Implement VAPI and ERNIE 4.0 Integration

Write the Python code to integrate VAPI for voice input/output and ERNIE 4.0 as the primary generative model within your LangChain agent. This should include setting up VAPI for streaming audio and creating a custom LangChain LLM wrapper for ERNIE 4.0, or utilizing a pre-existing integration if available. Show how the transcribed text from VAPI is passed to the LangChain agent and how the agent's text response is converted back to speech. Include error handling for API calls.

```python
from langchain.agents import AgentExecutor, create_react_agent
from langchain_core.messages import HumanMessage, AIMessage
from langchain_core.prompts import PromptTemplate
from langchain_core.tools import Tool
# Assuming VAPI and ERNIE 4.0 wrappers/SDKs are installed
# from vapi_sdk import VapiClient
# from ernie_llm import ErnieLLM

# ... (define custom tools like MusicSearchTool, PlaylistBuilderTool)

# llm = ErnieLLM(api_key="YOUR_ERNIE_API_KEY")
# tools = [MusicSearchTool(), PlaylistBuilderTool()]
# prompt = PromptTemplate(...)
# agent = create_react_agent(llm, tools, prompt)
# agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True, memory=ConversationBufferMemory())

# def handle_voice_input(audio_data):
#    # Use VAPI to transcribe audio
#    transcribed_text = vapi_client.transcribe(audio_data)
#    response_text = agent_executor.invoke({"input": transcribed_text})["output"]
#    # Use VAPI to synthesize speech
#    vapi_client.synthesize_speech(response_text)
#    return response_text
```