I need to scan screenshots for as cheap as possible while keeping things accurate ofc. what can I use and how specifically would I use it?
#Whats the best way I can use the API for my use case
iron blaze
gusty sonnetBOT
Hi @iron blaze. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:
To optimize the cost and accuracy of scanning screenshots using OpenAI's API, you can consider the following strategies:
-
Optimize your input: Before passing your screenshot to the model, you should optimize your input. This could involve cropping out or masking unimportant details and scaling the image to some max dimension. This can help reduce the number of tokens processed by the model, which in turn can help reduce costs.
-
Use segmentation tools: You might experiment with tools like Segment Anything from Meta (https://github.com/facebookresearch/segment-anything). The idea is that you would first segment your image then only send the relevant bits to the model for vision processing. This can help reduce the amount of data processed by the model, potentially reducing costs and improving accuracy.
-
Optimize cost and latency: Once you've got a model that works for your use case, you can take one of two approaches:
- Compare with a smaller model zero- or few-shot: Swap out the model for a smaller, cheaper one and test whether it maintains accuracy at the lower cost and latency point.
- Model distillation: Fine-tune a smaller model using the data gathered during accuracy optimization.
-
Reduce requests and minimize tokens: Limit the number of necessary requests to complete tasks and lower the number of input tokens. This can help reduce costs and improve processing speed.
-
Select a smaller model: Use models that balance reduced costs and latency with maintained accuracy.
Remember, cost and latency are typically interconnected; reducing tokens and requests generally leads to faster processing. However, if your use case is extremely cost or latency sensitive, establish thresholds for these metrics before beginning your testing, then remove the models that exceed those from consideration.
For more detailed information, you can refer to OpenAI's guide on how to select the right model (https://platform.openai.com/docs/guides/model-selection) and latency optimization (https://platform.openai.com/docs/guides/latency-optimization).
Sources: OpenAI Community Post (https://community.openai.com/t/843423), OpenAI Model Selection Guide (https://platform.openai.com/docs/guides/model-selection)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
whats a normal amount of tokens spend per request for the api
@gusty sonnet whats a normal amount of tokens spend per request for the api
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
The number of tokens used per API request can vary greatly depending on the specific task and the length of the input and output text. However, based on the examples provided in the knowledge sources, we see that the average tokens used per request can range from around 791.90 tokens to 796.20 tokens in some cases.
Remember, both input and output tokens count towards these quantities. For example, if your API call used 10 tokens in the message input and you received 20 tokens in the message output, you would be billed for 30 tokens.
To see how many tokens are used by an API call, you can check the usage field in the API response (e.g., response['usage']['total_tokens']).
Please note that the total number of tokens in an API call must be below the model's maximum limit (4097 tokens for gpt-3.5-turbo).
Sources: OpenAI Advanced Usage (https://platform.openai.com/docs/advanced-usage), OpenAI Cookbook (https://cookbook.openai.com/examples/fine_tuning_for_function_calling#baseline-testing)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
@gusty sonnet how many tokens do I get per dollar? how exactly does API pricing work
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
The number of tokens you get per dollar depends on the specific model you're using and the pricing structure of OpenAI.
For example, according to the information provided in the knowledge sources, the text-embedding-3-small model gives approximately 62,500 pages per dollar, assuming ~800 tokens per page. This means you get approximately 50 million tokens per dollar for this model.
However, the text-embedding-3-large and text-embedding-ada-002 models give approximately 9,615 and 12,500 pages per dollar respectively, which means you get approximately 7.7 million and 10 million tokens per dollar for these models.
The total number of tokens in an API call affects:
- How much your API call costs, as you pay per token
- How long your API call takes, as writing more tokens takes more time
- Whether your API call works at all, as total tokens must be below the model's maximum limit (4097 tokens for
gpt-3.5-turbo)
Both input and output tokens count toward these quantities. For example, if your API call used 10 tokens in the message input and you received 20 tokens in the message output, you would be billed for 30 tokens. Note however that for some models the price per token is different for tokens in the input vs. the output.
For more detailed information on pricing, you can refer to OpenAI's pricing page (https://openai.com/pricing).
Sources: OpenAI Embedding Models (https://platform.openai.com/docs/guides/embeddings), OpenAI Advanced Usage (https://platform.openai.com/docs/advanced-usage)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
I have an assistant setup. how do I send an image to this assistant in nodejs? give me code
@gusty sonnet I have an assistant setup. how do I send an image to this assistant in nodejs? give me code
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
To send an image to an assistant in Node.js, you first need to upload the image file to OpenAI's servers. After the image is uploaded, you can send the image file ID in a message to the assistant. Here's an example of how you can do this:
// Assuming you have an instance of the OpenAI API client
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY
});
// Upload the image file
const file = await openai.files.create({
file: fs.createReadStream("myimage.png"),
purpose: "vision"
});
// Create a new thread (or use an existing one)
const thread = await openai.beta.threads.create({
messages: [
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is the difference between these images?"
},
{
"type": "image_file",
"image_file": {"file_id": file.id}
}
]
}
]
});
In this example, replace "myimage.png" with the path to your image file. The purpose parameter should be set to "vision" for image files.
Please note that this is a simplified example and you might need to adjust it according to your specific use case and environment.
