somew1nd
5d92939d91
Preserve user guidance through history compression, stabilize Flash index targets, and retire withdrawn checks without applying stale verdicts. Improve runtime diagnostics, tool responses, and history rendering. Simplify documentation and comments. Validation: 2076 tests passed in the full suite; 381 affected tests and 26 frontend tests passed after cleanup. Ruff and the quality ratchet passed.
297 lines
11 KiB
Python
297 lines
11 KiB
Python
# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""LLM & Multimodal Vision Credentials Readiness Probe."""
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from typing import Any
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from artemis.config import settings
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from artemis.core.diagnostics.probes.base import BaseProbe
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from artemis.core.diagnostics.schema import (
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ProbeAction,
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ProbeCategory,
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ProbeResult,
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ProbeStatus,
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)
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class LLMCredentialsProbe(BaseProbe):
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"""Probe verifying Gemini and multi-provider multimodal LLM credentials."""
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@property
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def probe_id(self) -> str:
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return "gemini_api_key"
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@property
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def category(self) -> ProbeCategory:
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return ProbeCategory.CREDENTIALS
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@property
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def is_blocker(self) -> bool:
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return True
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def _mask_key(self, key_str: str) -> str:
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"""Helper to safely mask an API credential for display."""
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if len(key_str) > 10:
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return f"{key_str[:6]}...{key_str[-4:]}"
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return "***"
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async def probe(self) -> ProbeResult:
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import os
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from artemis.config.settings import is_placeholder_key
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gemini_key = settings.get_api_key("google")
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openai_key = settings.get_api_key("openai")
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claude_key = settings.get_api_key("anthropic")
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openrouter_key = settings.get_api_key("openrouter")
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xai_key = settings.get_api_key("xai")
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ocr_key = settings.get_api_key("ocr")
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configured_providers: list[dict[str, Any]] = []
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api_keys_map: dict[str, str] = {}
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if gemini_key and not is_placeholder_key(gemini_key):
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g_val = gemini_key.get_secret_value()
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configured_providers.append(
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{
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"provider": "google",
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"label": "Gemini",
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"masked": self._mask_key(g_val),
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"raw_key": g_val,
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"key": g_val,
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}
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)
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api_keys_map["google"] = g_val
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api_keys_map["gemini"] = g_val
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if openai_key and not is_placeholder_key(openai_key):
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o_val = openai_key.get_secret_value()
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configured_providers.append(
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{
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"provider": "openai",
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"label": "ChatGPT",
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"masked": self._mask_key(o_val),
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"raw_key": o_val,
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"key": o_val,
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}
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)
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api_keys_map["openai"] = o_val
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if claude_key and not is_placeholder_key(claude_key):
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c_val = claude_key.get_secret_value()
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configured_providers.append(
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{
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"provider": "anthropic",
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"label": "Claude",
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"masked": self._mask_key(c_val),
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"raw_key": c_val,
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"key": c_val,
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}
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)
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api_keys_map["anthropic"] = c_val
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if openrouter_key and not is_placeholder_key(openrouter_key):
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or_val = openrouter_key.get_secret_value()
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configured_providers.append(
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{
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"provider": "openrouter",
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"label": "OpenRouter",
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"masked": self._mask_key(or_val),
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"raw_key": or_val,
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"key": or_val,
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}
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)
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api_keys_map["openrouter"] = or_val
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if xai_key and not is_placeholder_key(xai_key):
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x_val = xai_key.get_secret_value()
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configured_providers.append(
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{
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"provider": "xai",
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"label": "xAI (Grok)",
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"masked": self._mask_key(x_val),
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"raw_key": x_val,
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"key": x_val,
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}
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)
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api_keys_map["xai"] = x_val
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# Detect any custom model endpoints or environment variables defined in files
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for env_var, label, prov_id in [
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("DEEPSEEK_API_KEY", "DeepSeek", "deepseek"),
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("GROQ_API_KEY", "Groq", "groq"),
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("OPENAI_BASE_URL", "Custom OpenAI Endpoint", "custom"),
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("OLLAMA_BASE_URL", "Local Ollama", "ollama"),
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("VLLM_BASE_URL", "vLLM Endpoint", "vllm"),
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("VERTEX_AI_PROJECT", "Google Cloud Vertex AI", "vertexai"),
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]:
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val = os.environ.get(env_var)
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if val and val.strip() and not is_placeholder_key(val.strip()):
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configured_providers.append(
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{
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"provider": prov_id,
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"label": label,
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"masked": self._mask_key(val.strip()),
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"raw_key": val.strip(),
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"key": val.strip(),
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}
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)
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api_keys_map[prov_id] = val.strip()
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if ocr_key and not is_placeholder_key(ocr_key):
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api_keys_map["ocr"] = ocr_key.get_secret_value()
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current_active_key = (
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gemini_key.get_secret_value()
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if gemini_key
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else (configured_providers[0]["key"] if configured_providers else "")
