feat: add z.ai/GLM, Kimi/Moonshot, MiniMax as first-class providers
Adds 4 new direct API-key providers (zai, kimi-coding, minimax, minimax-cn) to the inference provider system. All use standard OpenAI-compatible chat/completions endpoints with Bearer token auth. Core changes: - auth.py: Extended ProviderConfig with api_key_env_vars and base_url_env_var fields. Added providers to PROVIDER_REGISTRY. Added provider aliases (glm, z-ai, zhipu, kimi, moonshot). Added auto-detection of API-key providers in resolve_provider(). Added resolve_api_key_provider_credentials() and get_api_key_provider_status() helpers. - runtime_provider.py: Added generic API-key provider branch in resolve_runtime_provider() — any provider with auth_type='api_key' is automatically handled. - main.py: Added providers to hermes model menu with generic _model_flow_api_key_provider() flow. Updated _has_any_provider_configured() to check all provider env vars. Updated argparse --provider choices. - setup.py: Added providers to setup wizard with API key prompts and curated model lists. - config.py: Added env vars (GLM_API_KEY, KIMI_API_KEY, MINIMAX_API_KEY, etc.) to OPTIONAL_ENV_VARS. - status.py: Added API key display and provider status section. - doctor.py: Added connectivity checks for each provider endpoint. - cli.py: Updated provider docstrings. Docs: Updated README.md, .env.example, cli-config.yaml.example, cli-commands.md, environment-variables.md, configuration.md. Tests: 50 new tests covering registry, aliases, resolution, auto-detection, credential resolution, and runtime provider dispatch. Inspired by PR #33 (numman-ali) which proposed a provider registry approach. Credit to tars90percent (PR #473) and manuelschipper (PR #420) for related provider improvements merged earlier in this changeset.
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teknium1
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15 changed files with 1032 additions and 15 deletions
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@ -729,6 +729,10 @@ def run_setup_wizard(args):
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"Login with OpenAI Codex",
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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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"Z.AI / GLM (Zhipu AI models)",
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"Kimi / Moonshot (Kimi coding models)",
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"MiniMax (global endpoint)",
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"MiniMax China (mainland China endpoint)",
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]
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if keep_label:
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provider_choices.append(keep_label)
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@ -864,14 +868,143 @@ def run_setup_wizard(args):
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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: provider_idx == 4 (Keep current) — only shown when a provider already exists
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elif provider_idx == 4: # Z.AI / GLM
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selected_provider = "zai"
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print()
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print_header("Z.AI / GLM API Key")
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pconfig = PROVIDER_REGISTRY["zai"]
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print_info(f"Provider: {pconfig.name}")
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print_info(f"Base URL: {pconfig.inference_base_url}")
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print_info("Get your API key at: https://open.bigmodel.cn/")
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print()
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existing_key = get_env_value("GLM_API_KEY") or get_env_value("ZAI_API_KEY")
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if existing_key:
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print_info(f"Current: {existing_key[:8]}... (configured)")
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if prompt_yes_no("Update API key?", False):
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api_key = prompt(" GLM API key", password=True)
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if api_key:
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save_env_value("GLM_API_KEY", api_key)
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print_success("GLM API key updated")
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else:
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api_key = prompt(" GLM API key", password=True)
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if api_key:
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save_env_value("GLM_API_KEY", api_key)
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print_success("GLM 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 custom endpoint vars if switching
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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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_update_config_for_provider("zai", pconfig.inference_base_url)
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elif provider_idx == 5: # Kimi / Moonshot
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selected_provider = "kimi-coding"
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print()
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print_header("Kimi / Moonshot API Key")
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pconfig = PROVIDER_REGISTRY["kimi-coding"]
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print_info(f"Provider: {pconfig.name}")
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print_info(f"Base URL: {pconfig.inference_base_url}")
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print_info("Get your API key at: https://platform.moonshot.cn/")
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print()
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existing_key = get_env_value("KIMI_API_KEY")
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if existing_key:
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print_info(f"Current: {existing_key[:8]}... (configured)")
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if prompt_yes_no("Update API key?", False):
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api_key = prompt(" Kimi API key", password=True)
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if api_key:
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save_env_value("KIMI_API_KEY", api_key)
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print_success("Kimi API key updated")
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else:
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api_key = prompt(" Kimi API key", password=True)
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if api_key:
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save_env_value("KIMI_API_KEY", api_key)
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print_success("Kimi 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 custom endpoint vars if switching
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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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_update_config_for_provider("kimi-coding", pconfig.inference_base_url)
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elif provider_idx == 6: # MiniMax
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selected_provider = "minimax"
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print()
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print_header("MiniMax API Key")
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pconfig = PROVIDER_REGISTRY["minimax"]
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print_info(f"Provider: {pconfig.name}")
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print_info(f"Base URL: {pconfig.inference_base_url}")
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print_info("Get your API key at: https://platform.minimaxi.com/")
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print()
