When using the "View Code" feature in the playground environment, the sample code displayed does not work as intended.

Gobillion YC S21 0 Reputation points
2024-04-03T02:41:49.21+00:00

proided sample code:-import openai, os, requests

openai.api_type = "azure"

# Azure OpenAI on your own data is only supported by the 2023-08-01-preview API version

openai.api_version = "2023-08-01-preview"

# Azure OpenAI setup

openai.api_base = "https://acs-forms-demo-openai.openai.azure.com/" # Add your endpoint here

openai.api_key = os.getenv("OPENAI_API_KEY") # Add your OpenAI API key here

deployment_id = "gpt-35-turbo" # Add your deployment ID here

# Azure AI Search setup

search_endpoint = "https://acs-forms-azure-ai-search.search.windows.net"; # Add your Azure AI Search endpoint here

search_key = os.getenv("SEARCH_KEY"); # Add your Azure AI Search admin key here

search_index_name = "havistoteaindex"; # Add your Azure AI Search index name here

def setup_byod(deployment_id: str) -> None:


"""Sets up the OpenAI Python SDK to use your own data for the chat endpoint.

:param deployment_id: The deployment ID for the model to use with your own data.

To remove this configuration, simply set openai.requestssession to None.

"""

class BringYourOwnDataAdapter(requests.adapters.HTTPAdapter):

    def send(self, request, **kwargs):

        request.url = f"{openai.api_base}/openai/deployments/{deployment_id}/extensions/chat/completions?api-version={openai.api_version}"

        return super().send(request, **kwargs)

session = requests.Session()

# Mount a custom adapter which will use the extensions endpoint for any call using the given deployment_id

session.mount(

    prefix=f"{openai.api_base}/openai/deployments/{deployment_id}",

    adapter=BringYourOwnDataAdapter()

)

openai.requestssession = session
setup_byod(deployment_id)

message_text = [{"role": "user", "content": "What are the differences between Azure Machine Learning and Azure AI services?"}]

completion = openai.ChatCompletion.create(

messages=message_text,

deployment_id=deployment_id,

dataSources=[  # camelCase is intentional, as this is the format the API expects

  {
  "type": "AzureCognitiveSearch",

  "parameters": {

"endpoint": "'$search_endpoint'",
"indexName": "'$search_index'",
"semanticConfiguration": "default",
"queryType": "simple",
"fieldsMapping": {
"contentFieldsSeparator": "\n",
  "contentFields": [
"content"
],
"filepathField": "filepath",
 "titleField": "title",
 "urlField": "url",
"vectorFields": []
},
"inScope": true,
"roleInformation": "You are an AI assistant that helps people find information.",
"filter": null,
"strictness": 3,
"topNDocuments": 5,
"key": "'$search_key'"
 }
}
],
enhancements=undefined,
temperature=0,
top_p=1,
max_tokens=800,
stop=null,
stream=true)
print(completion)  

Error in this code :-openai.error.InvalidRequestError: Unrecognized request argument supplied: dataSources

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