Add C++ and Python low-latency inference docs

README.md

@@ -176,6 +176,8 @@ pip install huggingface_hub
 python download_from_hf.py --low-latency
 ```
 
+### C++ deployment
+
 Simulation:
 
 ```bash
@@ -201,6 +203,37 @@ cd gear_sonic_deploy
 `_encoder.onnx` and `_decoder.onnx` internally. For the full VLA deployment
 flow, see the [VLA Inference guide](https://nvlabs.github.io/GR00T-WholeBodyControl/tutorials/vla_inference.html).
 
+### Python launcher
+
+The Python VLA launcher can start the same low-latency C++ deployment pane and
+run the Python VLA client, keyboard publisher, and optional data exporter:
+
+```bash
+python gear_sonic/scripts/launch_inference.py \
+    --deploy-checkpoint policy/low_latency/model \
+    --deploy-obs-config policy/low_latency/observation_config.yaml \
+    --camera-host 192.168.123.164 \
+    --prompt "pick up the cup"
+```
+
+### Python checkpoint evaluation
+
+For Isaac Lab evaluation or rendering from the released PyTorch checkpoint:
+
+```bash
+python download_from_hf.py --training --low-latency
+python download_from_hf.py --sample
+
+python gear_sonic/eval_agent_trl.py \
+    +checkpoint=low_latency/last.pt \
+    +headless=False \
+    ++num_envs=1 \
+    ++manager_env.observations.policy.enable_corruption=False \
+    ++manager_env.observations.tokenizer.enable_corruption=False \
+    "++manager_env.commands.motion.motion_lib_cfg.motion_file=sample_data/robot_filtered" \
+    "++manager_env.commands.motion.motion_lib_cfg.smpl_motion_file=sample_data/smpl_filtered"
+```
+
 ## Documentation
 
 📚 **[Full Documentation](https://nvlabs.github.io/GR00T-WholeBodyControl/)**