fix: rename-completeness sweep + correct install hints + broken doc commands

LICENSE

@@ -4,8 +4,8 @@ License text copyright (c) 2020 MariaDB Corporation Ab, All Rights Reserved.
 Parameters
 
 Licensor:             FastCrest
-Licensed Work:        Reflex Version 0.5.0 or later. The Licensed Work is (c) 2026
-                      FastCrest
+Licensed Work:        Tether (formerly Reflex) Version 0.5.0 or later. The
+                      Licensed Work is (c) 2026 FastCrest
 Additional Use Grant: You may make production use of the Licensed Work, provided
                       Your use does not include offering the Licensed Work to third
                       parties on a hosted or embedded basis in order to compete with 

README.md

@@ -185,9 +185,9 @@ when you're ready for per-robot normalization + ActionGuard clamping.
 Then from your code:
 
 ```python
-from tether.client import ReflexClient
+from tether.client import TetherClient
 
-with ReflexClient("http://localhost:8000") as client:
+with TetherClient("http://localhost:8000") as client:
     with client.episode() as ep:                       # auto episode_id, RTC reset
         result = ep.act(image=numpy_frame, state=[0.1, 0.2, ...])
         print(result["actions"])                       # list of action chunks
@@ -240,9 +240,9 @@ The Python client sets `X-Tether-Key` when `api_key` is provided:
 ```python
 import os
 
-from tether.client import ReflexClient
+from tether.client import TetherClient
 
-with ReflexClient("http://localhost:8000", api_key=os.environ["TETHER_API_KEY"]) as client:
+with TetherClient("http://localhost:8000", api_key=os.environ["TETHER_API_KEY"]) as client:
     result = client.act(
         image=numpy_frame,
         state=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6],

dashboards/grafana_template.json

@@ -2,7 +2,7 @@
   "annotations": {
     "list": []
   },
-  "description": "Reflex VLA serve — out-of-the-box dashboard. 5 panels: latency p99, cache hit rate, in-flight, safety/SLO violations, server up. Tested against Grafana 10.4.0 (schemaVersion 39). Datasource ${DS_PROMETHEUS} resolved at import time. See features/01_serve/subfeatures/_ecosystem/prometheus-grafana.md.",
+  "description": "Tether VLA serve — out-of-the-box dashboard. 5 panels: latency p99, cache hit rate, in-flight, safety/SLO violations, server up. Tested against Grafana 10.4.0 (schemaVersion 39). Datasource ${DS_PROMETHEUS} resolved at import time. See features/01_serve/subfeatures/_ecosystem/prometheus-grafana.md.",
   "editable": true,
   "fiscalYearStartMonth": 0,
   "graphTooltip": 1,
@@ -48,7 +48,7 @@
             "uid": "${DS_PROMETHEUS}"
           },
           "editorMode": "code",
-          "expr": "histogram_quantile(0.99, sum(rate(reflex_act_latency_seconds_bucket[5m])) by (embodiment, le))",
+          "expr": "histogram_quantile(0.99, sum(rate(tether_act_latency_seconds_bucket[5m])) by (embodiment, le))",
           "legendFormat": "p99 — {{embodiment}}",
           "range": true,
           "refId": "A"
@@ -99,7 +99,7 @@
             "uid": "${DS_PROMETHEUS}"
           },
           "editorMode": "code",
-          "expr": "sum(rate(reflex_cache_hit_total[5m])) / (sum(rate(reflex_cache_hit_total[5m])) + sum(rate(reflex_cache_miss_total[5m])))",
+          "expr": "sum(rate(tether_cache_hit_total[5m])) / (sum(rate(tether_cache_hit_total[5m])) + sum(rate(tether_cache_miss_total[5m])))",
