NousResearch/hermes-agent

Auxiliary and vision LLM timeout configuration issues

Cluster 3404 · agent. Data as of 2026-10-28 11:56 UTC

Nothing open on GitHub. Fix merged in #3597 on 28 Mar 2026. Check it covers your case.

open issues

open PRs

items grouped

Known?: Yes. 3 related items grouped here, 1 issue already closed.
Fix event: A fix was merged to main in PR #3597. Check it covers your case. No release data is tracked.
Tracker: The maintainers' tracker marks this unresolved. That is separate from the fix event.
Still open: Nothing open on GitHub.

Next step: read #3597, then check it covers your case.

Read #3597 Pick up a Lab task

These issues and PRs concern default HTTP timeouts (often 30s) being too short for auxiliary LLM calls, vision analysis, and context compression when using slow or local model endpoints. The work spans bug reports, fixes, and feature requests for making these timeouts configurable and auto-adjusted for local inference.

Open issues0

No open issues.

Open PRs0

No open pull requests.

Fixes on record

Merged to main. A stamp counts the issues a fix is linked to.

#3597 feat(agent): configurable timeouts for auxiliary LLM calls via config.yaml (salvage #3406)

merged to main

files: agent/auxiliary_client.py, agent/context_compressor.py, agent/title_generator.py, hermes_cli/config.py

Show the diff

agent/auxiliary_client.py

@@ -1458,6 +1458,29 @@ def _resolve_task_provider_model(
     return "auto", resolved_model, None, None
 
 
+_DEFAULT_AUX_TIMEOUT = 30.0
+
+
+def _get_task_timeout(task: str, default: float = _DEFAULT_AUX_TIMEOUT) -> float:
+    """Read timeout from auxiliary.{task}.timeout in config, falling back to *default*."""
+    if not task:
+        return default
+    try:
+        from hermes_cli.config import load_config
+        config = load_config()
+    except ImportError:
+        return default
+    aux = config.get("auxiliary", {}) if isinstance(config, dict) else {}
+    task_config = aux.get(task, {}) if isinstance(aux, dict) else {}
+    raw = task_config.get("timeout")
+    if raw is not None:
+        try:
+            return float(raw)
+        except (ValueError, TypeError):
+            pass
+    return default
+
+
 def _build_call_kwargs(
     provider: str,
     model: str,
@@ -1515,7 +1538,7 @@ def call_llm(
     temperature: float = None,
     max_tokens: int = None,
     tools: list = None,
-    timeout: float = 30.0,
+    timeout: float = None,
     extra_body: dict = None,
 ) -> Any:
     """Centralized synchronous LLM call.
@@ -1533,7 +1556,7 @@ def call_llm(
         temperature: Sampling temperature (None = provider default).
         max_tokens: Max output tokens (handles max_tokens vs max_completion_tokens).
         tools: Tool definitions (for function calling).
-        timeout: Request timeout in seconds.
+        timeout: Request timeout in seconds (None = read from auxiliary.{task}.timeout config).
         extra_body: Additional request body fields.
 
     Returns:
@@ -1598,10 +1621,12 @@ def call_llm(
                 f"No LLM provider configured for task={task} provider={resolved_provider}. "
                 f"Run: hermes setup")
 
+    effective_timeout = timeout if timeout is not None else _get_task_timeout(task)
+
     kwargs = _build_call_kwargs(
         resolved_provider, final_model, messages,
         temperature=temperature, max_tokens=[redacted:secret-assignment]
-        tools=tools, timeout=timeout, extra_body=extra_body,
+        tools=tools, timeout=effective_timeout, extra_body=extra_body,
         base_url=resolved_base_url)
 
