code: def ecd_config_dict_llm_encoder_multiple_features() -> Dict[str, Any]:
      return {
          MODEL_TYPE: MODEL_ECD,
          INPUT_FEATURES: [
              {TYPE: BINARY, NAME: "in1"},
              {
                  TYPE: TEXT,
                  NAME: "in2",
                  ENCODER: {
                      TYPE: MODEL_LLM,
                      BASE_MODEL: "HuggingFaceH4/tiny-random-LlamaForCausalLM",
                  },
              },
          ],
          OUTPUT_FEATURES: [{TYPE: BINARY, NAME: "out1"}],
      }
  
imports: from typing import Any, Dict, Optional
  import pytest
  from ludwig.constants import BASE_MODEL, BINARY, ENCODER, INPUT_FEATURES, MODEL_ECD, MODEL_GBM, MODEL_LLM, MODEL_TYPE, NAME, OUTPUT_FEATURES, TEXT, TYPE
  from ludwig.schema.encoders.text_encoders import BERTConfig
  from ludwig.schema.encoders.utils import get_encoder_cls
  from ludwig.schema.features.preprocessing.text import TextPreprocessingConfig
  from ludwig.schema.model_config import ModelConfig
  from ludwig.utils.config_utils import config_uses_llm
label_desc: Use image node_id 7 for calling a global function with example usage: ecd_config_dict_llm_encoder_multiple_features() and returns: dict