None of the questions regarding the token usage gets answered I see. Still awaiting any update on th

OOwl Reddy None of the questions regarding the token usage gets answered I see. Still await...

V

Vikash•8/28/24, 3:26 AM

I see CF use another metric called Neurons, but can’t find how it’s calculated on docs or any way to see that in ai.run() response on runtime to calculate for each user using the app.

VVikash I see CF use another metric called Neurons, but can’t find how it’s calculated ...

O

Owl ReddyOP•8/28/24, 3:32 AM

https://ai.cloudflare.com/#pricing-calculator You can check that here but there's no definite way to measure the usage of neurons or tokens based on individual queries. All we have is an estimate but no clear usage based metrics. Maybe in the birthday week next month they might change that or it'll just get ignored like most of the messages about token usage.
Beta models are free for now so they wont show up on pricing calculator

�

😈 Donkey 💫•8/28/24, 4:46 AM

const response = await ai.run(model || "@cf/stabilityai/stable-diffusion-xl-base-1.0", requestInput);
// Store the image name in R2, in background        
ctx.waitUntil(updateRecentImages(imageName, (await generateThumbs(imageName, '400x', true)), input, env, response));
return new Response(response, {
    headers: {
        "content-type": "image/png",
    },
});

const response = await ai.run(model || "@cf/stabilityai/stable-diffusion-xl-base-1.0", requestInput);
// Store the image name in R2, in background        
ctx.waitUntil(updateRecentImages(imageName, (await generateThumbs(imageName, '400x', true)), input, env, response));
return new Response(response, {
    headers: {
        "content-type": "image/png",
    },
});

const response = await ai.run(model || "@cf/stabilityai/stable-diffusion-xl-base-1.0", requestInput);
// Store the image name in R2, in background        
ctx.waitUntil(updateRecentImages(imageName, (await generateThumbs(imageName, '400x', true)), input, env, response));
return new Response(response, {
    headers: {
        "content-type": "image/png",
    },
});

const response = await ai.run(model || "@cf/stabilityai/stable-diffusion-xl-base-1.0", requestInput);
// Store the image name in R2, in background        
ctx.waitUntil(updateRecentImages(imageName, (await generateThumbs(imageName, '400x', true)), input, env, response));
return new Response(response, {
    headers: {
        "content-type": "image/png",
    },
});

response should be Unit8Array not Response class, but problem it's read once (I guess), which causing

TypeError: The ReadableStream has been locked to a reader.

TypeError: The ReadableStream has been locked to a reader.

TypeError: The ReadableStream has been locked to a reader.

TypeError: The ReadableStream has been locked to a reader. prevent updateRecentImages works

do you have any idea?

Mmichelle check back soon 👀

1

1984 Ford Laser•8/28/24, 6:26 AM

Im checking back soon! Any news on TTS models?

V

vampirehunter•8/28/24, 9:49 AM

can anyone please tell me what is the limit of worker ai for free tier it says 10000 neurons , what does it mean and i have no idea i have made few request to try the llama model and the request were successful but on the dashboard i cant see my request
help plz

Vvampirehunter can anyone please tell me what is the limit of worker ai for free tier it says 1...

V

vin•8/28/24, 3:16 PM

here is a calculator https://ai.cloudflare.com/#pricing-calculator , you can consider it as amount of computation, but frankly it's still a pretty confused concept...

A

AhmedHalat•8/29/24, 12:58 PM

Anyone know where to lookup error codes?

{
  "errors": [
    {
      "message": "Server Error",
      "code": 6001
    }
  ],
  "success": false,
  "result": {},
  "messages": []
}

{
  "errors": [
    {
      "message": "Server Error",
      "code": 6001
    }
  ],
  "success": false,
  "result": {},
  "messages": []
}

{
  "errors": [
    {
      "message": "Server Error",
      "code": 6001
    }
  ],
  "success": false,
  "result": {},
  "messages": []
}

{
  "errors": [
    {
      "message": "Server Error",
      "code": 6001
    }
  ],
  "success": false,
  "result": {},
  "messages": []
}

FFlare Workers AI currently only supports popular open-source models provided by the Cl...

A

Avocadio•8/29/24, 2:47 PM

has anything changed?

