Is there a good worker template with AI integration. Like a website where you can write and ask thin

Kkaktus___Is there a good worker template with AI integration. Like a website where you ca...

C

Craig Dennis•3/7/24, 12:39 AM

I'm working on that...unlaunched yet, but let me know if this is along the lines of what you are looking for: https://github.com/craigsdennis/chat-workers-ai-base

GitHub

GitHub - craigsdennis/chat-workers-ai-base: A base starter for chat...

A base starter for chat apps on Cloudflare Workers AI platform - craigsdennis/chat-workers-ai-base

Kkaktus___Is there a good worker template with AI integration. Like a website where you ca...

C

Craig Dennis•3/7/24, 12:45 AM

https://base-chat.pages.dev

CCraig Dennis https://base-chat.pages.dev

S

Sam•3/7/24, 9:24 AM

lmao is this normal?

CCraig Dennis https://base-chat.pages.dev

K

kaktus___OP•3/7/24, 2:35 PM

That's perfect thank you! :)

K

kaktus___OP•3/7/24, 3:47 PM

I'm a bit confused rn.
Why am I getting this error? Did I forget to bind something?

16:45:04.582 Executing user command: npx wrangler tail AI
16:45:07.041
16:45:07.157 ✘ [ERROR] A request to the Cloudflare API (/accounts/userid/workers/scripts/AI/bindings) failed.
16:45:07.157

LLogan Grasby You can test LLMs side by side with this tool I hacked together. We'll have a mo...

K

kaktus___OP•3/7/24, 6:03 PM

That's also cool ;D

K

kaktus___OP•3/7/24, 6:03 PM

Thanks :)

Ssludge kinda humorous, and proof that 'true' AI is a long way off

I

Isaac McFadyen•3/8/24, 2:08 AM

Keep in mind this is running Phi 2 which, while state-of-the-art, is still a very small model.

I

Isaac McFadyen•3/8/24, 2:09 AM

You'd likely get much better results with LLaMa 7B or 13B.

S

Strike•3/8/24, 2:43 AM

Maybe I'm getting the wrong thing but wouldn't small specialized models be the goto thing for workers AI?

S

Strike•3/8/24, 2:44 AM

Last I remember the models are run on onnx afterall right?

S

Strike•3/8/24, 2:45 AM

Maybe I'm thinking of constellations(which isn't that also workers AI or did the vision change?), because I also see that seemingly the custom upload feature doesn't exist

S

scotto•3/8/24, 7:40 PM

Can we add this one https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1 ?

mixedbread-ai/mxbai-embed-large-v1 · Hugging Face

S

scotto•3/8/24, 7:40 PM

Outperforms open ai embedding in theory

Ssludge no matter what I send to `@cf/microsoft/resnet-50` I get an internal server erro...

R

Raylight•3/10/24, 1:09 PM

Works for me with code that looks something like this. Tested it with text-to-image generated images, i.e. 256x256 or 1024x1024 PNGs.

const formData = await request.formData();
const inputImg = formData.get("image");

const formData = await request.formData();
const inputImg = formData.get("image");

const formData = await request.formData();
const inputImg = formData.get("image");

const formData = await request.formData();
const inputImg = formData.get("image");

A. Using worker binding:

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const response = await ai.run(model, inputs);

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const response = await ai.run(model, inputs);

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const response = await ai.run(model, inputs);

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const response = await ai.run(model, inputs);

B. Using API, sending JSON:

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const fetchOptions = {
   method: "POST", 
   body: JSON.stringify(inputs),
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "application/json" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const fetchOptions = {
   method: "POST", 
   body: JSON.stringify(inputs),
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "application/json" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const fetchOptions = {
   method: "POST", 
   body: JSON.stringify(inputs),
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "application/json" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

const inputs = {
   image: [...new Uint8Array(await inputImg.arrayBuffer())],
};
const fetchOptions = {
   method: "POST", 
   body: JSON.stringify(inputs),
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "application/json" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

