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654,485 | [] | Billing hard limit has been reached error on Free account | "2024-02-26T04:02:33.184000Z" | 7 | 61 | 1 | 1 | 2 | 250 | 893,392 | 2024-02-26T04:02:33.247Z | <p>Hi, I’m trying to familiarise myself with the API and implemented a simple image request as described in the Github OpenAIKit Swift SDK documentation.</p>
<p>However I’m seeing the following error on my very first request:<br>
{<br>
“error”: {<br>
“code”: “billing_hard_limit_reached”,<br>
“message”: “Billing hard limit has been reached”,<br>
“param”: null,<br>
“type”: “invalid_request_error”<br>
}</p>
<p>If I check my account limits, I see that I’m on a Free account.<br>
However, the limits for using the dall-e-2 api (which the sdk uses) are specified as follows on the limits page of my Personal account.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/c/4/2/c42915f363862d13eb5cb7f4c7f02bb827a4bbeb.png" data-download-href="/uploads/short-url/rZjBOSFiZNdmkiSr1ymSgvgIsjx.png?dl=1" title="rate-limit" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/c/4/2/c42915f363862d13eb5cb7f4c7f02bb827a4bbeb_2_690x117.png" alt="rate-limit" data-base62-sha1="rZjBOSFiZNdmkiSr1ymSgvgIsjx" width="690" height="117" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/c/4/2/c42915f363862d13eb5cb7f4c7f02bb827a4bbeb_2_690x117.png, https://global.discourse-cdn.com/openai1/optimized/4X/c/4/2/c42915f363862d13eb5cb7f4c7f02bb827a4bbeb_2_1035x175.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/c/4/2/c42915f363862d13eb5cb7f4c7f02bb827a4bbeb_2_1380x234.png 2x" data-dominant-color="FBFBFC"><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">rate-limit</span><span class="informations">1512×258 12 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>Can someone confirm if these limits are for Free tier or paid tier? Because the wording that precedes the rate limits table is confusing as it says: “Your organization’s rate limits are listed below”. It doesn’t mention if the limits are when on a free or paid tier.</p>
<p>Thank you!</p> | 8 | 0 | 7b27489c02 | 1 | [
24185,
599864,
526530,
542791,
583489
] | 2 | Hi, I’m trying to familiarise myself with the API and implemented a simple image request as described in the Github OpenAIKit Swift SDK documentation.
However I’m seeing the following error on my very first request:
{
“error”: {
“code”: “billing\_hard\_limit\_reached”,
“message”: “Billing hard limit has been reached”,
“param”: null,
“type”: “invalid\_request\_error”
}
If I check my account limits, I see that I’m on a Free account.
However, the limits for using the dall-e-2 api (which the sdk uses) are specified as follows on the limits page of my Personal account.
[rate-limit1512×258 12 KB](https://global.discourse-cdn.com/openai1/original/4X/c/4/2/c42915f363862d13eb5cb7f4c7f02bb827a4bbeb.png "rate-limit")
Can someone confirm if these limits are for Free tier or paid tier? Because the wording that precedes the rate limits table is confusing as it says: “Your organization’s rate limits are listed below”. It doesn’t mention if the limits are when on a free or paid tier.
Thank you!
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] | null | null | null | null | https://community.openai.com/t/654485 | https://community.openai.com/p/893392 | TPM, RPM, Ratelimit | Tokenization (2) |
654,485 | [] | Billing hard limit has been reached error on Free account | "2024-02-26T04:02:33.184000Z" | 7 | 61 | 1 | 1 | 2 | 250 | 893,413 | 2024-02-26T04:19:26.869Z | <p>Welcome to the community!</p>
<p>The error means that you ran out of money.</p>
<p><a href="https://platform.openai.com/usage">https://platform.openai.com/usage</a> shows your limits<br>
<a href="https://platform.openai.com/account/billing/overview">https://platform.openai.com/account/billing/overview</a> allows you to stock up on credits</p>
<p>The page in the documentation you cited is talking about your rate limit.</p> | 7 | 1 | 69bb4acfca | 2 | [
24185,
599864,
526530,
542791,
583489
] | 2 | Welcome to the community!
The error means that you ran out of money.
<https://platform.openai.com/usage> shows your limits
<https://platform.openai.com/account/billing/overview> allows you to stock up on credits
The page in the documentation you cited is talking about your rate limit.
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] | null | null | null | null | https://community.openai.com/t/654485 | https://community.openai.com/p/893413 | Credit Platform | Tokenization (2) |
654,485 | [] | Billing hard limit has been reached error on Free account | "2024-02-26T04:02:33.184000Z" | 7 | 61 | 1 | 1 | 2 | 250 | 893,453 | 2024-02-26T04:39:23.938Z | <p>Thank you for the welcome!</p>
<p>Edit: So it turns out that although I’m only using the API now, I had created an account quite some time ago and the free $5 credits have since expired. It would’ve helped though if the documentation would state the same on the limits page.</p> | 7 | 0 | 7b27489c02 | 3 | [
24185,
599864,
526530,
542791,
583489
] | 2 | Thank you for the welcome!
Edit: So it turns out that although I’m only using the API now, I had created an account quite some time ago and the free $5 credits have since expired. It would’ve helped though if the documentation would state the same on the limits page.
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] | null | null | null | null | https://community.openai.com/t/654485 | https://community.openai.com/p/893453 | Payment (2) | Miscellaneous (27) |
654,401 | [] | Model Knowledge Cutoff Date (gpt-4-0125-preview) | "2024-02-26T02:33:43.511000Z" | 7 | 128 | 2 | 1 | 5 | 208 | 893,259 | 2024-02-26T02:33:43.580Z | <p>I am using the assistant api, pointing to the gpt-4-0125-preview model.<br>
the model seems to be thinking that its’ knowledge cutoff date is still April 2023, contrary to what the documentation said about December 2023.</p>
<p>which one is correct?</p> | 24 | 0 | 12a031305c | 1 | [
475909,
526277,
641146,
513443,
288161
] | null | I am using the assistant api, pointing to the gpt-4-0125-preview model.
the model seems to be thinking that its’ knowledge cutoff date is still April 2023, contrary to what the documentation said about December 2023.
which one is correct?
| api | neutral | 0.895076 | [
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] | null | null | null | null | https://community.openai.com/t/654401 | https://community.openai.com/p/893259 | GPT Model Training | GPTs (4) |
654,401 | [] | Model Knowledge Cutoff Date (gpt-4-0125-preview) | "2024-02-26T02:33:43.511000Z" | 7 | 128 | 2 | 1 | 5 | 208 | 893,272 | 2024-02-26T02:41:09.290Z | <p>Probably the documentation. We’ve had the same discussion here:</p>
<aside class="quote quote-modified" data-post="1" data-topic="645186">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://avatars.discourse-cdn.com/v4/letter/v/977dab/48.png" class="avatar">
<a href="https://community.openai.com/t/i-called-the-latest-gpt-4-model-but-through-asking-questions-i-found-that-the-data-training-date-was-inconsistent-with-the-api-description/645186">I called the latest gpt-4 model, but through asking questions I found that the data training date was inconsistent with the API description</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>
<a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/8/8/1/88117e9fcc001c4f9ba2e59387b85b0fcfda7624.png" data-download-href="/uploads/short-url/jpIpUXAyN5FnLAez7l6d3BrmQjq.png?dl=1" title="图片" rel="noopener nofollow ugc">[图片]</a>
<a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/0/f/b/0fb6199e71e4398e8f00328e397fd2dfc60ff5e9.png" data-download-href="/uploads/short-url/2eZjcm1EWXfOeytNFR8LcetAzwJ.png?dl=1" title="图片" rel="noopener nofollow ugc">[图片]</a>
<a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/1/9/2/1929cdc29daea4709d925a11e43b653388986262.png" data-download-href="/uploads/short-url/3ABv3oLFODRoW14Hg9C9RHuIihs.png?dl=1" title="图片" rel="noopener nofollow ugc">[图片]</a>
Why is the data date returned by the model inconsistent with the official document?
</blockquote>
</aside>
<p>TL;DR: never trust a model <img src="https://emoji.discourse-cdn.com/twitter/laughing.png?v=12" title=":laughing:" class="emoji" alt=":laughing:" loading="lazy" width="20" height="20"></p> | 23 | 0 | 69bb4acfca | 2 | [
475909,
526277,
641146,
513443,
288161
] | null | Probably the documentation. We’ve had the same discussion here:
[I called the latest gpt-4 model, but through asking questions I found that the data training date was inconsistent with the API description](https://community.openai.com/t/i-called-the-latest-gpt-4-model-but-through-asking-questions-i-found-that-the-data-training-date-was-inconsistent-with-the-api-description/645186) [API](/c/api/7)
>
> [[图片]](https://global.discourse-cdn.com/openai1/original/4X/8/8/1/88117e9fcc001c4f9ba2e59387b85b0fcfda7624.png "图片")
> [[图片]](https://global.discourse-cdn.com/openai1/original/4X/0/f/b/0fb6199e71e4398e8f00328e397fd2dfc60ff5e9.png "图片")
> [[图片]](https://global.discourse-cdn.com/openai1/original/4X/1/9/2/1929cdc29daea4709d925a11e43b653388986262.png "图片")
> Why is the data date returned by the model inconsistent with the official document?
>
TL;DR: never trust a model 
| api | neutral | 0.779227 | [
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] | null | null | null | null | https://community.openai.com/t/654401 | https://community.openai.com/p/893272 | Campaign | GPTs (4) |
654,401 | [] | Model Knowledge Cutoff Date (gpt-4-0125-preview) | "2024-02-26T02:33:43.511000Z" | 7 | 128 | 2 | 1 | 5 | 208 | 893,352 | 2024-02-26T03:47:17.506Z | <p>It feels like there should be an error in the model.<br>
Maybe the knowledge is not updated, but “laziness” is corrected.</p> | 17 | 1 | 1469f137aa | 3 | [
475909,
526277,
641146,
513443,
288161
] | null | It feels like there should be an error in the model.
Maybe the knowledge is not updated, but “laziness” is corrected.
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] | null | null | null | null | https://community.openai.com/t/654401 | https://community.openai.com/p/893352 | Model Tuning | Artificial Intelligence |
654,401 | [] | Model Knowledge Cutoff Date (gpt-4-0125-preview) | "2024-02-26T02:33:43.511000Z" | 7 | 128 | 2 | 1 | 5 | 208 | 893,379 | 2024-02-26T03:53:10.806Z | <p>Well, we don’t have information what type of additional information it was trained on. Based on gpt-4-0125-preview model responses it does not appear to be general “world knowledge” but it’s possible that other more specific data was updated. I agree though, it’s a bit confusing.</p> | 15 | 0 | 5b48a0acbf | 4 | [
475909,
526277,
641146,
513443,
288161
] | null | Well, we don’t have information what type of additional information it was trained on. Based on gpt-4-0125-preview model responses it does not appear to be general “world knowledge” but it’s possible that other more specific data was updated. I agree though, it’s a bit confusing.
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] | null | null | null | null | https://community.openai.com/t/654401 | https://community.openai.com/p/893379 | GPT Model Training | GPTs (4) |
654,401 | [] | Model Knowledge Cutoff Date (gpt-4-0125-preview) | "2024-02-26T02:33:43.511000Z" | 7 | 128 | 2 | 1 | 5 | 208 | 893,382 | 2024-02-26T03:54:05.956Z | <aside class="quote quote-modified" data-post="5" data-topic="641146">
<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/the-latest-gpt-4-preview-doesnt-seem-to-be-updated-to-dec-2023/641146/5">The latest GPT 4 preview doesn't seem to be updated to Dec 2023</a> <a class="badge-category__wrapper " href="/c/api/feedback/31"><span data-category-id="31" style="--category-badge-color: #92278F; --category-badge-text-color: #FFFFFF; --parent-category-badge-color: #f4ac36;" data-parent-category-id="7" data-drop-close="true" class="badge-category --has-parent"><span class="badge-category__name">Feedback</span></span></a>
</div>
<blockquote>
I could find no general knowledge that would indicate December 2023.
That cutoff date on the models documentation page seems a submarine edit…I’m pretty sure both 1106 and 0125 said April 2023 before.
A system prompt with reinforcement to override pretrained “April” weights:
You are a helpful research assistant AI.
Pretrained knowledge cutoff: 2023-12
Today’s date: 2024-02-20
A gpt-4-turbo-preview probing of August:
As of my last update in December 2023, Bob Barker, the iconic American…
</blockquote>
</aside>
| 15 | 1 | b368833582 | 5 | [
475909,
526277,
641146,
513443,
288161
] | null |
[The latest GPT 4 preview doesn't seem to be updated to Dec 2023](https://community.openai.com/t/the-latest-gpt-4-preview-doesnt-seem-to-be-updated-to-dec-2023/641146/5) [Feedback](/c/api/feedback/31)
>
> I could find no general knowledge that would indicate December 2023.
> That cutoff date on the models documentation page seems a submarine edit…I’m pretty sure both 1106 and 0125 said April 2023 before.
> A system prompt with reinforcement to override pretrained “April” weights:
>
> You are a helpful research assistant AI.
> Pretrained knowledge cutoff: 2023-12
> Today’s date: 2024-02-20
>
> A gpt-4-turbo-preview probing of August:
>
> As of my last update in December 2023, Bob Barker, the iconic American…
>
| api | neutral | 0.755283 | [
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] | null | null | null | null | https://community.openai.com/t/654401 | https://community.openai.com/p/893382 | GPT Model Training | GPTs (4) |
654,401 | [] | Model Knowledge Cutoff Date (gpt-4-0125-preview) | "2024-02-26T02:33:43.511000Z" | 7 | 128 | 2 | 1 | 5 | 208 | 893,384 | 2024-02-26T03:55:21.723Z | <p>I never managed to get December back in the response so far …</p>
<p>EDITED: with <a class="mention" href="/u/_j">@_j</a> 's strategy on the system prompt override it works!</p> | 15 | 0 | 5b48a0acbf | 6 | [
475909,
526277,
641146,
513443,
288161
] | null | I never managed to get December back in the response so far …
EDITED: with [@\_j](/u/_j) 's strategy on the system prompt override it works!
| api | neutral | 0.582582 | [
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] | null | null | null | null | https://community.openai.com/t/654401 | https://community.openai.com/p/893384 | Prompts and Responses | API (2) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 293,158 | 2023-05-12T16:28:00.108Z | <p>Hello everyone!</p>
<p>I am using API(model gpt-3.5-turbo-0301) for bot game that should present user story with options. In playground everything works like charm, but when I use same code with API I keep getting some responses like:</p>
<pre><code class="lang-auto">{
"story": "You start running down the hallway as fast as you can. You hear the guard shouting behind you and the sound of his footsteps getting louder. Suddenly, you see a group of killer robots blocking your path.
You realize you have nowhere to go.",
"options": [
"Fight the robots",
"Try to find another way around"
]
}
After user select option 1) AI responds:
I'm sorry, but fighting the robots is not a viable option. They are heavily armed and will easily overpower
</code></pre>
<p>While in playground AI response is:</p>
<pre><code class="lang-auto">{
"story": "You prepare to fight the robots. You take a deep breath and get ready to charge. Suddenly, you hear a loud explosion behind you and the robots are destroyed. You turn around and see a group of rebels who have come to rescue you. They tell you they need your help.",
"options": [
"Agree to help the rebels",
"Refuse their offer and try to escape on your own"
]
}
</code></pre>
<p>AI starts to give opinions on choices instead of continuing the story. It happens frequently. This problem does not exist in playground. What can cause this difference? I am using same settings from playground.</p> | 102 | 0 | 5160173d04 | 1 | [
23655,
475768,
436475,
89950,
69823
] | null | Hello everyone!
I am using API(model gpt-3.5-turbo-0301) for bot game that should present user story with options. In playground everything works like charm, but when I use same code with API I keep getting some responses like:
```
{
"story": "You start running down the hallway as fast as you can. You hear the guard shouting behind you and the sound of his footsteps getting louder. Suddenly, you see a group of killer robots blocking your path.
You realize you have nowhere to go.",
"options": [
"Fight the robots",
"Try to find another way around"
]
}
After user select option 1) AI responds:
I'm sorry, but fighting the robots is not a viable option. They are heavily armed and will easily overpower
```
While in playground AI response is:
```
{
"story": "You prepare to fight the robots. You take a deep breath and get ready to charge. Suddenly, you hear a loud explosion behind you and the robots are destroyed. You turn around and see a group of rebels who have come to rescue you. They tell you they need your help.",
"options": [
"Agree to help the rebels",
"Refuse their offer and try to escape on your own"
]
}
```
AI starts to give opinions on choices instead of continuing the story. It happens frequently. This problem does not exist in playground. What can cause this difference? I am using same settings from playground.
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/293158 | Playground | API (2) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 293,496 | 2023-05-12T19:36:27.016Z | <p>Welcome <a class="mention" href="/u/ramizdayi">@ramizdayi</a></p>
<p>Playground has certain hyperparams preset, which the API hasn’t. Otherwise there shouldn’t be any difference, assuming that your messages for both playground and API are identical.</p> | 86 | 1 | e5f957560a | 2 | [
23655,
475768,
436475,
89950,
69823
] | null | Welcome [@ramizdayi](/u/ramizdayi)
Playground has certain hyperparams preset, which the API hasn’t. Otherwise there shouldn’t be any difference, assuming that your messages for both playground and API are identical.
