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zero-config planoai up: synthesize pass-through proxy when no config file
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4 changed files with 261 additions and 5 deletions
167
cli/planoai/defaults.py
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167
cli/planoai/defaults.py
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"""Default config synthesizer for zero-config ``planoai up``.
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When the user runs ``planoai up`` in a directory with no ``config.yaml`` /
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``plano_config.yaml``, we synthesize a pass-through config that covers the
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common LLM providers and auto-wires OTel export to ``localhost:4317`` so
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``planoai obs`` works out of the box.
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Auth handling:
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- If the provider's env var is set, bind ``access_key: $ENV_VAR``.
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- Otherwise set ``passthrough_auth: true`` so the client's own Authorization
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header is forwarded. No env var is required to start the proxy.
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"""
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from __future__ import annotations
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import os
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from dataclasses import dataclass
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DEFAULT_LLM_LISTENER_PORT = 12000
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# plano_config validation requires an http:// scheme on the OTLP endpoint.
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DEFAULT_OTLP_ENDPOINT = "http://localhost:4317"
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@dataclass(frozen=True)
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class ProviderDefault:
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name: str
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env_var: str
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base_url: str
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model_pattern: str
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# Only set for providers whose prefix in the model pattern is NOT one of the
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# built-in SUPPORTED_PROVIDERS in cli/planoai/config_generator.py. For
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# built-ins, the validator infers the interface from the model prefix and
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# rejects configs that set this field explicitly.
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provider_interface: str | None = None
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# Keep ordering stable so synthesized configs diff cleanly across runs.
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PROVIDER_DEFAULTS: list[ProviderDefault] = [
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ProviderDefault(
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name="openai",
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env_var="OPENAI_API_KEY",
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base_url="https://api.openai.com/v1",
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model_pattern="openai/*",
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),
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ProviderDefault(
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name="anthropic",
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env_var="ANTHROPIC_API_KEY",
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base_url="https://api.anthropic.com/v1",
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model_pattern="anthropic/*",
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),
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ProviderDefault(
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name="gemini",
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env_var="GEMINI_API_KEY",
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base_url="https://generativelanguage.googleapis.com/v1beta",
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model_pattern="gemini/*",
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),
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ProviderDefault(
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name="groq",
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env_var="GROQ_API_KEY",
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base_url="https://api.groq.com/openai/v1",
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model_pattern="groq/*",
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),
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ProviderDefault(
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name="deepseek",
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env_var="DEEPSEEK_API_KEY",
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base_url="https://api.deepseek.com/v1",
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model_pattern="deepseek/*",
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),
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ProviderDefault(
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name="mistral",
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env_var="MISTRAL_API_KEY",
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base_url="https://api.mistral.ai/v1",
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model_pattern="mistral/*",
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),
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# DigitalOcean Gradient is OpenAI-compatible and `do` is not in the built-in
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# SUPPORTED_PROVIDERS list, so we must provide provider_interface explicitly.
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ProviderDefault(
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name="do",
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env_var="DO_API_KEY",
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base_url="https://inference.do-ai.run/v1",
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model_pattern="do/*",
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provider_interface="openai",
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),
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]
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@dataclass
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class DetectionResult:
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with_keys: list[ProviderDefault]
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passthrough: list[ProviderDefault]
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@property
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def summary(self) -> str:
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parts = []
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if self.with_keys:
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parts.append(
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"env-keyed: " + ", ".join(p.name for p in self.with_keys)
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)
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if self.passthrough:
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parts.append(
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"pass-through: " + ", ".join(p.name for p in self.passthrough)
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)
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return " | ".join(parts) if parts else "no providers"
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def detect_providers(env: dict[str, str] | None = None) -> DetectionResult:
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env = env if env is not None else dict(os.environ)
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with_keys: list[ProviderDefault] = []
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passthrough: list[ProviderDefault] = []
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for p in PROVIDER_DEFAULTS:
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val = env.get(p.env_var)
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if val:
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with_keys.append(p)
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else:
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passthrough.append(p)
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return DetectionResult(with_keys=with_keys, passthrough=passthrough)
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def synthesize_default_config(
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env: dict[str, str] | None = None,
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*,
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listener_port: int = DEFAULT_LLM_LISTENER_PORT,
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otel_endpoint: str = DEFAULT_OTLP_ENDPOINT,
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) -> dict:
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"""Build a pass-through config dict suitable for validation + envoy rendering.
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The returned dict can be dumped to YAML and handed to the existing `planoai up`
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pipeline unchanged.
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"""
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detection = detect_providers(env)
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def _entry(p: ProviderDefault, base: dict) -> dict:
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row: dict = {"name": p.name, "model": p.model_pattern, "base_url": p.base_url}
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if p.provider_interface is not None:
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row["provider_interface"] = p.provider_interface
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row.update(base)
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return row
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model_providers: list[dict] = []
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for p in detection.with_keys:
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model_providers.append(_entry(p, {"access_key": f"${p.env_var}"}))
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for p in detection.passthrough:
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model_providers.append(_entry(p, {"passthrough_auth": True}))
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# We intentionally don't mark any provider as `default: true` here:
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# the validator rejects wildcard models (e.g. `openai/*`) as defaults, and
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# all our entries are wildcards. Clients should prefix model names (e.g.