A

Avocadio•8/29/24, 2:47 PM

can we deploy our own pretrained models

R

rajeev•8/30/24, 5:50 PM

Hi,
Not sure if this is the right place for this, but the docs directed me to this server

I was playing around with Workers AI text generation models and have found that setting

top_p

top_p

top_p

top_p or

repetition_penalty

repetition_penalty

repetition_penalty

repetition_penalty value to

0

0 causes

Cloudflare API Error

Cloudflare API Error

Cloudflare API Error

Cloudflare API Error

If we are using streaming then we directly get the

data: [DONE]

data: [DONE]

data: [DONE]

data: [DONE] event,
if non-streaming then it is a

500 "Cloudflare API error"

500 "Cloudflare API error"

500 "Cloudflare API error"

500 "Cloudflare API error"

As per the docs the minimum allowed values for

top_p

top_p

top_p

top_p &

repetition_penalty

repetition_penalty

repetition_penalty

repetition_penalty is 0, so ideally we shouldn't get any error..

R

Ramilysk•8/31/24, 10:40 PM

https://tenor.com/view/cool-sunglasses-swag-penguin-with-gif-16107429049852947642

Tenor

O

Oreki•9/3/24, 3:54 AM

Are there some hidden output token limits? My response seems to be cut short after 2000 words regardless of whether I'm streaming or not on beta models

X

xav•9/3/24, 12:37 PM

Hey, I'm using llama-3.1-8b-instruct to classify and reject spam/inappropriate messages, it works mostly fine, but I'm struggling to reliably return a structured output (eg a json {"appropriate": boolean}).

X

xav•9/3/24, 12:39 PM

is there a trick beside finetuning the prompt and hope for the best? so far, asking to classify messages in other languages than english seems to trip the model (eg. it sometimes returns "approprié" as the key if the message is in french)

X

xav•9/3/24, 12:41 PM

I'm aware there are more specific models, eg. https://huggingface.co/predibase/jigsaw my question is how to tell the workers AI to answer following a specific structure

predibase/jigsaw · Hugging Face

M

mr.niko.la•9/3/24, 2:49 PM

Can we add Parler-TTS to ai workers ?

Parler-TTS is the Hugging Face open source model

Is there any that has implement TTS on cloudflare edge ?

OOreki Are there some hidden output token limits? My response seems to be cut short aft...

R

Raylight•9/3/24, 3:00 PM

Yes, and the limit depends on the model. See workers-ai

RRaylight Yes, and the limit depends on the model. See https://discord.com/channels/59531...

O

Oreki•9/3/24, 4:01 PM

I don't think

@cf/meta/llama-3.1-8b-instruct-fp8

@cf/meta/llama-3.1-8b-instruct-fp8

@cf/meta/llama-3.1-8b-instruct-fp8

@cf/meta/llama-3.1-8b-instruct-fp8 has 32k token limit

O

Oreki•9/3/24, 4:01 PM

I tried it as well, and it somewhat stopped at 3000 characters

Xxav Hey, I'm using llama-3.1-8b-instruct to classify and reject spam/inappropriate m...

R

rob•9/3/24, 8:59 PM

try feeding a asisstant response starting of "{" in the mesg hustoy and itll try. I have a few triks that yield 99% success or so if you want to DM me

V

Vikash•9/6/24, 8:59 AM

How to bind Vector index to Pages project, the button show "Get started" and redirect to /vectorize page while I aleady have an index.

VVikash How to bind Vector index to Pages project, the button show "Get started" and red...

V

Vikash•9/6/24, 4:38 PM

I used the API directly to update bindings, the dashboard is broken I think

V

Vikash•9/6/24, 4:41 PM

I am getting dimensions error in indexing. Any suggestion?

VECTOR_UPSERT_ERROR (code = 40012): invalid vector for id="sdfksd", expected 768 dimensions, and got 1024 dimensions

VECTOR_UPSERT_ERROR (code = 40012): invalid vector for id="sdfksd", expected 768 dimensions, and got 1024 dimensions

VECTOR_UPSERT_ERROR (code = 40012): invalid vector for id="sdfksd", expected 768 dimensions, and got 1024 dimensions

