How do I resolve error DeploymentNotFound for Azure OpenAI Python API call?

Amin, Ishmael 10 Reputation points

I'm running the code from my desktop and connecting to Azure OpenAI Service.
 The Deployment exists in Azure associated with Deployment "gpt-35-turbo". 

<Response [404]>
    "error": {
        "code": "DeploymentNotFound",
        "message": "The API deployment for this resource does not exist. If you created the deployment within the last 5 minutes, please wait a moment and try again."
Azure OpenAI Service
Azure OpenAI Service
An Azure service that provides access to OpenAI’s GPT-3 models with enterprise capabilities.
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  1. Chris Hoder - MSFT 96 Reputation points Microsoft Employee

    Hi -- can you share a bit more code on how you are calling the API. This is likely either (1) the deployment name in your code doesn't match a deployment in the resource or (2) the deployment was not yet complete.

    1 person found this answer helpful.

  2. Ahmad MK 0 Reputation points

    I am getting the same error with this code:

    deployment_name = "Summarization"
    # Create LLM via Azure OpenAI Service
    llm = AzureOpenAI(deployment_name=deployment_name)
    llm_predictor = LLMPredictor(llm=llm)
    embedding_llm = LangchainEmbedding(OpenAIEmbeddings())
    # Define prompt helper
    max_input_size = 3000
    num_output = 256
    chunk_size_limit = 1000 # token window size per document
    max_chunk_overlap = 20 # overlap for each token fragment
    prompt_helper = PromptHelper(max_input_size=max_input_size, num_output=num_output, max_chunk_overlap=max_chunk_overlap, chunk_size_limit=chunk_size_limit)
    # Read txt files from data directory
    documents = SimpleDirectoryReader('data').load_data()
    index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, embed_model=embedding_llm, prompt_helper=prompt_helper)