LLM Provider

def list_models() -> list[str]

from llm_provider import list_models

try:
    models = list_models()
    print("Available models:")
    for model in models:
        print(f"  - {model}")
except Exception as e:
    print(f"Could not connect to Ollama: {e}")

# From main.py startup sequence
models = list_models()
if not models:
    error("No models found on Ollama. Pull a model first (e.g. 'ollama pull llama3.2:3b').")
    sys.exit(1)

for idx, model_name in enumerate(models):
    print(colored(f" {idx + 1}. {model_name}", "cyan"))

def select_model(model: str) -> None

from llm_provider import select_model, list_models

# List and select a model
models = list_models()
if models:
    select_model(models[0])  # Select first available model
    print(f"Using model: {models[0]}")

# Select model from config or prompt user
configured_model = get_ollama_model()
if configured_model:
    select_model(configured_model)
    success(f"Using configured model: {configured_model}")
else:
    # Interactive selection
    models = list_models()
    model_choice = models[choice_idx]
    select_model(model_choice)
    success(f"Using model: {model_choice}")

def get_active_model() -> str | None

from llm_provider import get_active_model, select_model

active = get_active_model()
if active is None:
    print("No model selected yet")
    select_model("llama3.2:3b")
else:
    print(f"Active model: {active}")

# Pass active model to CRON jobs
cron_script_path = os.path.join(ROOT_DIR, "src", "cron.py")
command = ["python", cron_script_path, "youtube", selected_account['id'], get_active_model()]

def generate_text(prompt: str, model_name: str = None) -> str

from llm_provider import select_model, generate_text

# Select a model first
select_model("llama3.2:3b")

# Generate text using selected model
response = generate_text("Write a short description for a tech review video")
print(response)

# Override model for specific call
response = generate_text(
    "Write a tweet about AI",
    model_name="mistral:latest"
)
print(response)

# Example: Generating YouTube video script
from llm_provider import generate_text

prompt = f"Create a {niche} video script about {topic}"
script = generate_text(prompt)

# Example: Generating Twitter post
prompt = f"Write a tweet about {topic} in {language}"
tweet = generate_text(prompt)

from config import get_ollama_base_url
import ollama

# Internal client creation
client = ollama.Client(host=get_ollama_base_url())

from llm_provider import list_models, select_model, get_active_model, generate_text
from config import get_ollama_model

# 1. Check if model is configured
configured_model = get_ollama_model()

if configured_model:
    # Use configured model
    select_model(configured_model)
    print(f"Using configured model: {configured_model}")
else:
    # List available models
    models = list_models()
    
    if not models:
        print("Error: No models available. Run 'ollama pull llama3.2:3b' first.")
        exit(1)
    
    # Select first available model
    select_model(models[0])
    print(f"Using model: {models[0]}")

# 2. Verify active model
active = get_active_model()
print(f"Active model: {active}")

# 3. Generate text
try:
    response = generate_text("Write a 3-sentence video description about space exploration")
    print(f"Generated: {response}")
except RuntimeError as e:
    print(f"Error: {e}")

# 4. Generate with different model
response = generate_text(
    "Write a tweet about Python programming",
    model_name="mistral:latest"
)
print(f"Tweet: {response}")

try:
    models = list_models()
except Exception as e:
    print(f"Could not connect to Ollama: {e}")
    print("Make sure Ollama is running: 'ollama serve'")

try:
    response = generate_text("Hello")
except RuntimeError as e:
    print(e)  # "No Ollama model selected. Call select_model() first or pass model_name."