C. Using API, sending PNG as is:

const fetchOptions = {
   method: "POST",
   body: inputImg,
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "image/png" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

const fetchOptions = {
   method: "POST",
   body: inputImg,
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "image/png" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

const fetchOptions = {
   method: "POST",
   body: inputImg,
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "image/png" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

const fetchOptions = {
   method: "POST",
   body: inputImg,
   headers: { authorization: `Bearer ${apiToken}`, "content-type": "image/png" }
};
const response = await fetch(`https://api.cloudflare.com/client/v4/accounts/${apiAccount}/ai/run/${model}`, fetchOptions);

I get lower latency (tested with a black <1 kB 256x256 png) using a worker binding, but worker CPU time is another story. A quick test on a ~1.5 MB 1024x1024 png gave me ~700-900 ms

CPU time using option A, ~100-150 ms using option B, and <5 ms using option C.

R

rodrigo•3/10/24, 5:33 PM

I'm having a CORS errors using langchain:

Access to fetch at 'https://api.cloudflare.com/client/v4/accounts/.../ai/run/@cf/meta/llama-2-7b-chat-int8' from origin 'http://localhost:3100' has been blocked by CORS policy: Response to preflight request doesn't pass access control check: No 'Access-Control-Allow-Origin' header is present on the requested resource. If an opaque response serves your needs, set the request's mode to 'no-cors' to fetch the resource with CORS disabled.

Access to fetch at 'https://api.cloudflare.com/client/v4/accounts/.../ai/run/@cf/meta/llama-2-7b-chat-int8' from origin 'http://localhost:3100' has been blocked by CORS policy: Response to preflight request doesn't pass access control check: No 'Access-Control-Allow-Origin' header is present on the requested resource. If an opaque response serves your needs, set the request's mode to 'no-cors' to fetch the resource with CORS disabled.

Access to fetch at 'https://api.cloudflare.com/client/v4/accounts/.../ai/run/@cf/meta/llama-2-7b-chat-int8' from origin 'http://localhost:3100' has been blocked by CORS policy: Response to preflight request doesn't pass access control check: No 'Access-Control-Allow-Origin' header is present on the requested resource. If an opaque response serves your needs, set the request's mode to 'no-cors' to fetch the resource with CORS disabled.

Access to fetch at 'https://api.cloudflare.com/client/v4/accounts/.../ai/run/@cf/meta/llama-2-7b-chat-int8' from origin 'http://localhost:3100' has been blocked by CORS policy: Response to preflight request doesn't pass access control check: No 'Access-Control-Allow-Origin' header is present on the requested resource. If an opaque response serves your needs, set the request's mode to 'no-cors' to fetch the resource with CORS disabled.

How do I set CORS headers using langchain?

M

Max Frai•3/11/24, 5:09 PM

Hello, I call api inside nodejs:

    const url = `https://api.cloudflare.com/client/v4/accounts/d1a..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning`;
    const headers = {
        Authorization: `Bearer ${CFAI_TOKEN}`,
    };
    const response = await axios.post(url, {prompt}, {headers});

    const fs = require("fs");
    fs.writeFileSync("image.png", response.data);

    const url = `https://api.cloudflare.com/client/v4/accounts/d1a..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning`;
    const headers = {
        Authorization: `Bearer ${CFAI_TOKEN}`,
    };
    const response = await axios.post(url, {prompt}, {headers});

    const fs = require("fs");
    fs.writeFileSync("image.png", response.data);

    const url = `https://api.cloudflare.com/client/v4/accounts/d1a..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning`;
    const headers = {
        Authorization: `Bearer ${CFAI_TOKEN}`,
    };
    const response = await axios.post(url, {prompt}, {headers});

    const fs = require("fs");
    fs.writeFileSync("image.png", response.data);

    const url = `https://api.cloudflare.com/client/v4/accounts/d1a..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning`;
    const headers = {
        Authorization: `Bearer ${CFAI_TOKEN}`,
    };
    const response = await axios.post(url, {prompt}, {headers});

    const fs = require("fs");
    fs.writeFileSync("image.png", response.data);

