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https://github.com/NousResearch/hermes-agent.git
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Merge branch 'main' of github.com:NousResearch/hermes-agent into feat/ink-refactor
This commit is contained in:
Brooklyn Nicholson
commit
097702c8a7
55 changed files with 4904 additions and 51 deletions
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@ -1370,6 +1370,8 @@ def select_provider_and_model(args=None):
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_model_flow_anthropic(config, current_model)
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elif selected_provider == "kimi-coding":
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_model_flow_kimi(config, current_model)
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elif selected_provider == "bedrock":
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_model_flow_bedrock(config, current_model)
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elif selected_provider in ("gemini", "deepseek", "xai", "zai", "kimi-coding-cn", "minimax", "minimax-cn", "kilocode", "opencode-zen", "opencode-go", "ai-gateway", "alibaba", "huggingface", "xiaomi", "arcee"):
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_model_flow_api_key_provider(config, selected_provider, current_model)
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@ -2656,6 +2658,252 @@ def _model_flow_kimi(config, current_model=""):
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print("No change.")
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def _model_flow_bedrock_api_key(config, region, current_model=""):
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"""Bedrock API Key mode — uses the OpenAI-compatible bedrock-mantle endpoint.
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For developers who don't have an AWS account but received a Bedrock API Key
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from their AWS admin. Works like any OpenAI-compatible endpoint.
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"""
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from hermes_cli.auth import _prompt_model_selection, _save_model_choice, deactivate_provider
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from hermes_cli.config import load_config, save_config, get_env_value, save_env_value
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from hermes_cli.models import _PROVIDER_MODELS
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mantle_base_url = f"https://bedrock-mantle.{region}.api.aws/v1"
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# Prompt for API key
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existing_key = get_env_value("AWS_BEARER_TOKEN_BEDROCK") or ""
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if existing_key:
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print(f" Bedrock API Key: {existing_key[:12]}... ✓")
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else:
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print(f" Endpoint: {mantle_base_url}")
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print()
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try:
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import getpass
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api_key = getpass.getpass(" Bedrock API Key: ").strip()
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except (KeyboardInterrupt, EOFError):
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print()
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return
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if not api_key:
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print(" Cancelled.")
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return
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save_env_value("AWS_BEARER_TOKEN_BEDROCK", api_key)
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existing_key = api_key
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print(" ✓ API key saved.")
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print()
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# Model selection — use static list (mantle doesn't need boto3 for discovery)
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model_list = _PROVIDER_MODELS.get("bedrock", [])
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print(f" Showing {len(model_list)} curated models")
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if model_list:
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selected = _prompt_model_selection(model_list, current_model=current_model)
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else:
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try:
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selected = input(" Model ID: ").strip()
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except (KeyboardInterrupt, EOFError):
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selected = None
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if selected:
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_save_model_choice(selected)
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# Save as custom provider pointing to bedrock-mantle
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cfg = load_config()
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model = cfg.get("model")
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if not isinstance(model, dict):
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model = {"default": model} if model else {}
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cfg["model"] = model
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model["provider"] = "custom"
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model["base_url"] = mantle_base_url
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model.pop("api_mode", None) # chat_completions is the default
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# Also save region in bedrock config for reference
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bedrock_cfg = cfg.get("bedrock", {})
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if not isinstance(bedrock_cfg, dict):
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bedrock_cfg = {}
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bedrock_cfg["region"] = region
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cfg["bedrock"] = bedrock_cfg
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# Save the API key env var name so hermes knows where to find it
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save_env_value("OPENAI_API_KEY", existing_key)
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save_env_value("OPENAI_BASE_URL", mantle_base_url)
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save_config(cfg)
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deactivate_provider()
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print(f" Default model set to: {selected} (via Bedrock API Key, {region})")
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print(f" Endpoint: {mantle_base_url}")
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else:
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print(" No change.")
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def _model_flow_bedrock(config, current_model=""):
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"""AWS Bedrock provider: verify credentials, pick region, discover models.
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Uses the native Converse API via boto3 — not the OpenAI-compatible endpoint.
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Auth is handled by the AWS SDK default credential chain (env vars, profile,
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instance role), so no API key prompt is needed.
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"""
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from hermes_cli.auth import _prompt_model_selection, _save_model_choice, deactivate_provider
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from hermes_cli.config import load_config, save_config
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from hermes_cli.models import _PROVIDER_MODELS
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# 1. Check for AWS credentials
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try:
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from agent.bedrock_adapter import (
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has_aws_credentials,
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resolve_aws_auth_env_var,
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resolve_bedrock_region,
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discover_bedrock_models,
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)
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except ImportError:
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print(" ✗ boto3 is not installed. Install it with:")
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print(" pip install boto3")
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print()
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return
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if not has_aws_credentials():
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print(" ⚠ No AWS credentials detected via environment variables.")