           "legendFormat": "Hit rate",
           "refId": "A"
         }
@@ -146,8 +146,8 @@
             "type": "prometheus",
             "uid": "${DS_PROMETHEUS}"
           },
-          "expr": "reflex_server_up",
-          "legendFormat": "reflex serve",
+          "expr": "tether_server_up",
+          "legendFormat": "tether serve",
           "refId": "A"
         }
       ],
@@ -181,7 +181,7 @@
             "type": "prometheus",
             "uid": "${DS_PROMETHEUS}"
           },
-          "expr": "sum(rate(reflex_safety_violations_total[5m])) by (violation_kind)",
+          "expr": "sum(rate(tether_safety_violations_total[5m])) by (violation_kind)",
           "legendFormat": "safety: {{violation_kind}}",
           "refId": "A"
         },
@@ -190,7 +190,7 @@
             "type": "prometheus",
             "uid": "${DS_PROMETHEUS}"
           },
-          "expr": "sum(rate(reflex_slo_violations_total[5m])) by (slo_kind)",
+          "expr": "sum(rate(tether_slo_violations_total[5m])) by (slo_kind)",
           "legendFormat": "SLO: {{slo_kind}}",
           "refId": "B"
         }
@@ -235,7 +235,7 @@
             "type": "prometheus",
             "uid": "${DS_PROMETHEUS}"
           },
-          "expr": "sum(reflex_in_flight_requests) by (embodiment)",
+          "expr": "sum(tether_in_flight_requests) by (embodiment)",
           "legendFormat": "{{embodiment}}",
           "refId": "A"
         }
@@ -247,7 +247,7 @@
   "refresh": "10s",
   "schemaVersion": 39,
   "style": "dark",
-  "tags": ["reflex-vla", "serve"],
+  "tags": ["tether-vla", "serve"],
   "templating": {
     "list": [
       {
@@ -260,15 +260,15 @@
           "type": "prometheus",
           "uid": "${DS_PROMETHEUS}"
         },
-        "definition": "label_values(reflex_act_latency_seconds_count, embodiment)",
+        "definition": "label_values(tether_act_latency_seconds_count, embodiment)",
         "hide": 0,
         "includeAll": true,
         "multi": true,
         "name": "embodiment",
         "options": [],
         "query": {
           "qryType": 1,
-          "query": "label_values(reflex_act_latency_seconds_count, embodiment)",
+          "query": "label_values(tether_act_latency_seconds_count, embodiment)",
           "refId": "PrometheusVariableQueryEditor-VariableQuery"
         },
         "refresh": 1,
@@ -285,15 +285,15 @@
           "type": "prometheus",
           "uid": "${DS_PROMETHEUS}"
         },
-        "definition": "label_values(reflex_act_latency_seconds_count, model_id)",
+        "definition": "label_values(tether_act_latency_seconds_count, model_id)",
         "hide": 0,
         "includeAll": true,
         "multi": true,
         "name": "model_id",
         "options": [],
         "query": {
           "qryType": 1,
-          "query": "label_values(reflex_act_latency_seconds_count, model_id)",
+          "query": "label_values(tether_act_latency_seconds_count, model_id)",
           "refId": "PrometheusVariableQueryEditor-VariableQuery"
         },
         "refresh": 1,
@@ -305,8 +305,8 @@
   "time": { "from": "now-1h", "to": "now" },
   "timepicker": {},
   "timezone": "",
-  "title": "Reflex VLA Serve",
-  "uid": "reflex-vla-serve",
+  "title": "Tether VLA Serve",
+  "uid": "tether-vla-serve",
   "version": 1,
   "weekStart": ""
 }

