sacred flume
How many files can I upload at once per GPT?
Up to 20 files per GPT for the lifetime of that GPT. Keep in mind there are file size restrictions and usage caps per user/org.
this was the FAQ in openai
but am not understanding it..
can someone explain?
how many audio files or images i can upload to gpt4 omni at once?
warm knotBOT
Hi @sacred flume. I'm kapa.ai, your friendly support bot. I will try to answer your question by searching through the knowledge base. :wave:
You can upload up to 20 files per GPT for the lifetime of that GPT. This limit applies to all types of files, including audio files and images. However, there are also file size restrictions and usage caps that you need to be aware of:
If you exceed these limits, an error will be displayed.
As for GPT-4 Omni, it supports image uploads in the Chat Completions API. However, the specific number of images that can be uploaded at once is not specified in the provided sources.
For more detailed information, you can refer to the following sources:
sacred flume
@warm knot what do u mean lifetime
warm knotBOT
Let me check the knowledge base for you. One moment! :books:
The term "lifetime" in this context refers to the duration for which a specific instance of a GPT model is used. For example, if you're using a specific instance of GPT-3 or GPT-4 for a project, you can upload up to 20 files to that instance over the course of its use. Once you've reached this limit, you won't be able to upload more files to that specific instance.
However, if you start a new project with a new instance of the GPT model, the file upload count would reset, and you could upload up to 20 files to this new instance.
Please note that these are general interpretations of the term "lifetime" in this context, and the specific details might vary based on OpenAI's policies and the specific usage of the GPT models. For more accurate information, you might want to reach out to OpenAI's support.
sacred flume
@warm knot how many audio files i can upload to gpt4 omni through api>?
warm knotBOT
Let me check the knowledge base for you. One moment! :books:
As per the information available in the provided sources, GPT-4o (Omni) currently supports text and vision modalities, with support for audio coming in the following weeks to a small group of trusted partners. However, the specific number of audio files that can be uploaded at once is not specified in the provided sources.
sacred flume
@warm knot
Hi, this is my below code
from config.config_loader import cfg
from langchain.output_parsers import RetryOutputParser
from langchain_core.exceptions import OutputParserException
from langchain_core.prompts import PromptTemplate
from langchain_core.runnables import RunnableLambda, RunnableParallel
from config.config_loader import cfg, parser, prompts
from langchain.output_parsers import PydanticOutputParser
from typing import List
from pydantic import BaseModel, Field
class SuggestionsResponse(BaseModel):
suggestions: List[str] = Field(description="List of questions to be suggested")
prompt_template = prompts["generate_suggestions_prompt"]
parser = PydanticOutputParser(pydantic_object=SuggestionsResponse)
prompt = PromptTemplate(
template=prompt_template,
input_variables=["user_question"],
partial_variables={"format_instructions": parser.get_format_instructions()},
)
retry_parser = RetryOutputParser.from_llm(parser=parser, llm=cfg.llm)
completion_chain = prompt | cfg.llm
main_chain = RunnableParallel(
completion=completion_chain, prompt_value=prompt
) | RunnableLambda(lambda x: retry_parser.parse_with_prompt(**x))
out = main_chain.invoke({"query": "What is your name?"})
i am getting this error
ValidationError: 1 validation error for Generation
text
str type expected (type=type_error.str)
warm knotBOT
Let me check the knowledge base for you. One moment! :books:
The error message you're seeing, ValidationError: 1 validation error for Generation text str type expected (type=type_error.str), typically occurs when the Pydantic library expects a string (str) type but receives a different type instead.
In your code, the error might be related to the SuggestionsResponse class or the data you're passing to the main_chain.invoke() method. However, without more context or information about the data types and structures used in your code, it's difficult to pinpoint the exact cause of the error.
Here are a few things you could check:
Ensure that the suggestions field in the SuggestionsResponse class is receiving a list of strings as expected.
Check the data type of the query value you're passing to main_chain.invoke(). Make sure it's a string.
Review the PydanticOutputParser and RetryOutputParser classes, and ensure they're expecting and handling data types correctly.
If the error persists, you might want to reach out to the maintainers of the libraries you're using or ask for help on a platform like StackOverflow, providing them with more context and information about your code and the data you're working with.
sacred flume
@warm knot Hey, the below is my code
async def stream_response() -> AsyncGenerator[str, None]:
chunks = []
with get_openai_callback() as cb:
async for chunk in chain_with_history.astream(
{"question": user_question},
config=config,
):
chunks.append(chunk)
log_structured(
"debug",
f"Streaming chunk: {chunk.content}",
request_id=request.request_id,
event="streaming_chunk",
)
yield chunk.content
But Tokens Used: 0
Prompt Tokens: 0
Completion Tokens: 0
Successful Requests: 0
Total Cost (USD): $0.0
could someone help?
warm knotBOT
Let me check the knowledge base for you. One moment! :books:
Based on the provided sources, there isn't enough information to diagnose the issue with your code. The code snippet you've shared seems to be part of a larger codebase, and without additional context or information about the rest of your code, it's difficult to pinpoint the exact cause of the issue.
However, here are a few general suggestions that might help:
Check your input: Ensure that the user_question variable you're passing to chain_with_history.astream() is correctly defined and contains the expected data.
Check your configuration: Make sure the config variable you're passing to chain_with_history.astream() is correctly defined and contains the necessary configuration for your OpenAI API call.
Check your OpenAI API setup: Ensure that you've correctly set up your OpenAI API, including your API key and any other necessary configuration.
Check your callback function: Make sure the get_openai_callback() function is correctly defined and is properly handling the chunks of data received from the OpenAI API.
Check your logs: The log_structured() function call in your code suggests that you're logging the chunks of data received from the OpenAI API. Check these logs for any errors or unexpected data.
If the issue persists, you might want to reach out to OpenAI's support or ask for help on a platform like StackOverflow, providing them with more context and information about your code and the data you're working with.