feat: enhance auxiliary model configuration and environment variable handling
- Added support for auxiliary model overrides in the configuration, allowing users to specify providers and models for vision and web extraction tasks. - Updated the CLI configuration example to include new auxiliary model settings. - Enhanced the environment variable mapping in the CLI to accommodate auxiliary model configurations. - Improved the resolution logic for auxiliary clients to support task-specific provider overrides. - Updated relevant documentation and comments for clarity on the new features and their usage.
This commit is contained in:
@@ -4,7 +4,7 @@ Provides a single resolution chain so every consumer (context compression,
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session search, web extraction, vision analysis, browser vision) picks up
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the best available backend without duplicating fallback logic.
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Resolution order for text tasks:
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Resolution order (same for text and vision tasks):
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1. OpenRouter (OPENROUTER_API_KEY)
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2. Nous Portal (~/.hermes/auth.json active provider)
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3. Custom endpoint (OPENAI_BASE_URL + OPENAI_API_KEY)
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@@ -14,10 +14,10 @@ Resolution order for text tasks:
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— checked via PROVIDER_REGISTRY entries with auth_type='api_key'
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6. None
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Resolution order for vision/multimodal tasks:
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1. OpenRouter
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2. Nous Portal
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3. None (custom endpoints can't substitute for Gemini multimodal)
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Per-task provider overrides (e.g. AUXILIARY_VISION_PROVIDER,
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CONTEXT_COMPRESSION_PROVIDER) can force a specific provider for each task:
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"openrouter", "nous", or "main" (= steps 3-5).
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Default "auto" follows the full chain above.
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"""
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import json
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@@ -337,59 +337,122 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
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return None, None
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# ── Public API ──────────────────────────────────────────────────────────────
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# ── Provider resolution helpers ─────────────────────────────────────────────
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def get_text_auxiliary_client() -> Tuple[Optional[OpenAI], Optional[str]]:
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"""Return (client, model_slug) for text-only auxiliary tasks.
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def _get_auxiliary_provider(task: str = "") -> str:
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"""Read the provider override for a specific auxiliary task.
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Falls through OpenRouter -> Nous Portal -> custom endpoint -> Codex OAuth
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-> direct API-key providers -> (None, None).
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Checks AUXILIARY_{TASK}_PROVIDER first (e.g. AUXILIARY_VISION_PROVIDER),
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then CONTEXT_{TASK}_PROVIDER (for the compression section's summary_provider),
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then falls back to "auto". Returns one of: "auto", "openrouter", "nous", "main".
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"""
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# 1. OpenRouter
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if task:
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for prefix in ("AUXILIARY_", "CONTEXT_"):
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val = os.getenv(f"{prefix}{task.upper()}_PROVIDER", "").strip().lower()
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if val and val != "auto":
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return val
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return "auto"
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def _try_openrouter() -> Tuple[Optional[OpenAI], Optional[str]]:
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or_key = os.getenv("OPENROUTER_API_KEY")
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if or_key:
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logger.debug("Auxiliary text client: OpenRouter")
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return OpenAI(api_key=or_key, base_url=OPENROUTER_BASE_URL,
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default_headers=_OR_HEADERS), _OPENROUTER_MODEL
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if not or_key:
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return None, None
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logger.debug("Auxiliary client: OpenRouter")
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return OpenAI(api_key=or_key, base_url=OPENROUTER_BASE_URL,
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default_headers=_OR_HEADERS), _OPENROUTER_MODEL
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# 2. Nous Portal
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def _try_nous() -> Tuple[Optional[OpenAI], Optional[str]]:
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nous = _read_nous_auth()
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if nous:
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global auxiliary_is_nous
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auxiliary_is_nous = True
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logger.debug("Auxiliary text client: Nous Portal")
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return (
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OpenAI(api_key=_nous_api_key(nous), base_url=_nous_base_url()),
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_NOUS_MODEL,
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)
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if not nous:
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return None, None
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global auxiliary_is_nous
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auxiliary_is_nous = True
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logger.debug("Auxiliary client: Nous Portal")
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return (
