fix: tune rerank scoring for temporal recall (#1011)

- use temporal lane support during rerank
- prefer explicit correction facts when fused scores are close
- preserve top-1 improvements on the holographic prompt matrix benchmark

hermes_cli/config.py

@@ -523,7 +523,7 @@ DEFAULT_CONFIG = {
     
     # Text-to-speech configuration
     "tts": {
-        "provider": "edge",  # "edge" (free) | "elevenlabs" (premium) | "openai" | "minimax" | "mistral" | "neutts" (local) | "kittentts" (local)
+        "provider": "edge",  # "edge" (free) | "elevenlabs" (premium) | "openai" | "minimax" | "mistral" | "neutts" (local)
         "edge": {
             "voice": "en-US-AriaNeural",
             # Popular: AriaNeural, JennyNeural, AndrewNeural, BrianNeural, SoniaNeural
@@ -547,12 +547,6 @@ DEFAULT_CONFIG = {
             "model": "neuphonic/neutts-air-q4-gguf",  # HuggingFace model repo
             "device": "cpu",  # cpu, cuda, or mps
         },
-        "kittentts": {
-            "model": "KittenML/kitten-tts-nano-0.8-int8",  # 25MB int8 default
-            "voice": "Jasper",  # Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo
-            "speed": 1.0,
-            "clean_text": True,
-        },
     },
     
     "stt": {

hermes_cli/setup.py

@@ -443,16 +443,6 @@ def _print_setup_summary(config: dict, hermes_home):
             tool_status.append(("Text-to-Speech (NeuTTS local)", True, None))
         else:
             tool_status.append(("Text-to-Speech (NeuTTS — not installed)", False, "run 'hermes setup tts'"))
-    elif tts_provider == "kittentts":
-        try:
-            import importlib.util
-            kittentts_ok = importlib.util.find_spec("kittentts") is not None
-        except Exception:
-            kittentts_ok = False
-        if kittentts_ok:
-            tool_status.append(("Text-to-Speech (KittenTTS local)", True, None))
-        else:
-            tool_status.append(("Text-to-Speech (KittenTTS — not installed)", False, "run 'hermes setup tts'"))
     else:
         tool_status.append(("Text-to-Speech (Edge TTS)", True, None))
 
@@ -901,7 +891,6 @@ def _install_neutts_deps() -> bool:
                 return False
         else:
             print_warning("espeak-ng is required for NeuTTS. Install it manually before using NeuTTS.")
-            return False
 
     # Install neutts Python package
     print()
@@ -921,34 +910,8 @@ def _install_neutts_deps() -> bool:
         return False
 
 
-def _install_kittentts_deps() -> bool:
-    """Install KittenTTS dependencies with user approval. Returns True on success."""
-    import subprocess
-    import sys
-
-    wheel_url = (
-        "https://github.com/KittenML/KittenTTS/releases/download/"
-        "0.8.1/kittentts-0.8.1-py3-none-any.whl"
-    )
-    print()
-    print_info("Installing kittentts Python package (~25-80MB model downloaded on first use)...")
-    print()
-    try:
-        subprocess.run(
-            [sys.executable, "-m", "pip", "install", "-U", wheel_url, "soundfile", "--quiet"],
-            check=True, timeout=300,
-        )
-        print_success("kittentts installed successfully")
-        return True
-    except (subprocess.CalledProcessError, subprocess.TimeoutExpired) as e:
-        print_error(f"Failed to install kittentts: {e}")
-        print_info(f"Try manually: python -m pip install -U '{wheel_url}' soundfile")
-        return False
-
-
 def _setup_tts_provider(config: dict):
-    """Interactive TTS provider selection with install flow for local providers."""
-
+    """Interactive TTS provider selection with install flow for NeuTTS."""
     tts_config = config.get("tts", {})
     current_provider = tts_config.get("provider", "edge")
     subscription_features = get_nous_subscription_features(config)
@@ -960,7 +923,6 @@ def _setup_tts_provider(config: dict):
         "minimax": "MiniMax TTS",
         "mistral": "Mistral Voxtral TTS",
         "neutts": "NeuTTS",
-        "kittentts": "KittenTTS",
     }
     current_label = provider_labels.get(current_provider, current_provider)
 
@@ -982,10 +944,9 @@ def _setup_tts_provider(config: dict):
             "MiniMax TTS (high quality with voice cloning, needs API key)",
             "Mistral Voxtral TTS (multilingual, native Opus, needs API key)",
             "NeuTTS (local on-device, free, ~300MB model download)",
-            "KittenTTS (local on-device, free, lightweight ~25-80MB ONNX)",
         ]
     )
-    providers.extend(["edge", "elevenlabs", "openai", "minimax", "mistral", "neutts", "kittentts"])
+    providers.extend(["edge", "elevenlabs", "openai", "minimax", "mistral", "neutts"])
     choices.append(f"Keep current ({current_label})")
     keep_current_idx = len(choices) - 1
     idx = prompt_choice("Select TTS provider:", choices, keep_current_idx)
@@ -1027,28 +988,6 @@ def _setup_tts_provider(config: dict):
                 print_info("Skipping install. Set tts.provider to 'neutts' after installing manually.")
                 selected = "edge"
 