     # Handle max_tokens vs max_completion_tokens retry
@@ -1683,7 +1708,7 @@ async def async_call_llm(
     temperature: float = None,
     max_tokens: int = None,
     tools: list = None,
-    timeout: float = 30.0,
+    timeout: float = None,
     extra_body: dict = None,
 ) -> Any:
     """Centralized asynchronous LLM call.
@@ -1744,10 +1769,12 @@ async def async_call_llm(
                 f"No LLM provider configured for task={task} provider={resolved_provider}. "
                 f"Run: hermes setup")
 
+    effective_timeout = timeout if timeout is not None else _get_task_timeout(task)
+
     kwargs = _build_call_kwargs(
         resolved_provider, final_model, messages,
         temperature=temperature, max_tokens=[redacted:secret-assignment]
-        tools=tools, timeout=timeout, extra_body=extra_body,
+        tools=tools, timeout=effective_timeout, extra_body=extra_body,
         base_url=resolved_base_url)
 
     try:

agent/context_compressor.py

@@ -347,7 +347,7 @@ def _generate_summary(self, turns_to_summarize: List[Dict[str, Any]]) -> Optiona
                 "messages": [{"role": "user", "content": prompt}],
                 "temperature": 0.3,
                 "max_tokens": [redacted:secret-assignment] * 2,
-                "timeout": 45.0,
+                # timeout resolved from auxiliary.compression.timeout config by call_llm
             }
             if self.summary_model:
                 call_kwargs["model"] = self.summary_model

agent/title_generator.py

@@ -19,7 +19,7 @@
 )
 
 
-def generate_title(user_message: str, assistant_response: str, timeout: float = 15.0) -> Optional[str]:
+def generate_title(user_message: str, assistant_response: str, timeout: float = 30.0) -> Optional[str]:
     """Generate a session title from the first exchange.
 
     Uses the auxiliary LLM client (cheapest/fastest available model).

hermes_cli/config.py

@@ -227,42 +227,49 @@ def ensure_hermes_home():
             "model": "",
             "base_url": "",
             "api_key": "",
+            "timeout": 30,         # seconds — increase for slow local models
         },
         "compression": {
             "provider": "auto",
             "model": "",
             "base_url": "",
             "api_key": "",
+            "timeout": 120,        # seconds — compression summarises large contexts; increase for local models
         },
         "session_search": {
             "provider": "auto",
             "model": "",
             "base_url": "",
             "api_key": "",
+            "timeout": 30,
         },
         "skills_hub": {
             "provider": "auto",
             "model": "",
             "base_url": "",
             "api_key": "",
+            "timeout": 30,
         },
         "approval": {
             "provider": "auto",
             "model": "",           # fast/cheap model recommended (e.g. gemini-flash, haiku)
             "base_url": "",
             "api_key": "",
+            "timeout": 30,
         },
         "mcp": {
             "provider": "auto",
             "model": "",
             "base_url": "",
             "api_key": "",
+            "timeout": 30,
         },
         "flush_memories": {
             "provider": "auto",
             "model": "",
             "base_url": "",
             "api_key": "",
+            "timeout": 30,
         },
     },

1 PR closed without merging

From the close comments: merged via another change 1

#3406 feat(agent): configurable timeouts for auxiliary LLM calls and context compression · merged via another change → #3597

Closed issues · 1

Closed#3404[Feature]: Configurable timeouts for auxiliary call_llm and context compression

How this cluster was grouped

Link evidence (structural links throughout): every member is connected by structural evidence: shared changed files, or a closing/superseded reference.
Pairwise link density 0.67: the share of item pairs that carry a link, counting a structural link in full and a relevance-only link at 0.36. 1.00 means every pair is linked.

Pick up a Lab task

Check whether a fix covers the open issues here, with your own agent. Bring back evidence for maintainers.

Open the Lab

At a glance

Subsystem: agent
Merged PRs: #3597
Closed issues: 1
Attempts: 1 PR closed without merging
Fix link checked: 28 Mar 2026. This confirmation is old and may be out of date (a revert or reopen would not have invalidated it here); re-verify.

For your agent

The same facts, typed.

cluster/3404.json
cluster/3404.md