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OpenAI(api_key=_nous_api_key(nous), base_url=_nous_base_url()),
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_NOUS_MODEL,
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)
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# 3. Custom endpoint (both base URL and key must be set)
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def _try_custom_endpoint() -> Tuple[Optional[OpenAI], Optional[str]]:
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custom_base = os.getenv("OPENAI_BASE_URL")
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custom_key = os.getenv("OPENAI_API_KEY")
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if custom_base and custom_key:
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model = os.getenv("OPENAI_MODEL") or os.getenv("LLM_MODEL") or "gpt-4o-mini"
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logger.debug("Auxiliary text client: custom endpoint (%s)", model)
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return OpenAI(api_key=custom_key, base_url=custom_base), model
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if not custom_base or not custom_key:
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return None, None
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model = os.getenv("OPENAI_MODEL") or os.getenv("LLM_MODEL") or "gpt-4o-mini"
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logger.debug("Auxiliary client: custom endpoint (%s)", model)
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return OpenAI(api_key=custom_key, base_url=custom_base), model
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# 4. Codex OAuth -- uses the Responses API (only endpoint the token
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# can access), wrapped to look like a chat.completions client.
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def _try_codex() -> Tuple[Optional[Any], Optional[str]]:
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codex_token = _read_codex_access_token()
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if codex_token:
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logger.debug("Auxiliary text client: Codex OAuth (%s via Responses API)", _CODEX_AUX_MODEL)
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real_client = OpenAI(api_key=codex_token, base_url=_CODEX_AUX_BASE_URL)
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return CodexAuxiliaryClient(real_client, _CODEX_AUX_MODEL), _CODEX_AUX_MODEL
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if not codex_token:
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return None, None
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logger.debug("Auxiliary client: Codex OAuth (%s via Responses API)", _CODEX_AUX_MODEL)
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real_client = OpenAI(api_key=codex_token, base_url=_CODEX_AUX_BASE_URL)
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return CodexAuxiliaryClient(real_client, _CODEX_AUX_MODEL), _CODEX_AUX_MODEL
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# 5. Direct API-key providers (z.ai/GLM, Kimi/Moonshot, MiniMax, etc.)
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api_client, api_model = _resolve_api_key_provider()
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if api_client is not None:
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return api_client, api_model
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# 6. Nothing available
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logger.debug("Auxiliary text client: none available")
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def _resolve_forced_provider(forced: str) -> Tuple[Optional[OpenAI], Optional[str]]:
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"""Resolve a specific forced provider. Returns (None, None) if creds missing."""
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if forced == "openrouter":
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client, model = _try_openrouter()
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if client is None:
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logger.warning("auxiliary.provider=openrouter but OPENROUTER_API_KEY not set")
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return client, model
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if forced == "nous":
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client, model = _try_nous()
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if client is None:
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logger.warning("auxiliary.provider=nous but Nous Portal not configured (run: hermes login)")
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return client, model
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if forced == "main":
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# "main" = skip OpenRouter/Nous, use the main chat model's credentials.
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for try_fn in (_try_custom_endpoint, _try_codex, _resolve_api_key_provider):
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client, model = try_fn()
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if client is not None:
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return client, model
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logger.warning("auxiliary.provider=main but no main endpoint credentials found")
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return None, None
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# Unknown provider name — fall through to auto
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logger.warning("Unknown auxiliary.provider=%r, falling back to auto", forced)
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return None, None
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def get_async_text_auxiliary_client():
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def _resolve_auto() -> Tuple[Optional[OpenAI], Optional[str]]:
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"""Full auto-detection chain: OpenRouter → Nous → custom → Codex → API-key → None."""
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for try_fn in (_try_openrouter, _try_nous, _try_custom_endpoint,
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_try_codex, _resolve_api_key_provider):
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client, model = try_fn()
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if client is not None:
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return client, model
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logger.debug("Auxiliary client: none available")
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return None, None
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# ── Public API ──────────────────────────────────────────────────────────────
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def get_text_auxiliary_client(task: str = "") -> Tuple[Optional[OpenAI], Optional[str]]:
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"""Return (client, default_model_slug) for text-only auxiliary tasks.