VECTOR_UPSERT_ERROR (code = 40012): invalid vector for id="sdfksd", expected 768 dimensions, and got 1024 dimensions

const embeddingResult = await env.AI.run('@cf/baai/bge-large-en-v1.5', {
      text:  value,      
    });
    const embeddingBatch: number[][] = embeddingResult.data;

    await env.VECTORIZE.upsert(
      embeddingBatch.map((embedding, index) => ({
        id: sourceId,
        values: embedding,
        namespace: 'default',
        metadata: {
          id: sessionId
        },
      }))
    );

const embeddingResult = await env.AI.run('@cf/baai/bge-large-en-v1.5', {
      text:  value,      
    });
    const embeddingBatch: number[][] = embeddingResult.data;

    await env.VECTORIZE.upsert(
      embeddingBatch.map((embedding, index) => ({
        id: sourceId,
        values: embedding,
        namespace: 'default',
        metadata: {
          id: sessionId
        },
      }))
    );

const embeddingResult = await env.AI.run('@cf/baai/bge-large-en-v1.5', {
      text:  value,      
    });
    const embeddingBatch: number[][] = embeddingResult.data;

    await env.VECTORIZE.upsert(
      embeddingBatch.map((embedding, index) => ({
        id: sourceId,
        values: embedding,
        namespace: 'default',
        metadata: {
          id: sessionId
        },
      }))
    );

const embeddingResult = await env.AI.run('@cf/baai/bge-large-en-v1.5', {
      text:  value,      
    });
    const embeddingBatch: number[][] = embeddingResult.data;

    await env.VECTORIZE.upsert(
      embeddingBatch.map((embedding, index) => ({
        id: sourceId,
        values: embedding,
        namespace: 'default',
        metadata: {
          id: sessionId
        },
      }))
    );

VVikash I am getting dimensions error in indexing. Any suggestion? ``` VECTOR_UPSERT_E...

A

ac•9/6/24, 5:03 PM

bge-large is a 1024-dimension model, so the vectorize index needs to be 1024 dimension as well. Looks like it's 768. bge-base is a 768-dimension model

V

Vikash•9/6/24, 5:17 PM

Ok thanks, I will use the base model

V

Vikash•9/6/24, 5:18 PM

Also, anyway to alter index to change it to 1024?

J

JustinNoel•9/7/24, 12:37 PM

I'm getting really horrible results with all of the text to image AI models (I've tried all of the ones CF has). I'm using the prompts below and getting garbage responses like those in this image.

Does anyone have suggestions on how to actually get what I want?

export default {
  async fetch(request, env) {
    const inputs = {
      prompt: "create an image  that is 512x512. the background should be a solid, plain, yellow color. text over the background should say 'Learn How to Pronounce MySQL' in English. Text should be red and use an Arial font. ",
      negative_prompt: "There shOuld not be any other effects or images.",
      height: 512,
      width: 1024
    };

    const response = await env.AI.run(
      "@cf/bytedance/stable-diffusion-xl-lightning",
      inputs
    );

    return new Response(response, {
      headers: {
        "content-type": "image/png",
      },
    });

  },
};

export default {
  async fetch(request, env) {
    const inputs = {
      prompt: "create an image  that is 512x512. the background should be a solid, plain, yellow color. text over the background should say 'Learn How to Pronounce MySQL' in English. Text should be red and use an Arial font. ",
      negative_prompt: "There shOuld not be any other effects or images.",
      height: 512,
      width: 1024
    };

    const response = await env.AI.run(
      "@cf/bytedance/stable-diffusion-xl-lightning",
      inputs
    );

    return new Response(response, {
      headers: {
        "content-type": "image/png",
      },
    });

  },
};

export default {
  async fetch(request, env) {
    const inputs = {
      prompt: "create an image  that is 512x512. the background should be a solid, plain, yellow color. text over the background should say 'Learn How to Pronounce MySQL' in English. Text should be red and use an Arial font. ",
      negative_prompt: "There shOuld not be any other effects or images.",
      height: 512,
      width: 1024
    };

    const response = await env.AI.run(
      "@cf/bytedance/stable-diffusion-xl-lightning",
      inputs
    );

    return new Response(response, {
      headers: {
        "content-type": "image/png",
      },
    });

  },
};

export default {
  async fetch(request, env) {
    const inputs = {
      prompt: "create an image  that is 512x512. the background should be a solid, plain, yellow color. text over the background should say 'Learn How to Pronounce MySQL' in English. Text should be red and use an Arial font. ",
      negative_prompt: "There shOuld not be any other effects or images.",
      height: 512,
      width: 1024
    };

    const response = await env.AI.run(
      "@cf/bytedance/stable-diffusion-xl-lightning",
      inputs
    );

    return new Response(response, {
      headers: {
        "content-type": "image/png",
      },
    });

  },
};

K

katopz•9/7/24, 2:03 PM

SD is bad at text, Should be better when CF support FLUX i think

K

katopz•9/7/24, 2:06 PM

Text Embeddings also useless to me, only en no multi-language model

K

katopz•9/7/24, 2:10 PM

Other model also outdate, LoRA stuck at

llama-2

llama-2

llama-2

llama-2 , CF ai seem to be useless to me atm.