The problem is that image.png is bad image. It's like 2-3MB size but I can't view it, image viewer says its corrupted. When I make same request from terminal the file is okay:

curl https://api.cloudflare.com/client/v4/accounts/d1a65..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning \
  -X POST \
  -H "Authorization: Bearer ****" \
  -d '{ "prompt": "cyberpunk cat" }' --output "cli.png"

curl https://api.cloudflare.com/client/v4/accounts/d1a65..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning \
  -X POST \
  -H "Authorization: Bearer ****" \
  -d '{ "prompt": "cyberpunk cat" }' --output "cli.png"

curl https://api.cloudflare.com/client/v4/accounts/d1a65..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning \
  -X POST \
  -H "Authorization: Bearer ****" \
  -d '{ "prompt": "cyberpunk cat" }' --output "cli.png"

curl https://api.cloudflare.com/client/v4/accounts/d1a65..../ai/run/@cf/bytedance/stable-diffusion-xl-lightning \
  -X POST \
  -H "Authorization: Bearer ****" \
  -d '{ "prompt": "cyberpunk cat" }' --output "cli.png"

M

Max Frai•3/11/24, 5:12 PM

Okay, that was easy... Maybe someone will also have this issue:

    const response = await axios({
        method: "post",
        url,
        data: {prompt},
        headers,
        responseType: "arraybuffer",
    });

    const response = await axios({
        method: "post",
        url,
        data: {prompt},
        headers,
        responseType: "arraybuffer",
    });

    const response = await axios({
        method: "post",
        url,
        data: {prompt},
        headers,
        responseType: "arraybuffer",
    });

    const response = await axios({
        method: "post",
        url,
        data: {prompt},
        headers,
        responseType: "arraybuffer",
    });

We need to specity returned data type as binary

K

kingmesal•3/12/24, 6:44 PM

OKAY, it has been weeks that I have been getting this error:

InferenceUpstreamError: ERROR 3001: Unknown internal error

InferenceUpstreamError: ERROR 3001: Unknown internal error

InferenceUpstreamError: ERROR 3001: Unknown internal error

InferenceUpstreamError: ERROR 3001: Unknown internal error
Can ANYONE tell me WHAT causes this error when calling

@cf/baai/bge-large-en-v1.5

@cf/baai/bge-large-en-v1.5

@cf/baai/bge-large-en-v1.5

@cf/baai/bge-large-en-v1.5 ?

A

acusti•3/12/24, 9:08 PM

since upgrading

@cloudflare/ai

@cloudflare/ai

@cloudflare/ai

@cloudflare/ai from 1.0.53 to 1.1.0, using the

stream: true

stream: true

stream: true

stream: true option when invoking

ai.run(…)

ai.run(…)

ai.run(…)

ai.run(…) no longer streams in the response as would be expected. instead, there are no messages for the most part until the very end when suddenly the entirety of the response streams in at once (still broken into chunks but in extremely rapid succession). here’s how i am using it:

    const ai = new Ai(env.AI);
    const model = '@cf/openchat/openchat-3.5-0106';
    const stream = await ai.run(model, {
        messages: getMessagesFromPrompt({ model, prompt }),
        stream: true,
    });

    return new Response(stream, {
        headers: { 'content-type': 'text/event-stream' },
    });

    const ai = new Ai(env.AI);
    const model = '@cf/openchat/openchat-3.5-0106';
    const stream = await ai.run(model, {
        messages: getMessagesFromPrompt({ model, prompt }),
        stream: true,
    });

    return new Response(stream, {
        headers: { 'content-type': 'text/event-stream' },
    });

    const ai = new Ai(env.AI);
    const model = '@cf/openchat/openchat-3.5-0106';
    const stream = await ai.run(model, {
        messages: getMessagesFromPrompt({ model, prompt }),
        stream: true,
    });

    return new Response(stream, {
        headers: { 'content-type': 'text/event-stream' },
    });

    const ai = new Ai(env.AI);
    const model = '@cf/openchat/openchat-3.5-0106';
    const stream = await ai.run(model, {
        messages: getMessagesFromPrompt({ model, prompt }),
        stream: true,
    });

    return new Response(stream, {
        headers: { 'content-type': 'text/event-stream' },
    });

M

Marc•3/13/24, 7:25 PM

Is there any timeline for when a multilingual embedding model will be added? It's a requirement for our use case and the only thing stopping us from using this product

Mmichelle do you have a model in mind?