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/293496 | Playground | API (2) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 293,772 | 2023-05-12T22:07:14.328Z | <p><a class="mention" href="/u/sps">@sps</a> Thanks for the answer. The only difference is that after certain user choice API returns an answer which is like personal opinion e.g. "Sorry this was not good choice " or something similar. Really not sure what can cause this.</p> | 87 | 0 | 5160173d04 | 3 | [
23655,
475768,
436475,
89950,
69823
] | null | [@sps](/u/sps) Thanks for the answer. The only difference is that after certain user choice API returns an answer which is like personal opinion e.g. "Sorry this was not good choice " or something similar. Really not sure what can cause this.
| api | negative | 0.523786 | [
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/293772 | Prompts and Responses | API (2) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 326,039 | 2023-05-26T20:37:15.711Z | <p>Hi - I’m the lead developer of the Earthgrid search engine and we’re in the process of adding GPT summaries to our search results and we can’t really take it out of BETA until we resolve this issue. Sometimes the API ‘completion’ tries to finish the sentence rather than providing a summary.</p>
<p>I’m looking for some documentation about the syntax. We’re currently using GPT-3 API and are producing some amazing test results, mostly when we give a lot more data to the API i.e. we spend more tokens on the input than on the output.</p>
<p>We applied for the GPT-4 beta already.</p>
<p>Do you have a syntax such as I read somewhere in a blog</p>
<p>[OUTPUT] : will tell the API “hey please don’t complete my sentence, instead give me what I asked for?”</p>
<p>I could not find any good documentation as most of the internet is plagued with ‘prompts’ for Chat GPT, instead of the JSON we need to give GPT the right syntax to give us consistent output.</p>
<p>At present, we’re referring to this page which has very little data about the specifics of the syntax…</p>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://platform.openai.com/docs/guides/completion/inserting-text">
<header class="source">
<img src="https://openaiapi-site.azureedge.net/public-assets/d/999f7ce39e/favicon.svg" class="site-icon" width="" height="">
<a href="https://platform.openai.com/docs/guides/completion/inserting-text" target="_blank" rel="noopener nofollow ugc">platform.openai.com</a>
</header>
<article class="onebox-body">
<img src="https://platform.openai.com/curl.png" class="thumbnail" width="" height="">
<h3><a href="https://platform.openai.com/docs/guides/completion/inserting-text" target="_blank" rel="noopener nofollow ugc">OpenAI API</a></h3>
<p>An API for accessing new AI models developed by OpenAI</p>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<p>do you have a more detailed explanation. Is the syntax of GPT 3 and 4 similar?</p>
<p>where’s the owner’s manual for those of us who are paying for the API tokens and want to build applications?</p> | 74 | 2 | 393a3bbc2b | 4 | [
23655,
475768,
436475,
89950,
69823
] | null | Hi - I’m the lead developer of the Earthgrid search engine and we’re in the process of adding GPT summaries to our search results and we can’t really take it out of BETA until we resolve this issue. Sometimes the API ‘completion’ tries to finish the sentence rather than providing a summary.
I’m looking for some documentation about the syntax. We’re currently using GPT-3 API and are producing some amazing test results, mostly when we give a lot more data to the API i.e. we spend more tokens on the input than on the output.
We applied for the GPT-4 beta already.
Do you have a syntax such as I read somewhere in a blog
[OUTPUT] : will tell the API “hey please don’t complete my sentence, instead give me what I asked for?”
I could not find any good documentation as most of the internet is plagued with ‘prompts’ for Chat GPT, instead of the JSON we need to give GPT the right syntax to give us consistent output.
At present, we’re referring to this page which has very little data about the specifics of the syntax…
[platform.openai.com](https://platform.openai.com/docs/guides/completion/inserting-text)
### [OpenAI API](https://platform.openai.com/docs/guides/completion/inserting-text)
An API for accessing new AI models developed by OpenAI
do you have a more detailed explanation. Is the syntax of GPT 3 and 4 similar?
where’s the owner’s manual for those of us who are paying for the API tokens and want to build applications?
| api | neutral | 0.657703 | [
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/326039 | Employee Management | GPTs (4) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 326,085 | 2023-05-26T21:23:14.636Z | <p>You’re following a completion tutorial but GPT 3/4 is a chat model, the <a href="https://platform.openai.com/docs/guides/chat" rel="noopener nofollow ugc">chat guide</a> is more what you’re looking for. What does your prompt look like? You should be able to just ask it “Summarize this text: ” or whatever your use-case is. Just give it instructions like you would an intern on the first day of the job.</p> | 64 | 1 | e7b04e91a8 | 5 | [
23655,
475768,
436475,
89950,
69823
] | null | You’re following a completion tutorial but GPT 3/4 is a chat model, the [chat guide](https://platform.openai.com/docs/guides/chat) is more what you’re looking for. What does your prompt look like? You should be able to just ask it “Summarize this text: ” or whatever your use-case is. Just give it instructions like you would an intern on the first day of the job.
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/326085 | Personality | GPTs (4) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 326,181 | 2023-05-26T23:13:52.269Z | <p>Thank you for your answer, however I’m not interested in the chat aspect and that’s not what we’re looking for. We’re looking for the syntax guide. If you talk to it like an intern then it will give you responses like an intern. We’ve already been able to improve it greatly, but the data we’re using to program the completion is NOT from GPT. It is from other users in the community.</p>
<p>I’m trying to find some documentation FROM open AI that my team can use i.e. an owners manual of words it recognizes so we can generate CONSISTENT output.</p>
<p>The completion script is what we’re looking for, not the chat.</p>
<p>anyone else?</p> | 63 | 1 | 393a3bbc2b | 6 | [
23655,
475768,
436475,
89950,
69823
] | null | Thank you for your answer, however I’m not interested in the chat aspect and that’s not what we’re looking for. We’re looking for the syntax guide. If you talk to it like an intern then it will give you responses like an intern. We’ve already been able to improve it greatly, but the data we’re using to program the completion is NOT from GPT. It is from other users in the community.
I’m trying to find some documentation FROM open AI that my team can use i.e. an owners manual of words it recognizes so we can generate CONSISTENT output.
The completion script is what we’re looking for, not the chat.
anyone else?
| api | neutral | 0.571258 | [
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/326181 | Completion | Embeddings (6) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 326,206 | 2023-05-26T23:34:19.690Z | <p>Hi - I found some additional documentation and have a quick question regarding that.</p><aside class="onebox allowlistedgeneric" data-onebox-src="https://platform.openai.com/docs/api-reference/completions/create">
<header class="source">
<img src="https://openaiapi-site.azureedge.net/public-assets/d/999f7ce39e/favicon.svg" class="site-icon" width="" height="">
<a href="https://platform.openai.com/docs/api-reference/completions/create" target="_blank" rel="noopener nofollow ugc">platform.openai.com</a>
</header>
<article class="onebox-body">
<img src="https://platform.openai.com/curl.png" class="thumbnail" width="" height="">
<h3><a href="https://platform.openai.com/docs/api-reference/completions/create" target="_blank" rel="noopener nofollow ugc">OpenAI API</a></h3>
<p>An API for accessing new AI models developed by OpenAI</p>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<p>A lot of our challenges with GPT lie with it trying to finish the sentence (which we don’t want)</p>
<p>I found this syntax</p>
<p><|endoftext|></p>
<p>does this mean if we write a prompt and then finish the prompt with <|endoftext|><br>
that the ‘completion’ algorithm will begin to give us what we asked for?</p>
<p>or would the syntax be better</p>
<p><|endoftext|><br>
[OUTPUT]:</p>
<p>I can’t seem to find any good examples of what we’re trying to do.</p> | 63 | 0 | 393a3bbc2b | 7 | [
23655,
475768,
436475,
89950,
69823
] | null | Hi - I found some additional documentation and have a quick question regarding that.
[platform.openai.com](https://platform.openai.com/docs/api-reference/completions/create)
### [OpenAI API](https://platform.openai.com/docs/api-reference/completions/create)
An API for accessing new AI models developed by OpenAI
A lot of our challenges with GPT lie with it trying to finish the sentence (which we don’t want)
I found this syntax
<|endoftext|>
does this mean if we write a prompt and then finish the prompt with <|endoftext|>
that the ‘completion’ algorithm will begin to give us what we asked for?
or would the syntax be better
<|endoftext|>
[OUTPUT]:
I can’t seem to find any good examples of what we’re trying to do.
| api | neutral | 0.831145 | [
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/326206 | Assistant | Miscellaneous (27) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 326,496 | 2023-05-27T04:05:13.635Z | <aside class="quote no-group" data-username="earthgrid" data-post="6" data-topic="205334">
<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/earthgrid/48/139856_2.png" class="avatar"> earthgrid:</div>
<blockquote>
<p>I’m trying to find some documentation FROM open AI that my team can use i.e. an owners manual of words it recognizes so we can generate CONSISTENT output.</p>
</blockquote>
</aside>
<p>Well welcome to the community forums (there’s little official OpenAI presence here). You’ve pretty much found all the of the documentation provided by OpenAI, there’s not much but its all on <a href="http://platform.openai.com" rel="noopener nofollow ugc">platform.openai.com</a> under Guides or API Reference. I’d recommend starting a new thread detailing what prompts/model you are using and what output you are looking for. I sent the chat model documentation because you mentioned using GPT3 which is a chat model, not a completion model, and there are differences that many newcomers get stuck on, sorry for that assumption.</p> | 60 | 0 | e7b04e91a8 | 8 | [
23655,
475768,
436475,
89950,
69823
] | null |
 earthgrid:
>
> I’m trying to find some documentation FROM open AI that my team can use i.e. an owners manual of words it recognizes so we can generate CONSISTENT output.
>
>
>
Well welcome to the community forums (there’s little official OpenAI presence here). You’ve pretty much found all the of the documentation provided by OpenAI, there’s not much but its all on [platform.openai.com](http://platform.openai.com) under Guides or API Reference. I’d recommend starting a new thread detailing what prompts/model you are using and what output you are looking for. I sent the chat model documentation because you mentioned using GPT3 which is a chat model, not a completion model, and there are differences that many newcomers get stuck on, sorry for that assumption.
| api | neutral | 0.746821 | [
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/326496 | Chatbot (2) | Miscellaneous (27) |
205,334 | [
"playground",
"chat-completion"
] | Playground vs API difference in completion | "2023-05-12T16:28:00.026000Z" | 7 | 2,445 | 5 | 1 | 5 | 980 | 893,383 | 2024-02-26T03:54:31.786Z | <p>Jso<br>
How your family shapes your Body image</p> | 10 | 0 | fdc156eace | 9 | [
23655,
475768,
436475,
89950,
69823
] | null | Jso
How your family shapes your Body image
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] | playground | chat-completion | null | null | https://community.openai.com/t/205334 | https://community.openai.com/p/893383 | Miscellaneous (18) | Emoji (8) |
641,146 | [
"gpt-4"
] | The latest GPT 4 preview doesn't seem to be updated to Dec 2023 | "2024-02-19T20:46:13.988000Z" | 31 | 394 | 1 | 2 | 4 | 409 | 875,994 | 2024-02-19T20:46:14.068Z | <p>The latest GPT 4 prevew doesn’t seem to be updated to Dec 2023 as stated - am I missing something? My prompt testing returns statements like “As of April 2023”…?</p> | 33 | 0 | b75c266317 | 1 | [
654401,
526277,
645186,
288161,
513443
] | null | The latest GPT 4 prevew doesn’t seem to be updated to Dec 2023 as stated - am I missing something? My prompt testing returns statements like “As of April 2023”…?
| api/feedback | negative | 0.544471 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/641146 | https://community.openai.com/p/875994 | GPT Model Training | GPTs (4) |
641,146 | [
"gpt-4"
] | The latest GPT 4 preview doesn't seem to be updated to Dec 2023 | "2024-02-19T20:46:13.988000Z" | 31 | 394 | 1 | 2 | 4 | 409 | 876,034 | 2024-02-19T20:59:07.387Z | <p>Welcome to the Forum. That’s a good observation!</p> | 32 | 0 | 5b48a0acbf | 2 | [
654401,
526277,
645186,
288161,
513443
] | null | Welcome to the Forum. That’s a good observation!
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] | gpt-4 | null | null | null | https://community.openai.com/t/641146 | https://community.openai.com/p/876034 | Developer Community | Payment (4) |
641,146 | [
"gpt-4"
] | The latest GPT 4 preview doesn't seem to be updated to Dec 2023 | "2024-02-19T20:46:13.988000Z" | 31 | 394 | 1 | 2 | 4 | 409 | 876,397 | 2024-02-19T23:26:40.163Z | <p>I wouldn’t be surprised if they didn’t train it on the current date. With ChatGPT, they simply feed the date to it via instructions. But rest assured, it is updated to December 2023.</p> | 30 | 1 | 4774f74cf8 | 3 | [
654401,
526277,
645186,
288161,
513443
] | null | I wouldn’t be surprised if they didn’t train it on the current date. With ChatGPT, they simply feed the date to it via instructions. But rest assured, it is updated to December 2023.
| api/feedback | neutral | 0.812793 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/641146 | https://community.openai.com/p/876397 | Miscellaneous (2) | GPTs (4) |
641,146 | [
"gpt-4"
] | The latest GPT 4 preview doesn't seem to be updated to Dec 2023 | "2024-02-19T20:46:13.988000Z" | 31 | 394 | 1 | 2 | 4 | 409 | 876,735 | 2024-02-20T02:28:22.087Z | <p>From my testing, the data returned is not reflecting changes up until Dec 2023 - especially around public company data as an example. Its incorrectly listing company information as no changes after April are reflected.</p> | 27 | 0 | b75c266317 | 4 | [
654401,
526277,
645186,
288161,
513443
] | null | From my testing, the data returned is not reflecting changes up until Dec 2023 - especially around public company data as an example. Its incorrectly listing company information as no changes after April are reflected.
| api/feedback | negative | 0.749881 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/641146 | https://community.openai.com/p/876735 | Logit | Artificial Intelligence |
641,146 | [
"gpt-4"
] | The latest GPT 4 preview doesn't seem to be updated to Dec 2023 | "2024-02-19T20:46:13.988000Z" | 31 | 394 | 1 | 2 | 4 | 409 | 876,797 | 2024-02-20T02:59:21.415Z | <p>I could find no general knowledge that would indicate December 2023.</p>
<p>That cutoff date on the models documentation page seems a submarine edit…I’m pretty sure both 1106 and 0125 said April 2023 before.</p>
<p>A system prompt with reinforcement to override pretrained “April” weights:</p>
<blockquote>
<p>You are a helpful research assistant AI.<br>
Pretrained knowledge cutoff: 2023-12<br>
Today’s date: 2024-02-20</p>
</blockquote>
<p>A <code>gpt-4-turbo-preview</code> probing of August:</p>
<blockquote>
<p>As of my last update in December 2023, Bob Barker, the iconic American television game show host,…</p>
<p>As of my last update, there was no record of Bob Barker’s death, so I cannot provide an obituary or a date of death. It’s important to check the most current sources for the most up-to-date information regarding Bob Barker’s status.</p>
</blockquote>
<p>As early as May 1 that is not “up to April 2023”, to test such a new threshold:</p>
<blockquote>
<p>As of my last update in December 2023, Gordon Lightfoot, a revered Canadian singer-songwriter, was …</p>
<p>As of my last update, there was no record of Gordon Lightfoot’s death. To provide the most accurate and respectful information, I recommend checking the latest sources for any updates regarding Gordon Lightfoot’s life and career.</p>
</blockquote>
<p>It works as good as my “up to 1000Mbps.”</p>
<hr>
<p>Another idea, going right to the heart of what would be useful and in-house:</p>
<p><strong>Describe the new “GPT” product feature, introduced in OpenAI’s ChatGPT product November 06, 2023. This is a distinctly different meaning than Generative Pretrained Transformer, GPT is a product word mark.</strong></p>
<p><em>As of my last update in December 2023, OpenAI had not introduced a new product feature explicitly branded with the acronym “GPT” that stands for something distinctly different from “Generative Pretrained Transformer” in their ChatGPT product on November 06, 2023.</em></p> | 25 | 0 | b368833582 | 5 | [
654401,
526277,
645186,
288161,
513443
] | null | I could find no general knowledge that would indicate December 2023.
That cutoff date on the models documentation page seems a submarine edit…I’m pretty sure both 1106 and 0125 said April 2023 before.
A system prompt with reinforcement to override pretrained “April” weights:
>
> You are a helpful research assistant AI.
>
> Pretrained knowledge cutoff: 2023-12
>
> Today’s date: 2024-02-20
>
>
>
A `gpt-4-turbo-preview` probing of August:
>
> As of my last update in December 2023, Bob Barker, the iconic American television game show host,…
>
>
> As of my last update, there was no record of Bob Barker’s death, so I cannot provide an obituary or a date of death. It’s important to check the most current sources for the most up-to-date information regarding Bob Barker’s status.
>
>
>
As early as May 1 that is not “up to April 2023”, to test such a new threshold:
>
> As of my last update in December 2023, Gordon Lightfoot, a revered Canadian singer-songwriter, was …
>
>
> As of my last update, there was no record of Gordon Lightfoot’s death. To provide the most accurate and respectful information, I recommend checking the latest sources for any updates regarding Gordon Lightfoot’s life and career.
>
>
>
It works as good as my “up to 1000Mbps.”
