feat: add multi-provider authentication and inference provider selection
- Implemented a multi-provider authentication system for the Hermes Agent, supporting OAuth for Nous Portal and traditional API key methods for OpenRouter and custom endpoints. - Enhanced CLI with commands for logging in and out of providers, allowing users to authenticate and manage their credentials easily. - Updated configuration options to select inference providers, with detailed documentation on usage and setup. - Improved status reporting to include authentication status and provider details, enhancing user awareness of their current configuration. - Added new files for authentication handling and updated existing components to integrate the new provider system.
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teknium1
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9 changed files with 1639 additions and 113 deletions
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@ -437,127 +437,233 @@ def run_setup_wizard(args):
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print_info("You can edit these files directly or use 'hermes config edit'")
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# =========================================================================
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# Step 1: OpenRouter API Key (Required for tools)
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# Step 1: Inference Provider Selection
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# =========================================================================
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print_header("OpenRouter API Key (Required)")
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print_info("OpenRouter is used for vision, web scraping, and tool operations")
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print_info("even if you use a custom endpoint for your main agent.")
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print_info("Get your API key at: https://openrouter.ai/keys")
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print_header("Inference Provider")
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print_info("Choose how to connect to your main chat model.")
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print()
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# Detect current provider state
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from hermes_cli.auth import (
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get_active_provider, get_provider_auth_state, PROVIDER_REGISTRY,
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format_auth_error, AuthError, fetch_nous_models,
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resolve_nous_runtime_credentials, _update_config_for_provider,
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)
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existing_custom = get_env_value("OPENAI_BASE_URL")
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existing_or = get_env_value("OPENROUTER_API_KEY")
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if existing_or:
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print_info(f"Current: {existing_or[:8]}... (configured)")
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if prompt_yes_no("Update OpenRouter API key?", False):
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active_oauth = get_active_provider()
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# Build "keep current" label
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if active_oauth and active_oauth in PROVIDER_REGISTRY:
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keep_label = f"Keep current ({PROVIDER_REGISTRY[active_oauth].name})"
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elif existing_custom:
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keep_label = f"Keep current (Custom: {existing_custom})"
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elif existing_or:
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keep_label = "Keep current (OpenRouter)"
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else:
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keep_label = "Keep current"
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provider_choices = [
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"Login with Nous Portal (Nous Research subscription)",
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"OpenRouter API key (100+ models, pay-per-use)",
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"Custom OpenAI-compatible endpoint (self-hosted / VLLM / etc.)",
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keep_label,
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]
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provider_idx = prompt_choice("Select your inference provider:", provider_choices, 3)
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# Track which provider was selected for model step
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selected_provider = None # "nous", "openrouter", "custom", or None (keep)
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nous_models = [] # populated if Nous login succeeds
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if provider_idx == 0: # Nous Portal
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selected_provider = "nous"
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print()
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print_header("Nous Portal Login")
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print_info("This will open your browser to authenticate with Nous Portal.")
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print_info("You'll need a Nous Research account with an active subscription.")
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print()
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try:
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from hermes_cli.auth import _login_nous, ProviderConfig
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import argparse
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mock_args = argparse.Namespace(
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portal_url=None, inference_url=None, client_id=None,
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scope=None, no_browser=False, timeout=15.0,
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ca_bundle=None, insecure=False,
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)
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pconfig = PROVIDER_REGISTRY["nous"]
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_login_nous(mock_args, pconfig)
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# Fetch models for the selection step
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try:
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creds = resolve_nous_runtime_credentials(
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min_key_ttl_seconds=5 * 60, timeout_seconds=15.0,
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)
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nous_models = fetch_nous_models(
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inference_base_url=creds.get("base_url", ""),
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api_key=creds.get("api_key", ""),
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)
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except Exception:
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pass
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except SystemExit:
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print_warning("Nous Portal login was cancelled or failed.")
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print_info("You can try again later with: hermes login")
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selected_provider = None
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except Exception as e:
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print_error(f"Login failed: {e}")
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print_info("You can try again later with: hermes login")
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selected_provider = None
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elif provider_idx == 1: # OpenRouter
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selected_provider = "openrouter"
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print()
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print_header("OpenRouter API Key")
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print_info("OpenRouter provides access to 100+ models from multiple providers.")