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Args:
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task: Optional task name ("compression", "web_extract") to check
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for a task-specific provider override.
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Callers may override the returned model with a per-task env var
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(e.g. CONTEXT_COMPRESSION_MODEL, AUXILIARY_WEB_EXTRACT_MODEL).
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"""
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forced = _get_auxiliary_provider(task)
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if forced != "auto":
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return _resolve_forced_provider(forced)
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return _resolve_auto()
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def get_async_text_auxiliary_client(task: str = ""):
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"""Return (async_client, model_slug) for async consumers.
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For standard providers returns (AsyncOpenAI, model). For Codex returns
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@@ -398,7 +461,7 @@ def get_async_text_auxiliary_client():
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"""
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from openai import AsyncOpenAI
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sync_client, model = get_text_auxiliary_client()
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sync_client, model = get_text_auxiliary_client(task)
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if sync_client is None:
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return None, None
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@@ -417,30 +480,16 @@ def get_async_text_auxiliary_client():
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def get_vision_auxiliary_client() -> Tuple[Optional[OpenAI], Optional[str]]:
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"""Return (client, model_slug) for vision/multimodal auxiliary tasks.
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"""Return (client, default_model_slug) for vision/multimodal auxiliary tasks.
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Only OpenRouter and Nous Portal qualify — custom endpoints cannot
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substitute for Gemini multimodal.
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Checks AUXILIARY_VISION_PROVIDER for a forced provider, otherwise
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auto-detects. Callers may override the returned model with
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AUXILIARY_VISION_MODEL.
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"""
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# 1. OpenRouter
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or_key = os.getenv("OPENROUTER_API_KEY")
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if or_key:
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logger.debug("Auxiliary vision client: OpenRouter")
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return OpenAI(api_key=or_key, base_url=OPENROUTER_BASE_URL,
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default_headers=_OR_HEADERS), _OPENROUTER_MODEL
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# 2. Nous Portal
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nous = _read_nous_auth()
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if nous:
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logger.debug("Auxiliary vision client: Nous Portal")
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return (
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OpenAI(api_key=_nous_api_key(nous), base_url=_nous_base_url()),
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_NOUS_MODEL,
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)
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# 3. Nothing suitable
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logger.debug("Auxiliary vision client: none available")
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return None, None
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forced = _get_auxiliary_provider("vision")
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if forced != "auto":
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return _resolve_forced_provider(forced)
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return _resolve_auto()
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def get_auxiliary_extra_body() -> dict:
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@@ -53,7 +53,7 @@ class ContextCompressor:
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self.last_completion_tokens = 0
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self.last_total_tokens = 0
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self.client, default_model = get_text_auxiliary_client()
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self.client, default_model = get_text_auxiliary_client("compression")
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self.summary_model = summary_model_override or default_model
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def update_from_response(self, usage: Dict[str, Any]):
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@@ -209,8 +209,58 @@ compression:
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threshold: 0.85
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# Model to use for generating summaries (fast/cheap recommended)
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# This model compresses the middle turns into a concise summary
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# This model compresses the middle turns into a concise summary.
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# IMPORTANT: it receives the full middle section of the conversation, so it
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# MUST support a context length at least as large as your main model's.
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summary_model: "google/gemini-3-flash-preview"
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# Provider for the summary model (default: "auto")
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# Options: "auto", "openrouter", "nous", "main"
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# summary_provider: "auto"
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# =============================================================================
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# Auxiliary Models (Advanced — Experimental)
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# =============================================================================
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# Hermes uses lightweight "auxiliary" models for side tasks: image analysis,
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# browser screenshot analysis, web page summarization, and context compression.
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#
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# By default these use Gemini Flash via OpenRouter or Nous Portal and are
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# auto-detected from your credentials. You do NOT need to change anything
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# here for normal usage.