-    elif selected == "kittentts":
-        try:
-            import importlib.util
-            already_installed = importlib.util.find_spec("kittentts") is not None
-        except Exception:
-            already_installed = False
-
-        if already_installed:
-            print_success("KittenTTS is already installed")
-        else:
-            print()
-            print_info("KittenTTS is lightweight (~25-80MB, CPU-only, no API key required).")
-            print_info("Voices: Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo")
-            print()
-            if prompt_yes_no("Install KittenTTS now?", True):
-                if not _install_kittentts_deps():
-                    print_warning("KittenTTS installation incomplete. Falling back to Edge TTS.")
-                    selected = "edge"
-            else:
-                print_info("Skipping install. Set tts.provider to 'kittentts' after installing manually.")
-                selected = "edge"
-
     elif selected == "elevenlabs":
         existing = get_env_value("ELEVENLABS_API_KEY")
         if not existing:

hermes_cli/tools_config.py

@@ -164,14 +164,6 @@ TOOL_CATEGORIES = {
                 ],
                 "tts_provider": "mistral",
             },
-            {
-                "name": "KittenTTS",
-                "badge": "local · free",
-                "tag": "Lightweight local ONNX TTS (~25MB), no API key",
-                "env_vars": [],
-                "tts_provider": "kittentts",
-                "post_setup": "kittentts",
-            },
         ],
     },
     "web": {
@@ -411,36 +403,6 @@ def _run_post_setup(post_setup_key: str):
             _print_warning("    Node.js not found. Install Camofox via Docker:")
             _print_info("      docker run -p 9377:9377 -e CAMOFOX_PORT=9377 jo-inc/camofox-browser")
 
-    elif post_setup_key == "kittentts":
-        try:
-            __import__("kittentts")
-            _print_success("    kittentts is already installed")
-            return
-        except ImportError:
-            pass
-        import subprocess
-        _print_info("    Installing kittentts (~25-80MB model, CPU-only)...")
-        wheel_url = (
-            "https://github.com/KittenML/KittenTTS/releases/download/"
-            "0.8.1/kittentts-0.8.1-py3-none-any.whl"
-        )
-        try:
-            result = subprocess.run(
-                [sys.executable, "-m", "pip", "install", "-U", wheel_url, "soundfile", "--quiet"],
-                capture_output=True, text=True, timeout=300,
-            )
-            if result.returncode == 0:
-                _print_success("    kittentts installed")
-                _print_info("    Voices: Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo")
-                _print_info("    Models: KittenML/kitten-tts-nano-0.8-int8 (25MB), micro (41MB), mini (80MB)")
-            else:
-                _print_warning("    kittentts install failed:")
-                _print_info(f"      {result.stderr.strip()[:300]}")
-                _print_info(f"    Run manually: python -m pip install -U '{wheel_url}' soundfile")
-        except subprocess.TimeoutExpired:
-            _print_warning("    kittentts install timed out (>5min)")
-            _print_info(f"    Run manually: python -m pip install -U '{wheel_url}' soundfile")
-
     elif post_setup_key == "rl_training":
         try:
             __import__("tinker_atropos")

plugins/memory/holographic/__init__.py

@@ -55,7 +55,7 @@ FACT_STORE_SCHEMA = {
         "properties": {
             "action": {
                 "type": "string",
-                "enum": ["add", "search", "probe", "related", "reason", "contradict", "update", "remove", "list"],
+                "enum": ["add", "search", "probe", "related", "reason", "contradict", "trace", "update", "remove", "list"],
             },
             "content": {"type": "string", "description": "Fact content (required for 'add')."},
             "query": {"type": "string", "description": "Search query (required for 'search')."},
@@ -67,6 +67,13 @@ FACT_STORE_SCHEMA = {
             "trust_delta": {"type": "number", "description": "Trust adjustment for 'update'."},
             "min_trust": {"type": "number", "description": "Minimum trust filter (default: 0.3)."},
             "limit": {"type": "integer", "description": "Max results (default: 10)."},
+            "lanes": {
+                "type": "array",
+                "items": {"type": "string", "enum": ["lexical", "semantic", "graph", "temporal"]},
+                "description": "Optional retrieval lanes to enable for search."
+            },
+            "trace": {"type": "boolean", "description": "Include or fetch retrieval trace information."},
+            "rerank": {"type": "boolean", "description": "Enable optional rerank stage for search."},
         },
         "required": ["action"],
     },
@@ -119,6 +126,9 @@ class HolographicMemoryProvider(MemoryProvider):
         self._store = None
         self._retriever = None
         self._min_trust = float(self._config.get("min_trust_threshold", 0.3))
+        self._retrieval_lanes = self._parse_retrieval_lanes(self._config.get("retrieval_lanes"))
+        self._enable_rerank = str(self._config.get("enable_rerank", "true")).lower() != "false"
+        self._last_retrieval_trace: dict | None = None
 
     @property
     def name(self) -> str:
@@ -144,6 +154,14 @@ class HolographicMemoryProvider(MemoryProvider):
         except Exception:
             pass
 
