Zero-config planoai up: pass-through proxy with auto-detected providers (#890)

cli/planoai/defaults.py

@@ -0,0 +1,163 @@
+"""Default config synthesizer for zero-config ``planoai up``.
+
+When the user runs ``planoai up`` in a directory with no ``config.yaml`` /
+``plano_config.yaml``, we synthesize a pass-through config that covers the
+common LLM providers and auto-wires OTel export to ``localhost:4317`` so
+``planoai obs`` works out of the box.
+
+Auth handling:
+- If the provider's env var is set, bind ``access_key: $ENV_VAR``.
+- Otherwise set ``passthrough_auth: true`` so the client's own Authorization
+  header is forwarded. No env var is required to start the proxy.
+"""
+
+from __future__ import annotations
+
+import os
+from dataclasses import dataclass
+
+DEFAULT_LLM_LISTENER_PORT = 12000
+# plano_config validation requires an http:// scheme on the OTLP endpoint.
+DEFAULT_OTLP_ENDPOINT = "http://localhost:4317"
+
+
+@dataclass(frozen=True)
+class ProviderDefault:
+    name: str
+    env_var: str
+    base_url: str
+    model_pattern: str
+    # Only set for providers whose prefix in the model pattern is NOT one of the
+    # built-in SUPPORTED_PROVIDERS in cli/planoai/config_generator.py. For
+    # built-ins, the validator infers the interface from the model prefix and
+    # rejects configs that set this field explicitly.
+    provider_interface: str | None = None
+
+
+# Keep ordering stable so synthesized configs diff cleanly across runs.
+PROVIDER_DEFAULTS: list[ProviderDefault] = [
+    ProviderDefault(
+        name="openai",
+        env_var="OPENAI_API_KEY",
+        base_url="https://api.openai.com/v1",
+        model_pattern="openai/*",
+    ),
+    ProviderDefault(
+        name="anthropic",
+        env_var="ANTHROPIC_API_KEY",
+        base_url="https://api.anthropic.com/v1",
+        model_pattern="anthropic/*",
+    ),
+    ProviderDefault(
+        name="gemini",
+        env_var="GEMINI_API_KEY",
+        base_url="https://generativelanguage.googleapis.com/v1beta",
+        model_pattern="gemini/*",
+    ),
+    ProviderDefault(
+        name="groq",
+        env_var="GROQ_API_KEY",
+        base_url="https://api.groq.com/openai/v1",
+        model_pattern="groq/*",
+    ),
+    ProviderDefault(
+        name="deepseek",
+        env_var="DEEPSEEK_API_KEY",
+        base_url="https://api.deepseek.com/v1",
+        model_pattern="deepseek/*",
+    ),
+    ProviderDefault(
+        name="mistral",
+        env_var="MISTRAL_API_KEY",
+        base_url="https://api.mistral.ai/v1",
+        model_pattern="mistral/*",
+    ),
+    # DigitalOcean Gradient is a first-class provider post-#889 — the
+    # `digitalocean/` model prefix routes to the built-in Envoy cluster, no
+    # base_url needed at runtime.
+    ProviderDefault(
+        name="digitalocean",
+        env_var="DO_API_KEY",
+        base_url="https://inference.do-ai.run/v1",
+        model_pattern="digitalocean/*",
+    ),
+]
+
+
+@dataclass
+class DetectionResult:
+    with_keys: list[ProviderDefault]
+    passthrough: list[ProviderDefault]
+
+    @property
+    def summary(self) -> str:
+        parts = []
+        if self.with_keys:
+            parts.append("env-keyed: " + ", ".join(p.name for p in self.with_keys))
+        if self.passthrough:
+            parts.append("pass-through: " + ", ".join(p.name for p in self.passthrough))
+        return " | ".join(parts) if parts else "no providers"
+
+
+def detect_providers(env: dict[str, str] | None = None) -> DetectionResult:
+    env = env if env is not None else dict(os.environ)
+    with_keys: list[ProviderDefault] = []
+    passthrough: list[ProviderDefault] = []
+    for p in PROVIDER_DEFAULTS:
+        val = env.get(p.env_var)
+        if val:
+            with_keys.append(p)
+        else:
+            passthrough.append(p)
+    return DetectionResult(with_keys=with_keys, passthrough=passthrough)
+
+
+def synthesize_default_config(
+    env: dict[str, str] | None = None,
+    *,
+    listener_port: int = DEFAULT_LLM_LISTENER_PORT,
+    otel_endpoint: str = DEFAULT_OTLP_ENDPOINT,
+) -> dict:
+    """Build a pass-through config dict suitable for validation + envoy rendering.
+
+    The returned dict can be dumped to YAML and handed to the existing `planoai up`
+    pipeline unchanged.
+    """
+    detection = detect_providers(env)
+
+    def _entry(p: ProviderDefault, base: dict) -> dict:
+        row: dict = {"name": p.name, "model": p.model_pattern, "base_url": p.base_url}
+        if p.provider_interface is not None:
+            row["provider_interface"] = p.provider_interface
+        row.update(base)
+        return row
+
+    model_providers: list[dict] = []
+    for p in detection.with_keys:
+        model_providers.append(_entry(p, {"access_key": f"${p.env_var}"}))
+    for p in detection.passthrough:
+        model_providers.append(_entry(p, {"passthrough_auth": True}))
+
+    # No explicit `default: true` entry is synthesized: the plano config
+    # validator rejects wildcard models as defaults, and brightstaff already
+    # registers bare model names as lookup keys during wildcard expansion
+    # (crates/common/src/llm_providers.rs), so `{"model": "gpt-4o-mini"}`
+    # without a prefix resolves via the openai wildcard without needing
+    # `default: true`. See discussion on #890.
+
+    return {
+        "version": "v0.4.0",
+        "listeners": [
+            {
+                "name": "llm",
+                "type": "model",
+                "port": listener_port,
+                "address": "0.0.0.0",
+            }
+        ],
+        "model_providers": model_providers,
+        "tracing": {
+            "random_sampling": 100,
+            "opentracing_grpc_endpoint": otel_endpoint,
+        },
+    }