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print(" Bedrock will use boto3's default credential chain (IMDS, SSO, etc.)")
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print()
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auth_var = resolve_aws_auth_env_var()
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if auth_var:
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print(f" AWS credentials: {auth_var} ✓")
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else:
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print(" AWS credentials: boto3 default chain (instance role / SSO)")
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print()
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# 2. Region selection
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current_region = resolve_bedrock_region()
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try:
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region_input = input(f" AWS Region [{current_region}]: ").strip()
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except (KeyboardInterrupt, EOFError):
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print()
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return
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region = region_input or current_region
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# 2b. Authentication mode
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print(" Choose authentication method:")
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print()
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print(" 1. IAM credential chain (recommended)")
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print(" Works with EC2 instance roles, SSO, env vars, aws configure")
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print(" 2. Bedrock API Key")
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print(" Enter your Bedrock API Key directly — also supports")
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print(" team scenarios where an admin distributes keys")
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print()
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try:
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auth_choice = input(" Choice [1]: ").strip()
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except (KeyboardInterrupt, EOFError):
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print()
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return
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if auth_choice == "2":
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_model_flow_bedrock_api_key(config, region, current_model)
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return
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# 3. Model discovery — try live API first, fall back to static list
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print(f" Discovering models in {region}...")
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live_models = discover_bedrock_models(region)
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if live_models:
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_EXCLUDE_PREFIXES = (
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"stability.", "cohere.embed", "twelvelabs.", "us.stability.",
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"us.cohere.embed", "us.twelvelabs.", "global.cohere.embed",
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"global.twelvelabs.",
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)
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_EXCLUDE_SUBSTRINGS = ("safeguard", "voxtral", "palmyra-vision")
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filtered = []
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for m in live_models:
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mid = m["id"]
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if any(mid.startswith(p) for p in _EXCLUDE_PREFIXES):
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continue
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if any(s in mid.lower() for s in _EXCLUDE_SUBSTRINGS):
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continue
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filtered.append(m)
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# Deduplicate: prefer inference profiles (us.*, global.*) over bare
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# foundation model IDs.
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profile_base_ids = set()
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for m in filtered:
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mid = m["id"]
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if mid.startswith(("us.", "global.")):
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base = mid.split(".", 1)[1] if "." in mid[3:] else mid
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profile_base_ids.add(base)
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deduped = []
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for m in filtered:
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mid = m["id"]
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if not mid.startswith(("us.", "global.")) and mid in profile_base_ids:
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continue
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deduped.append(m)
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_RECOMMENDED = [
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"us.anthropic.claude-sonnet-4-6",
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"us.anthropic.claude-opus-4-6",
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"us.anthropic.claude-haiku-4-5",
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"us.amazon.nova-pro",
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"us.amazon.nova-lite",
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"us.amazon.nova-micro",
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"deepseek.v3",
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"us.meta.llama4-maverick",
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"us.meta.llama4-scout",
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]
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def _sort_key(m):
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mid = m["id"]
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for i, rec in enumerate(_RECOMMENDED):
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if mid.startswith(rec):
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return (0, i, mid)
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if mid.startswith("global."):
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return (1, 0, mid)
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return (2, 0, mid)
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deduped.sort(key=_sort_key)
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model_list = [m["id"] for m in deduped]
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print(f" Found {len(model_list)} text model(s) (filtered from {len(live_models)} total)")
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else:
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model_list = _PROVIDER_MODELS.get("bedrock", [])
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if model_list:
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print(f" Using {len(model_list)} curated models (live discovery unavailable)")
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else:
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print(" No models found. Check IAM permissions for bedrock:ListFoundationModels.")
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return
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# 4. Model selection
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if model_list:
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selected = _prompt_model_selection(model_list, current_model=current_model)
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else:
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try:
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selected = input(" Model ID: ").strip()
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except (KeyboardInterrupt, EOFError):
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selected = None
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if selected:
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_save_model_choice(selected)
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cfg = load_config()
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model = cfg.get("model")
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if not isinstance(model, dict):
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model = {"default": model} if model else {}
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cfg["model"] = model
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model["provider"] = "bedrock"
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model["base_url"] = f"https://bedrock-runtime.{region}.amazonaws.com"
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model.pop("api_mode", None) # bedrock_converse is auto-detected
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bedrock_cfg = cfg.get("bedrock", {})
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if not isinstance(bedrock_cfg, dict):
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bedrock_cfg = {}
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bedrock_cfg["region"] = region
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cfg["bedrock"] = bedrock_cfg
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save_config(cfg)
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deactivate_provider()
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print(f" Default model set to: {selected} (via AWS Bedrock, {region})")
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else:
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print(" No change.")
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def _model_flow_api_key_provider(config, provider_id, current_model=""):
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"""Generic flow for API-key providers (z.ai, MiniMax, OpenCode, etc.)."""
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from hermes_cli.auth import (
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