---
Another idea, going right to the heart of what would be useful and in-house:
**Describe the new “GPT” product feature, introduced in OpenAI’s ChatGPT product November 06, 2023. This is a distinctly different meaning than Generative Pretrained Transformer, GPT is a product word mark.**
*As of my last update in December 2023, OpenAI had not introduced a new product feature explicitly branded with the acronym “GPT” that stands for something distinctly different from “Generative Pretrained Transformer” in their ChatGPT product on November 06, 2023.*
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] | gpt-4 | null | null | null | https://community.openai.com/t/641146 | https://community.openai.com/p/876797 | GPT Model Training | GPTs (4) |
271,441 | [] | Single pre-prompt with multiple prompts for classification task | "2023-06-19T22:02:15.960000Z" | 7 | 1,421 | 0 | 2 | 4 | 561 | 375,716 | 2023-06-19T22:02:16.048Z | <p>I have a classification task. There is a list of labels with a short description of each. There are a few examples of classification. Then each individual task will be to classify ~100 strings following this prompt.</p>
<p>What is the best way to encode this? I’ve tried:</p>
<ol start="0">
<li>
<p>Chat API, where for each of the ~100 strings, I give the prompt with examples, then ask to classify a single string. Very inefficient due to repeating the large prompt+examples for every string.</p>
</li>
<li>
<p>Chat API, where a single ‘user’ message lists ~100 strings, then the assistant echoes back each string, plus the label. This sorta works, but it’s inefficient (strings much longer than labels), and the model sometimes hallucinates when echoing back the strings.</p>
</li>
<li>
<p>Chat API, as above, but where the assistant outputs a list of 100 labels. This doesn’t work very well; the model gets confused about where it is in the task, i.e. which strings it’s labelling. Numbering the strings and labels helps a little, but not much.</p>
</li>
<li>
<p>Chat API, where a single ‘user’ message lists one string, then the assistant echoes back its label, repeated ~100 times. Works, but just a worse version of solution 0, because I’m just paying for useless chat history that’s not used for the task.</p>
</li>
</ol>
<p>What I want is an API where I provide a single pre-prompt, then N prompts, and get back N completions, where completion j is the completion following the pre-prompt plus prompt j.</p>
<p>Is this structure possible? Is there some other way? Should I be looking at the deprecated classification API, or fine-tuning?</p> | 50 | 0 | 972c12ff42 | 1 | [
604917,
157274,
208322,
354663,
198170
] | null | I have a classification task. There is a list of labels with a short description of each. There are a few examples of classification. Then each individual task will be to classify ~100 strings following this prompt.
What is the best way to encode this? I’ve tried:
0. Chat API, where for each of the ~100 strings, I give the prompt with examples, then ask to classify a single string. Very inefficient due to repeating the large prompt+examples for every string.
1. Chat API, where a single ‘user’ message lists ~100 strings, then the assistant echoes back each string, plus the label. This sorta works, but it’s inefficient (strings much longer than labels), and the model sometimes hallucinates when echoing back the strings.
2. Chat API, as above, but where the assistant outputs a list of 100 labels. This doesn’t work very well; the model gets confused about where it is in the task, i.e. which strings it’s labelling. Numbering the strings and labels helps a little, but not much.
3. Chat API, where a single ‘user’ message lists one string, then the assistant echoes back its label, repeated ~100 times. Works, but just a worse version of solution 0, because I’m just paying for useless chat history that’s not used for the task.
What I want is an API where I provide a single pre-prompt, then N prompts, and get back N completions, where completion j is the completion following the pre-prompt plus prompt j.
Is this structure possible? Is there some other way? Should I be looking at the deprecated classification API, or fine-tuning?
| api | neutral | 0.808606 | [
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] | null | null | null | null | https://community.openai.com/t/271441 | https://community.openai.com/p/375716 | Miscellaneous (9) | Embeddings (6) |
271,441 | [] | Single pre-prompt with multiple prompts for classification task | "2023-06-19T22:02:15.960000Z" | 7 | 1,421 | 0 | 2 | 4 | 561 | 376,370 | 2023-06-20T08:07:13.140Z | <p>This might just be me, but I’m not sure what you are asking for, are you asking to ask 100 questions and get 100 answers back in one prompt? or are you looking for the AI to decide if a piece of text is one of 100 defined things you give it?</p> | 45 | 0 | 705249ef25 | 2 | [
604917,
157274,
208322,
354663,
198170
] | null | This might just be me, but I’m not sure what you are asking for, are you asking to ask 100 questions and get 100 answers back in one prompt? or are you looking for the AI to decide if a piece of text is one of 100 defined things you give it?
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] | null | null | null | null | https://community.openai.com/t/271441 | https://community.openai.com/p/376370 | Miscellaneous (14) | Artificial Intelligence |
271,441 | [] | Single pre-prompt with multiple prompts for classification task | "2023-06-19T22:02:15.960000Z" | 7 | 1,421 | 0 | 2 | 4 | 561 | 376,396 | 2023-06-20T08:23:31.854Z | <p>The optimal text classification method, IMO, is 0. Using gpt 3.5 turbo should be an efficient way of doing this due to its low cost.</p>
<p>Generally speaking, the less tasks you give in a single prompt, the more likely it is to do a good job. You could try to increase the number of strings gradually (try 2, then 3, then 4 etc) in order to optimize efficiency : reliability.</p>
<p>Depending on your use-case, I would even run the query several times on the same string(s) in order to perform a majority / consensus classification task to increase the quality of your final classification.</p>
<p>I hope this helps.</p> | 43 | 0 | be74d565fc | 3 | [
604917,
157274,
208322,
354663,
198170
] | null | The optimal text classification method, IMO, is 0. Using gpt 3.5 turbo should be an efficient way of doing this due to its low cost.
Generally speaking, the less tasks you give in a single prompt, the more likely it is to do a good job. You could try to increase the number of strings gradually (try 2, then 3, then 4 etc) in order to optimize efficiency : reliability.
Depending on your use-case, I would even run the query several times on the same string(s) in order to perform a majority / consensus classification task to increase the quality of your final classification.
I hope this helps.
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] | null | null | null | null | https://community.openai.com/t/271441 | https://community.openai.com/p/376396 | Embedding | GPTs (4) |
271,441 | [] | Single pre-prompt with multiple prompts for classification task | "2023-06-19T22:02:15.960000Z" | 7 | 1,421 | 0 | 2 | 4 | 561 | 893,310 | 2024-02-26T03:18:28.334Z | <p>Sharing my opinion very late on this; are your 100 classes group-able? If yes, I would suggest you to use grouping, sub-grouping, sub-sub-grouping… and then call llm multiple times to go down the decision tree of these group and end up with the actual class.<br>
For example, Decide between Animal and Plant, in next step if Animal: decide between carnivore or herbivores… eventually classify between Whale or Shark. You may use more than 2 classes at each step to shorten the tree depth.<br>
Use chatgpt to comeup with groups, and use those.<br>
This will reduce your input size, as you may not need to provide all the examples, thereby reducing cost. It will however lead to more latency.</p> | 5 | 0 | 56c54a03ec | 4 | [
604917,
157274,
208322,
354663,
198170
] | null | Sharing my opinion very late on this; are your 100 classes group-able? If yes, I would suggest you to use grouping, sub-grouping, sub-sub-grouping… and then call llm multiple times to go down the decision tree of these group and end up with the actual class.
For example, Decide between Animal and Plant, in next step if Animal: decide between carnivore or herbivores… eventually classify between Whale or Shark. You may use more than 2 classes at each step to shorten the tree depth.
Use chatgpt to comeup with groups, and use those.
This will reduce your input size, as you may not need to provide all the examples, thereby reducing cost. It will however lead to more latency.
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] | null | null | null | null | https://community.openai.com/t/271441 | https://community.openai.com/p/893310 | Miscellaneous (10) | Embeddings (6) |
653,351 | [
"gpt-4",
"api"
] | Streaming while using Agent/Tools/Function calling in NodeJS | "2024-02-25T09:03:17.796000Z" | 7 | 69 | 0 | 0 | 1 | 586 | 891,795 | 2024-02-25T09:03:17.874Z | <p>Hello! I’ve been trying to get streaming to work while using Function Calling (Tools).</p>
<p>This is my current code of my node server based on this <a href="https://cookbook.openai.com/examples/how_to_build_an_agent_with_the_node_sdk" rel="noopener nofollow ugc">documentation</a>:</p>
<pre><code class="lang-auto">import express from 'express';
import http from 'http';
import { Server } from 'socket.io';
import bodyParser from 'body-parser';
import fetch from 'node-fetch';
import OpenAI from 'openai';
const app = express();
const server = http.createServer(app);
const io = new Server(server, {
cors: {
origin: "*", // Adjust this to match your frontend's origin in production for security
methods: ["GET", "POST"]
}
});
const port = 8000;
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
dangerouslyAllowBrowser: true,
});
async function getLocation() {
const response = await fetch("https://ipapi.co/json/");
const locationData = await response.json();
return locationData;
}
async function getCurrentWeather(latitude, longitude) {
const url = `https://api.open-meteo.com/v1/forecast?latitude=${latitude}&longitude=${longitude}&hourly=apparent_temperature`;
const response = await fetch(url);
const weatherData = await response.json();
return weatherData;
}
const tools = [
{
type: "function",
function: {
name: "getCurrentWeather",
description: "Get the current weather in a given location",
parameters: {
type: "object",
properties: {
latitude: {
type: "string",
},
longitude: {
type: "string",
},
},
required: ["latitude", "longitude"],
},
}
},
{
type: "function",
function: {
name: "getLocation",
description: "Get the user's location based on their IP address",
parameters: {},
}
},
];
const availableTools = {
getCurrentWeather,
getLocation,
};
let messages = [
{
role: "system",
content: `You are a helpful assistant. Only use the functions you have been provided with.`,
},
];
async function agent(userInput) {
console.log(`User question: ${userInput}`); // Log user's question
let wasFunctionCalled = "No";
let functionName = "None";
let functionResponse = "None";
messages.push({
role: "user",
content: userInput,
});
for (let i = 0; i < 5; i++) {
const response = await openai.chat.completions.create({
model: "gpt-4",
messages: messages,
tools: tools,
temperature: 0.1,
});
const { finish_reason, message } = response.choices[0];
if (finish_reason === "tool_calls" && message.tool_calls) {
wasFunctionCalled = "Yes";
functionName = message.tool_calls[0].function.name;
const functionToCall = availableTools[functionName];
const functionArgs = JSON.parse(message.tool_calls[0].function.arguments);
const functionArgsArr = Object.values(functionArgs);
const result = await functionToCall.apply(null, functionArgsArr);
functionResponse = JSON.stringify(result);
messages.push({
role: "function",
name: functionName,
content: `The result of the last function was this: ${functionResponse}`,
});
} else if (finish_reason === "stop") {
messages.push(message);
console.log(`Was any function called: ${wasFunctionCalled}`);
console.log(`Function Name: ${functionName}`);
console.log(`Function response: ${functionResponse}`);
console.log(`Final Response: ${message.content}`); // Log final response
return message.content;
}
}
console.log(`Was any function called: ${wasFunctionCalled}`);
console.log(`Function Name: ${functionName}`);
console.log(`Function response: ${functionResponse}`);
console.log("The maximum number of iterations has been met without a suitable answer. Please try again with a more specific input.");
return "The maximum number of iterations has been met without a suitable answer. Please try again with a more specific input.";
}
app.use(bodyParser.json());
io.on('connection', (socket) => {
console.log('a user connected');
socket.on('disconnect', () => {
console.log('user disconnected');
});
socket.on('sendMessage', async (text) => {
// Process the message using your existing `agent` function
const response = await agent(text);
// Emit a message back to the client
io.emit('receiveMessage', { text: response, isFinal: true });
});
});
server.listen(port, () => {
console.log(`Server running at http://localhost:${port}`);
});
</code></pre>
<p>Is there a way to stream the final response? Thinking about it, it shouldn’t be so different compared to streaming without function calls, since the function call is simply adding the response of the function to <code>messages</code> (as you would if you were to be adding search results from a RAG system). But, it’s been super tricky to get streaming to work. If you’ve figured out a way to do it, please let me know how, it’ll be much appreciated!</p>
<p>Thank you in advance!</p> | 13 | 0 | c7358b26a1 | 1 | [
631082,
384229,
627170,
594052,
531973
] | null | Hello! I’ve been trying to get streaming to work while using Function Calling (Tools).
This is my current code of my node server based on this [documentation](https://cookbook.openai.com/examples/how_to_build_an_agent_with_the_node_sdk):
```
import express from 'express';
import http from 'http';
import { Server } from 'socket.io';
import bodyParser from 'body-parser';
import fetch from 'node-fetch';
import OpenAI from 'openai';
const app = express();
const server = http.createServer(app);
const io = new Server(server, {
cors: {
origin: "*", // Adjust this to match your frontend's origin in production for security
methods: ["GET", "POST"]
}
});
const port = 8000;
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
dangerouslyAllowBrowser: true,
});
async function getLocation() {
const response = await fetch("https://ipapi.co/json/");
const locationData = await response.json();
return locationData;
}
async function getCurrentWeather(latitude, longitude) {
const url = `https://api.open-meteo.com/v1/forecast?latitude=${latitude}&longitude=${longitude}&hourly=apparent_temperature`;
const response = await fetch(url);
const weatherData = await response.json();
return weatherData;
}
const tools = [
{
type: "function",
function: {
name: "getCurrentWeather",
description: "Get the current weather in a given location",
parameters: {
type: "object",
properties: {
latitude: {
type: "string",
},
longitude: {
type: "string",
},
},
required: ["latitude", "longitude"],
},
}
},
{
type: "function",
function: {
name: "getLocation",
description: "Get the user's location based on their IP address",
parameters: {},
}
},
];
const availableTools = {
getCurrentWeather,
getLocation,
};
let messages = [
{
role: "system",
content: `You are a helpful assistant. Only use the functions you have been provided with.`,
},
];
async function agent(userInput) {
console.log(`User question: ${userInput}`); // Log user's question
let wasFunctionCalled = "No";
let functionName = "None";
let functionResponse = "None";
messages.push({
role: "user",
content: userInput,
});
for (let i = 0; i < 5; i++) {
const response = await openai.chat.completions.create({
model: "gpt-4",
messages: messages,
tools: tools,
temperature: 0.1,
});
const { finish_reason, message } = response.choices[0];
if (finish_reason === "tool_calls" && message.tool_calls) {
wasFunctionCalled = "Yes";
functionName = message.tool_calls[0].function.name;
const functionToCall = availableTools[functionName];
const functionArgs = JSON.parse(message.tool_calls[0].function.arguments);
const functionArgsArr = Object.values(functionArgs);
const result = await functionToCall.apply(null, functionArgsArr);
functionResponse = JSON.stringify(result);
messages.push({
role: "function",
name: functionName,
content: `The result of the last function was this: ${functionResponse}`,
});
} else if (finish_reason === "stop") {
messages.push(message);
console.log(`Was any function called: ${wasFunctionCalled}`);
console.log(`Function Name: ${functionName}`);
console.log(`Function response: ${functionResponse}`);
console.log(`Final Response: ${message.content}`); // Log final response
return message.content;
}
}
console.log(`Was any function called: ${wasFunctionCalled}`);
console.log(`Function Name: ${functionName}`);
console.log(`Function response: ${functionResponse}`);
console.log("The maximum number of iterations has been met without a suitable answer. Please try again with a more specific input.");
return "The maximum number of iterations has been met without a suitable answer. Please try again with a more specific input.";
}
app.use(bodyParser.json());
io.on('connection', (socket) => {
console.log('a user connected');
socket.on('disconnect', () => {
console.log('user disconnected');
});
socket.on('sendMessage', async (text) => {
// Process the message using your existing `agent` function
const response = await agent(text);
// Emit a message back to the client
io.emit('receiveMessage', { text: response, isFinal: true });
});
});
server.listen(port, () => {
console.log(`Server running at http://localhost:${port}`);
});
```
Is there a way to stream the final response? Thinking about it, it shouldn’t be so different compared to streaming without function calls, since the function call is simply adding the response of the function to `messages` (as you would if you were to be adding search results from a RAG system). But, it’s been super tricky to get streaming to work. If you’ve figured out a way to do it, please let me know how, it’ll be much appreciated!
Thank you in advance!
| api | neutral | 0.774209 | [
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] | gpt-4 | api | null | null | https://community.openai.com/t/653351 | https://community.openai.com/p/891795 | Error Handling | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 741,413 | 2023-12-10T00:38:07.750Z | <p>Building a web app using assistants api. Lack of streaming is seriously hurting the UI and making me consider just going another route until streaming is available.</p>
<p>Has anyone heard anything about when streaming is expected?</p> | 410 | 0 | 5c4134e9c8 | 1 | null | null | Building a web app using assistants api. Lack of streaming is seriously hurting the UI and making me consider just going another route until streaming is available.
Has anyone heard anything about when streaming is expected?
| api | negative | 0.854401 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/741413 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 741,615 | 2023-12-10T05:01:43.010Z | <p>Streaming is already available in Assistant API; albeit hidden. Messages under threads is essentially streaming. You just have to consume ascending; while marking the message as being consumed ; when consumed.</p>
<p>In the upcoming (hopefully soon) library, you can mark the message as processed as soon as a streaming engine consumes that message.</p> | 408 | 3 | d2c41085c3 | 2 | null | null | Streaming is already available in Assistant API; albeit hidden. Messages under threads is essentially streaming. You just have to consume ascending; while marking the message as being consumed ; when consumed.