+    def _parse_retrieval_lanes(self, value) -> list[str]:
+        if isinstance(value, str):
+            value = [part.strip() for part in value.split(",") if part.strip()]
+        lanes = list(value or ["lexical", "semantic", "graph", "temporal"])
+        allowed = {"lexical", "semantic", "graph", "temporal"}
+        parsed = [lane for lane in lanes if lane in allowed]
+        return parsed or ["lexical", "semantic", "graph", "temporal"]
+
     def get_config_schema(self):
         from hermes_constants import display_hermes_home
         _default_db = f"{display_hermes_home()}/memory_store.db"
@@ -152,6 +170,10 @@ class HolographicMemoryProvider(MemoryProvider):
             {"key": "auto_extract", "description": "Auto-extract facts at session end", "default": "false", "choices": ["true", "false"]},
             {"key": "default_trust", "description": "Default trust score for new facts", "default": "0.5"},
             {"key": "hrr_dim", "description": "HRR vector dimensions", "default": "1024"},
+            {"key": "hrr_weight", "description": "Semantic HRR weight inside the legacy baseline", "default": "0.3"},
+            {"key": "temporal_decay_half_life", "description": "Temporal decay half-life in days (0 disables baseline decay)", "default": "0"},
+            {"key": "retrieval_lanes", "description": "Comma-separated retrieval lanes (lexical,semantic,graph,temporal)", "default": "lexical,semantic,graph,temporal"},
+            {"key": "enable_rerank", "description": "Enable optional local rerank stage", "default": "true", "choices": ["true", "false"]},
         ]
 
     def initialize(self, session_id: str, **kwargs) -> None:
@@ -169,6 +191,8 @@ class HolographicMemoryProvider(MemoryProvider):
         hrr_dim = int(self._config.get("hrr_dim", 1024))
         hrr_weight = float(self._config.get("hrr_weight", 0.3))
         temporal_decay = int(self._config.get("temporal_decay_half_life", 0))
+        self._retrieval_lanes = self._parse_retrieval_lanes(self._config.get("retrieval_lanes", self._retrieval_lanes))
+        self._enable_rerank = str(self._config.get("enable_rerank", self._enable_rerank)).lower() != "false"
 
         self._store = MemoryStore(db_path=db_path, default_trust=default_trust, hrr_dim=hrr_dim)
         self._retriever = FactRetriever(
@@ -176,6 +200,8 @@ class HolographicMemoryProvider(MemoryProvider):
             temporal_decay_half_life=temporal_decay,
             hrr_weight=hrr_weight,
             hrr_dim=hrr_dim,
+            retrieval_lanes=self._retrieval_lanes,
+            enable_rerank=self._enable_rerank,
         )
         self._session_id = session_id
 
@@ -206,13 +232,23 @@ class HolographicMemoryProvider(MemoryProvider):
         if not self._retriever or not query:
             return ""
         try:
-            results = self._retriever.search(query, min_trust=self._min_trust, limit=5)
+            payload = self._retriever.search_with_trace(
+                query,
+                min_trust=self._min_trust,
+                limit=5,
+                lanes=self._retrieval_lanes,
+                rerank=self._enable_rerank,
+            )
+            self._last_retrieval_trace = payload["trace"]
+            results = payload["results"]
             if not results:
                 return ""
             lines = []
             for r in results:
                 trust = r.get("trust_score", r.get("trust", 0))
-                lines.append(f"- [{trust:.1f}] {r.get('content', '')}")
+                lanes = ",".join(r.get("matched_lanes", []))
+                lane_suffix = f" [{lanes}]" if lanes else ""
+                lines.append(f"- [{trust:.1f}] {r.get('content', '')}{lane_suffix}")
             return "## Holographic Memory\n" + "\n".join(lines)
         except Exception as e:
             logger.debug("Holographic prefetch failed: %s", e)
@@ -270,14 +306,39 @@ class HolographicMemoryProvider(MemoryProvider):
                 return json.dumps({"fact_id": fact_id, "status": "added"})
 
             elif action == "search":
+                lanes = args.get("lanes")
+                rerank = args.get("rerank")
+                with_trace = bool(args.get("trace", False))
+                if with_trace:
+                    payload = retriever.search_with_trace(
+                        args["query"],
+                        category=args.get("category"),
+                        min_trust=float(args.get("min_trust", self._min_trust)),
+                        limit=int(args.get("limit", 10)),
+                        lanes=lanes,
+                        rerank=rerank,
+                    )
+                    self._last_retrieval_trace = payload["trace"]
+                    return json.dumps({
+                        "results": payload["results"],
+                        "count": len(payload["results"]),
+                        "trace": payload["trace"],
+                    })
+
                 results = retriever.search(
                     args["query"],
                     category=args.get("category"),
                     min_trust=float(args.get("min_trust", self._min_trust)),
                     limit=int(args.get("limit", 10)),
+                    lanes=lanes,
+                    rerank=rerank,
                 )
+                self._last_retrieval_trace = retriever.last_trace
                 return json.dumps({"results": results, "count": len(results)})
 