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print_info("Get your API key at: https://openrouter.ai/keys")
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if existing_or:
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print_info(f"Current: {existing_or[:8]}... (configured)")
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if prompt_yes_no("Update OpenRouter API key?", False):
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api_key = prompt(" OpenRouter API key", password=True)
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if api_key:
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save_env_value("OPENROUTER_API_KEY", api_key)
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print_success("OpenRouter API key updated")
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else:
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api_key = prompt(" OpenRouter API key", password=True)
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if api_key:
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save_env_value("OPENROUTER_API_KEY", api_key)
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print_success("OpenRouter API key updated")
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else:
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api_key = prompt(" OpenRouter API key", password=True)
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if api_key:
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save_env_value("OPENROUTER_API_KEY", api_key)
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print_success("OpenRouter API key saved")
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else:
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print_warning("Skipped - some tools (vision, web scraping) won't work without this")
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# =========================================================================
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# Step 2: Main Agent Provider
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# =========================================================================
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print_header("Main Agent Provider")
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print_info("Choose how to connect to your main chat model.")
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existing_custom = get_env_value("OPENAI_BASE_URL")
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provider_choices = [
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"OpenRouter (use same key for agent - recommended)",
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"Custom OpenAI-compatible endpoint (separate from OpenRouter)",
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f"Keep current" + (f" ({existing_custom})" if existing_custom else " (OpenRouter)")
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]
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provider_idx = prompt_choice("Select your main agent provider:", provider_choices, 2)
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if provider_idx == 0: # OpenRouter for agent too
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# Clear any custom endpoint - will use OpenRouter
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print_success("OpenRouter API key saved")
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else:
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print_warning("Skipped - agent won't work without an API key")
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# Clear any custom endpoint if switching to OpenRouter
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if existing_custom:
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save_env_value("OPENAI_BASE_URL", "")
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save_env_value("OPENAI_API_KEY", "")
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print_success("Agent will use OpenRouter")
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elif provider_idx == 1: # Custom endpoint
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print_info("Custom OpenAI-Compatible Endpoint Configuration:")
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elif provider_idx == 2: # Custom endpoint
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selected_provider = "custom"
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print()
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print_header("Custom OpenAI-Compatible Endpoint")
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print_info("Works with any API that follows OpenAI's chat completions spec")
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# Show current values if set
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current_url = get_env_value("OPENAI_BASE_URL") or ""
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current_key = get_env_value("OPENAI_API_KEY")
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current_model = config.get('model', '')
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if current_url:
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print_info(f" Current URL: {current_url}")
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if current_key:
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print_info(f" Current key: {current_key[:8]}... (configured)")
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base_url = prompt(" API base URL (e.g., https://api.example.com/v1)", current_url)
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api_key = prompt(" API key", password=True)
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model_name = prompt(" Model name (e.g., gpt-4, claude-3-opus)", current_model)
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if base_url:
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save_env_value("OPENAI_BASE_URL", base_url)
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if api_key:
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save_env_value("OPENAI_API_KEY", api_key)
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if model_name:
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config['model'] = model_name
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save_env_value("LLM_MODEL", model_name)
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print_success("Custom endpoint configured")
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# else: Keep current (provider_idx == 2)
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# else: provider_idx == 3, keep current
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# =========================================================================
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# Step 3: Model Selection
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# Step 1b: OpenRouter API Key for tools (if not already set)
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# =========================================================================
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print_header("Default Model")
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current_model = config.get('model', 'anthropic/claude-opus-4.6')
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print_info(f"Current: {current_model}")
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model_choices = [
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"anthropic/claude-opus-4.6 (recommended)",
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"anthropic/claude-sonnet-4.5",
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"anthropic/claude-opus-4.5",
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"openai/gpt-5.2",
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"openai/gpt-5.2-codex",
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"google/gemini-3-pro-preview",
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"google/gemini-3-flash-preview",
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"z-ai/glm-4.7",
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"moonshotai/kimi-k2.5",
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"minimax/minimax-m2.1",
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"Custom model",
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f"Keep current ({current_model})"
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]
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model_idx = prompt_choice("Select default model:", model_choices, 11) # Default: keep current
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model_map = {
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0: "anthropic/claude-opus-4.6",
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1: "anthropic/claude-sonnet-4.5",
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2: "anthropic/claude-opus-4.5",
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3: "openai/gpt-5.2",
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4: "openai/gpt-5.2-codex",
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5: "google/gemini-3-pro-preview",
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6: "google/gemini-3-flash-preview",
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7: "z-ai/glm-4.7",
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8: "moonshotai/kimi-k2.5",
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9: "minimax/minimax-m2.1",
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}
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if model_idx in model_map:
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config['model'] = model_map[model_idx]
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# Also update LLM_MODEL in .env so it stays in sync (cli.py reads .env first)
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save_env_value("LLM_MODEL", model_map[model_idx])
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elif model_idx == 10: # Custom
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custom = prompt("Enter model name (e.g., anthropic/claude-opus-4.6)")
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if custom:
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config['model'] = custom
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save_env_value("LLM_MODEL", custom)
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# else: Keep current (model_idx == 11)
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# Tools (vision, web, MoA) use OpenRouter independently of the main provider.