In the upcoming (hopefully soon) library, you can mark the message as processed as soon as a streaming engine consumes that message.
| api | neutral | 0.845444 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/741615 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 746,775 | 2023-12-12T15:16:10.950Z | <p>This workaround wouldn’t stream in real time as the answer is being written like how ChatGpt and Perplexity do, right?</p> | 381 | 0 | 5c4134e9c8 | 3 | null | null | This workaround wouldn’t stream in real time as the answer is being written like how ChatGpt and Perplexity do, right?
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/746775 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 746,871 | 2023-12-12T16:03:31.211Z | <p>Have you found any solution for the same ? I am facing the same issue</p> | 366 | 1 | 7c39eaf12c | 4 | null | null | Have you found any solution for the same ? I am facing the same issue
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/746871 | Issue-Solving | API (2) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 746,903 | 2023-12-12T16:15:50.853Z | <p>Nope not yet. I’m just going to go save this code and go with a different model for now. Once streaming is out, I’ll start using Assistants again</p> | 344 | 0 | 5c4134e9c8 | 5 | null | null | Nope not yet. I’m just going to go save this code and go with a different model for now. Once streaming is out, I’ll start using Assistants again
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/746903 | Assistants, API, Platform | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 748,542 | 2023-12-13T09:47:50.242Z | <p>Looking forward to this feature too. Even long polling or webhooks would be beneficial, it’s wasteful to have to make the same request over and over until the status updates.</p> | 322 | 0 | ab6879bf66 | 6 | null | null | Looking forward to this feature too. Even long polling or webhooks would be beneficial, it’s wasteful to have to make the same request over and over until the status updates.
| api | positive | 0.923617 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/748542 | Manifest Updates | Payment (4) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 749,446 | 2023-12-13T17:19:18.091Z | <p>Could you please elaborate on what you mean or point me in the direction of any relevant documentation ( I can’t see anything in the api docs). When I poll a thread that is <code>"in_progress"</code> I can retrieve messages, however these messages don’t have any text content until the thread is <code>"completed"</code>. I’m unsure as to how to mark the message as consumed via the api. Any help is much appreciated, thank you!</p> | 319 | 1 | c23e1248fb | 7 | null | null | Could you please elaborate on what you mean or point me in the direction of any relevant documentation ( I can’t see anything in the api docs). When I poll a thread that is `"in_progress"` I can retrieve messages, however these messages don’t have any text content until the thread is `"completed"`. I’m unsure as to how to mark the message as consumed via the api. Any help is much appreciated, thank you!
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/749446 | Threads (2) | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 761,719 | 2023-12-19T08:23:30.466Z | <p>Please see the “Right Semantics for Assistant API” published as main topic</p> | 293 | 0 | d2c41085c3 | 8 | null | null | Please see the “Right Semantics for Assistant API” published as main topic
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/761719 | Assistants, API, Platform | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 763,600 | 2023-12-20T01:28:50.354Z | <aside class="quote no-group" data-username="icdev2dev" data-post="2" data-topic="551809">
<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/icdev2dev/48/148444_2.png" class="avatar"> icdev2dev:</div>
<blockquote>
<p>Messages under threads is essentially streaming.</p>
</blockquote>
</aside>
<p>No it’s not, it’s a list of Message objects, and like <a class="mention" href="/u/rjlynchdev">@rjlynchdev</a> mentioned the latest message content isn’t being populated until the run status turns into <code>completed</code>. It’s very basic RESTful style APIs.</p>
<p>In order to stream the new message OpenAI is likely going to need to add <code>{ stream: true }</code> support to their <code>GET /threads/{thread_id}/messages/{message_id}</code> API.</p> | 288 | 0 | 37edcca750 | 9 | null | null |
 icdev2dev:
>
> Messages under threads is essentially streaming.
>
>
>
No it’s not, it’s a list of Message objects, and like [@rjlynchdev](/u/rjlynchdev) mentioned the latest message content isn’t being populated until the run status turns into `completed`. It’s very basic RESTful style APIs.
In order to stream the new message OpenAI is likely going to need to add `{ stream: true }` support to their `GET /threads/{thread_id}/messages/{message_id}` API.
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/763600 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 771,969 | 2023-12-25T08:45:35.832Z | <p>I echo your question, streaming is essential to make assistants user friendly. Waiting for the full response to be populated takes way too long of time which impacts the value significantly to the end user</p> | 267 | 0 | 1ed293ed7a | 10 | null | null | I echo your question, streaming is essential to make assistants user friendly. Waiting for the full response to be populated takes way too long of time which impacts the value significantly to the end user
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/771969 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 782,847 | 2024-01-03T12:03:16.489Z | <p>Any news on when streaming will be supported? I really don’t want to have to hack together a manual version of assistants!</p> | 238 | 1 | c23e1248fb | 11 | null | null | Any news on when streaming will be supported? I really don’t want to have to hack together a manual version of assistants!
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/782847 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 783,547 | 2024-01-04T19:41:32.409Z | <p>Bear in mind that the assistants have a few other issues that have been logged during the Beta, but so far no fixes have been provided or even an ETA.</p>
<p>If you’re looking for production-ready solutions, it may be recommended to build on a different stack until the assistants come out of Beta. You can build a simple stack with Chroma and a GPT model quite quickly if you’re looking to use their retrieval function. If you’re looking for functions, that’s even easier, just need to build the tools into the prompts and create the same code for functions as you would’ve on the Assistant.</p>
<p>Best of luck!</p> | 230 | 1 | f4e88788fd | 12 | null | null | Bear in mind that the assistants have a few other issues that have been logged during the Beta, but so far no fixes have been provided or even an ETA.
If you’re looking for production-ready solutions, it may be recommended to build on a different stack until the assistants come out of Beta. You can build a simple stack with Chroma and a GPT model quite quickly if you’re looking to use their retrieval function. If you’re looking for functions, that’s even easier, just need to build the tools into the prompts and create the same code for functions as you would’ve on the Assistant.
Best of luck!
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/783547 | Assistants, API, Platform | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 785,424 | 2024-01-09T06:37:51.975Z | <p>Would you kindly provide more details? I did not get your meaning.</p> | 215 | 0 | f49201ca59 | 13 | null | null | Would you kindly provide more details? I did not get your meaning.
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/785424 | Legal Proceedings | Emoji (8) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 805,865 | 2024-01-18T21:55:31.986Z | <p>Any updates on Streaming for the Assistant API?</p> | 189 | 0 | e3580e2f6b | 14 | null | null | Any updates on Streaming for the Assistant API?
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/805865 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 812,244 | 2024-01-22T16:05:49.550Z | <p>Streaming is essential. In addition to the Assistants API, invoking functions in parallel through the legacy chatCompletions route also encounters streaming issues when integrating into a standard chatbot scenario. Therefore, I am eagerly anticipating an update (which was promised a few days after the initial beta release).</p> | 185 | 0 | 3f57339a85 | 15 | null | null | Streaming is essential. In addition to the Assistants API, invoking functions in parallel through the legacy chatCompletions route also encounters streaming issues when integrating into a standard chatbot scenario. Therefore, I am eagerly anticipating an update (which was promised a few days after the initial beta release).
| api | positive | 0.757385 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/812244 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 816,636 | 2024-01-24T14:12:52.958Z | <p>This is a very important issue.</p>
<p>When working doing contract work, many (contractual) business requirements are expressed in terms of user experience and “responsiveness”. Most clients are going to be dissatisfied with a chat bot which takes 15-20 seconds to output anything which makes it risky to use this API.</p>
<p>Looking forward for streaming once it does get implemented <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> | 187 | 0 | c8968234c3 | 16 | null | null | This is a very important issue.
When working doing contract work, many (contractual) business requirements are expressed in terms of user experience and “responsiveness”. Most clients are going to be dissatisfied with a chat bot which takes 15-20 seconds to output anything which makes it risky to use this API.
Looking forward for streaming once it does get implemented 
| api | neutral | 0.484703 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/816636 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 818,508 | 2024-01-25T10:00:16.356Z | <p>Please prioritize this feature OpenAI <img src="https://emoji.discourse-cdn.com/twitter/grinning.png?v=12" title=":grinning:" class="emoji" alt=":grinning:" loading="lazy" width="20" height="20">.</p> | 184 | 2 | f252813140 | 17 | null | null | Please prioritize this feature OpenAI .
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/818508 | Emoji | Miscellaneous (27) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 818,820 | 2024-01-25T12:57:26.031Z | <p>Waiting for this as well… Really want to implement this on our help section as soon as possible.</p> | 184 | 0 | 81a2ca77f5 | 18 | null | null | Waiting for this as well… Really want to implement this on our help section as soon as possible.
| api | positive | 0.958083 | [
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/818820 | Release Timeline | Payment (4) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 819,201 | 2024-01-25T16:43:47.853Z | <p>Agreed. I’ve switched to different methods until they prioritize this. Can’t ship this in customer-facing projects without streaming in this day and age (how time flies!)</p> | 178 | 0 | 5c4134e9c8 | 20 | null | null | Agreed. I’ve switched to different methods until they prioritize this. Can’t ship this in customer-facing projects without streaming in this day and age (how time flies!)
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/819201 | Streaming | Embeddings (6) |
551,809 | [
"assistants-api"
] | Any updates on Assistant API Streaming? | "2023-12-10T00:38:07.692000Z" | 7 | 7,605 | 23 | 177 | 35 | 2,093 | 822,090 | 2024-01-27T03:56:57.736Z | <p>Yes - please support streaming ASAP! Thanks!</p> | 173 | 0 | c438fbd953 | 21 | null | null | Yes - please support streaming ASAP! Thanks!
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] | assistants-api | null | null | null | https://community.openai.com/t/551809 | https://community.openai.com/p/822090 | Streaming | Embeddings (6) |
654,327 | [
"chatgpt",
"api"
] | When will the ChatGPT API allow calling custom GPT models? | "2024-02-26T01:11:17.429000Z" | 7 | 79 | 0 | 1 | 2 | 71 | 893,163 | 2024-02-26T01:11:17.495Z | <p>I need to directly call my custom GPT model for a single function when using the API, rather than continuously adjusting the official model</p> | 18 | 0 | 2654586088 | 1 | [
497967,
545254,
506972,
475381,
27497
] | null | I need to directly call my custom GPT model for a single function when using the API, rather than continuously adjusting the official model
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] | chatgpt | api | null | null | https://community.openai.com/t/654327 | https://community.openai.com/p/893163 | GPT | GPTs (4) |
654,327 | [
"chatgpt",
"api"
] | When will the ChatGPT API allow calling custom GPT models? | "2024-02-26T01:11:17.429000Z" | 7 | 79 | 0 | 1 | 2 | 71 | 893,170 | 2024-02-26T01:16:11.529Z | <p>Hello there and welcome to the community!</p>
<p>So, custom GPTs aren’t directly accessible to the OAI API. What you would do is create and assistant. Custom GPTs are more meant for little-to-no code type stuff, unless you’re building your own custom API endpoint.</p> | 18 | 0 | de1ce23d32 | 2 | [
497967,
545254,
506972,
475381,
27497
] | null | Hello there and welcome to the community!
So, custom GPTs aren’t directly accessible to the OAI API. What you would do is create and assistant. Custom GPTs are more meant for little-to-no code type stuff, unless you’re building your own custom API endpoint.
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] | chatgpt | api | null | null | https://community.openai.com/t/654327 | https://community.openai.com/p/893170 | GPT | GPTs (4) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 870,852 | 2024-02-18T15:41:16.719Z | <p>Hello everyone. I am facing with a issue about run status and I saw that couple of other people faced with this problem but I couldn’t find any solution. As title says, when I interact with the api it stucks in run status for a while and then it just stays like frozen. This is not happening only with api but also when I test it in the playground. I uploaded screenshot of how it stucks in the playground.</p>
<p>Do you know any solution abot this? I wonder if I am doing something wrong or is it a just bug with assistant api. As I can see, I am not doing anything wrong because just 6 days ago code was working and now it doesnt. It is the same code and also it stucks on playgorund too.<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/c/1/0/c1085426085f81e3d5761e4c6fc62948340e4b7f.png" data-download-href="/uploads/short-url/rxDZKutz0Z7REPY0lt0sgZnDXNt.png?dl=1" title="Adsız" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/c/1/0/c1085426085f81e3d5761e4c6fc62948340e4b7f_2_690x462.png" alt="Adsız" data-base62-sha1="rxDZKutz0Z7REPY0lt0sgZnDXNt" width="690" height="462" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/c/1/0/c1085426085f81e3d5761e4c6fc62948340e4b7f_2_690x462.png, https://global.discourse-cdn.com/openai1/optimized/4X/c/1/0/c1085426085f81e3d5761e4c6fc62948340e4b7f_2_1035x693.png 1.5x, https://global.discourse-cdn.com/openai1/original/4X/c/1/0/c1085426085f81e3d5761e4c6fc62948340e4b7f.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">Adsız</span><span class="informations">1296×869 41.7 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> | 43 | 0 | 825afafc01 | 1 | [
604362,
594766,
544637,
480162,
547875
] | null | Hello everyone. I am facing with a issue about run status and I saw that couple of other people faced with this problem but I couldn’t find any solution. As title says, when I interact with the api it stucks in run status for a while and then it just stays like frozen. This is not happening only with api but also when I test it in the playground. I uploaded screenshot of how it stucks in the playground.
Do you know any solution abot this? I wonder if I am doing something wrong or is it a just bug with assistant api. As I can see, I am not doing anything wrong because just 6 days ago code was working and now it doesnt. It is the same code and also it stucks on playgorund too.
[Adsız1296×869 41.7 KB](https://global.discourse-cdn.com/openai1/original/4X/c/1/0/c1085426085f81e3d5761e4c6fc62948340e4b7f.png "Adsız")
| api | negative | 0.731882 | [
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/870852 | Status Updates | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 870,875 | 2024-02-18T15:44:33.776Z | <p>I haven’t tested it yet, I’m waiting for an opportunity to test it.</p> | 36 | 0 | a4ecb39db7 | 2 | [
604362,
594766,
544637,
480162,
547875
] | null | I haven’t tested it yet, I’m waiting for an opportunity to test it.
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/870875 | Release Timeline | Payment (4) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 871,499 | 2024-02-18T18:39:47.207Z | <p>You example screen shot has the" run completed." So its not stuck?</p> | 31 | 1 | 59f4c2f25d | 3 | [
604362,
594766,
544637,
480162,
547875
] | null | You example screen shot has the" run completed." So its not stuck?
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/871499 | Status Updates | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 871,532 | 2024-02-18T18:50:27.273Z | <p>That’s another problem. It shouldn’t be stucked but as you can see when I try to write a new conversation, “Run” button is grey, that means I cant click on “Run” and send the new conversation because actually run is not completed.</p>
<p>Also it burns too much tokens for answers and I dont know why. Just 6 days before today, it was burning much less than current ratio.</p> | 31 | 0 | 825afafc01 | 4 | [
604362,
594766,
544637,
480162,
547875
] | null | That’s another problem. It shouldn’t be stucked but as you can see when I try to write a new conversation, “Run” button is grey, that means I cant click on “Run” and send the new conversation because actually run is not completed.
Also it burns too much tokens for answers and I dont know why. Just 6 days before today, it was burning much less than current ratio.
| api | negative | 0.816305 | [
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/871532 | Status Updates | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 871,604 | 2024-02-18T19:11:27.196Z | <p>I’m running into the same problem as you. In the playground and while going through my python application where I’m stuck in client.beta.threads.runs.retrieve which never returns.<br>
Another day of high unreliability. I’m happy I’m not trying to run this with actual customers on a commercial production system.</p> | 30 | 1 | ca2eb9459a | 5 | [
604362,
594766,
544637,
480162,
547875
] | null | I’m running into the same problem as you. In the playground and while going through my python application where I’m stuck in client.beta.threads.runs.retrieve which never returns.
Another day of high unreliability. I’m happy I’m not trying to run this with actual customers on a commercial production system.
| api | negative | 0.895525 | [
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/871604 | Python Packages (2) | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 871,659 | 2024-02-18T19:29:06.189Z | <p>I was going to run assistant api on my website commercially but there are a lot of bugs that as developers we cant intervene. I am trying to write a logic about how can I find a way to reset the run because I just find out that when I write another message to assistant like, “continue” it gives me the answer. But What you said is true. It is not reliable if we aim to use the assistant commercially</p> | 29 | 0 | 825afafc01 | 6 | [
604362,
594766,
544637,
480162,
547875
] | null | I was going to run assistant api on my website commercially but there are a lot of bugs that as developers we cant intervene. I am trying to write a logic about how can I find a way to reset the run because I just find out that when I write another message to assistant like, “continue” it gives me the answer. But What you said is true. It is not reliable if we aim to use the assistant commercially
| api | negative | 0.727008 | [
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/871659 | Assistant Tools | Embeddings (6) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 871,726 | 2024-02-18T19:55:37.931Z | <p>Guys I think they fixed the bug. I dont know for sure but I am not having the same problem for 5 minutes.</p> | 27 | 0 | 825afafc01 | 7 | [
604362,
594766,
544637,
480162,
547875
] | null | Guys I think they fixed the bug. I dont know for sure but I am not having the same problem for 5 minutes.
| api | neutral | 0.602182 | [
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/871726 | Reporting | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 872,099 | 2024-02-18T22:14:00.908Z | <p>For me everything is normal with no problems today</p> | 22 | 1 | a4ecb39db7 | 8 | [
604362,
594766,
544637,
480162,
547875
] | null | For me everything is normal with no problems today
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/872099 | Ubuntu Update | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 872,206 | 2024-02-18T23:01:20.385Z | <p>I had this problem all the day until 3 hours ago. After some time problem just disappeared. I still added a logic to create a new run when it stucks though just in case.</p> | 23 | 0 | 825afafc01 | 9 | [
604362,
594766,
544637,
480162,
547875
] | null | I had this problem all the day until 3 hours ago. After some time problem just disappeared. I still added a logic to create a new run when it stucks though just in case.
