Trying to make a REST Call to get steps details - API Version not supported

Sai Vamsi 0 Reputation points
2026-10-03T05:12:09.3566667+00:00

Hello,

I am trying to use Azure OpenAI from a Databricks notebook to generate PySpark code for a Bronze Loader Agent.

i am getting azure open ai endpoint not supporting Bad Request Error API version not supported error message .
for sample this is mycode

My code:


client = AzureOpenAI(
    api_key="xxxx",
    api_version="2024-11-20",
    azure_endpoint="https://xxx.services.ai.azure.com/api/projects/proj-default"
)

def call_llm(prompt):
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": prompt}]
    )
    
    content = response.choices[0].message.content.strip()

    # HARD CLEANING (VERY IMPORTANT)
    if content.lower().startswith("python"):
        content = content[len("python"):].strip()

    # Remove markdown blocks
    content = content.replace("```python", "").replace("```", "").strip()

    return content


# ---------- Bronze Loader Agent ----------
def bronze_loader_agent(volume_path, catalog, schema, max_retries=3):
    
    print("\nRunning Bronze Loader Agent...")
    print("Volume Path:", volume_path)

    base_prompt = f"""
    You are a senior data engineer working in Databricks.

    Generate ONLY valid PySpark code.

    Task:
    - Read all CSV files from: {volume_path}
    - Use dbutils.fs.ls()
    - Loop through files
    - Extract table name (remove .csv, lowercase)
    - Load CSV (header=True, inferSchema=True)
    - Write RAW data to Delta tables
    - delete from the volume after processing

    Target:
    {catalog}.{schema}.<table_name>

    STRICT RULES:
    - ONLY Python code
    - NO explanations
    - NO markdown
    - DO NOT use f-strings
    - Use string concatenation ONLY
    - DO NOT create SparkSession
    - Ensure code is COMPLETE and EXECUTABLE

    """

    attempt = 0
    last_error = None
    code = None

    while attempt < max_retries:
        print(f"\nAttempt {attempt + 1} generating/fixing code...\n")

        if attempt == 0:
            prompt = base_prompt
        else:
            prompt = f"""
            The following PySpark code failed during execution.

            FAILED CODE:
            {code}

            ERROR MESSAGE:
            {last_error}

            Your task:
            - Fix the code so it runs successfully
            - Keep the original intent intact
            - Ensure no syntax errors
            - Ensure variables are correct
            - Ensure complete statements

            STRICT RULES:
            - Return ONLY corrected Python code
            - NO explanations
            - NO markdown
            - DO NOT use f-strings
            - Ensure code is COMPLETE and EXECUTABLE
            """

        code = call_llm(prompt)

        # Clean markdown just in case
        code = code.replace("```python", "").replace("```", "").strip()

        print("===== GENERATED CODE =====\n", code)

        try:
            print("\nExecuting code...\n")
            exec(code, globals())

            print("\n Bronze loading completed!")
            return {
                "status": "success",
                "generated_code": code,
                "attempts": attempt + 1
            }

        except Exception as e:
            last_error = str(e)

            print(f"\n Execution failed (Attempt {attempt + 1})")
            print("Error:", last_error)

            attempt += 1

    print("\n All attempts failed!")

    return {
        "status": "failed",
        "final_code": code,
        "error": last_error,
        "attempts": max_retries
    }

cell 2:


result = bronze_loader_agent(
    volume_path="/Volumes/retail_data/bronze/raw_data_volume/",
    catalog="retail_data",
    schema="bronze"
)

print(result)

However, I receive error message:

BadRequestError: Error code: 400
{
    'error': {
        'code': 'BadRequest',
        'message': 'API version not supported'
    }
}

how to resolve this issue ? I keep getting an error message

Azure Databricks
Azure Databricks

An Apache Spark-based analytics platform optimized for Azure.


Your answer

Answers can be marked as 'Accepted' by the question author and 'Recommended' by moderators, which helps users know the answer solved the author's problem.