dashboards/tether_fleet.json

@@ -1,6 +1,6 @@
 {
   "annotations": { "list": [] },
-  "description": "Tether fleet dashboard — per-robot breakdown. Requires `tether serve --robot-id <id>` on each process so the `reflex_robot_info` gauge is populated. Panels join hot metrics against robot_info via `instance`. Tested against Grafana 10.4.0 (schemaVersion 39). See features/01_serve/subfeatures/_ecosystem/fleet-telemetry/fleet-telemetry.md.",
+  "description": "Tether fleet dashboard — per-robot breakdown. Requires `tether serve --robot-id <id>` on each process so the `tether_robot_info` gauge is populated. Panels join hot metrics against robot_info via `instance`. Tested against Grafana 10.4.0 (schemaVersion 39). See features/01_serve/subfeatures/_ecosystem/fleet-telemetry/fleet-telemetry.md.",
   "editable": true,
   "fiscalYearStartMonth": 0,
   "graphTooltip": 1,
@@ -11,7 +11,7 @@
     {
       "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
       "title": "Active robots",
-      "description": "Count of robot processes reporting `reflex_robot_info`. One series per robot_id; drops to 0 when a robot goes offline.",
+      "description": "Count of robot processes reporting `tether_robot_info`. One series per robot_id; drops to 0 when a robot goes offline.",
       "gridPos": { "h": 4, "w": 6, "x": 0, "y": 0 },
       "id": 1,
       "type": "stat",
@@ -30,7 +30,7 @@
       "targets": [
         {
           "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
-          "expr": "count(reflex_robot_info{robot_id=~\"$robot\"})",
+          "expr": "count(tether_robot_info{robot_id=~\"$robot\"})",
           "legendFormat": "robots",
           "refId": "A"
         }
@@ -58,7 +58,7 @@
         {
           "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
           "editorMode": "code",
-          "expr": "histogram_quantile(0.99, sum by (le, instance) (rate(reflex_act_latency_seconds_bucket[5m]))) * on (instance) group_left(robot_id) reflex_robot_info{robot_id=~\"$robot\"}",
+          "expr": "histogram_quantile(0.99, sum by (le, instance) (rate(tether_act_latency_seconds_bucket[5m]))) * on (instance) group_left(robot_id) tether_robot_info{robot_id=~\"$robot\"}",
           "legendFormat": "{{robot_id}}",
           "refId": "A"
         }
@@ -81,7 +81,7 @@
       "targets": [
         {
           "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
-          "expr": "sum by (instance) (rate(reflex_act_latency_seconds_count[1m])) * on (instance) group_left(robot_id) reflex_robot_info{robot_id=~\"$robot\"}",
+          "expr": "sum by (instance) (rate(tether_act_latency_seconds_count[1m])) * on (instance) group_left(robot_id) tether_robot_info{robot_id=~\"$robot\"}",
           "legendFormat": "{{robot_id}}",
           "refId": "A"
         }
@@ -104,7 +104,7 @@
       "targets": [
         {
           "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
-          "expr": "sum by (instance, violation_kind) (increase(reflex_safety_violations_total[5m])) * on (instance) group_left(robot_id) reflex_robot_info{robot_id=~\"$robot\"}",
+          "expr": "sum by (instance, violation_kind) (increase(tether_safety_violations_total[5m])) * on (instance) group_left(robot_id) tether_robot_info{robot_id=~\"$robot\"}",
           "legendFormat": "{{robot_id}} / {{violation_kind}}",
           "refId": "A"
         }
@@ -126,7 +126,7 @@
       "targets": [
         {
           "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
-          "expr": "sum by (instance) (reflex_in_flight_requests) * on (instance) group_left(robot_id) reflex_robot_info{robot_id=~\"$robot\"}",
+          "expr": "sum by (instance) (tether_in_flight_requests) * on (instance) group_left(robot_id) tether_robot_info{robot_id=~\"$robot\"}",
           "legendFormat": "{{robot_id}}",
           "refId": "A"
         }
@@ -148,7 +148,7 @@
       "targets": [
         {
           "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
-          "expr": "sum by (instance, slo_kind) (increase(reflex_slo_violations_total[5m])) * on (instance) group_left(robot_id) reflex_robot_info{robot_id=~\"$robot\"}",
+          "expr": "sum by (instance, slo_kind) (increase(tether_slo_violations_total[5m])) * on (instance) group_left(robot_id) tether_robot_info{robot_id=~\"$robot\"}",
           "legendFormat": "{{robot_id}} / {{slo_kind}}",
           "refId": "A"
         }
@@ -157,20 +157,20 @@
   ],
   "refresh": "10s",
   "schemaVersion": 39,
-  "tags": ["reflex", "fleet", "vla"],
+  "tags": ["tether", "fleet", "vla"],
   "templating": {
     "list": [
       {
         "current": { "selected": true, "text": "All", "value": "$__all" },
         "datasource": { "type": "prometheus", "uid": "${DS_PROMETHEUS}" },
-        "definition": "label_values(reflex_robot_info, robot_id)",
+        "definition": "label_values(tether_robot_info, robot_id)",
         "hide": 0,
         "includeAll": true,
         "label": "Robot",
         "multi": true,
         "name": "robot",
         "options": [],
-        "query": { "query": "label_values(reflex_robot_info, robot_id)", "refId": "StandardVariableQuery" },
+        "query": { "query": "label_values(tether_robot_info, robot_id)", "refId": "StandardVariableQuery" },
         "refresh": 2,
         "regex": "",
         "skipUrlSync": false,
@@ -182,8 +182,8 @@
   "time": { "from": "now-1h", "to": "now" },
   "timepicker": {},
   "timezone": "",
-  "title": "Reflex Fleet",
-  "uid": "reflex-fleet",
+  "title": "Tether Fleet",
+  "uid": "tether-fleet",
   "version": 1,
   "weekStart": "",
   "__inputs": [

docs/getting_started.md

@@ -48,7 +48,7 @@ tether export nvidia/GR00T-N1.6-3B --target orin --output ./gr00t
 Each command:
 1. Downloads the checkpoint from HuggingFace (cached after first run)
 2. Runs the model-specific exporter (auto-dispatches based on key prefix)
-3. Writes ONNX + reflex_config.json into `--output`
+3. Writes ONNX + tether_config.json into `--output`
 4. Validates the ONNX numerically against the PyTorch reference (max_diff < 1e-5)
 5. If trtexec is available, builds a TensorRT engine
 
