafbFaNb" width="690" height="406" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/6/6/7/667eb8d18d2812137c28993ab7398bdd5fa33399_2_690x406.png, https://global.discourse-cdn.com/openai1/original/4X/6/6/7/667eb8d18d2812137c28993ab7398bdd5fa33399.png 1.5x, https://global.discourse-cdn.com/openai1/original/4X/6/6/7/667eb8d18d2812137c28993ab7398bdd5fa33399.png 2x" data-dominant-color="FAFAFB"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image</span><span class="informations">936×552 21.8 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p><em><strong>b.</strong></em> asking again, sometimes results in generic error:<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/2/4/2/2420556570a91df1d331469d03d59e8f73bd984b.png" data-download-href="/uploads/short-url/59AsIXIO7IEpNrXJCKQBI0xlTmP.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/2/4/2/2420556570a91df1d331469d03d59e8f73bd984b_2_690x467.png" alt="image" data-base62-sha1="59AsIXIO7IEpNrXJCKQBI0xlTmP" width="690" height="467" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/2/4/2/2420556570a91df1d331469d03d59e8f73bd984b_2_690x467.png, https://global.discourse-cdn.com/openai1/optimized/4X/2/4/2/2420556570a91df1d331469d03d59e8f73bd984b_2_1035x700.png 1.5x, https://global.discourse-cdn.com/openai1/original/4X/2/4/2/2420556570a91df1d331469d03d59e8f73bd984b.png 2x" data-dominant-color="FBFBFB"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image</span><span class="informations">1127×763 27.6 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p><em><strong>c.</strong></em> In some cases, there are, just errors getting issues accessing the file<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/f/9/9/f992ca770d6cdc4fde8250ffa83996a3f146a51b.png" data-download-href="/uploads/short-url/zBPo42YhsshLksxpT8jqUB7xoJd.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/f/9/9/f992ca770d6cdc4fde8250ffa83996a3f146a51b_2_629x500.png" alt="image" data-base62-sha1="zBPo42YhsshLksxpT8jqUB7xoJd" width="629" height="500" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/f/9/9/f992ca770d6cdc4fde8250ffa83996a3f146a51b_2_629x500.png, https://global.discourse-cdn.com/openai1/optimized/4X/f/9/9/f992ca770d6cdc4fde8250ffa83996a3f146a51b_2_943x750.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/f/9/9/f992ca770d6cdc4fde8250ffa83996a3f146a51b_2_1258x1000.png 2x" data-dominant-color="F7F7F7"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image</span><span class="informations">1623×1289 180 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p><em><strong>d.</strong></em> And last - not able to understand the information of the file…<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/2/2/5/225f8b8878d2ad34ca815c3ed7ebd0512e340e7e.png" data-download-href="/uploads/short-url/4U4WaUHP2wSzKcLwNC5neAtRzCm.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/2/2/5/225f8b8878d2ad34ca815c3ed7ebd0512e340e7e_2_624x500.png" alt="image" data-base62-sha1="4U4WaUHP2wSzKcLwNC5neAtRzCm" width="624" height="500" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/2/2/5/225f8b8878d2ad34ca815c3ed7ebd0512e340e7e_2_624x500.png, https://global.discourse-cdn.com/openai1/optimized/4X/2/2/5/225f8b8878d2ad34ca815c3ed7ebd0512e340e7e_2_936x750.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/2/2/5/225f8b8878d2ad34ca815c3ed7ebd0512e340e7e_2_1248x1000.png 2x" data-dominant-color="FAFAFA"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image</span><span class="informations">1663×1331 153 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p> | 160 | 1 | eec240834b | 11 | null | null | For those who asked for more information, here it is:
I created a very simple example, hoping that I can expand from there. As you can see below, it showed the same instability and issues. I would really like to know if anyone has the formula for making this work, and if so - how?!
**1.** I created a txt file, with the following content:
“The information below describes the house that the user is currently looking to buy:
The house size is 2000 square feet.
The house address is 5453 Ellenvale Ave. Wooodland Hills, CA 91367
The house exterior color is green.
There are 3 bedrooms and 2 bathrooms in the house.”
**2.** I created an Assistant via the playground, using the gpt-3.5-1106 model.
I included the following instructions: “You are a helpful real estate agent, answering questions about a house that the user is looking to buy.”
The Assistant tools include “retrieval” with the file above, and the “function” below -
{
“name”: “get\_price”,
“parameters”: {
“type”: “object”,
“properties”: {
“zipcode”: {
“type”: “string”,
“description”: “The zip code of the house”
}
},
“required”: [“zipcode”]
},
“description”: “Get the current price of the house”
}
**3** Then, I used the playground, here are the results.
***a.*** Asking for the number of bedrooms in the house, results in invocation of the get\_price API call, despite the fact that the data is in the attached file.