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#
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# WARNING: Overriding these with providers other than OpenRouter or Nous Portal
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# is EXPERIMENTAL and may not work. Not all models/providers support vision,
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# produce usable summaries, or accept the same API format. Change at your own
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# risk — if things break, reset to "auto" / empty values.
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#
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# Each task has its own provider + model pair so you can mix providers.
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# For example: OpenRouter for vision (needs multimodal), but your main
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# local endpoint for compression (just needs text).
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#
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# Provider options:
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# "auto" - Best available: OpenRouter → Nous Portal → main endpoint (default)
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# "openrouter" - Force OpenRouter (requires OPENROUTER_API_KEY)
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# "nous" - Force Nous Portal (requires: hermes login)
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# "main" - Use the same provider & credentials as your main chat model.
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# Skips OpenRouter/Nous and uses your custom endpoint
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# (OPENAI_BASE_URL), Codex OAuth, or API-key provider directly.
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# Useful if you run a local model and want auxiliary tasks to
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# use it too.
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#
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# Model: leave empty to use the provider's default. When empty, OpenRouter
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# uses "google/gemini-3-flash-preview" and Nous uses "gemini-3-flash".
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# Other providers pick a sensible default automatically.
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#
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# auxiliary:
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# # Image analysis: vision_analyze tool + browser screenshots
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# vision:
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# provider: "auto"
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# model: "" # e.g. "google/gemini-2.5-flash", "openai/gpt-4o"
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#
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# # Web page scraping / summarization + browser page text extraction
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# web_extract:
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# provider: "auto"
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# model: ""
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# =============================================================================
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# Persistent Memory
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24
cli.py
24
cli.py
@@ -333,12 +333,36 @@ def load_cli_config() -> Dict[str, Any]:
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"enabled": "CONTEXT_COMPRESSION_ENABLED",
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"threshold": "CONTEXT_COMPRESSION_THRESHOLD",
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"summary_model": "CONTEXT_COMPRESSION_MODEL",
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"summary_provider": "CONTEXT_COMPRESSION_PROVIDER",
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}
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for config_key, env_var in compression_env_mappings.items():
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if config_key in compression_config:
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os.environ[env_var] = str(compression_config[config_key])
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# Apply auxiliary model overrides to environment variables.
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# Vision and web_extract each have their own provider + model pair.
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# (Compression is handled in the compression section above.)
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# Only set env vars for non-empty / non-default values so auto-detection
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# still works.
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auxiliary_config = defaults.get("auxiliary", {})
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auxiliary_task_env = {
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# config key → (provider env var, model env var)
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"vision": ("AUXILIARY_VISION_PROVIDER", "AUXILIARY_VISION_MODEL"),
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"web_extract": ("AUXILIARY_WEB_EXTRACT_PROVIDER", "AUXILIARY_WEB_EXTRACT_MODEL"),
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}
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for task_key, (prov_env, model_env) in auxiliary_task_env.items():
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task_cfg = auxiliary_config.get(task_key, {})
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if not isinstance(task_cfg, dict):
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continue
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prov = str(task_cfg.get("provider", "")).strip()
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model = str(task_cfg.get("model", "")).strip()
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if prov and prov != "auto":
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os.environ[prov_env] = prov
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if model:
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os.environ[model_env] = model
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return defaults
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# Load configuration at module startup
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@@ -87,6 +87,20 @@ DEFAULT_CONFIG = {
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"enabled": True,
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"threshold": 0.85,
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"summary_model": "google/gemini-3-flash-preview",
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"summary_provider": "auto",
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},
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# Auxiliary model overrides (advanced). By default Hermes auto-selects
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# the provider and model for each side task. Set these to override.