M

Marc•3/14/24, 2:14 AM

Honestly nothing to specific. We just need to handle text that is potentially in different languages. We are currently using this model:
https://huggingface.co/intfloat/multilingual-e5-small

intfloat/multilingual-e5-small · Hugging Face

I

Isaac McFadyen•3/14/24, 12:03 PM

I believe BGE-3M was also mentioned here at one point.

I

Isaac McFadyen•3/14/24, 12:03 PM

https://github.com/FlagOpen/FlagEmbedding/tree/master/FlagEmbedding/BGE_M3

Aacusti since upgrading `@cloudflare/ai` from 1.0.53 to 1.1.0, using the `stream: true` ...

�

😈 Donkey 💫•3/16/24, 5:00 AM

I see 1.1.10 come with massive bugs

A

alukach•3/17/24, 7:37 AM

Have others been able to run text-to-image models in NextJS apps that run on Pages? I have a nextJS app set up via C3 and a server action performing the following:

"use server";

import { getRequestContext } from "@cloudflare/next-on-pages";
import { Ai } from "@cloudflare/ai";


export async function createThread(prevState: any, formData: FormData) {
  const { env } = getRequestContext();
  const ai = new Ai(env.AI);

  const title = formData.get("title");
  const response = await ai.run(
    "@cf/stabilityai/stable-diffusion-xl-base-1.0",
    {
      prompt: title as string,
    }
  );

"use server";

import { getRequestContext } from "@cloudflare/next-on-pages";
import { Ai } from "@cloudflare/ai";


export async function createThread(prevState: any, formData: FormData) {
  const { env } = getRequestContext();
  const ai = new Ai(env.AI);

  const title = formData.get("title");
  const response = await ai.run(
    "@cf/stabilityai/stable-diffusion-xl-base-1.0",
    {
      prompt: title as string,
    }
  );

"use server";

import { getRequestContext } from "@cloudflare/next-on-pages";
import { Ai } from "@cloudflare/ai";


export async function createThread(prevState: any, formData: FormData) {
  const { env } = getRequestContext();
  const ai = new Ai(env.AI);

  const title = formData.get("title");
  const response = await ai.run(
    "@cf/stabilityai/stable-diffusion-xl-base-1.0",
    {
      prompt: title as string,
    }
  );

"use server";

import { getRequestContext } from "@cloudflare/next-on-pages";
import { Ai } from "@cloudflare/ai";


export async function createThread(prevState: any, formData: FormData) {
  const { env } = getRequestContext();
  const ai = new Ai(env.AI);

  const title = formData.get("title");
  const response = await ai.run(
    "@cf/stabilityai/stable-diffusion-xl-base-1.0",
    {
      prompt: title as string,
    }
  );

However, I'm running into

Error: A Node.js API is used (DecompressionStream) which is not supported in the Edge Runtime. Learn more: https://nextjs.org/docs/api-reference/edge-runtime

Error: A Node.js API is used (DecompressionStream) which is not supported in the Edge Runtime. Learn more: https://nextjs.org/docs/api-reference/edge-runtime

Error: A Node.js API is used (DecompressionStream) which is not supported in the Edge Runtime. Learn more: https://nextjs.org/docs/api-reference/edge-runtime

Error: A Node.js API is used (DecompressionStream) which is not supported in the Edge Runtime. Learn more: https://nextjs.org/docs/api-reference/edge-runtime

I'm guessing there some decompression going on under the hood with the AI interface?