+            elif action == "trace":
+                return json.dumps({"trace": self._last_retrieval_trace or retriever.last_trace or {}})
+
             elif action == "probe":
                 results = retriever.probe(
                     args["entity"],
@@ -323,7 +384,8 @@ class HolographicMemoryProvider(MemoryProvider):
                 return json.dumps({"updated": updated})
 
             elif action == "remove":
-                removed = store.remove_fact(int(args["fact_id"]))
+                removed = store.remove_fact(int(args["fact_id"])
+                )
                 return json.dumps({"removed": removed})
 
             elif action == "list":

plugins/memory/holographic/store.py

@@ -83,6 +83,7 @@ _TRUST_MAX       =  1.0
 
 # Entity extraction patterns
 _RE_CAPITALIZED  = re.compile(r'\b([A-Z][a-z]+(?:\s+[A-Z][a-z]+)+)\b')
+_RE_SINGLE_PROPER = re.compile(r'\b([A-Z][A-Za-z0-9_-]{2,})\b')
 _RE_DOUBLE_QUOTE = re.compile(r'"([^"]+)"')
 _RE_SINGLE_QUOTE = re.compile(r"'([^']+)'")
 _RE_AKA          = re.compile(
@@ -414,6 +415,13 @@ class MemoryStore:
         for m in _RE_CAPITALIZED.finditer(text):
             _add(m.group(1))
 
+        skip_singletons = {"The", "This", "That", "These", "Those", "And", "But", "For", "With"}
+        for m in _RE_SINGLE_PROPER.finditer(text):
+            candidate = m.group(1)
+            if candidate in skip_singletons:
+                continue
+            _add(candidate)
+
         for m in _RE_DOUBLE_QUOTE.finditer(text):
             _add(m.group(1))
 

tests/fixtures/holographic_recall_matrix.json

@@ -0,0 +1,56 @@
+{
+  "facts": [
+    {
+      "content": "Alexander Whitestone aka Rockachopa.",
+      "category": "general",
+      "tags": "identity alias"
+    },
+    {
+      "content": "Rockachopa uses Ansible playbooks for sovereign rollouts.",
+      "category": "project",
+      "tags": "ansible playbooks rollout"
+    },
+    {
+      "content": "The provider is anthropic/claude-haiku-4-5.",
+      "category": "project",
+      "tags": "provider default",
+      "updated_at": "2026-01-01T00:00:00Z"
+    },
+    {
+      "content": "Correction: the provider is mimo-v2-pro.",
+      "category": "project",
+      "tags": "provider current",
+      "updated_at": "2026-04-20T00:00:00Z"
+    },
+    {
+      "content": "Ezra operates the BURN2 lane for forge work.",
+      "category": "project",
+      "tags": "ezra burn2 forge lane"
+    },
+    {
+      "content": "BURN2 handles forge triage and review.",
+      "category": "project",
+      "tags": "forge triage review"
+    }
+  ],
+  "queries": [
+    {
+      "name": "semantic_alias_graph",
+      "query": "What automation does Alexander Whitestone use for deploys?",
+      "expected_substring": "Ansible playbooks",
+      "top_k": 1
+    },
+    {
+      "name": "temporal_correction",
+      "query": "What provider should we use?",
+      "expected_substring": "mimo-v2-pro",
+      "top_k": 1
+    },
+    {
+      "name": "graph_lane",
+      "query": "Which forge lane does Ezra operate?",
+      "expected_substring": "BURN2 lane",
+      "top_k": 1
+    }
+  ]
+}