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"auxiliary": {
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"vision": {
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"provider": "auto", # auto | openrouter | nous | main
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"model": "", # e.g. "google/gemini-2.5-flash", "gpt-4o"
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},
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"web_extract": {
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"provider": "auto",
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"model": "",
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},
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},
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"display": {
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@@ -913,6 +927,31 @@ def show_config():
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if enabled:
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print(f" Threshold: {compression.get('threshold', 0.85) * 100:.0f}%")
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print(f" Model: {compression.get('summary_model', 'google/gemini-3-flash-preview')}")
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comp_provider = compression.get('summary_provider', 'auto')
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if comp_provider != 'auto':
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print(f" Provider: {comp_provider}")
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# Auxiliary models
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auxiliary = config.get('auxiliary', {})
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aux_tasks = {
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"Vision": auxiliary.get('vision', {}),
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"Web extract": auxiliary.get('web_extract', {}),
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}
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has_overrides = any(
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t.get('provider', 'auto') != 'auto' or t.get('model', '')
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for t in aux_tasks.values()
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)
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if has_overrides:
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print()
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print(color("◆ Auxiliary Models (overrides)", Colors.CYAN, Colors.BOLD))
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for label, task_cfg in aux_tasks.items():
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prov = task_cfg.get('provider', 'auto')
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mdl = task_cfg.get('model', '')
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if prov != 'auto' or mdl:
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parts = [f"provider={prov}"]
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if mdl:
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parts.append(f"model={mdl}")
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print(f" {label:12s} {', '.join(parts)}")
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# Messaging
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print()
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@@ -151,10 +151,10 @@ class TestGetTextAuxiliaryClient:
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assert model is None
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class TestCodexNotInVisionClient:
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"""Codex fallback should NOT apply to vision tasks."""
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class TestVisionClientFallback:
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"""Vision client uses the same full fallback chain as text."""
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def test_vision_returns_none_without_openrouter_nous(self):
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def test_vision_returns_none_without_any_credentials(self):
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with patch("agent.auxiliary_client._read_nous_auth", return_value=None):
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client, model = get_vision_auxiliary_client()
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assert client is None
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||||
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@@ -63,7 +63,7 @@ import time
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import requests
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from typing import Dict, Any, Optional, List
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from pathlib import Path
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from agent.auxiliary_client import get_vision_auxiliary_client
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||||
from agent.auxiliary_client import get_vision_auxiliary_client, get_text_auxiliary_client
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||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@@ -80,8 +80,28 @@ DEFAULT_SESSION_TIMEOUT = 300
|
||||
# Max tokens for snapshot content before summarization
|
||||
SNAPSHOT_SUMMARIZE_THRESHOLD = 8000
|
||||
|
||||
# Resolve vision auxiliary client for extraction/vision tasks
|
||||
_aux_vision_client, EXTRACTION_MODEL = get_vision_auxiliary_client()
|
||||
# Vision client — for browser_vision (screenshot analysis)
|
||||
_aux_vision_client, _DEFAULT_VISION_MODEL = get_vision_auxiliary_client()
|
||||
|
||||
# Text client — for page snapshot summarization (same config as web_extract)
|
||||
_aux_text_client, _DEFAULT_TEXT_MODEL = get_text_auxiliary_client("web_extract")
|
||||
|
||||
# Module-level alias for availability checks
|
||||
EXTRACTION_MODEL = _DEFAULT_TEXT_MODEL or _DEFAULT_VISION_MODEL
|
||||
|
||||
|
||||
def _get_vision_model() -> str:
|
||||
"""Model for browser_vision (screenshot analysis — multimodal)."""
|
||||
return (os.getenv("AUXILIARY_VISION_MODEL", "").strip()
|
||||
or _DEFAULT_VISION_MODEL
|
||||
or "google/gemini-3-flash-preview")
|
||||
|
||||
|
||||
def _get_extraction_model() -> str:
|
||||
"""Model for page snapshot text summarization — same as web_extract."""
|
||||
return (os.getenv("AUXILIARY_WEB_EXTRACT_MODEL", "").strip()
|
||||
or _DEFAULT_TEXT_MODEL
|
||||
or "google/gemini-3-flash-preview")
|
||||
|
||||
|
||||
def _is_local_mode() -> bool:
|
||||
@@ -860,9 +880,9 @@ def _extract_relevant_content(
|
||||
) -> str:
|
||||
"""Use LLM to extract relevant content from a snapshot based on the user's task.