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# Prompt for OpenRouter key if not set and a non-OpenRouter provider was chosen.
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if selected_provider in ("nous", "custom") and not get_env_value("OPENROUTER_API_KEY"):
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print()
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print_header("OpenRouter API Key (for tools)")
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print_info("Tools like vision analysis, web search, and MoA use OpenRouter")
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print_info("independently of your main inference provider.")
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print_info("Get your API key at: https://openrouter.ai/keys")
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api_key = prompt(" OpenRouter API key (optional, press Enter to skip)", password=True)
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if api_key:
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save_env_value("OPENROUTER_API_KEY", api_key)
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print_success("OpenRouter API key saved (for tools)")
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else:
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print_info("Skipped - some tools (vision, web scraping) won't work without this")
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# =========================================================================
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# Step 2: Model Selection (adapts based on provider)
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# =========================================================================
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if selected_provider != "custom": # Custom already prompted for model name
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print_header("Default Model")
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current_model = config.get('model', 'anthropic/claude-opus-4.6')
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print_info(f"Current: {current_model}")
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if selected_provider == "nous" and nous_models:
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# Dynamic model list from Nous Portal
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model_choices = [f"{m}" for m in nous_models]
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model_choices.append("Custom model")
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model_choices.append(f"Keep current ({current_model})")
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# Post-login validation: warn if current model might not be available
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if current_model and current_model not in nous_models:
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print_warning(f"Your current model ({current_model}) may not be available via Nous Portal.")
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print_info("Select a model from the list, or keep current to use it anyway.")
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print()
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model_idx = prompt_choice("Select default model:", model_choices, len(model_choices) - 1)
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if model_idx < len(nous_models):
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config['model'] = nous_models[model_idx]
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save_env_value("LLM_MODEL", nous_models[model_idx])
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elif model_idx == len(nous_models): # Custom
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custom = prompt("Enter model name")
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if custom:
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config['model'] = custom
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save_env_value("LLM_MODEL", custom)
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# else: keep current
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else:
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# Static list for OpenRouter / fallback
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model_choices = [
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"anthropic/claude-opus-4.6 (recommended)",
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"anthropic/claude-sonnet-4.5",
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"anthropic/claude-opus-4.5",
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"openai/gpt-5.2",
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"openai/gpt-5.2-codex",
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"google/gemini-3-pro-preview",
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"google/gemini-3-flash-preview",
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"z-ai/glm-4.7",
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"moonshotai/kimi-k2.5",
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"minimax/minimax-m2.1",
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"Custom model",
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f"Keep current ({current_model})"
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]
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model_idx = prompt_choice("Select default model:", model_choices, 11)
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model_map = {
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0: "anthropic/claude-opus-4.6",
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1: "anthropic/claude-sonnet-4.5",
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2: "anthropic/claude-opus-4.5",
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3: "openai/gpt-5.2",
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4: "openai/gpt-5.2-codex",
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5: "google/gemini-3-pro-preview",
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6: "google/gemini-3-flash-preview",
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7: "z-ai/glm-4.7",
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8: "moonshotai/kimi-k2.5",
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9: "minimax/minimax-m2.1",
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}
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if model_idx in model_map:
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config['model'] = model_map[model_idx]
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save_env_value("LLM_MODEL", model_map[model_idx])
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elif model_idx == 10: # Custom
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custom = prompt("Enter model name (e.g., anthropic/claude-opus-4.6)")
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if custom:
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config['model'] = custom
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save_env_value("LLM_MODEL", custom)
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# else: Keep current (model_idx == 11)
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# =========================================================================
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# Step 4: Terminal Backend
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