Reduct PHI in audio and transcription

  pip install -e .

BASE_URL = "https://voiceharbor.ai"
admin_token = "your_admin_token_here"

# Create a developer token for usage with Voice Harbor
usage_token = VoiceHarborClient.create_developer_token(BASE_URL, admin_token)

# Received developer token stored below:
print(f"Developer token stored: ./credentials/VoiceHarbor_Developer.credential.<date>.yaml")

BASE_URL = "https://voiceharbor.ai"
usage_token = "your_usage_token_here"

# Create a new job on the server via the class method.
# Create a new job immediately.
job_id = VoiceHarborClient.create_job(BASE_URL, usage_token)
print(f"Job created with ID: {job_id}")

# Initialize the client with the new job_id and input directory.
client = VoiceHarborClient(
    base_url=BASE_URL,
    job_id=job_id,
    token=usage_token,  # Ensure correct token is used here
    inputs_dir="./inputs"
)

# Build job parameters (e.g., list of agents and any other details).
job_params = {
    "agents": ["health-generic"],  # Define agents for transcription or analysis
    "files": []  # The submit_files method will append uploaded file names.
}

# Upload input files.
job_params = client.submit_files(job_params)

# Immediately submit the job file (YAML)
job_file = client.submit_job(job_params)
print(f"Job file submitted: {job_file}")

# Wait for and download the processed results.
downloaded_results = client.download_results(output_dir="./results")
print("Downloaded results:", downloaded_results)