[image936×552 21.8 KB](https://global.discourse-cdn.com/openai1/original/4X/6/6/7/667eb8d18d2812137c28993ab7398bdd5fa33399.png "image")
***b.*** asking again, sometimes results in generic error:
[image1127×763 27.6 KB](https://global.discourse-cdn.com/openai1/original/4X/2/4/2/2420556570a91df1d331469d03d59e8f73bd984b.png "image")
***c.*** In some cases, there are, just errors getting issues accessing the file
[image1623×1289 180 KB](https://global.discourse-cdn.com/openai1/original/4X/f/9/9/f992ca770d6cdc4fde8250ffa83996a3f146a51b.png "image")
***d.*** And last - not able to understand the information of the file…
[image1663×1331 153 KB](https://global.discourse-cdn.com/openai1/original/4X/2/2/5/225f8b8878d2ad34ca815c3ed7ebd0512e340e7e.png "image")
| api | neutral | 0.812147 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/714190 | Campaign | GPTs (4) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 714,895 | 2023-11-28T22:02:38.494Z | <p>I just posted a complete Python app that implements both retrieval and functions here: <a href="https://github.com/dbookstaber/OpenAI_Assist_All_Tools" class="inline-onebox" rel="noopener nofollow ugc">GitHub - dbookstaber/OpenAI_Assist_All_Tools: Simple demo of OpenAI Assistant with all tool types</a></p>
<p>The only thing that has been unreliable while I’ve played with it is the retrieval of CSV contents. I didn’t get that to work until I uploaded the CSV separately through playground, and even then it took a few queries.</p> | 132 | 0 | b7800d23af | 12 | null | null | I just posted a complete Python app that implements both retrieval and functions here: [GitHub - dbookstaber/OpenAI\_Assist\_All\_Tools: Simple demo of OpenAI Assistant with all tool types](https://github.com/dbookstaber/OpenAI_Assist_All_Tools)
The only thing that has been unreliable while I’ve played with it is the retrieval of CSV contents. I didn’t get that to work until I uploaded the CSV separately through playground, and even then it took a few queries.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/714895 | Miscellaneous (7) | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 721,824 | 2023-12-01T15:59:16.490Z | <p>Have you managed to solve the problem? The same thing is happening to me.</p> | 118 | 0 | 62b579b9e3 | 13 | null | null | Have you managed to solve the problem? The same thing is happening to me.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/721824 | Issue-Solving | API (2) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 731,488 | 2023-12-05T15:18:31.518Z | <p>I’m running into a similar problem, and I’d be interested to hear how far people have got.</p>
<p>The easiest way to describe my use-case is as follows:</p>
<p>The assistant has access to some files, and the knowledge retrieval tool is enabled.</p>
<p>The assistant also has function calling, in order to return a response in a JSON / structured format.</p>
<p>Imagine that the input text is a support email. The assistant should look within the attached files, and then provide knowledge based answers.</p>
<p>The assistant should respond with say 3 “possible replies” in a structured JSON format, so that it can be appropriately and reliably displayed on the front-end.</p>
<p>At the moment I’m not sure if it’s possible to do this 2x tool use within a single “run”.</p>
<p>One possible solution is to do multiple steps - Get the knowledge needed, and then form some replies using the function calling.</p>
<p>Any help or input would be greatly appreciated</p> | 110 | 0 | b2f3733f4b | 14 | null | null | I’m running into a similar problem, and I’d be interested to hear how far people have got.
The easiest way to describe my use-case is as follows:
The assistant has access to some files, and the knowledge retrieval tool is enabled.
The assistant also has function calling, in order to return a response in a JSON / structured format.
Imagine that the input text is a support email. The assistant should look within the attached files, and then provide knowledge based answers.
The assistant should respond with say 3 “possible replies” in a structured JSON format, so that it can be appropriately and reliably displayed on the front-end.
At the moment I’m not sure if it’s possible to do this 2x tool use within a single “run”.
One possible solution is to do multiple steps - Get the knowledge needed, and then form some replies using the function calling.
Any help or input would be greatly appreciated
| api | neutral | 0.759539 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/731488 | Miscellaneous (9) | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 731,714 | 2023-12-05T16:49:11.517Z | <p>No solution yet, I am still tinkering around trying to find consistency.</p> | 105 | 1 | eec240834b | 15 | null | null | No solution yet, I am still tinkering around trying to find consistency.
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/731714 | Headache | Emoji (8) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 754,996 | 2023-12-16T04:10:30.632Z | <p>You could try setting file_ids array in the Request body when create message.<br>
<a href="https://platform.openai.com/docs/api-reference/messages/createMessage" class="onebox" target="_blank" rel="noopener nofollow ugc">https://platform.openai.com/docs/api-reference/messages/createMessage</a></p> | 75 | 1 | a3fd35cb4e | 16 | null | null | You could try setting file\_ids array in the Request body when create message.
<https://platform.openai.com/docs/api-reference/messages/createMessage>
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/754996 | File Management | Embeddings (6) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 773,862 | 2023-12-26T19:35:52.249Z | <aside class="quote no-group" data-username="cesar.saccone" data-post="16" data-topic="530158">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://avatars.discourse-cdn.com/v4/letter/c/ecccb3/48.png" class="avatar"> cesar.saccone:</div>
<blockquote>
<p>array in the Request body when create mes</p>
</blockquote>
</aside>
<p>how will that address what I am asking about?</p> | 67 | 0 | eec240834b | 17 | null | null |
 cesar.saccone:
>
> array in the Request body when create mes
>
>
>
how will that address what I am asking about?
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/773862 | Miscellaneous (5) | Miscellaneous (27) |
530,158 | [
"assistants-api"
] | Assistants with both "retrieval" and "function" | "2023-11-27T20:15:23.436000Z" | 7 | 4,472 | 10 | 17 | 16 | 2,041 | 793,498 | 2024-01-12T15:43:23.837Z | <p>Has anyone found a way to trigger for retrieval and functions to work together?</p> | 58 | 0 | 1b29dcce7b | 18 | null | null | Has anyone found a way to trigger for retrieval and functions to work together?
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] | assistants-api | null | null | null | https://community.openai.com/t/530158 | https://community.openai.com/p/793498 | Functions (4) | Embeddings (6) |