If it matters, my next step is to write the response as a file to R2, so I'm not sure that I actually need to decompress for my purposes...

Mmichelle any bugs other than this one? we were able to reproduce this one and looking at ...

�

😈 Donkey 💫•3/17/24, 4:12 PM

This is how I generate image:

const response: AiTextToImageOutput = await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

const response: AiTextToImageOutput = await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

const response: AiTextToImageOutput = await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

const response: AiTextToImageOutput = await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input);

then put in R2

env.MY_BUCKET.put(newImageName, response)

env.MY_BUCKET.put(newImageName, response)

env.MY_BUCKET.put(newImageName, response)

env.MY_BUCKET.put(newImageName, response)

it works in 1.0.53
but It takes typeError in 1.1.0 when putting R2, with something about readable Stream, sorry about unclear error information because I rolled back version 1.0.53

�😈 Donkey 💫This is how I generate image: ```ts const response: AiTextToImageOutput = await...

A

acusti•3/17/24, 5:12 PM

it should be possible to improve the built-in

@cloudflare/ai

@cloudflare/ai

@cloudflare/ai

@cloudflare/ai types to narrow the return type based on the received

stream

stream

variable (

stream: true

stream: true

stream: true

stream: true means

ReadableStream<any>

ReadableStream<any>

ReadableStream<any>

ReadableStream<any>,

stream: false

stream: false

stream: false

stream: false means

AiTextToImageOutput

AiTextToImageOutput

AiTextToImageOutput

AiTextToImageOutput or the like), which would remove the need for this workaround.

that said, you can resolve the typescript errors by casting the return value instead of defining the variable type. so in your example, you would do:

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input)) as AiTextToImageOutput;

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input)) as AiTextToImageOutput;

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input)) as AiTextToImageOutput;

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", input)) as AiTextToImageOutput;

if instead you were passing in

stream: true

stream: true

stream: true

stream: true to the

ai.run(…)

ai.run(…)

ai.run(…)

ai.run(…) function, you would want to cast the result to

ReadableStream<any>

ReadableStream<any>

ReadableStream<any>

ReadableStream<any>:

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", {...input, stream: true})) as ReadableStream<any>;

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", {...input, stream: true})) as ReadableStream<any>;

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", {...input, stream: true})) as ReadableStream<any>;

const response = (await ai.run("@cf/stabilityai/stable-diffusion-xl-base-1.0", {...input, stream: true})) as ReadableStream<any>;

P

pups•3/18/24, 4:29 PM

any plans to launch a TTS model as well? like Coqui?

C

chand1012•3/20/24, 12:52 PM

Hello! I was wonder if some features were on the roadmap, and if not, I'd like to request them! I think that enforcing JSON output like Ollama and Llama.cpp do would be a great feature for devs who want to get structured data output consistently for parsing. Ollama lets you use

format: "json"

format: "json"

format: "json"

format: "json" in your request and it handles applying the grammar for you. See here for an example: https://github.com/ollama/ollama/blob/main/docs/api.md#generate-a-completion

Another features I'd like to see is the option to return token counts along with the response. Its hard to judge what my users are using with no token counts, and I don't really want to have to add a step in order to calculate them.

GitHub

ollama/docs/api.md at main · ollama/ollama

Get up and running with Llama 2, Mistral, Gemma, and other large language models. - ollama/ollama

R

Raylight•3/21/24, 11:22 AM

Is the

strength

strength

strength

strengthparameter for

@cf/runwayml/stable-diffusion-v1-5-img2img

@cf/runwayml/stable-diffusion-v1-5-img2img

@cf/runwayml/stable-diffusion-v1-5-img2img

@cf/runwayml/stable-diffusion-v1-5-img2img clamped and/or quantized in some weird way? Strength 0.095 generates an output that's close to identical to the source (albeit degraded), while 0.095001 generates a noisy version of the source. Strength 0.0 seems to produce as wildly different output as if it was set to 1.0. (Values outside the range 0.0 to 1.0 throws InferenceUpstreamError.)