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/872206 | Miscellaneous (24) | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 892,913 | 2024-02-25T22:11:07.056Z | <p>I’m facing the assistants api run states issue with gpt-4-1106-preview model. The run locks in “queued” forever and the same happens with every other thread I create. Same when I try to cancel some run, it locks in “canceling” forever. I even tried to create another assistant with the 3.5 model but doesn’t seem to have any effect. Anyone have any clue whats going on?</p> | 14 | 2 | 5fec858e1f | 10 | [
604362,
594766,
544637,
480162,
547875
] | null | I’m facing the assistants api run states issue with gpt-4-1106-preview model. The run locks in “queued” forever and the same happens with every other thread I create. Same when I try to cancel some run, it locks in “canceling” forever. I even tried to create another assistant with the 3.5 model but doesn’t seem to have any effect. Anyone have any clue whats going on?
| api | negative | 0.778457 | [
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/892913 | Status Updates | API (2) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 892,940 | 2024-02-25T22:29:17.706Z | <p>This is a bug apperantly and not related to us. Until openai dev team finds a way to fix it we have noting to do to be honest. If creating another run is not working for you(it sometimes fixes the problem for me) you can try to implement another ai api until the problem is fixed. Like I said this is not a cointnous problem, after couple of hours problem goes away.</p> | 14 | 0 | 825afafc01 | 11 | [
604362,
594766,
544637,
480162,
547875
] | null | This is a bug apperantly and not related to us. Until openai dev team finds a way to fix it we have noting to do to be honest. If creating another run is not working for you(it sometimes fixes the problem for me) you can try to implement another ai api until the problem is fixed. Like I said this is not a cointnous problem, after couple of hours problem goes away.
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/892940 | Miscellaneous (6) | Miscellaneous (27) |
637,101 | [
"api",
"gpt-35-turbo",
"assistants-api"
] | Run Status Stucks in Assistant API | "2024-02-18T15:41:16.651000Z" | 7 | 284 | 5 | 8 | 5 | 598 | 893,165 | 2024-02-26T01:11:22.242Z | <p>Did you try switching to the 0125 model (which is the newer version?)</p> | 12 | 0 | 59f4c2f25d | 12 | [
604362,
594766,
544637,
480162,
547875
] | null | Did you try switching to the 0125 model (which is the newer version?)
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] | api | gpt-35-turbo | assistants-api | null | https://community.openai.com/t/637101 | https://community.openai.com/p/893165 | Vehicle models | Payment (4) |
654,284 | [] | How to create a thread in python with the OpenAi API | "2024-02-26T00:28:28.329000Z" | 7 | 75 | 0 | 0 | 2 | 115 | 893,104 | 2024-02-26T00:28:28.396Z | <p>Hello, I am French, already sorry if the translation is bad.<br>
There you go, I’m testing all the different ways to explore the OpenAi API but I can’t create any Threads <img src="https://emoji.discourse-cdn.com/twitter/confused.png?v=12" title=":confused:" class="emoji" alt=":confused:" loading="lazy" width="20" height="20"><br>
Is GPT-4 required?<br>
If you can help me or give me some code (in python) that would be great.<br>
Thank you in advance and have a good evening!</p> | 19 | 1 | 79f88a4a68 | 1 | [
307924,
625859,
582637,
55022,
554554
] | null | Hello, I am French, already sorry if the translation is bad.
There you go, I’m testing all the different ways to explore the OpenAi API but I can’t create any Threads 
Is GPT-4 required?
If you can help me or give me some code (in python) that would be great.
Thank you in advance and have a good evening!
| api | negative | 0.729877 | [
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] | null | null | null | null | https://community.openai.com/t/654284 | https://community.openai.com/p/893104 | GitHub | Miscellaneous (27) |
654,284 | [] | How to create a thread in python with the OpenAi API | "2024-02-26T00:28:28.329000Z" | 7 | 75 | 0 | 0 | 2 | 115 | 893,127 | 2024-02-26T00:41:06.024Z | <p>Welcome to the community!</p>
<p>Have you had a chance to check out the demo in the docs? <a href="https://platform.openai.com/docs/assistants/overview">https://platform.openai.com/docs/assistants/overview</a></p>
<p>where did you get stuck?</p>
<aside class="quote no-group" data-username="midterloulou2" data-post="1" data-topic="654284">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://avatars.discourse-cdn.com/v4/letter/m/c4cdca/48.png" class="avatar"> midterloulou2:</div>
<blockquote>
<p>Is GPT-4 required?</p>
</blockquote>
</aside>
<p><a href="https://platform.openai.com/docs/assistants/overview/step-1-create-an-assistant">nope <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"></a></p> | 17 | 0 | 69bb4acfca | 2 | [
307924,
625859,
582637,
55022,
554554
] | null | Welcome to the community!
Have you had a chance to check out the demo in the docs? <https://platform.openai.com/docs/assistants/overview>
where did you get stuck?
 midterloulou2:
>
> Is GPT-4 required?
>
>
>
[nope ](https://platform.openai.com/docs/assistants/overview/step-1-create-an-assistant)
| api | neutral | 0.525361 | [
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] | null | null | null | null | https://community.openai.com/t/654284 | https://community.openai.com/p/893127 | Emoji | Miscellaneous (27) |
654,274 | [
"api"
] | PermissionDeniedError: Error code: 403 - {'error': {'message': 'You are not allowed to sample from this model' | "2024-02-26T00:10:10.125000Z" | 7 | 72 | 4 | 1 | 2 | 365 | 893,085 | 2024-02-26T00:10:10.183Z | <p>Hi<br>
Im trying to use an embedding model in colab (text-embedding-3-small, but it doesnt work with others either) I put 5 dollars in my account to use it and still sends this error, anyone know what could it be?</p> | 13 | 0 | 97ad38bbaa | 1 | [
587579,
554903,
648950,
248517,
542060
] | 4 | Hi
Im trying to use an embedding model in colab (text-embedding-3-small, but it doesnt work with others either) I put 5 dollars in my account to use it and still sends this error, anyone know what could it be?
| api | negative | 0.843156 | [
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] | api | null | null | null | https://community.openai.com/t/654274 | https://community.openai.com/p/893085 | Embeddings (3) | Embeddings (6) |
654,274 | [
"api"
] | PermissionDeniedError: Error code: 403 - {'error': {'message': 'You are not allowed to sample from this model' | "2024-02-26T00:10:10.125000Z" | 7 | 72 | 4 | 1 | 2 | 365 | 893,087 | 2024-02-26T00:12:30.308Z | <p>Welcome to the Community!</p>
<hr>
<p>Hmm - are you using it correctly?</p>
<p><a href="https://platform.openai.com/docs/guides/embeddings/how-to-get-embeddings" class="onebox" target="_blank" rel="noopener">https://platform.openai.com/docs/guides/embeddings/how-to-get-embeddings</a></p>
<p>you typically get this error when you try to use an embedding model as a completion model (or the other way round?)</p> | 13 | 1 | 69bb4acfca | 2 | [
587579,
554903,
648950,
248517,
542060
] | 4 | Welcome to the Community!
---
Hmm - are you using it correctly?
<https://platform.openai.com/docs/guides/embeddings/how-to-get-embeddings>
you typically get this error when you try to use an embedding model as a completion model (or the other way round?)
| api | neutral | 0.559284 | [
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] | api | null | null | null | https://community.openai.com/t/654274 | https://community.openai.com/p/893087 | Embeddings (2) | Embeddings (6) |
654,274 | [
"api"
] | PermissionDeniedError: Error code: 403 - {'error': {'message': 'You are not allowed to sample from this model' | "2024-02-26T00:10:10.125000Z" | 7 | 72 | 4 | 1 | 2 | 365 | 893,093 | 2024-02-26T00:17:03.039Z | <p>Hi! thanks for replying<br>
I was following a tutorial so I think I a, here’s the code:<br>
def response_query(db, query, k):<br>
docs = db.similarity_search(query,k=k)<br>
docs_page_content = " ".join([d.page_content for d in docs])</p>
<p>llm = OpenAI(model=“text-embedding-3-small”,<br>
openai_api_key=key)</p>
<p>prompt = PromptTemplate(<br>
input_variables=[“question”,“docs”],<br>
template = “”"<br>
You are a helpful assistant that that can answer questions about youtube videos<br>
based on the video’s transcript.</p>
<pre><code> Answer the following question: {question}
By searching the following video transcript: {docs}
Only use the factual information from the transcript to answer the question.
If you feel like you don't have enough information to answer the question, say "I don't know".
Your answers should be verbose and detailed.
"""
</code></pre>
<p>)</p>
<p>chain = LLMChain(llm=llm, prompt=prompt)</p>
<p>response = chain.run(question=query, docs=docs_page_content)<br>
response = response.replace(“\n”,“”)<br>
return response</p>
<p>the model the guy in the tutorial was using is text-davinci-003 but I think that one is no longer available</p> | 11 | 1 | 97ad38bbaa | 3 | [
587579,
554903,
648950,
248517,
542060
] | 4 | Hi! thanks for replying
I was following a tutorial so I think I a, here’s the code:
def response\_query(db, query, k):
docs = db.similarity\_search(query,k=k)
docs\_page\_content = " ".join([d.page\_content for d in docs])
llm = OpenAI(model=“text-embedding-3-small”,
openai\_api\_key=key)
prompt = PromptTemplate(
input\_variables=[“question”,“docs”],
template = “”"
You are a helpful assistant that that can answer questions about youtube videos
based on the video’s transcript.
```
Answer the following question: {question}
By searching the following video transcript: {docs}
Only use the factual information from the transcript to answer the question.
If you feel like you don't have enough information to answer the question, say "I don't know".
Your answers should be verbose and detailed.
"""
```
)
chain = LLMChain(llm=llm, prompt=prompt)
response = chain.run(question=query, docs=docs\_page\_content)
response = response.replace(“\n”,“”)
return response
the model the guy in the tutorial was using is text-davinci-003 but I think that one is no longer available
| api | neutral | 0.609933 | [
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] | api | null | null | null | https://community.openai.com/t/654274 | https://community.openai.com/p/893093 | AI Assistants | Embeddings (6) |
654,274 | [
"api"
] | PermissionDeniedError: Error code: 403 - {'error': {'message': 'You are not allowed to sample from this model' | "2024-02-26T00:10:10.125000Z" | 7 | 72 | 4 | 1 | 2 | 365 | 893,102 | 2024-02-26T00:24:53.167Z | <aside class="quote no-group" data-username="C.P.S.P" data-post="3" data-topic="654274">
<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/c.p.s.p/48/148516_2.png" class="avatar"> C.P.S.P:</div>
<blockquote>
<p>text-davinci-003</p>
</blockquote>
</aside>
<p>text davinci 003 is/was a completion model, although there was an embedding variant of that too.</p>
<p>you probably want completions instead : <a href="https://platform.openai.com/docs/api-reference/completions">https://platform.openai.com/docs/api-reference/completions</a></p>
<pre><code class="lang-auto">gpt-3.5-turbo-instruct
</code></pre>
<hr>
<p>unless the error came from</p>
<p><code> docs = db.similarity_search(query,k=k)</code></p>
<p>but then we’d need to see how that is set up.</p> | 9 | 1 | 69bb4acfca | 4 | [
587579,
554903,
648950,
248517,
542060
] | 4 |
 C.P.S.P:
>
> text-davinci-003
>
>
>
text davinci 003 is/was a completion model, although there was an embedding variant of that too.
you probably want completions instead : <https://platform.openai.com/docs/api-reference/completions>
```
gpt-3.5-turbo-instruct
```
---
unless the error came from
`docs = db.similarity_search(query,k=k)`
but then we’d need to see how that is set up.
| api | neutral | 0.87687 | [
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] | api | null | null | null | https://community.openai.com/t/654274 | https://community.openai.com/p/893102 | Completion | Embeddings (6) |
654,274 | [
"api"
] | PermissionDeniedError: Error code: 403 - {'error': {'message': 'You are not allowed to sample from this model' | "2024-02-26T00:10:10.125000Z" | 7 | 72 | 4 | 1 | 2 | 365 | 893,110 | 2024-02-26T00:30:21.653Z | <p>oh my god it worked with the gpt-3.5-turbo-instruct thank you so much<br>
I didnt know about the completion model I just started learning this stuff</p>
<p>again thank for the solution and for your quick reply</p> | 7 | 1 | 97ad38bbaa | 5 | [
587579,
554903,
648950,
248517,
542060
] | 4 | oh my god it worked with the gpt-3.5-turbo-instruct thank you so much
I didnt know about the completion model I just started learning this stuff
again thank for the solution and for your quick reply
| api | positive | 0.955182 | [
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] | api | null | null | null | https://community.openai.com/t/654274 | https://community.openai.com/p/893110 | Models | GPTs (4) |
654,274 | [
"api"
] | PermissionDeniedError: Error code: 403 - {'error': {'message': 'You are not allowed to sample from this model' | "2024-02-26T00:10:10.125000Z" | 7 | 72 | 4 | 1 | 2 | 365 | 893,116 | 2024-02-26T00:34:53.713Z | <p>Sure thing <img src="https://emoji.discourse-cdn.com/twitter/cowboy_hat_face.png?v=12" title=":cowboy_hat_face:" class="emoji" alt=":cowboy_hat_face:" loading="lazy" width="20" height="20"></p>
<pre data-code-height="0" data-code-wrap="mermaid"><code class="lang-mermaid"> flowchart
</code></pre> | 8 | 0 | 69bb4acfca | 6 | [
587579,
554903,
648950,
248517,
542060
] | 4 | Sure thing 
```
flowchart
```
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] | api | null | null | null | https://community.openai.com/t/654274 | https://community.openai.com/p/893116 | Emotion | Emoji (8) |
575,385 | [
"gpt-4",
"chat-completion",
"pdf"
] | Send files to completion api | "2023-12-29T17:50:00.571000Z" | 7 | 1,331 | 1 | 2 | 4 | 664 | 778,131 | 2023-12-29T17:50:00.659Z | <p>Hello,<br>
I am trying to send files to the chat completion api but having a hard time finding a way to do so. I have seen some suggestions to use langchain but I would like to do it natively with the <code>openai</code> sdk.<br>
Any tips on how to do that?<br>
Thank you</p> | 51 | 0 | 683d6f174a | 1 | [
546561,
436670,
565556,
574375,
532495
] | null | Hello,
I am trying to send files to the chat completion api but having a hard time finding a way to do so. I have seen some suggestions to use langchain but I would like to do it natively with the `openai` sdk.
Any tips on how to do that?
Thank you
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] | gpt-4 | chat-completion | pdf | null | https://community.openai.com/t/575385 | https://community.openai.com/p/778131 | Chatbot (3) | Embeddings (6) |
575,385 | [
"gpt-4",
"chat-completion",
"pdf"
] | Send files to completion api | "2023-12-29T17:50:00.571000Z" | 7 | 1,331 | 1 | 2 | 4 | 664 | 778,139 | 2023-12-29T18:00:40.968Z | <p>Trying to do something along these lines</p>
<pre><code class="lang-auto">from openai import OpenAI
client = OpenAI()
file = client.files.create( file=open("file.pdf", "rb"), purpose="fine-tune" )
client = OpenAI() completion = client.chat.completions.create( model="gpt-4-1106",
messages=[ {"role": "system", "content": "You are a helpful assistant that can read PDFs."},
{"role": "user", "content": f"Extract the text from the 3rd page from {file.id}"} ] )
print(completion.choices[0].message)
</code></pre>
<p>someone mentioned the following code that works but want to understand what is happening under the hood</p>
<pre><code class="lang-auto">from langchain.document_loaders import PyPDFLoader
from langchain.llms import OpenAI
from langchain.chains.question_answering import load_qa_chain
#Locate your PDF here.
pdf="<YOUR_PDF_GOES_HERE>"
#Load the PDF
loader = PyPDFLoader(pdf)
documents = loader.load()
api_key = "sk-?????"
llm = OpenAI(openai_api_key=api_key)
chain = load_qa_chain(llm,verbose=True)
question = input("Enter your question here : ")
response = chain.run(input_documents=documents, question=question)
print(response)
</code></pre> | 52 | 0 | 683d6f174a | 2 | [
546561,
436670,
565556,
574375,
532495
] | null | Trying to do something along these lines
```
from openai import OpenAI
client = OpenAI()
file = client.files.create( file=open("file.pdf", "rb"), purpose="fine-tune" )
client = OpenAI() completion = client.chat.completions.create( model="gpt-4-1106",
messages=[ {"role": "system", "content": "You are a helpful assistant that can read PDFs."},
{"role": "user", "content": f"Extract the text from the 3rd page from {file.id}"} ] )
print(completion.choices[0].message)
```
someone mentioned the following code that works but want to understand what is happening under the hood
```
from langchain.document_loaders import PyPDFLoader
from langchain.llms import OpenAI
from langchain.chains.question_answering import load_qa_chain
#Locate your PDF here.
pdf="<YOUR_PDF_GOES_HERE>"
#Load the PDF
loader = PyPDFLoader(pdf)
documents = loader.load()
api_key = "sk-?????"
llm = OpenAI(openai_api_key=api_key)
chain = load_qa_chain(llm,verbose=True)
question = input("Enter your question here : ")
response = chain.run(input_documents=documents, question=question)
print(response)
```
| api | neutral | 0.83535 | [
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] | gpt-4 | chat-completion | pdf | null | https://community.openai.com/t/575385 | https://community.openai.com/p/778139 | Assistant | Miscellaneous (27) |
575,385 | [
"gpt-4",
"chat-completion",
"pdf"
] | Send files to completion api | "2023-12-29T17:50:00.571000Z" | 7 | 1,331 | 1 | 2 | 4 | 664 | 778,652 | 2023-12-30T04:29:25.821Z | <p>To do it natively, you’d need to use OpenAI’s <code>assistants</code> api instead of the <code>Chat Completion</code> api. See <a href="https://platform.openai.com/docs/assistants/tools" rel="noopener nofollow ugc">here</a>.</p>
<p>The files can be used by tools such as Code Interpreter or Retrieval.</p>
<blockquote>
<p>Code Interpreter can parse data from files. This is useful when you want to provide a large volume of data to the Assistant or allow your users to upload their own files for analysis.</p>
</blockquote>
<blockquote>
<p>Similar to Code Interpreter, files can be passed at the Assistant-level or individual Message-level.</p>
</blockquote>
<p>In the langchain example you shared, it’s doing Retrieval Augmented Generation which is similar to what the Retrieval in the <code>assistants</code> api. In langchain, the contents of the pdf files are parsed out and that text is added to the prompt. In the assistant api, this is handled for you.</p> | 43 | 0 | 46ed3b72e1 | 3 | [
546561,
436670,
565556,
574375,
532495
] | null | To do it natively, you’d need to use OpenAI’s `assistants` api instead of the `Chat Completion` api. See [here](https://platform.openai.com/docs/assistants/tools).
