mirror of https://github.com/aliasrobotics/cai.git
fix: consistent model numbering between /model and /model-show for Ol… (#371)
fix: consistent model numbering between /model and /model-show for Ollama When using OLLAMA_API_BASE, model selection by number was incorrect. /model-show displayed Ollama models with certain numbers, but /model <number> selected different models from LiteLLM instead. This happened because both commands used separate caches with inconsistent numbering. Now they share a global cache that loads models in consistent order: predefined → LiteLLM → Ollama. Fixes model number mismatch when selecting Ollama models by number.
This commit is contained in:
pzabalegui
GitHub
parent
e932e30850
commit
7c2267d2b9
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@ -22,6 +22,10 @@ LITELLM_URL = (
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"model_prices_and_context_window.json"
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)
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# Global cache shared between /model and /model-show commands
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_GLOBAL_MODEL_CACHE = []
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_GLOBAL_MODEL_NUMBERS = {}
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def get_predefined_model_categories() -> Dict[str, List[Dict[str, str]]]:
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"""Get the predefined model categories as the single source of truth.
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@ -155,6 +159,43 @@ def get_predefined_model_names() -> List[str]:
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return [model["name"] for model in get_all_predefined_models()]
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def load_all_available_models() -> tuple[List[str], List[Dict[str, Any]]]:
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"""Load all available models (predefined + LiteLLM + Ollama) in consistent order.
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This ensures /model and /model-show use the same numbering.
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Returns:
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Tuple of (all_model_names, ollama_models_data)
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"""
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# Predefined models
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predefined = [model["name"] for model in get_all_predefined_models()]
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# LiteLLM models
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litellm_names = []
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try:
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response = requests.get(LITELLM_URL, timeout=5)
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if response.status_code == 200:
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litellm_names = sorted(response.json().keys())
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except Exception: # pylint: disable=broad-except
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pass
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# Ollama models
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ollama_data = []
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ollama_names = []
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try:
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api_base = get_ollama_api_base()
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response = requests.get(f"{api_base.replace('/v1', '')}/api/tags", timeout=1)
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if response.status_code == 200:
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data = response.json()
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ollama_data = data.get('models', data.get('items', []))
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ollama_names = [m.get('name', '') for m in ollama_data if m.get('name')]
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except Exception: # pylint: disable=broad-except
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pass
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all_models = predefined + litellm_names + ollama_names
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return all_models, ollama_data
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class ModelCommand(Command):
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"""Command for viewing and changing the current LLM model."""
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@ -196,29 +237,21 @@ class ModelCommand(Command):
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Returns:
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bool: True if the model was changed successfully
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"""
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# Get all predefined models from the shared source of truth
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# pylint: disable=invalid-name
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ALL_MODELS = get_all_predefined_models()
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# Also fetch LiteLLM model names to make numbering consistent with /model-show
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litellm_model_names = []
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try:
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response = requests.get(LITELLM_URL, timeout=5)
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if response.status_code == 200:
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litellm_data = response.json()
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# Add LiteLLM model names (sorted for consistency with /model-show)
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litellm_model_names = sorted(litellm_data.keys())
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except Exception: # pylint: disable=broad-except
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# Silently fail if LiteLLM is not available
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pass
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# Update cached models to include all models for number selection (consistent with /model-show)
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predefined_model_names = [model["name"] for model in ALL_MODELS]
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self.cached_models = predefined_model_names + litellm_model_names
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self.cached_model_numbers = {
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# Load all models with consistent numbering and update global cache
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global _GLOBAL_MODEL_CACHE, _GLOBAL_MODEL_NUMBERS
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_GLOBAL_MODEL_CACHE, ollama_models_data = load_all_available_models()
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_GLOBAL_MODEL_NUMBERS = {
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str(i): model_name
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for i, model_name in enumerate(self.cached_models, 1)
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for i, model_name in enumerate(_GLOBAL_MODEL_CACHE, 1)
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}
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self.cached_models = _GLOBAL_MODEL_CACHE
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self.cached_model_numbers = _GLOBAL_MODEL_NUMBERS
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# Get predefined and litellm counts for display
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ALL_MODELS = get_all_predefined_models()
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predefined_model_names = [model["name"] for model in ALL_MODELS]
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litellm_model_names = [m for m in self.cached_models[len(predefined_model_names):]
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if m not in [d.get('name') for d in ollama_models_data]]
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if not args: # pylint: disable=too-many-nested-blocks
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# Display current model
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@ -272,61 +305,35 @@ class ModelCommand(Command):
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model["description"]
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)
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# Ollama models (if available)
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# pylint: disable=too-many-nested-blocks
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try:
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# Get Ollama models with a short timeout to prevent hanging
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api_base = get_ollama_api_base()
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ollama_base = api_base.replace('/v1', '')
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response = requests.get(
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f"{ollama_base}/api/tags",
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timeout=1
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)
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if response.status_code == 200:
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data = response.json()
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ollama_models = []
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if 'models' in data:
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ollama_models = data['models']
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else:
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# Fallback for older Ollama versions
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ollama_models = data.get('items', [])
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# Add Ollama models to the table with continuing numbers
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# (after predefined models + LiteLLM models in numbering)
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start_index = len(predefined_model_names) + len(litellm_model_names) + 1
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for i, model in enumerate(ollama_models, start_index):
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model_name = model.get('name', '')
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model_size = model.get('size', 0)
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# Convert size to human-readable format
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size_str = ""
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if model_size:
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size_mb = model_size / (1024 * 1024)
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if model_size < 1024 * 1024 * 1024:
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size_str = f"{size_mb:.1f} MB"
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else:
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size_gb = size_mb / 1024
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size_str = f"{size_gb:.1f} GB"
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# Ollama models are free to use locally
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model_description = "Local model"
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if size_str:
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model_description += f" ({size_str})"
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model_table.add_row(
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str(i),
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model_name,
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"Ollama",
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"Local",
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"Free",
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"Free",
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model_description
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)
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# Add to cached models for numeric selection
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self.cached_models.append(model_name)
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self.cached_model_numbers[str(i)] = model_name