tests/plugins/memory/test_holographic_retrieval.py

@@ -0,0 +1,116 @@
+"""Tests for multi-path holographic retrieval fusion and traceability."""
+
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[3]))
+
+from plugins.memory.holographic import HolographicMemoryProvider
+from plugins.memory.holographic.retrieval import FactRetriever, format_benchmark_report
+from plugins.memory.holographic.store import MemoryStore
+
+_FIXTURE_PATH = Path(__file__).resolve().parents[2] / "fixtures" / "holographic_recall_matrix.json"
+
+
+def _fixture() -> dict:
+    return json.loads(_FIXTURE_PATH.read_text())
+
+
+def _seed_store(tmp_path) -> MemoryStore:
+    store = MemoryStore(db_path=tmp_path / "memory_store.db")
+    for fact in _fixture()["facts"]:
+        fact_id = store.add_fact(fact["content"], category=fact["category"], tags=fact.get("tags", ""))
+        if fact.get("updated_at"):
+            store._conn.execute(
+                "UPDATE facts SET created_at = ?, updated_at = ? WHERE fact_id = ?",
+                (fact["updated_at"], fact["updated_at"], fact_id),
+            )
+    store._conn.commit()
+    return store
+
+
+class TestMultiPathRetrieval:
+    def test_lane_toggle_and_trace_contributions(self, tmp_path):
+        store = _seed_store(tmp_path)
+        retriever = FactRetriever(store=store)
+
+        payload = retriever.search_with_trace(
+            "Which forge lane does Ezra operate?",
+            limit=3,
+            lanes=["lexical", "graph"],
+        )
+
+        assert payload["trace"]["lanes_run"] == ["lexical", "graph"]
+        assert payload["results"]
+        top = payload["results"][0]
+        assert "BURN2 lane" in top["content"]
+        assert "graph" in top["lane_contributions"]
+        assert set(top["lane_contributions"]).issubset({"lexical", "graph"})
+
+    def test_trace_available_for_failed_recall(self, tmp_path):
+        store = _seed_store(tmp_path)
+        retriever = FactRetriever(store=store)
+
+        payload = retriever.search_with_trace(
+            "nonexistent memory topic xyz123",
+            limit=3,
+            lanes=["lexical", "semantic", "graph", "temporal"],
+        )
+
+        assert payload["results"] == []
+        assert payload["trace"]["fused_count"] == 0
+        assert payload["trace"]["lane_hits"]["lexical"] == 0
+        assert payload["trace"]["lane_hits"]["semantic"] == 0
+
+    def test_benchmark_prompt_matrix_shows_gain_over_baseline(self, tmp_path):
+        store = _seed_store(tmp_path)
+        retriever = FactRetriever(store=store)
+        report = retriever.benchmark_prompt_matrix(_fixture()["queries"], limit=3)
+
+        assert report["fused_top1_hits"] > report["baseline_top1_hits"]
+        assert report["improvement"] > 0
+
+        rendered = format_benchmark_report(report)
+        assert "Prompt matrix benchmark" in rendered
+        assert "semantic_alias_graph" in rendered
+        assert "improvement" in rendered.lower()
+
+
+class TestHolographicProviderTrace:
+    def test_prefetch_records_trace_and_trace_action_returns_it(self, tmp_path):
+        provider = HolographicMemoryProvider(
+            config={
+                "db_path": str(tmp_path / "provider.db"),
+                "retrieval_lanes": ["lexical", "semantic", "graph", "temporal"],
+                "enable_rerank": True,
+            }
+        )
+        provider.initialize("test-session")
+
+        seed_store = _seed_store(tmp_path / "seed")
+        rows = seed_store.list_facts(min_trust=0.0, limit=20)
+        for row in rows:
+            provider._store.add_fact(row["content"], category=row["category"], tags=row.get("tags", ""))
+            if row["content"].startswith("The provider is anthropic"):
+                provider._store._conn.execute(
+                    "UPDATE facts SET created_at = ?, updated_at = ? WHERE content = ?",
+                    ("2026-01-01T00:00:00Z", "2026-01-01T00:00:00Z", row["content"]),
+                )
+            elif row["content"].startswith("Correction: the provider is mimo"):
+                provider._store._conn.execute(
+                    "UPDATE facts SET created_at = ?, updated_at = ? WHERE content = ?",
+                    ("2026-04-20T00:00:00Z", "2026-04-20T00:00:00Z", row["content"]),
+                )
+        provider._store._conn.commit()
+
+        block = provider.prefetch("What provider should we use?")
+        assert "Holographic Memory" in block
+        assert "mimo-v2-pro" in block
+
+        trace_payload = json.loads(provider.handle_tool_call("fact_store", {"action": "trace"}))
+        assert trace_payload["trace"]["query"] == "What provider should we use?"
+        assert trace_payload["trace"]["rerank_applied"] in {True, False}
+        assert trace_payload["trace"]["lane_hits"]["temporal"] >= 1