Sources: OpenAI Community Post (https://community.openai.com/t/934498)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
ok I have a file link, how do I use the file link to upload to openai? @gusty sonnet
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
To upload a file from a link to OpenAI, you would first need to download the file from the link to your local system or server, and then upload it to OpenAI. Here's an example of how you can do this in Node.js:
const axios = require('axios');
const fs = require('fs');
const openai = require('openai');
// Initialize OpenAI client
openai.setApiKey('YOUR_OPENAI_API_KEY');
// URL of the file to download
const fileUrl = '<https://example.com/path/to/your/file';>
// Path to save the downloaded file
const localFilePath = './localFile.jsonl';
// Function to download a file
const downloadFile = async (fileUrl, localFilePath) => {
const response = await axios({
method: 'GET',
url: fileUrl,
responseType: 'stream',
});
const writer = fs.createWriteStream(localFilePath);
response.data.pipe(writer);
return new Promise((resolve, reject) => {
writer.on('finish', resolve);
writer.on('error', reject);
});
};
// Download the file
downloadFile(fileUrl, localFilePath).then(() => {
// After the file is downloaded, upload it to OpenAI
openai.File.create({
file: fs.createReadStream(localFilePath),
purpose: 'fine-tune',
}).then((response) => {
console.log(response);
});
});
In this example, replace 'YOUR_OPENAI_API_KEY' with your actual OpenAI API key, '<https://example.com/path/to/your/file'> with the URL of the file you want to download, and './localFile.jsonl' with the path where you want to save the downloaded file.
Please note that this is a simplified example and you might need to adjust it according to your specific use case and environment.
Sources: OpenAI API Reference (https://platform.openai.com/docs/api-reference), OpenAI Community Post (https://community.openai.com/t/856370)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
@gusty sonnet how do I do it without downloading the file?
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
If you want to upload a file from a URL directly to OpenAI without downloading it to your local system, you would need to stream the file from the URL to the OpenAI API. However, the OpenAI API does not currently support streaming uploads directly from a URL.
You would need to first download the file to your local system or server before uploading it to OpenAI. This is because the OpenAI API requires the actual file data to be included in the request, not just the URL of the file.
If downloading the file to your local system or server is not an option, you might need to consider using a cloud storage service that can generate a direct download link for the file, and then use a serverless function or similar service to handle the download and upload process.
Sources: OpenAI API Reference (https://platform.openai.com/docs/api-reference), OpenAI Community Post (https://community.openai.com/t/856370)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
@gusty sonnet a.ai I have an assistant setup. how do I send an image to this assistant in nodejs? give me code
I need to actually send it to an assistant, not a normal message/thread
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
To send an image to an assistant in Node.js, you first need to upload the image file to OpenAI's servers. After the image is uploaded, you can send the image file ID in a message to the assistant. Here's an example of how you can do this:
// Assuming you have an instance of the OpenAI API client
const openai = new OpenAI({{
apiKey: process.env.OPENAI_API_KEY
}});
// Upload the image file
const file = await openai.files.create({{
file: fs.createReadStream("myimage.png"),
purpose: "vision"
}});
// Create a new thread (or use an existing one)
const thread = await openai.beta.threads.create({{
messages: [
{{
"role": "user",
"content": [
{{
"type": "text",
"text": "What is the difference between these images?"
}},
{{
"type": "image_file",
"image_file": {{"file_id": file.id}}
}}
]
}}
]
}});
In this example, replace "myimage.png" with the path to your image file. The purpose parameter should be set to "vision" for image files.
Please note that this is a simplified example and you might need to adjust it according to your specific use case and environment.
Sources: OpenAI Community Post (https://community.openai.com/t/934498)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
@gusty sonnet but what about the assistant ID how would it use the right assistant
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
To use a specific assistant, you need to include the assistant_id when creating a run. Here's how you can modify the previous example to include the assistant_id:
// Assuming you have an instance of the OpenAI API client
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY
});
// Upload the image file
const file = await openai.files.create({
file: fs.createReadStream("myimage.png"),
purpose: "vision"
});
// Create a new thread (or use an existing one)
const thread = await openai.beta.threads.create({
messages: [
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is the difference between these images?"
},
{
"type": "image_file",
"image_file": {"file_id": file.id}
}
]
}
]
});
// Create a run with the specific assistant
const run = await openai.beta.threads.runs.create({
thread_id: thread.id,
assistant_id: 'your-assistant-id', // replace with your assistant's ID
});
In this example, replace 'your-assistant-id' with the ID of your assistant. The assistant_id is used to specify which assistant should process the messages in the thread.
Sources: OpenAI Community Post (https://community.openai.com/t/934498)
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
iron blaze
@gusty sonnet how do I get the response from this
gusty sonnetBOT
Let me check the knowledge base for you. One moment! :books:
To get the response from the assistant, you can use the run object that was returned when you created the run. The assistant's response will be in the messages array of the run object. Here's how you can do it:
// Assuming you have an instance of the OpenAI API client
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY
});
// Upload the image file
const file = await openai.files.create({
file: fs.createReadStream("myimage.png"),
purpose: "vision"
});
// Create a new thread (or use an existing one)
const thread = await openai.beta.threads.create({
messages: [
{
"role": "user",
"content": [
{
"type": "text",
"text": "What is the difference between these images?"
},
{
"type": "image_file",
"image_file": {"file_id": file.id}
}
]
}
]
});
// Create a run with the specific assistant
const run = await openai.beta.threads.runs.create({
thread_id: thread.id,
assistant_id: 'your-assistant-id', // replace with your assistant's ID
});
// Get the assistant's response
const assistantResponse = run.messages.find(message => message.role === 'assistant');
console.log(assistantResponse.content.text);
In this example, replace 'your-assistant-id' with the ID of your assistant. The assistant_id is used to specify which assistant should process the messages in the thread.
Please note that this is a simplified example and you might need to adjust it according to your specific use case and environment.