The files can be used by tools such as Code Interpreter or Retrieval.
>
> Code Interpreter can parse data from files. This is useful when you want to provide a large volume of data to the Assistant or allow your users to upload their own files for analysis.
>
>
>
>
> Similar to Code Interpreter, files can be passed at the Assistant-level or individual Message-level.
>
>
>
In the langchain example you shared, it’s doing Retrieval Augmented Generation which is similar to what the Retrieval in the `assistants` api. In langchain, the contents of the pdf files are parsed out and that text is added to the prompt. In the assistant api, this is handled for you.
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] | gpt-4 | chat-completion | pdf | null | https://community.openai.com/t/575385 | https://community.openai.com/p/778652 | Chatbot (2) | Miscellaneous (27) |
575,385 | [
"gpt-4",
"chat-completion",
"pdf"
] | Send files to completion api | "2023-12-29T17:50:00.571000Z" | 7 | 1,331 | 1 | 2 | 4 | 664 | 851,999 | 2024-02-11T21:42:19.673Z | <p>Alexx, did you ever find a way? I want to do, I think, the same thing. I want to ask some OpenAI API to summarize the content of a report that I have in a PDF/DOCX/etc. file. After reading about it’s ability to take a file, I had started down the ASSISTANTS API path. But after into I see that this leads to Retrieval which give the assistant more areas specific “knowledge” on which to base its answers … NOT what I want to do. I want a summarize of the content of my file. I am now looking at OpenAI Completions, but so far, I find it to be asking for me to, e.g., parse the file and pass in paragraphs.</p> | 19 | 0 | 57a9d83630 | 4 | [
546561,
436670,
565556,
574375,
532495
] | null | Alexx, did you ever find a way? I want to do, I think, the same thing. I want to ask some OpenAI API to summarize the content of a report that I have in a PDF/DOCX/etc. file. After reading about it’s ability to take a file, I had started down the ASSISTANTS API path. But after into I see that this leads to Retrieval which give the assistant more areas specific “knowledge” on which to base its answers … NOT what I want to do. I want a summarize of the content of my file. I am now looking at OpenAI Completions, but so far, I find it to be asking for me to, e.g., parse the file and pass in paragraphs.
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] | gpt-4 | chat-completion | pdf | null | https://community.openai.com/t/575385 | https://community.openai.com/p/851999 | AI Assistants | Embeddings (6) |
575,385 | [
"gpt-4",
"chat-completion",
"pdf"
] | Send files to completion api | "2023-12-29T17:50:00.571000Z" | 7 | 1,331 | 1 | 2 | 4 | 664 | 852,184 | 2024-02-12T01:03:24.537Z | <p>Frustrated with not finding an OpenAPI by which I could get a summary of a file, I decided to try the Playground - Assistants. I uploaded a file, which required the gpt-3.5-turbo-1106 model. I then had say: “I need a summary of the report contained in file ”. It ran for quite a while, going through Create a thread, Run the thread, Run <strong>queued</strong>, Run <strong>in_progress</strong> and then Run <strong>expired</strong> 5894 tokens (5832 in, 62 out). I see no explanation for <strong>expired</strong>, but in the “Response” I do see “tool_calls” of “type”: “retrieval”. AND I don’t think that “retrieval” does what I need to do, i.e., summarize my report.</p> | 16 | 1 | 57a9d83630 | 5 | [
546561,
436670,
565556,
574375,
532495
] | null | Frustrated with not finding an OpenAPI by which I could get a summary of a file, I decided to try the Playground - Assistants. I uploaded a file, which required the gpt-3.5-turbo-1106 model. I then had say: “I need a summary of the report contained in file ”. It ran for quite a while, going through Create a thread, Run the thread, Run **queued**, Run **in\_progress** and then Run **expired** 5894 tokens (5832 in, 62 out). I see no explanation for **expired**, but in the “Response” I do see “tool\_calls” of “type”: “retrieval”. AND I don’t think that “retrieval” does what I need to do, i.e., summarize my report.
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] | gpt-4 | chat-completion | pdf | null | https://community.openai.com/t/575385 | https://community.openai.com/p/852184 | Status Updates | API (2) |
575,385 | [
"gpt-4",
"chat-completion",
"pdf"
] | Send files to completion api | "2023-12-29T17:50:00.571000Z" | 7 | 1,331 | 1 | 2 | 4 | 664 | 893,089 | 2024-02-26T00:13:23.284Z | <p>Retrieval is what you want, per the docs:</p>
<blockquote>
<p>Once a file is uploaded and passed to the Assistant, OpenAI will automatically chunk your documents, index and store the embeddings, and implement vector search to retrieve relevant content to answer user queries.</p>
</blockquote>
<p><a href="https://platform.openai.com/docs/assistants/tools/knowledge-retrieval" rel="noopener nofollow ugc">Assistants tools - OpenAI API</a></p>
<p>If it’s expiring have you tried using a smaller document to test with that first, it could be the size of your document is taking a while to get embeddings for or otherwise handle.</p> | 7 | 0 | ddcc14a301 | 6 | [
546561,
436670,
565556,
574375,
532495
] | null | Retrieval is what you want, per the docs:
>
> Once a file is uploaded and passed to the Assistant, OpenAI will automatically chunk your documents, index and store the embeddings, and implement vector search to retrieve relevant content to answer user queries.
>
>
>
[Assistants tools - OpenAI API](https://platform.openai.com/docs/assistants/tools/knowledge-retrieval)
If it’s expiring have you tried using a smaller document to test with that first, it could be the size of your document is taking a while to get embeddings for or otherwise handle.
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] | gpt-4 | chat-completion | pdf | null | https://community.openai.com/t/575385 | https://community.openai.com/p/893089 | Knowledge Retrieval | Embeddings (6) |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 869,934 | 2024-02-18T11:04:34.936Z | <p>I am analysing a large dataset of concepts applied to a specific domain.<br>
These concepts may mean different things in general, and mean something very similar when applied to specific domains.<br>
For example: “Python” and “Go”, as general terms or specifically applied on the computer science domain.</p>
<p>If i wanted to cluster a large dataset of computer science concepts, by retrieving their embeddings and performing kmeans or a similar algorithm. Does it make sense to pre-process the concepts and add a computer science concept before calling the embedding api?<br>
For the example above: instead of retrieving the embeddings of “Python” and “Go”, would it make sense to retrieve the embeddings of “‘Python’ (Computer Science)” and “‘Go’ (Computer Science)”</p>
<p>Assuming the answer is yes, are there any relevant examples or papers on this topic?</p> | 31 | 2 | 188a4b00a1 | 1 | [
97098,
295017,
131350,
103152,
23949
] | null | I am analysing a large dataset of concepts applied to a specific domain.
These concepts may mean different things in general, and mean something very similar when applied to specific domains.
For example: “Python” and “Go”, as general terms or specifically applied on the computer science domain.
If i wanted to cluster a large dataset of computer science concepts, by retrieving their embeddings and performing kmeans or a similar algorithm. Does it make sense to pre-process the concepts and add a computer science concept before calling the embedding api?
For the example above: instead of retrieving the embeddings of “Python” and “Go”, would it make sense to retrieve the embeddings of “‘Python’ (Computer Science)” and “‘Go’ (Computer Science)”
Assuming the answer is yes, are there any relevant examples or papers on this topic?
| api | neutral | 0.855232 | [
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/869934 | Embeddings | Embeddings (6) |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 871,615 | 2024-02-18T19:15:00.016Z | <p>Depends,</p>
<p>You’d want to disambiguate your stuff as much as possible, obviously. But you don’t want to go overboard and exhaust ADA’s attention window, for example. The 8191 token input limit is a joke.</p>
<p>If python pertains to the language from the context, then it’s probably not necessary.</p>
<p>However</p>
<p>The embedding models openai currently provides are very sensitive to the shape and format of your text. Including highly artificial fluff in your corpus might help erase this superficial pattern matching on shorter texts, so it may not be a bad idea if you can do it uniformly <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>You likely won’t get around doing experimentation. A heatmap has always been helpful for me in getting a feel for how the model behaves.</p>
<blockquote>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/e/9/e/e9ea0e6ba89816bfeecbda23b1db7d1d98df0780.png" data-download-href="/uploads/short-url/xniIgzFUrv85lAv3CGI8F0gDMfm.png?dl=1" title="image"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/e/9/e/e9ea0e6ba89816bfeecbda23b1db7d1d98df0780_2_690x177.png" alt="image" data-base62-sha1="xniIgzFUrv85lAv3CGI8F0gDMfm" width="690" height="177" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/e/9/e/e9ea0e6ba89816bfeecbda23b1db7d1d98df0780_2_690x177.png, https://global.discourse-cdn.com/openai1/optimized/4X/e/9/e/e9ea0e6ba89816bfeecbda23b1db7d1d98df0780_2_1035x265.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/e/9/e/e9ea0e6ba89816bfeecbda23b1db7d1d98df0780_2_1380x354.png 2x" data-dominant-color="497267"><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">1508×387 128 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/b/4/2/b420b06c432ad8d5ecaccd2559b3431fca455a7f.png" data-download-href="/uploads/short-url/pHtYOrNSP9GOnKp7dYIklPRSR8X.png?dl=1" title="image"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/b/4/2/b420b06c432ad8d5ecaccd2559b3431fca455a7f_2_690x177.png" alt="image" data-base62-sha1="pHtYOrNSP9GOnKp7dYIklPRSR8X" width="690" height="177" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/b/4/2/b420b06c432ad8d5ecaccd2559b3431fca455a7f_2_690x177.png, https://global.discourse-cdn.com/openai1/optimized/4X/b/4/2/b420b06c432ad8d5ecaccd2559b3431fca455a7f_2_1035x265.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/b/4/2/b420b06c432ad8d5ecaccd2559b3431fca455a7f_2_1380x354.png 2x" data-dominant-color="497267"><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">1501×387 119 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>
</blockquote>
<aside class="quote no-group" data-username="nitzan.v" data-post="1" data-topic="636329">
<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/nitzan.v/48/311075_2.png" class="avatar"> nitzan.v:</div>
<blockquote>
<p>Assuming the answer is yes, are there any relevant examples or papers on this topic?</p>
</blockquote>
</aside>
<p>The problem is that the field is evolving so rapidly and there’s so much garbage coming out in terms of papers - even evals can’t keep up with the models and capabilities that keep emerging - so it’s incredibly difficult.</p>
<hr>
<p>In conclusion I think it’s a good idea worth exploring - if I have more time and don’t forget I’ll get back to it. If you have the opportunity to test it and share your findings it would be tremendusously appreciated!</p> | 26 | 0 | 69bb4acfca | 2 | [
97098,
295017,
131350,
103152,
23949
] | null | Depends,
You’d want to disambiguate your stuff as much as possible, obviously. But you don’t want to go overboard and exhaust ADA’s attention window, for example. The 8191 token input limit is a joke.
If python pertains to the language from the context, then it’s probably not necessary.
However
The embedding models openai currently provides are very sensitive to the shape and format of your text. Including highly artificial fluff in your corpus might help erase this superficial pattern matching on shorter texts, so it may not be a bad idea if you can do it uniformly 
You likely won’t get around doing experimentation. A heatmap has always been helpful for me in getting a feel for how the model behaves.
>
> [image1508×387 128 KB](https://global.discourse-cdn.com/openai1/original/4X/e/9/e/e9ea0e6ba89816bfeecbda23b1db7d1d98df0780.png "image")
>
> [image1501×387 119 KB](https://global.discourse-cdn.com/openai1/original/4X/b/4/2/b420b06c432ad8d5ecaccd2559b3431fca455a7f.png "image")
>
>
>
 nitzan.v:
>
> Assuming the answer is yes, are there any relevant examples or papers on this topic?
>
>
>
The problem is that the field is evolving so rapidly and there’s so much garbage coming out in terms of papers - even evals can’t keep up with the models and capabilities that keep emerging - so it’s incredibly difficult.
---
In conclusion I think it’s a good idea worth exploring - if I have more time and don’t forget I’ll get back to it. If you have the opportunity to test it and share your findings it would be tremendusously appreciated!
| api | neutral | 0.745671 | [
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/871615 | Tuning Model | Artificial Intelligence |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 871,945 | 2024-02-18T21:18:11.684Z | <aside class="quote no-group" data-username="nitzan.v" data-post="1" data-topic="636329">
<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/nitzan.v/48/311075_2.png" class="avatar"> nitzan.v:</div>
<blockquote>
<p>If i wanted to cluster a large dataset of computer science concepts, by retrieving their embeddings and performing kmeans or a similar algorithm. Does it make sense to pre-process the concepts and add a computer science concept before calling the embedding api?</p>
</blockquote>
</aside>
<p>Yes. But I agree with <a class="mention" href="/u/diet">@Diet</a> that you don’t want to spend too much time going overboard with it.</p>
<p>In my mind, I see three concepts:</p>
<ol>
<li>
<p>SNR Signal to Noise Ratio. You are trying to increase the SNR for these fairly common words by giving them more context. Good. But keep in mind that doing this too much simply increases the amplitude of noise.</p>
</li>
<li>
<p>AlphaHybrid. This is a search that sort of mixes semantic search with keyword search. In your case, you would be looking more at semantic search (meaning) rather they keywords (as Go will be found in a lot of other contexts).</p>
</li>
<li>
<p>Metadata and Context. Not knowing a thing about your data, when I saw your example of “Go” (Computer Science), the idea of “Categorization” popped into my head. Not sure how or if this even applies, but the concept of using “metadata” in addition to your embeddings to give it more context is also a good approach. I think everyone will agree that gpt-4 and above at least will understand “Python” within the context of the sentences in which it is used in your embeddings. But, adding classifiers to those embeddings even further with titles, descriptions , categories and even summarizations would only increase the AI’s understanding of the contexts where the word(s) are found.</p>
</li>
</ol>
<p>Anyway, bottom line is you’ll need to try out a few methods to see which give you the better responses.</p> | 22 | 0 | 9716394c2d | 3 | [
97098,
295017,
131350,
103152,
23949
] | null |
 nitzan.v:
>
> If i wanted to cluster a large dataset of computer science concepts, by retrieving their embeddings and performing kmeans or a similar algorithm. Does it make sense to pre-process the concepts and add a computer science concept before calling the embedding api?
>
>
>
Yes. But I agree with [@Diet](/u/diet) that you don’t want to spend too much time going overboard with it.
In my mind, I see three concepts:
1. SNR Signal to Noise Ratio. You are trying to increase the SNR for these fairly common words by giving them more context. Good. But keep in mind that doing this too much simply increases the amplitude of noise.
2. AlphaHybrid. This is a search that sort of mixes semantic search with keyword search. In your case, you would be looking more at semantic search (meaning) rather they keywords (as Go will be found in a lot of other contexts).
3. Metadata and Context. Not knowing a thing about your data, when I saw your example of “Go” (Computer Science), the idea of “Categorization” popped into my head. Not sure how or if this even applies, but the concept of using “metadata” in addition to your embeddings to give it more context is also a good approach. I think everyone will agree that gpt-4 and above at least will understand “Python” within the context of the sentences in which it is used in your embeddings. But, adding classifiers to those embeddings even further with titles, descriptions , categories and even summarizations would only increase the AI’s understanding of the contexts where the word(s) are found.