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)
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metadata = {
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"configured_count": len(configured_providers),
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"providers": configured_providers,
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"has_ocr_key": ocr_key is not None,
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"current_key": current_active_key,
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"current_gemini_key": gemini_key.get_secret_value() if gemini_key else "",
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"api_keys": api_keys_map,
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}
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# Case 1: Gemini API Key configured (Standard / Recommended)
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if gemini_key:
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masked = self._mask_key(gemini_key.get_secret_value())
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return ProbeResult(
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id=self.probe_id,
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category=self.category,
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title="Multimodal LLM API Key",
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status=ProbeStatus.PASS,
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is_blocker=self.is_blocker,
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summary="Active (Gemini)",
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description=f"Gemini multimodal API credential is active ({masked}) and ready for vision and reasoning.",
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metadata=metadata,
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actions=[
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ProbeAction(
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action_type="hint",
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label="Provider Active",
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payload="Gemini 2.5 Flash / Pro Multimodal Engine is enabled.",
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)
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],
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)
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# Case 2: Other LLM provider configured
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if configured_providers:
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first_p = configured_providers[0]
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return ProbeResult(
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id=self.probe_id,
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category=self.category,
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title="Multimodal LLM API Key",
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status=ProbeStatus.PASS,
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is_blocker=self.is_blocker,
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summary=f"Active ({first_p['label']})",
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description=f"{first_p['label']} multimodal API credential is active ({first_p['masked']}).",
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metadata=metadata,
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actions=[
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ProbeAction(
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action_type="hint",
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label="Provider Active",
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payload=f"{first_p['label']} multimodal vision endpoint is active.",
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)
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],
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)
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# Case 3: No LLM key configured
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return ProbeResult(
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id=self.probe_id,
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category=self.category,
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title="Multimodal LLM API Key",
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status=ProbeStatus.FAIL,
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is_blocker=self.is_blocker,
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summary="Key Missing",
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description="No Multimodal LLM credential (e.g. GEMINI_API_KEY, OPENAI_API_KEY, ANTHROPIC_API_KEY) found in environment or .env file.",
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metadata=metadata,
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actions=[
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ProbeAction(
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action_type="command",
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label="Run Artemis Init",
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payload="artemis init",
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),
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ProbeAction(
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action_type="link",
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label="Get Google AI Studio Key",
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payload="https://aistudio.google.com/app/apikey",
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),
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],
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)
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class VisionOCRProbe(BaseProbe):
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"""Probe verifying optional Google Cloud Vision OCR credentials."""
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@property
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def probe_id(self) -> str:
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return "vision_ocr_key"
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@property
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def category(self) -> ProbeCategory:
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return ProbeCategory.CREDENTIALS
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@property
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def is_blocker(self) -> bool:
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return False
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def _mask_key(self, key_str: str) -> str:
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"""Helper to safely mask an API credential for display."""
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if len(key_str) > 10:
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return f"{key_str[:6]}...{key_str[-4:]}"
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return "***"
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async def probe(self) -> ProbeResult:
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from artemis.utils.ocr_api import is_ocr_configured
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ocr_key = settings.get_api_key("ocr")
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is_configured = is_ocr_configured() and ocr_key is not None
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if is_configured and ocr_key:
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val = ocr_key.get_secret_value()
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masked = self._mask_key(val)
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return ProbeResult(
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id=self.probe_id,
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category=self.category,
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title="Vision OCR API Key (Optional)",
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status=ProbeStatus.PASS,
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is_blocker=False,
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summary="Active & Configured",
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description=f"Google Cloud Vision OCR ({masked}) is active for image text recognition.",
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metadata={"configured": True, "masked_key": masked, "key": val, "raw_key": val},
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actions=[
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ProbeAction(
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action_type="hint",
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label="OCR Enabled",
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payload="OCR is active and will fuse text with UI XML hierarchy.",
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)
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],
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)
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return ProbeResult(
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id=self.probe_id,
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category=self.category,
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title="Vision OCR API Key (Optional)",
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status=ProbeStatus.PASS,
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is_blocker=False,
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summary="Not Configured (Optional)",
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description="OCR_API_KEY is not set. Perception uses the UI XML hierarchy without OCR.",
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metadata={"configured": False},
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actions=[
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ProbeAction(
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action_type="hint",
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label="Standard XML Perception",
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payload="Artemis uses pure UI layout parsing and Set-of-Marks visual grounding.",
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)
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],
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)
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