R

Raylight•3/21/24, 11:37 AM

While I'm at it, looks like

@cf/runwayml/stable-diffusion-v1-5-inpainting

@cf/runwayml/stable-diffusion-v1-5-inpainting

@cf/runwayml/stable-diffusion-v1-5-inpainting

@cf/runwayml/stable-diffusion-v1-5-inpainting throws InferenceUpstreamError on strength values below 0.05 (except 0). Haven't tested this on version 1.1.0, though.

Cchand1012 Hello! I was wonder if some features were on the roadmap, and if not, I'd like t...

A

acusti•3/22/24, 2:53 AM

@chand1012 i had this exact need (the

format: 'json'

format: 'json'

format: 'json'

format: 'json' option), and i couldn’t find a satisfactory solution out there, so i made a

parseAsJSON

parseAsJSON

parseAsJSON

parseAsJSON util that takes a string and parses it as JSON even if it has syntax errors or too many closing curly braces, or not enough curly braces, or overly escaped characters, or unescaped characters, or pre- and post-ambles, or…

it’s a JS (typescript) package available on NPM called

@acusti/parsing

@acusti/parsing

@acusti/parsing

@acusti/parsing. here’s the readme: https://github.com/acusti/uikit/tree/main/packages/parsing

i also implemented some simple few-shot prompting modelled on what’s documented in this guide to get the LLM to return JSON: https://www.pinecone.io/learn/llama-2/#Llama-2-Chat-Prompt-Structure

GitHub

uikit/packages/parsing at main · acusti/uikit

UI toolkit monorepo containing a React component library, UI utilities, a drag-and-drop library, and more - acusti/uikit

Llama 2: AI Developers Handbook | Pinecone

Llama 2 is the latest Large Language Model (LLM) from Meta AI. It has been released as an open-access model, enabling unrestricted access to corporations and open-source hackers alike. Here we learn how to use it with Hugging Face, LangChain, and as a conversational agent.

T

TheMightyPenguin•3/22/24, 4:05 AM

Hi all, I am trying to use cloudflare AI locally, running

wrangler dev

wrangler dev

, and I get the following error when I try using the

'@cf/facebook/bart-large-cnn'

'@cf/facebook/bart-large-cnn'

'@cf/facebook/bart-large-cnn'

'@cf/facebook/bart-large-cnn' model:

Uncaught (async) Error: InferenceUpstreamError: {"success":false,"errors":[{"code":10000,"message":"Authentication error"}]}

Uncaught (async) Error: InferenceUpstreamError: {"success":false,"errors":[{"code":10000,"message":"Authentication error"}]}

Uncaught (async) Error: InferenceUpstreamError: {"success":false,"errors":[{"code":10000,"message":"Authentication error"}]}

Uncaught (async) Error: InferenceUpstreamError: {"success":false,"errors":[{"code":10000,"message":"Authentication error"}]}

If I run

wrangler dev --remote

wrangler dev --remote

, it does work, but I cannot use remote mode as I also use Cloudflare Queues in my app together with workers AI, and queues do not work in remote mode.

Any ideas what might be wrong? I am using

"wrangler": "^3.36.0"

"wrangler": "^3.36.0"

"wrangler": "^3.36.0"

"wrangler": "^3.36.0" and

"@cloudflare/ai": "^1.1.0"

"@cloudflare/ai": "^1.1.0"

"@cloudflare/ai": "^1.1.0"

"@cloudflare/ai": "^1.1.0"

A

acusti•3/22/24, 3:02 PM

@TheMightyPenguin whenever i see

Authentication error

Authentication error

i run

wrangler login

wrangler login

wrangler login

wrangler login. it surprises me how often i have to re-authenticate when doing local dev (once every few days). i’ve speculated that it might have to do with how often i’m connecting to a different wifi network and changing my IP address, but that might be totally wrong. regardless, re-authing has always resolved it for me.

Is there a good worker template with AI integration. Like a website where you can write and ask thin

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