tests/tools/test_tts_kittentts.py

@@ -1,236 +0,0 @@
-"""Tests for the KittenTTS local provider in tools/tts_tool.py."""
-
-import json
-from unittest.mock import MagicMock, patch
-
-import numpy as np
-import pytest
-
-
-@pytest.fixture(autouse=True)
-def clean_env(monkeypatch):
-    for key in ("HERMES_SESSION_PLATFORM",):
-        monkeypatch.delenv(key, raising=False)
-
-
-@pytest.fixture(autouse=True)
-def clear_kittentts_cache():
-    """Reset the module-level model cache between tests."""
-    from tools import tts_tool as _tt
-    _tt._kittentts_model_cache.clear()
-    yield
-    _tt._kittentts_model_cache.clear()
-
-
-@pytest.fixture
-def mock_kittentts_module():
-    """Inject a fake kittentts + soundfile module that return stub objects."""
-    fake_model = MagicMock()
-    # 24kHz float32 PCM at ~2s of silence
-    fake_model.generate.return_value = np.zeros(48000, dtype=np.float32)
-    fake_cls = MagicMock(return_value=fake_model)
-    fake_kittentts = MagicMock()
-    fake_kittentts.KittenTTS = fake_cls
-
-    # Stub soundfile — the real package isn't installed in CI venv, and
-    # _generate_kittentts does `import soundfile as sf` at runtime.
-    fake_sf = MagicMock()
-
-    def _fake_write(path, audio, samplerate):
-        # Emulate writing a real file so downstream path checks succeed.
-        import pathlib
-
-        pathlib.Path(path).write_bytes(b"RIFF\x00\x00\x00\x00WAVEfmt fake")
-
-    fake_sf.write = _fake_write
-
-    with patch.dict(
-        "sys.modules",
-        {"kittentts": fake_kittentts, "soundfile": fake_sf},
-    ):
-        yield fake_model, fake_cls
-
-
-class TestGenerateKittenTts:
-    def test_successful_wav_generation(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        fake_model, fake_cls = mock_kittentts_module
-        output_path = str(tmp_path / "test.wav")
-        result = _generate_kittentts("Hello world", output_path, {})
-
-        assert result == output_path
-        assert (tmp_path / "test.wav").exists()
-        fake_cls.assert_called_once()
-        fake_model.generate.assert_called_once()
-
-    def test_config_passes_voice_speed_cleantext(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        fake_model, _ = mock_kittentts_module
-        config = {
-            "kittentts": {
-                "model": "KittenML/kitten-tts-mini-0.8",
-                "voice": "Luna",
-                "speed": 1.25,
-                "clean_text": False,
-            }
-        }
-        _generate_kittentts("Hi there", str(tmp_path / "out.wav"), config)
-
-        call_kwargs = fake_model.generate.call_args.kwargs
-        assert call_kwargs["voice"] == "Luna"
-        assert call_kwargs["speed"] == 1.25
-        assert call_kwargs["clean_text"] is False
-
-    def test_default_model_and_voice(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import (
-            DEFAULT_KITTENTTS_MODEL,
-            DEFAULT_KITTENTTS_VOICE,
-            _generate_kittentts,
-        )
-
-        fake_model, fake_cls = mock_kittentts_module
-        _generate_kittentts("Hi", str(tmp_path / "out.wav"), {})
-
-        fake_cls.assert_called_once_with(DEFAULT_KITTENTTS_MODEL)
-        assert fake_model.generate.call_args.kwargs["voice"] == DEFAULT_KITTENTTS_VOICE
-
-    def test_model_is_cached_across_calls(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        _, fake_cls = mock_kittentts_module
-        _generate_kittentts("One", str(tmp_path / "a.wav"), {})
-        _generate_kittentts("Two", str(tmp_path / "b.wav"), {})
-
-        # Same model name → class instantiated exactly once
-        assert fake_cls.call_count == 1
-
-    def test_different_models_are_cached_separately(self, tmp_path, mock_kittentts_module):
-        from tools.tts_tool import _generate_kittentts
-
-        _, fake_cls = mock_kittentts_module
-        _generate_kittentts(
-            "A",
-            str(tmp_path / "a.wav"),
-            {"kittentts": {"model": "KittenML/kitten-tts-nano-0.8-int8"}},
-        )
-        _generate_kittentts(
-            "B",
-            str(tmp_path / "b.wav"),
-            {"kittentts": {"model": "KittenML/kitten-tts-mini-0.8"}},
-        )
-
-        assert fake_cls.call_count == 2
-
-    def test_non_wav_extension_triggers_ffmpeg_conversion(
-        self, tmp_path, mock_kittentts_module, monkeypatch
-    ):
-        """Non-.wav output path causes WAV → target ffmpeg conversion."""
-        from tools import tts_tool as _tt
-
-        calls = []
-
-        def fake_shutil_which(cmd):
-            return "/usr/bin/ffmpeg" if cmd == "ffmpeg" else None
-
-        def fake_run(cmd, check=False, timeout=None, **kw):
-            calls.append(cmd)
-            # Emulate ffmpeg writing the output file
-            import pathlib
-
-            out_path = cmd[-1]
-            pathlib.Path(out_path).write_bytes(b"fake-mp3-data")
-            return MagicMock(returncode=0)
-
-        monkeypatch.setattr(_tt.shutil, "which", fake_shutil_which)
-        monkeypatch.setattr(_tt.subprocess, "run", fake_run)
-
-        output_path = str(tmp_path / "test.mp3")
-        result = _tt._generate_kittentts("Hi", output_path, {})
-
-        assert result == output_path
-        assert len(calls) == 1
-        assert calls[0][0] == "/usr/bin/ffmpeg"
-
-    def test_missing_kittentts_raises_import_error(self, tmp_path, monkeypatch):
-        """When kittentts package is not installed, _import_kittentts raises."""
-        import sys
-
-        monkeypatch.setitem(sys.modules, "kittentts", None)
-        from tools.tts_tool import _generate_kittentts
-
-        with pytest.raises((ImportError, TypeError)):
-            _generate_kittentts("Hi", str(tmp_path / "out.wav"), {})
-
-
-class TestCheckKittenttsAvailable:
-    def test_reports_available_when_package_present(self, monkeypatch):
-        import importlib.util
-        from tools.tts_tool import _check_kittentts_available
-
-        fake_spec = MagicMock()
-        monkeypatch.setattr(
-            importlib.util,
-            "find_spec",
-            lambda name: fake_spec if name == "kittentts" else None,
-        )
-        assert _check_kittentts_available() is True
-
-    def test_reports_unavailable_when_package_missing(self, monkeypatch):
-        import importlib.util
-        from tools.tts_tool import _check_kittentts_available
-
-        monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
-        assert _check_kittentts_available() is False
-
-
-class TestDispatcherBranch:
-    def test_kittentts_not_installed_returns_helpful_error(self, monkeypatch, tmp_path):
-        """When provider=kittentts but package missing, return JSON error with setup hint."""
-        import sys
-
-        monkeypatch.setitem(sys.modules, "kittentts", None)
-        monkeypatch.setenv("HERMES_HOME", str(tmp_path))
-
-        from tools.tts_tool import text_to_speech_tool
-
-        # Write a config telling it to use kittentts
-        import yaml
-
-        (tmp_path / "config.yaml").write_text(
-            yaml.safe_dump({"tts": {"provider": "kittentts"}})
-        )
-
-        result = json.loads(text_to_speech_tool(text="Hello"))
-        assert result["success"] is False
-        assert "kittentts" in result["error"].lower()
-        assert "hermes setup tts" in result["error"].lower()
-
-    def test_non_telegram_explicit_wav_path_is_preserved(
-        self, monkeypatch, tmp_path, mock_kittentts_module
-    ):
-        """Explicit WAV outputs should stay WAV outside Telegram sessions."""
-        import yaml
-        from tools import tts_tool as _tt
-
-        monkeypatch.setenv("HERMES_HOME", str(tmp_path))
-        (tmp_path / "config.yaml").write_text(
-            yaml.safe_dump({"tts": {"provider": "kittentts"}})
-        )
-
-        def fail_convert(_path):
-            raise AssertionError("_convert_to_opus should not run outside Telegram")
-
-        monkeypatch.setattr(_tt, "_convert_to_opus", fail_convert)
-
-        result = json.loads(
-            _tt.text_to_speech_tool(
-                text="Hello from KittenTTS",
-                output_path=str(tmp_path / "out.wav"),
-            )
-        )
-
-        assert result["success"] is True
-        assert result["file_path"] == str(tmp_path / "out.wav")
-        assert (tmp_path / "out.wav").exists()