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except Exception: # pylint: disable=broad-except
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# Ollama models (display from already loaded data)
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if ollama_models_data:
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start_index = len(predefined_model_names) + len(litellm_model_names) + 1
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for i, model in enumerate(ollama_models_data, start_index):
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model_name = model.get('name', '')
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model_size = model.get('size', 0)
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size_str = ""
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if model_size:
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size_mb = model_size / (1024 * 1024)
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if model_size < 1024 * 1024 * 1024:
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size_str = f"{size_mb:.1f} MB"
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else:
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size_gb = size_mb / 1024
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size_str = f"{size_gb:.1f} GB"
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model_description = "Local model"
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if size_str:
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model_description += f" ({size_str})"
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model_table.add_row(
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str(i),
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model_name,
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"Ollama",
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"Local",
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"Free",
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"Free",
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model_description
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)
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else: # pylint: disable=broad-except
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# Add a note about Ollama if we couldn't fetch models
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start_index = len(predefined_model_names) + len(litellm_model_names) + 1
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model_table.add_row(
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@ -436,6 +443,15 @@ class ModelShowCommand(Command):
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if args: # If there are still args left, use as search term
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search_term = args[0].lower()
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# Load all models and update global cache for consistent numbering with /model
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global _GLOBAL_MODEL_CACHE, _GLOBAL_MODEL_NUMBERS
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all_model_names, ollama_models_data = load_all_available_models()
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_GLOBAL_MODEL_CACHE = all_model_names
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_GLOBAL_MODEL_NUMBERS = {
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str(i): model_name
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for i, model_name in enumerate(_GLOBAL_MODEL_CACHE, 1)
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}
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# Fetch model pricing data from LiteLLM GitHub repository
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try:
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with console.status(
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@ -482,10 +498,14 @@ class ModelShowCommand(Command):
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# Count models for summary
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total_models = 0
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displayed_models = 0
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model_index = 1
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# Process and display models
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# Process and display models (use global cache for numbering)
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for model_name, model_info in sorted(model_data.items()):
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# Find the model index from global cache
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try:
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model_index = _GLOBAL_MODEL_CACHE.index(model_name) + 1
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except ValueError:
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continue # Model not in cache, skip
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total_models += 1
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# Skip if showing only supported models and no function calling
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@ -569,71 +589,46 @@ class ModelShowCommand(Command):
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features_str
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)
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model_index += 1
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# Now add Ollama models if available
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try:
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# Get Ollama models with a short timeout
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api_base = get_ollama_api_base()
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api_tags = f"{api_base.replace('/v1', '')}/api/tags"
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ollama_response = requests.get(api_tags, timeout=1)
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if ollama_response.status_code == 200:
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ollama_data = ollama_response.json()
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ollama_models = []
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if 'models' in ollama_data:
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ollama_models = ollama_data['models']
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# Add Ollama models to the table (already loaded in global cache)
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for model in ollama_models_data:
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model_name = model.get('name', '')
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# Skip if search term provided and not in model name
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if search_term and search_term not in model_name.lower():
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continue
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# Find index from global cache
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try:
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model_index = _GLOBAL_MODEL_CACHE.index(model_name) + 1
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except ValueError:
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continue
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total_models += 1
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displayed_models += 1
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model_size = model.get('size', 0)
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size_str = ""
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if model_size:
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size_mb = model_size / (1024 * 1024)
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if model_size < 1024 * 1024 * 1024:
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size_str = f"{size_mb:.1f} MB"
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else:
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# Fallback for older Ollama versions
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ollama_models = ollama_data.get('items', [])
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# Add Ollama models to the table
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for model in ollama_models:
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model_name = model.get('name', '')
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# Skip if search term provided and not in model name
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if (search_term and
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search_term not in model_name.lower()):
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continue
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total_models += 1
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displayed_models += 1
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model_size = model.get('size', 0)
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# Convert size to human-readable format
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size_str = ""
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if model_size:
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size_mb = model_size / (1024 * 1024)
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if model_size < 1024 * 1024 * 1024:
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size_str = f"{size_mb:.1f} MB"
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else:
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size_gb = size_mb / 1024
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size_str = f"{size_gb:.1f} GB"
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# Add row to table
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model_description = "Local model"
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if size_str:
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model_description += f" ({size_str})"
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model_table.add_row(
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str(model_index),
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model_name,
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"Ollama",
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"Varies",
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"Free",
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"Free",
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model_description
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)
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model_index += 1
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except Exception: # pylint: disable=broad-except
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# Silently fail if Ollama is not available
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# This is acceptable as Ollama is optional and we don't want to
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# disrupt the user experience if it's not running
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console.print(
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"[dim]Ollama models not available[/dim]",
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style="dim")
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size_gb = size_mb / 1024
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size_str = f"{size_gb:.1f} GB"
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model_description = "Local model"
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if size_str:
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model_description += f" ({size_str})"
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model_table.add_row(
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str(model_index),
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model_name,
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"Ollama",
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"Varies",
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"Free",
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"Free",
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model_description
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)
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# Display the table
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console.print(model_table)
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