Kkatopz SD is bad at text, Should be better when CF support FLUX i think 🤔

I

Isaac McFadyen•9/7/24, 5:07 PM

This ^ plus SD uses CLIP for prompting which doesn't like natural language very much... comma seperated tags work better, for example:
Bad:

create me an image that is 512x512, with text that says "my text here" and a red background, with yellow text

create me an image that is 512x512, with text that says "my text here" and a red background, with yellow text

create me an image that is 512x512, with text that says "my text here" and a red background, with yellow text

create me an image that is 512x512, with text that says "my text here" and a red background, with yellow text
Good:

red background, text saying "my text here", arial font, yellow color

red background, text saying "my text here", arial font, yellow color

red background, text saying "my text here", arial font, yellow color

red background, text saying "my text here", arial font, yellow color

K

katopz•9/8/24, 4:16 AM

yeah, that too.

U

user•9/8/24, 10:14 AM

is the documentation for stable-diffusion-xl-base-1.0 incorrect?

Cloudflare Docs

stable-diffusion-xl-base-1.0 | Cloudflare Workers AI docs

Diffusion-based text-to-image generative model by Stability AI. Generates and modify images based on text prompts.

U

user•9/8/24, 10:14 AM

it says the response is a binary string but its an object

U

user•9/8/24, 10:15 AM

or is it a blob?

U

user•9/8/24, 10:23 AM

response, not input

U

user•9/8/24, 10:24 AM

https://user.you-sk.id/XMGRn78KexWR

uwu

owo

U

user•9/8/24, 10:25 AM

it claims its a binary string but the type is an object with zero keys

U

user•9/8/24, 10:26 AM

sending a request to the api directly returns an image correctly

U

user•9/8/24, 10:27 AM

but using env.AI does not

U

user•9/8/24, 10:31 AM

ah

U

user•9/8/24, 10:35 AM

Then how come doing

New blob([res])

New blob([res])

New blob([res])

New blob([res]) returns a blob with raw content of

[object Object]

[object Object]

[object Object]

[object Object]?

U

user•9/8/24, 10:36 AM

logging JSON.stringify() on the response returns

{}

{}

{}

{}

U

user•9/8/24, 10:41 AM

    const input: TTIInput = {
        prompt: prompt,
        strength: strength,
    };

    const res = await env.AI.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

    const blob = new Blob([res]);

    console.log(await blob.text());

    const input: TTIInput = {
        prompt: prompt,
        strength: strength,
    };

    const res = await env.AI.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

    const blob = new Blob([res]);

    console.log(await blob.text());

    const input: TTIInput = {
        prompt: prompt,
        strength: strength,
    };

    const res = await env.AI.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

    const blob = new Blob([res]);

    console.log(await blob.text());

    const input: TTIInput = {
        prompt: prompt,
        strength: strength,
    };

    const res = await env.AI.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

    const blob = new Blob([res]);

    console.log(await blob.text());

U

user•9/8/24, 10:41 AM

this logs [object Object]

U

user•9/8/24, 10:52 AM

well, when I log JSON.stringify(res) it prints "{}"

U

user•9/8/24, 10:52 AM

so...

U

user•9/8/24, 10:57 AM

well i'd figure it would throw or return nil, or at the bare minimum return "[]"

U

user•9/8/24, 11:01 AM

? wdym

U

user•9/8/24, 11:03 AM

if i do

let a = new Uint8Array(1)
console.log(JSON.stringify(a))

let a = new Uint8Array(1)
console.log(JSON.stringify(a))

let a = new Uint8Array(1)
console.log(JSON.stringify(a))

let a = new Uint8Array(1)
console.log(JSON.stringify(a))

it logs

{"0":0}

{"0":0}

{"0":0}

{"0":0}, but when i log the response from ai.run it's just

{}

{}

{}

{}

None of the questions regarding the token usage gets answered I see. Still awaiting any update on th

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