Errors: text too long for vectorization. Tokens for text: 10440, max tokens per batch: 8192, ApiKey absolute token limit: 1000000'

Description

Hi there I am trying to generate some vector embeddings via Mistral AI but I am having few issues first of all I was getting 429 issue on object insertion i fixed it by limiting the number of request per seconds now I am getting this :

errors: text too long for vectorization. Tokens for text: 10440, max tokens per batch: 8192, ApiKey absolute token limit: 1000000’

client.collections.create(
    "Embeddings",
    vectorizer_config=[
        Configure.NamedVectors.text2vec_mistral(
            name="filecontent",
            source_properties=["filecontent"],
            model="mistral-embed"
        )
    ],
    # Additional parameters not shown
)

for row in rows:
      original_name = row.OriginalName
      full_text = row.FullText
    
    # Create object directly
      data_row = {
        "filename": original_name,
        "filecontent": full_text
      }
      print(f"Passing file : {original_name}")
      collection = client.collections.get("Embeddings")
      with collection.batch.rate_limit(requests_per_minute=30) as batch:
          obj_uuid = generate_uuid5(data_row)
          batch.add_object(
            properties=data_row  )
      
      if len(collection.batch.failed_objects) > 0:
          print(collection.batch.failed_objects)
      time.sleep(30)
    cursor.close()
    connection.close()

Any additional Information