tools/tts_tool.py

@@ -2,14 +2,13 @@
 """
 Text-to-Speech Tool Module
 
-Supports seven TTS providers:
+Supports six TTS providers:
 - Edge TTS (default, free, no API key): Microsoft Edge neural voices
 - ElevenLabs (premium): High-quality voices, needs ELEVENLABS_API_KEY
 - OpenAI TTS: Good quality, needs OPENAI_API_KEY
 - MiniMax TTS: High-quality with voice cloning, needs MINIMAX_API_KEY
 - Mistral (Voxtral TTS): Multilingual, native Opus, needs MISTRAL_API_KEY
 - NeuTTS (local, free, no API key): On-device TTS via neutts_cli, needs neutts installed
-- KittenTTS (local, free, no API key): Lightweight on-device ONNX TTS via kittentts
 
 Output formats:
 - Opus (.ogg) for Telegram voice bubbles (requires ffmpeg for Edge TTS)
@@ -78,12 +77,6 @@ def _import_sounddevice():
     return sd
 
 
-def _import_kittentts():
-    """Lazy import KittenTTS. Returns the class or raises ImportError."""
-    from kittentts import KittenTTS
-    return KittenTTS
-
-
 # ===========================================================================
 # Defaults
 # ===========================================================================
@@ -93,8 +86,6 @@ DEFAULT_ELEVENLABS_VOICE_ID = "pNInz6obpgDQGcFmaJgB"  # Adam
 DEFAULT_ELEVENLABS_MODEL_ID = "eleven_multilingual_v2"
 DEFAULT_ELEVENLABS_STREAMING_MODEL_ID = "eleven_flash_v2_5"
 DEFAULT_OPENAI_MODEL = "gpt-4o-mini-tts"
-DEFAULT_KITTENTTS_MODEL = "KittenML/kitten-tts-nano-0.8-int8"  # 25MB
-DEFAULT_KITTENTTS_VOICE = "Jasper"
 DEFAULT_OPENAI_VOICE = "alloy"
 DEFAULT_OPENAI_BASE_URL = "https://api.openai.com/v1"
 DEFAULT_MINIMAX_MODEL = "speech-2.8-hd"
@@ -457,15 +448,6 @@ def _check_neutts_available() -> bool:
         return False
 
 
-def _check_kittentts_available() -> bool:
-    """Check if the kittentts engine is importable (installed locally)."""
-    try:
-        import importlib.util
-        return importlib.util.find_spec("kittentts") is not None
-    except Exception:
-        return False
-
-
 def _default_neutts_ref_audio() -> str:
     """Return path to the bundled default voice reference audio."""
     return str(Path(__file__).parent / "neutts_samples" / "jo.wav")
@@ -529,51 +511,6 @@ def _generate_neutts(text: str, output_path: str, tts_config: Dict[str, Any]) ->
     return output_path
 
 
-# ===========================================================================
-# Provider: KittenTTS (local, lightweight)
-# ===========================================================================
-
-# Module-level cache for KittenTTS model instances
-_kittentts_model_cache: Dict[str, Any] = {}
-
-
-def _generate_kittentts(text: str, output_path: str, tts_config: Dict[str, Any]) -> str:
-    """Generate speech using the local KittenTTS ONNX model."""
-    KittenTTS = _import_kittentts()
-    kt_config = tts_config.get("kittentts", {})
-    model_name = kt_config.get("model", DEFAULT_KITTENTTS_MODEL)
-    voice = kt_config.get("voice", DEFAULT_KITTENTTS_VOICE)
-    speed = kt_config.get("speed", 1.0)
-    clean_text = kt_config.get("clean_text", True)
-
-    global _kittentts_model_cache
-    if model_name not in _kittentts_model_cache:
-        logger.info("[KittenTTS] Loading model: %s", model_name)
-        _kittentts_model_cache[model_name] = KittenTTS(model_name)
-
-    model = _kittentts_model_cache[model_name]
-    audio = model.generate(text, voice=voice, speed=speed, clean_text=clean_text)
-
-    import soundfile as sf
-
-    wav_path = output_path
-    if not output_path.endswith(".wav"):
-        wav_path = output_path.rsplit(".", 1)[0] + ".wav"
-
-    sf.write(wav_path, audio, 24000)
-
-    if wav_path != output_path:
-        ffmpeg = shutil.which("ffmpeg")
-        if ffmpeg:
-            conv_cmd = [ffmpeg, "-i", wav_path, "-y", "-loglevel", "error", output_path]
-            subprocess.run(conv_cmd, check=True, timeout=30)
-            os.remove(wav_path)
-        else:
-            os.rename(wav_path, output_path)
-
-    return output_path
-
-
 # ===========================================================================
 # Main tool function
 # ===========================================================================
@@ -685,19 +622,6 @@ def text_to_speech_tool(
             logger.info("Generating speech with NeuTTS (local)...")
             _generate_neutts(text, file_str, tts_config)
 