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existing_key = get_env_value("MINIMAX_API_KEY")
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if existing_key:
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print_info(f"Current: {existing_key[:8]}... (configured)")
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if prompt_yes_no("Update API key?", False):
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api_key = prompt(" MiniMax API key", password=True)
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if api_key:
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save_env_value("MINIMAX_API_KEY", api_key)
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print_success("MiniMax API key updated")
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else:
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api_key = prompt(" MiniMax API key", password=True)
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if api_key:
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save_env_value("MINIMAX_API_KEY", api_key)
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print_success("MiniMax 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 custom endpoint vars if switching
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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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_update_config_for_provider("minimax", pconfig.inference_base_url)
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elif provider_idx == 7: # MiniMax China
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selected_provider = "minimax-cn"
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print()
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print_header("MiniMax China API Key")
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pconfig = PROVIDER_REGISTRY["minimax-cn"]
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print_info(f"Provider: {pconfig.name}")
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print_info(f"Base URL: {pconfig.inference_base_url}")
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print_info("Get your API key at: https://platform.minimaxi.com/")
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print()
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existing_key = get_env_value("MINIMAX_CN_API_KEY")
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if existing_key:
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print_info(f"Current: {existing_key[:8]}... (configured)")
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if prompt_yes_no("Update API key?", False):
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api_key = prompt(" MiniMax CN API key", password=True)
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if api_key:
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save_env_value("MINIMAX_CN_API_KEY", api_key)
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print_success("MiniMax CN API key updated")
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else:
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api_key = prompt(" MiniMax CN API key", password=True)
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if api_key:
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save_env_value("MINIMAX_CN_API_KEY", api_key)
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print_success("MiniMax CN 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 custom endpoint vars if switching
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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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_update_config_for_provider("minimax-cn", pconfig.inference_base_url)
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# else: provider_idx == 8 (Keep current) — only shown when a provider already exists
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# =========================================================================
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# Step 1b: OpenRouter API Key for tools (if not already set)
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# =========================================================================
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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", "openai-codex", "custom") and not get_env_value("OPENROUTER_API_KEY"):
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if selected_provider in ("nous", "openai-codex", "custom", "zai", "kimi-coding", "minimax", "minimax-cn") 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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@ -944,6 +1077,60 @@ def run_setup_wizard(args):
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config['model'] = custom
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save_env_value("LLM_MODEL", custom)
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_update_config_for_provider("openai-codex", DEFAULT_CODEX_BASE_URL)
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elif selected_provider == "zai":
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zai_models = ["glm-5", "glm-4.7", "glm-4.5", "glm-4.5-flash"]
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model_choices = list(zai_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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keep_idx = len(model_choices) - 1
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model_idx = prompt_choice("Select default model:", model_choices, keep_idx)
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if model_idx < len(zai_models):
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config['model'] = zai_models[model_idx]
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save_env_value("LLM_MODEL", zai_models[model_idx])
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elif model_idx == len(zai_models):
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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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elif selected_provider == "kimi-coding":
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kimi_models = ["kimi-k2.5", "kimi-k2-thinking", "kimi-k2-turbo-preview"]
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model_choices = list(kimi_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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keep_idx = len(model_choices) - 1
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model_idx = prompt_choice("Select default model:", model_choices, keep_idx)
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if model_idx < len(kimi_models):
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config['model'] = kimi_models[model_idx]
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save_env_value("LLM_MODEL", kimi_models[model_idx])
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elif model_idx == len(kimi_models):
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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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elif selected_provider in ("minimax", "minimax-cn"):
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minimax_models = ["MiniMax-M2.5", "MiniMax-M2.5-highspeed", "MiniMax-M2.1"]
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model_choices = list(minimax_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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keep_idx = len(model_choices) - 1
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model_idx = prompt_choice("Select default model:", model_choices, keep_idx)
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if model_idx < len(minimax_models):
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config['model'] = minimax_models[model_idx]
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save_env_value("LLM_MODEL", minimax_models[model_idx])
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elif model_idx == len(minimax_models):
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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 (from canonical list)
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from hermes_cli.models import model_ids, menu_labels
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