us final version

planner.py

@@ -0,0 +1,91 @@
+from dataclasses import dataclass
+
+from openai import OpenAI
+from pydantic import BaseModel
+
+import config
+from config import SERVOS, HOME, clamp_pose
+from presets import EXAMPLES
+
+MAX_STEPS = 16
+MIN_MS, MAX_MS = 80, 6000
+
+
+class Step(BaseModel):
+    s1: int
+    s2: int
+    s3: int
+    s4: int
+    ms: int
+
+
+class Reply(BaseModel):
+    summary: str
+    steps: list[Step]
+
+
+@dataclass
+class Plan:
+    summary: str
+    steps: list  # [(pose, ms), ...]
+
+
+def _fmt(steps):
+    return "\n".join(f"  {list(pose)} over {ms}ms" for pose, ms in steps)
+
+
+def _instructions():
+    servos = "\n".join(
+        f"- {s.key} ({s.name}): {s.role}. range {s.lo}-{s.hi}, home {s.home}"
+        for s in SERVOS
+    )
+    examples = "\n\n".join(f'"{name}":\n{_fmt(steps)}' for name, steps in EXAMPLES.items())
+    return f"""You drive a small 4-servo robot arm. Turn the user's spoken command into keyframes.
+
+Servos (angles in degrees):
+{servos}
+
+Each step is an absolute pose [s1, s2, s3, s4] reached by moving all servos together over `ms` milliseconds.
+Repeat the same pose with a duration to hold still.
+
+Rules:
+- Stay inside each servo's range.
+- {MIN_MS}-{MAX_MS} ms per step, at most {MAX_STEPS} steps. ~4 degrees per 30 ms looks natural; go faster only for snappy moves.
+- Unless the user asks to hold a position, finish back at home {list(HOME)}.
+- Relative commands ("a bit more left", "lower") start from the current pose.
+- If the command has nothing to do with moving the arm, return no steps and say why in the summary.
+- summary: a few words describing the motion, in the user's language.
+
+Reference moves:
+
+{examples}"""
+
+
+class Planner:
+    def __init__(self):
+        if not config.OPENAI_API_KEY:
+            raise RuntimeError("OPENAI_API_KEY is not set")
+        self._client = OpenAI(api_key=config.OPENAI_API_KEY)
+
+    def plan(self, text, current_pose):
+        kwargs = {}
+        if config.OPENAI_REASONING_EFFORT:
+            kwargs["reasoning"] = {"effort": config.OPENAI_REASONING_EFFORT}
+
+        resp = self._client.responses.parse(
+            model=config.OPENAI_MODEL,
+            instructions=_instructions(),
+            input=f"Current pose: {list(current_pose)}\nCommand: {text}",
+            text_format=Reply,
+            timeout=30,
+            **kwargs,
+        )
+        reply = resp.output_parsed
+        if reply is None:
+            raise RuntimeError("model returned nothing usable")
+
+        steps = [
+            (clamp_pose((s.s1, s.s2, s.s3, s.s4)), max(MIN_MS, min(MAX_MS, s.ms)))
+            for s in reply.steps[:MAX_STEPS]
+        ]
+        return Plan(reply.summary.strip(), steps)