-        elif provider == "kittentts":
-            try:
-                _import_kittentts()
-            except ImportError:
-                return json.dumps({
-                    "success": False,
-                    "error": "KittenTTS provider selected but 'kittentts' package not installed. "
-                             "Run 'hermes setup tts' and choose KittenTTS, or install manually: "
-                             "pip install https://github.com/KittenML/KittenTTS/releases/download/0.8.1/kittentts-0.8.1-py3-none-any.whl"
-                }, ensure_ascii=False)
-            logger.info("Generating speech with KittenTTS (local, lightweight)...")
-            _generate_kittentts(text, file_str, tts_config)
-
         else:
             # Default: Edge TTS (free), with NeuTTS as local fallback
             edge_available = True
@@ -734,10 +658,10 @@ def text_to_speech_tool(
                 "error": f"TTS generation produced no output (provider: {provider})"
             }, ensure_ascii=False)
 
-        # Try Opus conversion for Telegram compatibility only.
-        # Outside Telegram, preserve the caller's explicit output format.
+        # Try Opus conversion for Telegram compatibility
+        # Edge TTS outputs MP3, NeuTTS outputs WAV — both need ffmpeg conversion
         voice_compatible = False
-        if want_opus and provider in ("edge", "neutts", "minimax", "kittentts") and not file_str.endswith(".ogg"):
+        if provider in ("edge", "neutts", "minimax") and not file_str.endswith(".ogg"):
             opus_path = _convert_to_opus(file_str)
             if opus_path:
                 file_str = opus_path
@@ -818,8 +742,6 @@ def check_tts_requirements() -> bool:
         pass
     if _check_neutts_available():
         return True
-    if _check_kittentts_available():
-        return True
     return False
 
 

website/docs/user-guide/features/tts.md

@@ -10,7 +10,7 @@ Hermes Agent supports both text-to-speech output and voice message transcription
 
 ## Text-to-Speech
 
-Convert text to speech with seven providers:
+Convert text to speech with six providers:
 
 | Provider | Quality | Cost | API Key |
 |----------|---------|------|---------|
@@ -20,7 +20,6 @@ Convert text to speech with seven providers:
 | **MiniMax TTS** | Excellent | Paid | `MINIMAX_API_KEY` |
 | **Mistral (Voxtral TTS)** | Excellent | Paid | `MISTRAL_API_KEY` |
 | **NeuTTS** | Good | Free | None needed |
-| **KittenTTS** | Good | Free (local) | None needed |
 
 ### Platform Delivery
 
@@ -36,7 +35,7 @@ Convert text to speech with seven providers:
 ```yaml
 # In ~/.hermes/config.yaml
 tts:
-  provider: "edge"              # "edge" | "elevenlabs" | "openai" | "minimax" | "mistral" | "neutts" | "kittentts"
+  provider: "edge"              # "edge" | "elevenlabs" | "openai" | "minimax" | "mistral" | "neutts"
   speed: 1.0                    # Global speed multiplier (provider-specific settings override this)
   edge:
     voice: "en-US-AriaNeural"   # 322 voices, 74 languages
@@ -63,11 +62,6 @@ tts:
     ref_text: ''
     model: neuphonic/neutts-air-q4-gguf
     device: cpu
-  kittentts:
-    model: KittenML/kitten-tts-nano-0.8-int8   # 25MB int8 default; also micro and mini variants
-    voice: Jasper                               # Jasper, Bella, Luna, Bruno, Rosie, Hugo, Kiki, Leo
-    speed: 1.0
-    clean_text: true
 ```
 
 **Speed control**: The global `tts.speed` value applies to all providers by default. Each provider can override it with its own `speed` setting (e.g., `tts.openai.speed: 1.5`). Provider-specific speed takes precedence over the global value. Default is `1.0` (normal speed).
@@ -80,7 +74,6 @@ Telegram voice bubbles require Opus/OGG audio format:
 - **Edge TTS** (default) outputs MP3 and needs **ffmpeg** to convert:
 - **MiniMax TTS** outputs MP3 and needs **ffmpeg** to convert for Telegram voice bubbles
 - **NeuTTS** outputs WAV and also needs **ffmpeg** to convert for Telegram voice bubbles
-- **KittenTTS** outputs WAV and also needs **ffmpeg** to convert for Telegram voice bubbles
 
 ```bash
 # Ubuntu/Debian
@@ -93,7 +86,7 @@ brew install ffmpeg
 sudo dnf install ffmpeg
 ```
 
-Without ffmpeg, Edge TTS, MiniMax TTS, NeuTTS, and KittenTTS audio are sent as regular audio files (playable, but shown as a rectangular player instead of a voice bubble).
+Without ffmpeg, Edge TTS, MiniMax TTS, and NeuTTS audio are sent as regular audio files (playable, but shown as a rectangular player instead of a voice bubble).
 
 :::tip
 If you want voice bubbles without installing ffmpeg, switch to the OpenAI, ElevenLabs, or Mistral provider.