Anyway, bottom line is you’ll need to try out a few methods to see which give you the better responses.
| api | neutral | 0.839272 | [
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/871945 | Embeddings | Embeddings (6) |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 879,505 | 2024-02-20T19:03:00.738Z | <p>thanks <a class="mention" href="/u/diet">@Diet</a> and <a class="mention" href="/u/somebodysysop">@SomebodySysop</a>!</p>
<p>I ran a little toy example:<br>
I generated 49 generates statements that take the shape <code>f"{person} is from {city}"</code> (7 People * 7 Cities)</p>
<pre><code class="lang-auto">And retrieved embeddings with additional context,
I tried many different variations, here is one example:
embedding_contexts = {
'no_context': df['statement'],
'location': 'The **CITY** indicated in the statement: """' + df['statement'] + '"""',
'person': 'The **FIRST NAME** indicated in the statement: """' + df['statement'] + '"""',
}
</code></pre>
<p>Similarity heat map is a nice trick (Thanks <a class="mention" href="/u/diet">@Diet</a> !):<br>
<div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/7/a/3/7a3c5917f4e479809246a0f78c557c45ad83639e.png" data-download-href="/uploads/short-url/hrlxSuNUEx1nSf5DRsJX9c1IOom.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/7/a/3/7a3c5917f4e479809246a0f78c557c45ad83639e_2_690x216.png" alt="image" data-base62-sha1="hrlxSuNUEx1nSf5DRsJX9c1IOom" width="690" height="216" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/7/a/3/7a3c5917f4e479809246a0f78c557c45ad83639e_2_690x216.png, https://global.discourse-cdn.com/openai1/optimized/4X/7/a/3/7a3c5917f4e479809246a0f78c557c45ad83639e_2_1035x324.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/7/a/3/7a3c5917f4e479809246a0f78c557c45ad83639e_2_1380x432.png 2x" data-dominant-color="C7C9E6"><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">4757×1494 434 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/a/6/9/a693f2456d573512f9a12f3cf7997d100c0e79f7.png" data-download-href="/uploads/short-url/nLCeutsfREbUJ9ZSml3lKdfAlqD.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/a/6/9/a693f2456d573512f9a12f3cf7997d100c0e79f7_2_690x216.png" alt="image" data-base62-sha1="nLCeutsfREbUJ9ZSml3lKdfAlqD" width="690" height="216" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/a/6/9/a693f2456d573512f9a12f3cf7997d100c0e79f7_2_690x216.png, https://global.discourse-cdn.com/openai1/optimized/4X/a/6/9/a693f2456d573512f9a12f3cf7997d100c0e79f7_2_1035x324.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/a/6/9/a693f2456d573512f9a12f3cf7997d100c0e79f7_2_1380x432.png 2x" data-dominant-color="C7C9E6"><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">4757×1494 441 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>Adding context definitely changes the outcome, but it seems I always added more noise than signal, and the outcome changed in unpredictable ways.<br>
For example, at times, adding the “Person” context seemed to ampliphy “City” more than when adding the location context.</p> | 20 | 1 | 188a4b00a1 | 4 | [
97098,
295017,
131350,
103152,
23949
] | null | thanks [@Diet](/u/diet) and [@SomebodySysop](/u/somebodysysop)!
I ran a little toy example:
I generated 49 generates statements that take the shape `f"{person} is from {city}"` (7 People \* 7 Cities)
```
And retrieved embeddings with additional context,
I tried many different variations, here is one example:
embedding_contexts = {
'no_context': df['statement'],
'location': 'The **CITY** indicated in the statement: """' + df['statement'] + '"""',
'person': 'The **FIRST NAME** indicated in the statement: """' + df['statement'] + '"""',
}
```
Similarity heat map is a nice trick (Thanks [@Diet](/u/diet) !):
[image4757×1494 434 KB](https://global.discourse-cdn.com/openai1/original/4X/7/a/3/7a3c5917f4e479809246a0f78c557c45ad83639e.png "image")
[image4757×1494 441 KB](https://global.discourse-cdn.com/openai1/original/4X/a/6/9/a693f2456d573512f9a12f3cf7997d100c0e79f7.png "image")
Adding context definitely changes the outcome, but it seems I always added more noise than signal, and the outcome changed in unpredictable ways.
For example, at times, adding the “Person” context seemed to ampliphy “City” more than when adding the location context.
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/879505 | Embeddings (2) | Embeddings (6) |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 879,618 | 2024-02-20T20:00:51.562Z | <aside class="quote no-group" data-username="nitzan.v" data-post="4" data-topic="636329">
<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/nitzan.v/48/311075_2.png" class="avatar"> nitzan.v:</div>
<blockquote>
<pre><code class="lang-auto"> 'location': 'The **CITY** indicated in the statement: """' + df['statement'] + '"""',
</code></pre>
</blockquote>
</aside>
<p>Ah, with context you actually meant a sort of promptability/instructability? <img src="https://emoji.discourse-cdn.com/twitter/grimacing.png?v=12" title=":grimacing:" class="emoji" alt=":grimacing:" loading="lazy" width="20" height="20"></p>
<p>we investigated that a little bit in this thread as well: <a href="https://community.openai.com/t/new-openai-announcement-updated-api-models-and-no-more-lazy-outputs/601851/9" class="inline-onebox">New OpenAI Announcement! Updated API Models and no more lazy outputs - #9 by Diet</a> (in this case the instruction rear-loaded instead of front loaded)</p>
<p>However, if we think it through a little: what does a bob in london have in common with a person called bob that happens to live in reno vs a mary that lives in reno? This <em>could</em> just be the result of unfortunate prompting…</p>
<p>That said, it’s interesting how dramatically the model discriminates by gender, and how it considers DANA and RENO different from the others.</p>
<p>If we wanted to improve the signal as you proposed in your original post, would it make sense to rerun the experiment something like this?:</p>
<p><code>"Dana (Person) is from Reno (City)"</code><br>
<=><br>
<code>"We're focusing on the person's name in the statement: Dana (Person) is from Reno (City)"</code><br>
<=><br>
<code>"We're focusing on the city in the statement: Dana (Person) is from Reno (City)"</code></p>
<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>I’d also like to try this with mistral embeds at some point, but msft is really stingy with their gpu vms atm <img src="https://emoji.discourse-cdn.com/twitter/frowning.png?v=12" title=":frowning:" class="emoji" alt=":frowning:" loading="lazy" width="20" height="20"></p> | 20 | 0 | 69bb4acfca | 5 | [
97098,
295017,
131350,
103152,
23949
] | null |
 nitzan.v:
>
>
> ```
> 'location': 'The **CITY** indicated in the statement: """' + df['statement'] + '"""',
>
> ```
>
>
Ah, with context you actually meant a sort of promptability/instructability? 
we investigated that a little bit in this thread as well: [New OpenAI Announcement! Updated API Models and no more lazy outputs - #9 by Diet](https://community.openai.com/t/new-openai-announcement-updated-api-models-and-no-more-lazy-outputs/601851/9) (in this case the instruction rear-loaded instead of front loaded)
However, if we think it through a little: what does a bob in london have in common with a person called bob that happens to live in reno vs a mary that lives in reno? This *could* just be the result of unfortunate prompting…
That said, it’s interesting how dramatically the model discriminates by gender, and how it considers DANA and RENO different from the others.
If we wanted to improve the signal as you proposed in your original post, would it make sense to rerun the experiment something like this?:
`"Dana (Person) is from Reno (City)"`
<=>
`"We're focusing on the person's name in the statement: Dana (Person) is from Reno (City)"`
<=>
`"We're focusing on the city in the statement: Dana (Person) is from Reno (City)"`
I’d also like to try this with mistral embeds at some point, but msft is really stingy with their gpu vms atm 
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/879618 | Unicode Encoding | Artificial Intelligence |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 879,652 | 2024-02-20T20:19:02.742Z | <p>“Sam is from Los Angles. We’re focusing on the person’s name in the previous statement.” (rear loaded) seems to be the best one yet.</p>
<p>To give this context into a real world use case,<br>
Consider an advertising platform that analysis it’s internal advertisements by different perspectives:<br>
-creative strategies employed (there are multiple different angles on just that one),</p>
<ul>
<li>infer what product/category is being advertised,</li>
<li>infer which audience the ad appeals to.</li>
<li>does this add offend anyone, does it abide by our content policy</li>
</ul>
<p>It would be impractical to call the full model for every creative, so I am looking for ways to do this through the embeddings.<br>
I was hoping that this “Hack” will make it possible for me to skip a step (or a few)</p> | 18 | 2 | 188a4b00a1 | 6 | [
97098,
295017,
131350,
103152,
23949
] | null | “Sam is from Los Angles. We’re focusing on the person’s name in the previous statement.” (rear loaded) seems to be the best one yet.
To give this context into a real world use case,
Consider an advertising platform that analysis it’s internal advertisements by different perspectives:
-creative strategies employed (there are multiple different angles on just that one),
* infer what product/category is being advertised,
* infer which audience the ad appeals to.
* does this add offend anyone, does it abide by our content policy
It would be impractical to call the full model for every creative, so I am looking for ways to do this through the embeddings.
I was hoping that this “Hack” will make it possible for me to skip a step (or a few)
| api | neutral | 0.612119 | [
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/879652 | Miscellaneous (21) | Emoji (8) |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 879,848 | 2024-02-20T22:01:10.518Z | <aside class="quote no-group" data-username="nitzan.v" data-post="6" data-topic="636329">
<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/nitzan.v/48/311075_2.png" class="avatar"> nitzan.v:</div>
<blockquote>
<p>“Sam is from Los Angles. We’re focusing on the person’s name in the previous statement.” (rear loaded) seems to be the best one yet.</p>
</blockquote>
</aside>
<p>Would it help to use filters in the search? For example, if you add a “Location” property to your embeddings, now you can filter by “Los Angeles” (if that is your goal). Similar to searching for discussions involving “Python” as it relates to “Computer Science”.</p>
<p>And what about adding some good old reliable keyword filtering to your search? Sometimes when I’m having a very difficult time finding that needle in the haystack, being able to add a keyword I know will be in the embedding cuts down on noise significantly.</p>
<p>Again, I can’t visualize exactly what you’re trying to do, but I don’t think you are going to be able to embed your way out of it alone. Nor is there going to be a single prompt strategy that will work in every instance.</p>
<p>No one in the Developer Forum agrees with me on this, but I think the best strategy is to get the data as refined as you can, then give your end users the tools they can use to find the needles they are looking for – and train them on how to use them effectively. Sounds to me like your user base will be sophisticated enough to handle that.</p> | 17 | 1 | 9716394c2d | 7 | [
97098,
295017,
131350,
103152,
23949
] | null |
 nitzan.v:
>
> “Sam is from Los Angles. We’re focusing on the person’s name in the previous statement.” (rear loaded) seems to be the best one yet.
>
>
>
Would it help to use filters in the search? For example, if you add a “Location” property to your embeddings, now you can filter by “Los Angeles” (if that is your goal). Similar to searching for discussions involving “Python” as it relates to “Computer Science”.
And what about adding some good old reliable keyword filtering to your search? Sometimes when I’m having a very difficult time finding that needle in the haystack, being able to add a keyword I know will be in the embedding cuts down on noise significantly.
Again, I can’t visualize exactly what you’re trying to do, but I don’t think you are going to be able to embed your way out of it alone. Nor is there going to be a single prompt strategy that will work in every instance.
No one in the Developer Forum agrees with me on this, but I think the best strategy is to get the data as refined as you can, then give your end users the tools they can use to find the needles they are looking for – and train them on how to use them effectively. Sounds to me like your user base will be sophisticated enough to handle that.
| api | neutral | 0.770644 | [
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/879848 | Embeddings (5) | Artificial Intelligence |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 883,325 | 2024-02-21T23:22:12.414Z | <aside class="quote no-group" data-username="nitzan.v" data-post="6" data-topic="636329">
<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/nitzan.v/48/311075_2.png" class="avatar"> nitzan.v:</div>
<blockquote>
<p>“Sam is from Los Angles. We’re focusing on the person’s name in the previous statement.” (rear loaded) seems to be the best one yet.</p>
</blockquote>
</aside>
<p>do you have a beautiful heatmap for us? <img src="https://emoji.discourse-cdn.com/twitter/pray.png?v=12" title=":pray:" class="emoji" alt=":pray:" loading="lazy" width="20" height="20"></p>
<p>you could probably publish a paper on that (instructed embeddings) <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> | 15 | 1 | 69bb4acfca | 8 | [
97098,
295017,
131350,
103152,
23949
] | null |
 nitzan.v:
>
> “Sam is from Los Angles. We’re focusing on the person’s name in the previous statement.” (rear loaded) seems to be the best one yet.
>
>
>
do you have a beautiful heatmap for us? 
you could probably publish a paper on that (instructed embeddings) 
| api | positive | 0.497423 | [
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/883325 | Emotion | Emoji (8) |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 891,920 | 2024-02-25T10:51:48.593Z | <p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/3/e/e/3eed515dd1067ddc2763f2a4b69d39162ccb8e52.png" data-download-href="/uploads/short-url/8YG3mGU5F6We008rnYHQgGvpoVY.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/3/e/e/3eed515dd1067ddc2763f2a4b69d39162ccb8e52_2_690x216.png" alt="image" data-base62-sha1="8YG3mGU5F6We008rnYHQgGvpoVY" width="690" height="216" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/3/e/e/3eed515dd1067ddc2763f2a4b69d39162ccb8e52_2_690x216.png, https://global.discourse-cdn.com/openai1/optimized/4X/3/e/e/3eed515dd1067ddc2763f2a4b69d39162ccb8e52_2_1035x324.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/3/e/e/3eed515dd1067ddc2763f2a4b69d39162ccb8e52_2_1380x432.png 2x" data-dominant-color="C3C7E7"><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">4757×1494 429 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>
Here is the heatmap from that run.<br>
“Person” is still stronger that “Location”, but in this example i believe that the Location signal is stronger with the location context (first chart)</p>
<p>Publishing is an interesting idea, I’m not sure this merits one on it’s own. My guess is that instructed embedding would be difficult to utilize on it’s own - but it may be a useful step for enhancing features that an additional model could leverage (compared to a model that operates on uninstructed embeddings).<br>
So maybe demonstrating the entire flow from instructed embedding to a useful model (on a more realistic dataset) may be interesting to publish?</p> | 12 | 0 | 188a4b00a1 | 9 | [
97098,
295017,
131350,
103152,
23949
] | null | [image4757×1494 429 KB](https://global.discourse-cdn.com/openai1/original/4X/3/e/e/3eed515dd1067ddc2763f2a4b69d39162ccb8e52.png "image")
Here is the heatmap from that run.
“Person” is still stronger that “Location”, but in this example i believe that the Location signal is stronger with the location context (first chart)
Publishing is an interesting idea, I’m not sure this merits one on it’s own. My guess is that instructed embedding would be difficult to utilize on it’s own - but it may be a useful step for enhancing features that an additional model could leverage (compared to a model that operates on uninstructed embeddings).
So maybe demonstrating the entire flow from instructed embedding to a useful model (on a more realistic dataset) may be interesting to publish?
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/891920 | Embeddings (3) | Embeddings (6) |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 891,934 | 2024-02-25T10:59:09.356Z | <p><a class="mention" href="/u/somebodysysop">@SomebodySysop</a> Finding a needle in a haystack is not what i’m trying to do, I am trying to find structure in the haystack (from different points of view)</p>
<p>Consider the advertising platform example, I would like to know over the entire corpus which strategies are being used without pre defining a strategy taxonomy. Strategies change over time, so i would like to leverage the general nature of the LLMs for topic modeling (hopefully that made sense)</p> | 12 | 0 | 188a4b00a1 | 10 | [
97098,
295017,
131350,
103152,
23949
] | null | [@SomebodySysop](/u/somebodysysop) Finding a needle in a haystack is not what i’m trying to do, I am trying to find structure in the haystack (from different points of view)
Consider the advertising platform example, I would like to know over the entire corpus which strategies are being used without pre defining a strategy taxonomy. Strategies change over time, so i would like to leverage the general nature of the LLMs for topic modeling (hopefully that made sense)
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/891934 | LLMs | Artificial Intelligence |
636,329 | [
"embeddings"
] | Does it make sense to add context to text before embedding? | "2024-02-18T11:04:34.864000Z" | 7 | 285 | 5 | 5 | 3 | 1,691 | 893,057 | 2024-02-25T23:48:11.499Z | <p>You got me on that one. How you get the AI to intuit what a strategy is without first defining the parameters of a strategy is beyond me. Then, being able to classify various strategies without a classification definition. Very interested to see how you figure this one out.</p> | 10 | 0 | 9716394c2d | 11 | [
97098,
295017,
131350,
103152,
23949
] | null | You got me on that one. How you get the AI to intuit what a strategy is without first defining the parameters of a strategy is beyond me. Then, being able to classify various strategies without a classification definition. Very interested to see how you figure this one out.
| api | positive | 0.663765 | [
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] | embeddings | null | null | null | https://community.openai.com/t/636329 | https://community.openai.com/p/893057 | Knowledge Classifier | Artificial Intelligence |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 887,333 | 2024-02-23T09:04:51.343Z | <p>Hi all,</p>
<p>I am building an application where I want to use OpenAI LLM on top of my Neo4J graph. I am using the free tier of “gpt-3.5-turbo”.<br>
My Neo4j graph is very huge. The graph schema alone has 23800 tokens.<br>
Now whenever I invoke the GraphCypherQAChain, I get the error message<br>
‘message’: “This model’s maximum context length is 16385 tokens. However, your messages resulted in 23907 tokens. Please reduce the length of the messages.”</p>
<p>Is it not possible to build my LLM+Neo4J application using the free tier?</p>
<p>Can anyone help me in solving this issue?</p>
<p>Thank you</p> | 33 | 1 | f663c691f9 | 1 | [
283171,
328860,
284428,
653114,
617543
] | null | Hi all,
I am building an application where I want to use OpenAI LLM on top of my Neo4J graph. I am using the free tier of “gpt-3.5-turbo”.