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# `openai/gpt-4o-mini`, `do/router:software-engineering`); the wildcard
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# matcher routes them to the correct provider.
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return {
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"version": "v0.4.0",
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"listeners": [
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{
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"name": "llm",
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"type": "model",
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"port": listener_port,
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"address": "0.0.0.0",
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}
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],
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"model_providers": model_providers,
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"tracing": {
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"random_sampling": 100,
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"opentracing_grpc_endpoint": otel_endpoint,
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},
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}
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@ -328,12 +328,30 @@ def up(file, path, foreground, with_tracing, tracing_port, docker, verbose):
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# Use the utility function to find config file
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plano_config_file = find_config_file(path, file)
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# Check if the file exists
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# Zero-config fallback: when no user config is present, synthesize a
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# pass-through config that covers the common LLM providers and
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# auto-wires OTel export to ``planoai obs``. See cli/planoai/defaults.py.
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if not os.path.exists(plano_config_file):
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console.print(
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f"[red]✗[/red] Config file not found: [dim]{plano_config_file}[/dim]"
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import yaml
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from planoai.defaults import (
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detect_providers,
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synthesize_default_config,
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)
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detection = detect_providers()
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cfg_dict = synthesize_default_config()
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default_dir = os.path.expanduser("~/.plano")
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os.makedirs(default_dir, exist_ok=True)
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synthesized_path = os.path.join(default_dir, "default_config.yaml")
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with open(synthesized_path, "w") as fh:
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yaml.safe_dump(cfg_dict, fh, sort_keys=False)
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plano_config_file = synthesized_path
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console.print(
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f"[dim]No plano config found; using defaults ({detection.summary}). "
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f"Listening on :12000, tracing -> http://localhost:4317.[/dim]"
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)
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sys.exit(1)
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if not docker:
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from planoai.native_runner import native_validate_config
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71
cli/test/test_defaults.py
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71
cli/test/test_defaults.py
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@ -0,0 +1,71 @@
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from pathlib import Path
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import jsonschema
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import yaml
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from planoai.defaults import (
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PROVIDER_DEFAULTS,
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detect_providers,
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synthesize_default_config,
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)
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_SCHEMA_PATH = Path(__file__).parents[2] / "config" / "plano_config_schema.yaml"
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def _schema() -> dict:
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return yaml.safe_load(_SCHEMA_PATH.read_text())
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def test_zero_env_vars_produces_pure_passthrough():
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cfg = synthesize_default_config(env={})
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assert cfg["version"] == "v0.4.0"
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assert cfg["listeners"][0]["port"] == 12000
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for provider in cfg["model_providers"]:
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assert provider.get("passthrough_auth") is True
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assert "access_key" not in provider
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# All known providers should be listed.
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names = {p["name"] for p in cfg["model_providers"]}
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assert "do" in names
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assert "openai" in names
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assert "anthropic" in names
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def test_env_keys_promote_providers_to_env_keyed():
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cfg = synthesize_default_config(
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env={"OPENAI_API_KEY": "sk-1", "DO_API_KEY": "do-1"}
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)
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by_name = {p["name"]: p for p in cfg["model_providers"]}
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assert by_name["openai"].get("access_key") == "$OPENAI_API_KEY"
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assert by_name["openai"].get("passthrough_auth") is None
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assert by_name["do"].get("access_key") == "$DO_API_KEY"
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# Unset env keys remain pass-through.
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assert by_name["anthropic"].get("passthrough_auth") is True
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def test_detection_summary_strings():
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det = detect_providers(env={"OPENAI_API_KEY": "sk", "DO_API_KEY": "d"})
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summary = det.summary
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assert "env-keyed" in summary and "openai" in summary and "do" in summary
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assert "pass-through" in summary
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def test_tracing_block_points_at_local_console():
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cfg = synthesize_default_config(env={})
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tracing = cfg["tracing"]
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assert tracing["opentracing_grpc_endpoint"] == "http://localhost:4317"
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# random_sampling is a percentage in the plano config — 100 = every span.
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assert tracing["random_sampling"] == 100
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def test_synthesized_config_validates_against_schema():
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cfg = synthesize_default_config(env={"OPENAI_API_KEY": "sk"})
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jsonschema.validate(cfg, _schema())
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def test_provider_defaults_do_is_configured():
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by_name = {p.name: p for p in PROVIDER_DEFAULTS}
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assert "do" in by_name
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assert by_name["do"].env_var == "DO_API_KEY"
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assert by_name["do"].base_url == "https://inference.do-ai.run/v1"
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assert by_name["do"].model_pattern == "do/*"
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2
cli/uv.lock
generated
2
cli/uv.lock
generated
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@ -337,7 +337,7 @@ wheels = [
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[[package]]
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name = "planoai"
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version = "0.4.18"
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version = "0.4.19"
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source = { editable = "." }
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dependencies = [
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{ name = "click" },
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