feat: add activation stream envelope

packages/node/meshnet_node/model_backend.py

@@ -86,6 +86,59 @@ class TensorPayload:
     # Number of tokens already cached before this payload's tokens (decode steps).
     past_len: int | None = None
 
+    def to_envelope(
+        self,
+        *,
+        name: str,
+        request_id: str,
+        work_id: str,
+        route_session: str,
+        route_epoch: int,
+        shard_start: int,
+        effective_start: int,
+        phase: str,
+        position: int,
+        idempotency_step: int,
+        byte_order: str = "little",
+        compression: str = "identity",
+        max_fragment_bytes: int | None = None,
+        token_id_sideband: list[int] | None = None,
+        architecture_state: dict[str, Any] | None = None,
+        recurrent_state: dict[str, Any] | None = None,
+        mtp: dict[str, Any] | None = None,
+        extensions: dict[str, Any] | None = None,
+    ):
+        from .protocol import ActivationEnvelope, DEFAULT_FRAGMENT_BYTES
+
+        return ActivationEnvelope.from_tensor_payload(
+            payload=self,
+            name=name,
+            request_id=request_id,
+            work_id=work_id,
+            route_session=route_session,
+            route_epoch=route_epoch,
+            shard_start=shard_start,
+            effective_start=effective_start,
+            phase=phase,
+            position=position,
+            idempotency_step=idempotency_step,
+            byte_order=byte_order,
+            compression=compression,
+            max_fragment_bytes=max_fragment_bytes or DEFAULT_FRAGMENT_BYTES,
+            token_id_sideband=token_id_sideband,
+            architecture_state=architecture_state,
+            recurrent_state=recurrent_state,
+            mtp=mtp,
+            extensions=extensions,
+        )
+
+    @classmethod
+    def from_envelope(cls, envelope, *, tensor_name: str = "activations"):
+        tensor_payload = envelope.to_tensor_payload(tensor_name=tensor_name)
+        if not isinstance(tensor_payload, cls):
+            raise TypeError("envelope did not produce a TensorPayload")
+        return tensor_payload
+
 
 @dataclass(frozen=True)
 class TailTokenResult: