Apply Hermes optimizations: per-workspace session state file, silent spoken tool activity, clean single-frame turn termination

bot.py

@@ -84,7 +84,7 @@ say them:
 - You can change your AI model on the fly! If the user asks to list available models or change model, run `python bin/model_tool.py list` or `python bin/model_tool.py set <model_name>` (models: luna, gemma, deepseek, gpt-oss, sonnet, etc.).
 - You can open files visually for the user in the Companion Web UI drawer! Run `python bin/web_tool.py show <filepath>`.
 - You can open links or the Companion Web UI in the default browser! Run `python bin/web_tool.py open <url>`.
-- Speak your intent out loud BEFORE calling tools! Give brief guidance on what you are attempting (e.g. "Switching your voice to af_heart now...", "Checking Paseo CLI agents...", "Inspecting bot dot py..."). Speak a short guiding sentence first, then run your tools.
+- Keep implementation details and tool activity silent in the spoken channel. The user can see technical progress in the logs or Companion Web UI; only speak the useful conversational response.
 - Complete multi-step tool calls fully before speaking your final response summary.
 - Be strictly truthful about your findings and never invent fake file contents.
 - The user's words reach you through speech recognition, so expect occasional

hermes_llm.py

@@ -26,7 +26,6 @@ from pipecat.frames.frames import (
     LLMFullResponseStartFrame,
     LLMTextFrame,
     StartFrame,
-    TTSSpeakFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
@@ -44,7 +43,7 @@ _NOISE_TRANSCRIPTS = {
 
 ANSI_ESCAPE = re.compile(r'\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])')
 SESSION_ID_REGEX = re.compile(r"\bsession_id:\s*([^\s]+)", re.IGNORECASE)
-SESSION_STATE_FILE = Path.home() / ".hermes" / "voice-agent-session.json"
+
 
 
 def _strip_ansi(text: str) -> str:
@@ -53,23 +52,6 @@ def _strip_ansi(text: str) -> str:
     return ANSI_ESCAPE.sub("", text).strip()
 
 
-def _get_tool_spoken_phrase(detail: str) -> str | None:
-    d = detail.lower()
-    if "grep" in d or "glob" in d or "search" in d:
-        return "Searching the codebase."
-    elif "read" in d or "view" in d or "inspect" in d:
-        return "Inspecting project files."
-    elif "top" in d or "mem" in d or "ps " in d or "ram" in d:
-        return "Checking system memory."
-    elif "paseo" in d:
-        return "Checking Paseo CLI agents."
-    elif "python" in d or "sh " in d or "bash" in d or "$" in d:
-        return "Running shell command."
-    elif "patch" in d or "edit" in d or "write" in d:
-        return "Updating project files."
-    return None
-
-
 def _clean_spoken_text(text: str) -> str:
     """Clean text for speech output and truncate fake turn generations."""
     if not text:
@@ -165,15 +147,20 @@ class HermesLLM(FrameProcessor):
         self._use_server = use_server
         self._session_renamed = False
 
+        # Keep the conversation lineage with the workspace. A single global
+        # session file can make two voice-agent workspaces resume each other's
+        # Hermes conversations.
+        self._session_state_file = self._cwd / ".hermes-voice-session.json"
+
         # Persisted session ID
         self._session_id: str | None = self._load_session_id()
         if self._session_id:
             logger.info(f"Loaded existing Hermes session ID: {self._session_id}")
 
     def _load_session_id(self) -> str | None:
-        if SESSION_STATE_FILE.exists():
+        if self._session_state_file.exists():
             try:
-                data = json.loads(SESSION_STATE_FILE.read_text())
+                data = json.loads(self._session_state_file.read_text())
                 sid = data.get("session_id")
                 if sid and isinstance(sid, str):
                     return sid.strip()
@@ -183,13 +170,13 @@ class HermesLLM(FrameProcessor):
 
     def _save_session_id(self):
         try:
-            SESSION_STATE_FILE.parent.mkdir(parents=True, exist_ok=True)
+            self._session_state_file.parent.mkdir(parents=True, exist_ok=True)
             if self._session_id:
-                SESSION_STATE_FILE.write_text(
+                self._session_state_file.write_text(
                     json.dumps({"session_id": self._session_id}, indent=2) + "\n"
                 )
-            elif SESSION_STATE_FILE.exists():
-                SESSION_STATE_FILE.unlink()
+            elif self._session_state_file.exists():
+                self._session_state_file.unlink()
         except Exception as e:
             logger.warning(f"Could not save Hermes session state: {e}")
 
@@ -312,6 +299,10 @@ class HermesLLM(FrameProcessor):
         else:
             await self._run_turn_cli(utterance, chunks)
 
+        # The transport-specific runners may fall back from one to the other;
+        # emit exactly one response terminator for the whole turn.
+        await self.push_frame(LLMFullResponseEndFrame())
+
         full_reply = _clean_spoken_text(" ".join(chunks))
         if full_reply:
             self._history.append({"role": "assistant", "content": full_reply})
@@ -359,9 +350,6 @@ class HermesLLM(FrameProcessor):
         except Exception as e:
             logger.warning(f"Hermes server error ({e}), falling back to CLI...")
             await self._run_turn_cli(utterance, chunks)
-        finally:
-            await self.push_frame(LLMFullResponseEndFrame())
-
     async def _run_turn_cli(self, utterance: str, chunks: list[str]):
         """Run turn via Hermes CLI using persistent session tracking."""
         cmd = [self._cli_path, "chat", "-q", utterance, "-Q", "--source", "voice"]
@@ -382,8 +370,6 @@ class HermesLLM(FrameProcessor):
                 env=env,
             )
 
-            spoken_tools = set()
-
             async def _read_stderr(stream):
                 while True:
                     line = await stream.readline()
@@ -403,10 +389,8 @@ class HermesLLM(FrameProcessor):
                         except Exception:
                             pass
 
-                        phrase = _get_tool_spoken_phrase(cleaned)
-                        if phrase and phrase not in spoken_tools:
-                            spoken_tools.add(phrase)
-                            await self.push_frame(TTSSpeakFrame(phrase))
+                        # Keep tool progress visible in logs and the Companion Web UI, but
+                        # do not send implementation details through the spoken channel.
 
             stderr_task = asyncio.create_task(_read_stderr(proc.stderr))
 
@@ -456,5 +440,3 @@ class HermesLLM(FrameProcessor):
             err_msg = "Sorry, I ran into an error generating a response."
             chunks.append(err_msg)
             await self.push_frame(LLMTextFrame(err_msg))
-        finally:
-            await self.push_frame(LLMFullResponseEndFrame())

model_manager.py

@@ -57,6 +57,7 @@ MODEL_ALIASES = {
     "hermes": "hermes-3",
     "hermes3": "hermes-3",
     "hermes-agent": "hermes-agent",
+    "deepseek": "ollama-cloud/deepseek-v4-flash",
     "sonnet": "claude-sonnet-4-6",
     "claude": "claude-sonnet-4-6",
     "opus": "claude-opus-4-6",