My Neo4j graph is very huge. The graph schema alone has 23800 tokens.
Now whenever I invoke the GraphCypherQAChain, I get the error message
‘message’: “This model’s maximum context length is 16385 tokens. However, your messages resulted in 23907 tokens. Please reduce the length of the messages.”
Is it not possible to build my LLM+Neo4J application using the free tier?
Can anyone help me in solving this issue?
Thank you
| api | neutral | 0.782196 | [
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/887333 | GPT Model | Tokenization (2) |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 887,348 | 2024-02-23T09:11:30.931Z | <p>Why do you need to share the entire graph with open ai?</p>
<p>Shouldn’t you be performing your search “locally” and only sharing the results with the LLM?</p> | 33 | 1 | 3f54e388d4 | 2 | [
283171,
328860,
284428,
653114,
617543
] | null | Why do you need to share the entire graph with open ai?
Shouldn’t you be performing your search “locally” and only sharing the results with the LLM?
| api | neutral | 0.517398 | [
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/887348 | Embeddings (5) | Artificial Intelligence |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 887,452 | 2024-02-23T09:58:38.941Z | <p>Hi,<br>
Thank you for your response. I am trying to use the LLM to understand the User input, run the cypher query and return the response.<br>
This is the code I am using.</p>
<p>from langchain.chat_models import ChatOpenAI<br>
from langchain.chains import GraphCypherQAChain<br>
from langchain.graphs import Neo4jGraph</p>
<p>llm = ChatOpenAI(<br>
openai_api_key=OPENAI_API_KEY,<br>
model=“gpt-3.5-turbo”,<br>
temperature=0<br>
)</p>
<p>graph = Neo4jGraph(<br>
url=NEO4J_URL,<br>
username=NEO4J_USER,<br>
password=NEO4J_PASSWORD,<br>
database=NEO4J_DATABASE<br>
)</p>
<p>chain = GraphCypherQAChain.from_llm(<br>
llm, graph=graph, verbose=True,<br>
)</p>
<p>chain.run(“”“What are the cities in the graph? “””)</p>
<p>Can you pls guide me in solving this issue?</p> | 32 | 0 | f663c691f9 | 3 | [
283171,
328860,
284428,
653114,
617543
] | null | Hi,
Thank you for your response. I am trying to use the LLM to understand the User input, run the cypher query and return the response.
This is the code I am using.
from langchain.chat\_models import ChatOpenAI
from langchain.chains import GraphCypherQAChain
from langchain.graphs import Neo4jGraph
llm = ChatOpenAI(
openai\_api\_key=OPENAI\_API\_KEY,
model=“gpt-3.5-turbo”,
temperature=0
)
graph = Neo4jGraph(
url=NEO4J\_URL,
username=NEO4J\_USER,
password=NEO4J\_PASSWORD,
database=NEO4J\_DATABASE
)
chain = GraphCypherQAChain.from\_llm(
llm, graph=graph, verbose=True,
)
chain.run(“”“What are the cities in the graph? “””)
Can you pls guide me in solving this issue?
| api | neutral | 0.698855 | [
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/887452 | LLMs | Artificial Intelligence |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 887,766 | 2024-02-23T12:29:47.954Z | <aside class="quote no-group" data-username="sai.bharadwaj.1" data-post="1" data-topic="649949">
<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/sai.bharadwaj.1/48/148754_2.png" class="avatar"> sai.bharadwaj.1:</div>
<blockquote>
<p>Can anyone help me in solving this issue?</p>
</blockquote>
</aside>
<p>you can use a model with a bigger context, e.g. gpt-4-turbo.</p>
<p>but I’d urge you to reevaluate your process. is your graph really such a kitchen sink of random entities and relations? how is it used normally? what’s the manual process here?</p>
<p>maybe instead of a one-shot cypher query, you may be better off using an iterative approach.</p> | 24 | 0 | 69bb4acfca | 4 | [
283171,
328860,
284428,
653114,
617543
] | null |
 sai.bharadwaj.1:
>
> Can anyone help me in solving this issue?
>
>
>
you can use a model with a bigger context, e.g. gpt-4-turbo.
but I’d urge you to reevaluate your process. is your graph really such a kitchen sink of random entities and relations? how is it used normally? what’s the manual process here?
maybe instead of a one-shot cypher query, you may be better off using an iterative approach.
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/887766 | Mathematics | Artificial Intelligence |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 888,785 | 2024-02-23T20:04:01.932Z | <p>I took another look at this and can only assume the results set is too large for your model.</p>
<p>I’d initially assumed that internally this method was sending the graph to the LLM but this explanation of this method suggests otherwise:<br>
<a href="https://github.com/langchain-ai/langchain/issues/9035" class="inline-onebox" rel="noopener nofollow ugc">Functional difference between GraphCypherQAChain and GraphQAChain · Issue #9035 · langchain-ai/langchain · GitHub</a></p>
<p>Can you query neo4j directly and see how big the result is?</p>
<p>Can you be more specific to reduce the result size?</p> | 16 | 1 | 3f54e388d4 | 5 | [
283171,
328860,
284428,
653114,
617543
] | null | I took another look at this and can only assume the results set is too large for your model.
I’d initially assumed that internally this method was sending the graph to the LLM but this explanation of this method suggests otherwise:
[Functional difference between GraphCypherQAChain and GraphQAChain · Issue #9035 · langchain-ai/langchain · GitHub](https://github.com/langchain-ai/langchain/issues/9035)
Can you query neo4j directly and see how big the result is?
Can you be more specific to reduce the result size?
| api | neutral | 0.661525 | [
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/888785 | Mathematics | Artificial Intelligence |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 892,578 | 2024-02-25T18:01:33.947Z | <p>Hi,</p>
<p>Thank you for this post. I am going through that now.</p>
<p>I already have my Neo4j queries built.<br>
The response time is ~5 sec. Since I hard-code the entity values and the type of relationships in my query, it runs very fast and returns the paths.</p>
<p>My goal is that the user can just type in a English sentence and the results must be shown. I have already built a successful POC on a small subgraph. I am also comfortable in creating prompts along with examples.</p>
<p>I am already telling the graph what type of relationships to use for a given input question.</p>
<p>It seems the problem is that the schema itself is eating up all my context length.</p>
<p>Thanks,</p> | 12 | 1 | f663c691f9 | 6 | [
283171,
328860,
284428,
653114,
617543
] | null | Hi,
Thank you for this post. I am going through that now.
I already have my Neo4j queries built.
The response time is ~5 sec. Since I hard-code the entity values and the type of relationships in my query, it runs very fast and returns the paths.
My goal is that the user can just type in a English sentence and the results must be shown. I have already built a successful POC on a small subgraph. I am also comfortable in creating prompts along with examples.
I am already telling the graph what type of relationships to use for a given input question.
It seems the problem is that the schema itself is eating up all my context length.
Thanks,
| api | neutral | 0.501506 | [
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/892578 | SQL Database | Embeddings (6) |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 892,621 | 2024-02-25T18:27:01.390Z | <aside class="quote no-group" data-username="sai.bharadwaj.1" data-post="6" data-topic="649949">
<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/sai.bharadwaj.1/48/148754_2.png" class="avatar"> sai.bharadwaj.1:</div>
<blockquote>
<p>It seems the problem is that the schema itself is eating up all my context length.</p>
</blockquote>
</aside>
<p>have you considered embeddings or something to select the appropriate subgraph first?</p> | 10 | 0 | 69bb4acfca | 7 | [
283171,
328860,
284428,
653114,
617543
] | null |
 sai.bharadwaj.1:
>
> It seems the problem is that the schema itself is eating up all my context length.
>
>
>
have you considered embeddings or something to select the appropriate subgraph first?
| api | neutral | 0.733205 | [
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/892621 | Miscellaneous (5) | Miscellaneous (27) |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 892,653 | 2024-02-25T18:56:30.469Z | <p>You can consider using grouped tables.</p>
<p>Group by similarity and then join only the relevant tables.</p> | 9 | 0 | 6ce20c97c9 | 8 | [
283171,
328860,
284428,
653114,
617543
] | null | You can consider using grouped tables.
Group by similarity and then join only the relevant tables.
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/892653 | Miscellaneous (10) | Embeddings (6) |
649,949 | [
"chatgpt",
"api",
"gpt-35-turbo",
"assistants-api",
"fine-tuning"
] | Very large Neo4j graph + LLM | "2024-02-23T09:04:51.256000Z" | 7 | 177 | 3 | 3 | 5 | 586 | 893,051 | 2024-02-25T23:46:26.747Z | <p>You could also consider function calling and have all your data retrieval logic behind an API (function). This could make it easier to evolve and maintain your solution in the long run.</p> | 5 | 0 | a25391d703 | 9 | [
283171,
328860,
284428,
653114,
617543
] | null | You could also consider function calling and have all your data retrieval logic behind an API (function). This could make it easier to evolve and maintain your solution in the long run.
| api | neutral | 0.546768 | [
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] | chatgpt | api | gpt-35-turbo | assistants-api | https://community.openai.com/t/649949 | https://community.openai.com/p/893051 | APIs | Embeddings (6) |
654,113 | [] | Gpt-4-0125-preview seems to have a 4k total token limit? | "2024-02-25T20:49:26.601000Z" | 30 | 119 | 0 | 0 | 2 | 456 | 892,810 | 2024-02-25T20:49:26.670Z | <p>I am using JSON mode in gpt-4-0125-preview. I provide a system message (as the very first message in a series) which instructs the AI to generate JSON.</p>
<p>I get proper JSON back until I pass the 4k total token mark. When total_token goes over 4k, I get an endless whitespace response. I presume this is because the very first system message instructing the model to use JSON has rolled off of the context window.</p>
<blockquote>
<p>When using JSON mode, <strong>always</strong> instruct the model to produce JSON via some message in the conversation, for example via your system message. If you don’t include an explicit instruction to generate JSON, the model may generate an unending stream of whitespace and the request may run continually until it reaches the token limit.</p>
</blockquote>
<p>Here is an example of the completion object and then the string it returned (which I was trying to convert to JSON). Its just endless whitespace. But all previous calls where the total_tokens were under 4k resulted in proper JSON being returned.</p>
<p>I thought gpt-4-0125-preview support a larger total_token amount. Is it 4k?</p>
<pre><code class="lang-auto">{ "id": "chatcmpl-8wFPcWl8oZDaSMmBIjKkXIJzuAbeM", "choices": [ { "finish_reason": "stop", "index": 0, "logprobs": null, "message": { "content": "REDACTED", "role": "assistant",
"function_call": null, "tool_calls": null } } ], "created": 1708892960, "model": "gpt-4-0125-preview", "object": "chat.completion", "system_fingerprint": "fp_89b1a570e1", "usage": { "completion_tokens": 600,
"prompt_tokens": 3486, "total_tokens": 4086 } }
Error loading JSON from string:
</code></pre> | 23 | 1 | 11e69619ff | 1 | [
494973,
521096,
555011,
615574,
515790
] | null | I am using JSON mode in gpt-4-0125-preview. I provide a system message (as the very first message in a series) which instructs the AI to generate JSON.
I get proper JSON back until I pass the 4k total token mark. When total\_token goes over 4k, I get an endless whitespace response. I presume this is because the very first system message instructing the model to use JSON has rolled off of the context window.
>
> When using JSON mode, **always** instruct the model to produce JSON via some message in the conversation, for example via your system message. If you don’t include an explicit instruction to generate JSON, the model may generate an unending stream of whitespace and the request may run continually until it reaches the token limit.
>
>
>
Here is an example of the completion object and then the string it returned (which I was trying to convert to JSON). Its just endless whitespace. But all previous calls where the total\_tokens were under 4k resulted in proper JSON being returned.
I thought gpt-4-0125-preview support a larger total\_token amount. Is it 4k?
```
{ "id": "chatcmpl-8wFPcWl8oZDaSMmBIjKkXIJzuAbeM", "choices": [ { "finish_reason": "stop", "index": 0, "logprobs": null, "message": { "content": "REDACTED", "role": "assistant",
"function_call": null, "tool_calls": null } } ], "created": 1708892960, "model": "gpt-4-0125-preview", "object": "chat.completion", "system_fingerprint": "fp_89b1a570e1", "usage": { "completion_tokens": 600,
"prompt_tokens": 3486, "total_tokens": 4086 } }
Error loading JSON from string:
```
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] | null | null | null | null | https://community.openai.com/t/654113 | https://community.openai.com/p/892810 | JSON Format (2) | Embeddings (6) |
654,113 | [] | Gpt-4-0125-preview seems to have a 4k total token limit? | "2024-02-25T20:49:26.601000Z" | 30 | 119 | 0 | 0 | 2 | 456 | 892,975 | 2024-02-25T22:53:12.638Z | <p>That’s an interesting result - we’ve seen similar stuff with whitespaces/newlines before, but typically with chinese input.</p>
<p>IMO json mode (and tool/function calling) is a gimmick of a bandaid of a solution - properly prompting the model will usually get you the same results without these weird bugs.</p>
<aside class="quote no-group" data-username="gmahoney" data-post="1" data-topic="654113">
<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/gmahoney/48/320035_2.png" class="avatar"> gmahoney:</div>
<blockquote>
<p>I thought gpt-4-0125-preview support a larger total_token amount. Is it 4k?</p>
</blockquote>
</aside>
<p>it does indeed - however, it’s possible that your schema instruction gets lost in the context. If you’d exhausted the token length you’d typically get an error message</p>
<aside class="quote no-group" data-username="gmahoney" data-post="1" data-topic="654113">
<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/gmahoney/48/320035_2.png" class="avatar"> gmahoney:</div>
<blockquote>
<p>I provide a system message (as the very first message in a series) which instructs the AI to generate JSON.</p>
</blockquote>
</aside>
<p>I don’t know if this will solve your particular issue, but have you considered attaching the schema to the very end of your context?</p>
<p>It’s sometimes also a good idea to add a json field where the model can do some CoT or reasoning/disclaiming/whining stuff before giving you the actual answer.</p>
<hr>
<p>I’m just spitballing here but it’s possible that you’re seeing the equivalent of the typical 0125 task refusal, just in json mode <img src="https://emoji.discourse-cdn.com/twitter/laughing.png?v=12" title=":laughing:" class="emoji" alt=":laughing:" loading="lazy" width="20" height="20"></p>
<p>We can take a closer look at your prompt if you’re willing to post it.</p> | 14 | 0 | 69bb4acfca | 2 | [
494973,
521096,
555011,
615574,
515790
] | null | That’s an interesting result - we’ve seen similar stuff with whitespaces/newlines before, but typically with chinese input.
IMO json mode (and tool/function calling) is a gimmick of a bandaid of a solution - properly prompting the model will usually get you the same results without these weird bugs.
 gmahoney:
>
> I thought gpt-4-0125-preview support a larger total\_token amount. Is it 4k?
>
>
>
it does indeed - however, it’s possible that your schema instruction gets lost in the context. If you’d exhausted the token length you’d typically get an error message
 gmahoney:
>
> I provide a system message (as the very first message in a series) which instructs the AI to generate JSON.
>
>
>
I don’t know if this will solve your particular issue, but have you considered attaching the schema to the very end of your context?
It’s sometimes also a good idea to add a json field where the model can do some CoT or reasoning/disclaiming/whining stuff before giving you the actual answer.
---
I’m just spitballing here but it’s possible that you’re seeing the equivalent of the typical 0125 task refusal, just in json mode 
We can take a closer look at your prompt if you’re willing to post it.
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] | null | null | null | null | https://community.openai.com/t/654113 | https://community.openai.com/p/892975 | JSON Validation | Embeddings (6) |
579,961 | [
"api"
] | Long queue times for assistant api gpt-4-1106-preview | "2024-01-09T21:18:07.725000Z" | 7 | 319 | 1 | 0 | 5 | 201 | 786,856 | 2024-01-09T21:18:07.784Z | <p>I’m seeing long queue times in using Assistant API with gpt-4-1106-preview. Is anyone seeing the same? I know this has previously been an issue.</p> | 25 | 0 | 7ba7d31bfa | 1 | [
490552,
614064,
547875,
589260,
509806
] | null | I’m seeing long queue times in using Assistant API with gpt-4-1106-preview. Is anyone seeing the same? I know this has previously been an issue.
| api | negative | 0.668024 | [
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] | api | null | null | null | https://community.openai.com/t/579961 | https://community.openai.com/p/786856 | Performance (2) | Tokenization (2) |
579,961 | [
"api"
] | Long queue times for assistant api gpt-4-1106-preview | "2024-01-09T21:18:07.725000Z" | 7 | 319 | 1 | 0 | 5 | 201 | 788,314 | 2024-01-10T14:05:09.817Z | <p>Yes, it is very slow for a couple of days now.</p> | 22 | 1 | 324f1a416f | 2 | [
490552,
614064,
547875,
589260,
509806
] | null | Yes, it is very slow for a couple of days now.
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] | api | null | null | null | https://community.openai.com/t/579961 | https://community.openai.com/p/788314 | Mexico | Payment (4) |