@@ -60,7 +60,7 @@ After export your output directory looks like:
 ./pi0/
 ├── expert_stack.onnx       # the graph (1.25MB)
 ├── expert_stack.onnx.data  # the weights (~1.3GB for pi0)
-├── reflex_config.json      # model meta — used by serve
+├── tether_config.json      # model meta — used by serve
 └── expert_stack.trt        # TRT engine (only if trtexec was available)
 ```
 

docs/verification.md

@@ -57,7 +57,7 @@ Total: **3 files, 247.5MB**
 | File | Size | SHA256 |
 |---|---|---|
 | `model.onnx` | 245.3MB | `a1b2c3d4...` |
-| `reflex_config.json` | 1.2KB | `e5f6a7b8...` |
+| `tether_config.json` | 1.2KB | `e5f6a7b8...` |
 | `tokenizer.json` | 957KB  | `f9a0b1c2...` |
 ```
 

pyproject.toml

@@ -15,7 +15,10 @@ classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
     "Topic :: Scientific/Engineering :: Artificial Intelligence",
-    "License :: OSI Approved :: Apache Software License",
+    # License is declared via the SPDX `license = "BUSL-1.1"` expression above
+    # (PEP 639). BUSL-1.1 is not OSI-approved, so there is no License ::
+    # classifier — and emitting an Apache one here would both misrepresent the
+    # license and conflict with the SPDX field on modern build backends.
     "Programming Language :: Python :: 3",
 ]
 

reference/NOTES.md

@@ -206,7 +206,7 @@ Our buffer is great, but we lack:
   Steps:
   1. Read `/reference/lerobot/src/lerobot/policies/xvla/action_hub.py` fully.
   2. Extract action space definitions (min/max per joint, continuous vs. discrete).
-  3. Add action denormalization to `predict()` post-inference. Needs a config field in `reflex_config.json` (action_space definition).
+  3. Add action denormalization to `predict()` post-inference. Needs a config field in `tether_config.json` (action_space definition).
   4. For RTC: add soft constraint checking in a new `ActionRTC` class (similar to `ActionGuard`). Return violations as telemetry, let the robot decide to replan.
 
 ### Priority for our roadmap

src/tether/ci_template.py

@@ -50,7 +50,7 @@
 
       - name: Validate round-trip parity
         run: |
-          tether validate ./sv_export --threshold 1e-4 --num-cases 3 --output-json > validate_result.json
+          tether validate export ./sv_export --threshold 1e-4 --num-cases 3 --output-json > validate_result.json
 
       - name: Upload validation report
         if: always()

src/tether/cli.py

@@ -36,7 +36,7 @@
 
 [bold cyan]Most-used:[/bold cyan]
   [green]tether chat[/green]                start the natural-language assistant
-  [green]tether chat --tui[/green]          ↳ full-screen TUI (needs [dim]pip install 'tether\\[tui]'[/dim])
+  [green]tether chat --tui[/green]          ↳ full-screen TUI (needs [dim]pip install 'fastcrest-tether\\[tui]'[/dim])
   [green]tether go --model X[/green]        one-command deploy: probe → pull → export → serve
   [green]tether doctor[/green]              diagnose install + GPU issues
   [green]tether models list[/green]         browse the curated model registry
@@ -3024,7 +3024,7 @@ def _find_lib(libname: str) -> str | None:
     # in the doctor table.
     libs = [
         ("libnvinfer.so.10", "TensorRT runtime",
-         r"pip install 'tether\[serve,gpu]' (brings tensorrt>=10)"),
+         r"pip install 'fastcrest-tether\[serve,gpu]' (brings tensorrt>=10)"),
         ("libcublas.so.12", "CUDA cuBLAS",
          r"pip install nvidia-cublas-cu12 (auto-included in \[serve,gpu])"),
         ("libcudnn.so.9", "CUDA cuDNN",
@@ -3614,7 +3614,7 @@ def _arch_from_name(name: str) -> str:
         add(
             "fastapi + uvicorn",
             False,
-            f"not installed — run `pip install 'tether\\[{extra}]'` for the server",
+            f"not installed — run `pip install 'fastcrest-tether\\[{extra}]'` for the server",
         )
 
     # safetensors

src/tether/verification_report.py

@@ -63,7 +63,7 @@ def _format_parity(parity: dict[str, Any] | None) -> str:
     if not parity:
         return (
             "## Parity\n\n"
-            "_Not yet verified._ Run `tether validate <export_dir>` to populate.\n"
+            "_Not yet verified._ Run `tether validate export <export_dir>` to populate.\n"
         )
     summary = parity.get("summary", {}) or {}
     results = parity.get("results", []) or []
@@ -174,7 +174,7 @@ def write_verification_report(
     if model_id != "unknown":
         lines.append("```bash")
         lines.append(f"tether export {model_id} --target {target} --output <dir>")
-        lines.append("tether validate <dir>")
+        lines.append("tether validate export <dir>")
         lines.append("```")
         lines.append("")
     lines.append(