|
||||
|
||||
Falls back to simple truncation when no auxiliary vision model is configured.
|
||||
Falls back to simple truncation when no auxiliary text model is configured.
|
||||
"""
|
||||
if _aux_vision_client is None or EXTRACTION_MODEL is None:
|
||||
if _aux_text_client is None:
|
||||
return _truncate_snapshot(snapshot_text)
|
||||
|
||||
if user_task:
|
||||
@@ -890,8 +910,8 @@ def _extract_relevant_content(
|
||||
|
||||
try:
|
||||
from agent.auxiliary_client import auxiliary_max_tokens_param
|
||||
response = _aux_vision_client.chat.completions.create(
|
||||
model=EXTRACTION_MODEL,
|
||||
response = _aux_text_client.chat.completions.create(
|
||||
model=_get_extraction_model(),
|
||||
messages=[{"role": "user", "content": extraction_prompt}],
|
||||
**auxiliary_max_tokens_param(4000),
|
||||
temperature=0.1,
|
||||
@@ -1316,7 +1336,7 @@ def browser_vision(question: str, task_id: Optional[str] = None) -> str:
|
||||
effective_task_id = task_id or "default"
|
||||
|
||||
# Check auxiliary vision client
|
||||
if _aux_vision_client is None or EXTRACTION_MODEL is None:
|
||||
if _aux_vision_client is None or _DEFAULT_VISION_MODEL is None:
|
||||
return json.dumps({
|
||||
"success": False,
|
||||
"error": "Browser vision unavailable: no auxiliary vision model configured. "
|
||||
@@ -1372,7 +1392,7 @@ def browser_vision(question: str, task_id: Optional[str] = None) -> str:
|
||||
# Use the sync auxiliary vision client directly
|
||||
from agent.auxiliary_client import auxiliary_max_tokens_param
|
||||
response = _aux_vision_client.chat.completions.create(
|
||||
model=EXTRACTION_MODEL,
|
||||
model=_get_vision_model(),
|
||||
messages=[
|
||||
{
|
||||
"role": "user",
|
||||
|
||||
@@ -468,7 +468,9 @@ def _handle_vision_analyze(args, **kw):
|
||||
image_url = args.get("image_url", "")
|
||||
question = args.get("question", "")
|
||||
full_prompt = f"Fully describe and explain everything about this image, then answer the following question:\n\n{question}"
|
||||
model = DEFAULT_VISION_MODEL or "google/gemini-3-flash-preview"
|
||||
model = (os.getenv("AUXILIARY_VISION_MODEL", "").strip()
|
||||
or DEFAULT_VISION_MODEL
|
||||
or "google/gemini-3-flash-preview")
|
||||
return vision_analyze_tool(image_url, full_prompt, model)
|
||||
|
||||
|
||||
|
||||
@@ -85,7 +85,13 @@ DEFAULT_MIN_LENGTH_FOR_SUMMARIZATION = 5000
|
||||
|
||||
# Resolve async auxiliary client at module level.
|
||||
# Handles Codex Responses API adapter transparently.
|
||||
_aux_async_client, DEFAULT_SUMMARIZER_MODEL = get_async_text_auxiliary_client()
|
||||
_aux_async_client, _DEFAULT_SUMMARIZER_MODEL = get_async_text_auxiliary_client("web_extract")
|
||||
|
||||
# Allow per-task override via config.yaml auxiliary.web_extract_model
|
||||
DEFAULT_SUMMARIZER_MODEL = (
|
||||
os.getenv("AUXILIARY_WEB_EXTRACT_MODEL", "").strip()
|
||||
or _DEFAULT_SUMMARIZER_MODEL
|
||||
)
|
||||
|
||||
_debug = DebugSession("web_tools", env_var="WEB_TOOLS_DEBUG")
|
||||
|
||||
|
||||
Reference in New Issue
Block a user