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https://github.com/magnus919/agent-skills.git
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Magnus Hedemark
526e1ac3f0
PydanticAI reads API keys from provider-specific env vars (OPENAI_API_KEY, DEEPSEEK_API_KEY, etc.) at Agent creation time. agent-council was reading AGENT_COUNCIL_API_KEY into a config dict but never setting the env var PydanticAI actually looks for. If a user had OPENAI_API_KEY set for something else, agent-council silently used the wrong key for debate agents. Fix: load_config() now maps AGENT_COUNCIL_API_KEY to the correct env var based on the model prefix (openai:, deepseek:, anthropic:, google:, etc.) and also maps AGENT_COUNCIL_BASE_URL to OPENAI_BASE_URL. Only sets if not already set, so explicit env vars take precedence. Signed-off-by: Magnus Hedemark <magnus919@pm.me>
95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
"""Configuration — env var loading with sensible defaults and .env support."""
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import os
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from pathlib import Path
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def _load_dotenv(path: Path | None = None) -> None:
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"""Load .env file using stdlib only. Looks for .env in cwd by default.
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Minimal implementation — no python-dotenv dependency. Handles:
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KEY=value
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KEY="quoted value"
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# comments
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export KEY=value (strips export prefix)
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"""
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dotenv_path = path or Path.cwd() / ".env"
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if not dotenv_path.exists():
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return
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for line in dotenv_path.read_text().splitlines():
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line = line.strip()
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if not line or line.startswith("#"):
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continue
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if line.startswith("export "):
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line = line[7:].strip()
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if "=" not in line:
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continue
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key, _, value = line.partition("=")
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key = key.strip()
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value = value.strip().strip("\"'")
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if key and key not in os.environ:
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os.environ[key] = value
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def load_config() -> dict:
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"""Load configuration from environment variables and .env files.
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Checks for a .env file in the current working directory first,
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then falls back to environment variables. Env vars always take
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precedence over .env values.
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Also sets the provider-specific API key env var (e.g. OPENAI_API_KEY,
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DEEPSEEK_API_KEY, ANTHROPIC_API_KEY) from AGENT_COUNCIL_API_KEY so
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PydanticAI picks it up regardless of what's in the environment.
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Returns dict with keys: api_key, model, base_url.
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Raises ValueError if AGENT_COUNCIL_API_KEY is not set.
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"""
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_load_dotenv()
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api_key = os.environ.get("AGENT_COUNCIL_API_KEY")
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model = os.environ.get("AGENT_COUNCIL_MODEL", "openai:gpt-5.6-luna")
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base_url = os.environ.get("AGENT_COUNCIL_BASE_URL")
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if not api_key:
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raise ValueError(
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"AGENT_COUNCIL_API_KEY is not set. "
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"Set it via environment variable or create a .env file:\n"
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" export AGENT_COUNCIL_API_KEY='sk-...'\n"
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" export AGENT_COUNCIL_MODEL='openai:gpt-5.6-luna' # or your model\n\n"
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"Or create a .env file in the current directory:\n"
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" AGENT_COUNCIL_API_KEY=sk-...\n"
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" AGENT_COUNCIL_MODEL=openai:gpt-5.6-luna"
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)
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# Map AGENT_COUNCIL_API_KEY to the provider-specific env var
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# that PydanticAI reads at Agent creation time.
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provider = model.split(":")[0] if ":" in model else "openai"
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provider_key_map = {
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"openai": "OPENAI_API_KEY",
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"deepseek": "DEEPSEEK_API_KEY",
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"anthropic": "ANTHROPIC_API_KEY",
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"google": "GOOGLE_API_KEY",
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"groq": "GROQ_API_KEY",
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"cohere": "COHERE_API_KEY",
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"mistral": "MISTRAL_API_KEY",
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"together": "TOGETHER_API_KEY",
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"xai": "XAI_API_KEY",
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"ollama": None, # no API key needed
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}
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env_var = provider_key_map.get(provider, "OPENAI_API_KEY")
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if env_var and not os.environ.get(env_var):
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os.environ[env_var] = api_key
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# Also set base URL if provided
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if base_url and not os.environ.get("OPENAI_BASE_URL"):
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os.environ["OPENAI_BASE_URL"] = base_url
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config = {
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"api_key": api_key,
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"model": model,
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}
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if base_url:
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config["base_url"] = base_url
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return config
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