fix(cli): guard crew chat description helpers against LLM failures

lib/crewai/src/crewai/cli/crew_chat.py

@@ -25,6 +25,9 @@ from crewai.utilities.version import get_crewai_version
 
 MIN_REQUIRED_VERSION: Final[Literal["0.98.0"]] = "0.98.0"
 
+DEFAULT_INPUT_DESCRIPTION: Final[str] = "Input value for the crew's tasks and agents."
+DEFAULT_CREW_DESCRIPTION: Final[str] = "A CrewAI crew."
+
 
 def check_conversational_crews_version(
     crewai_version: str, pyproject_data: dict[str, Any]
@@ -381,7 +384,10 @@ def load_crew_and_name() -> tuple[Crew, str]:
 
 
 def generate_crew_chat_inputs(
-    crew: Crew, crew_name: str, chat_llm: LLM | BaseLLM
+    crew: Crew,
+    crew_name: str,
+    chat_llm: LLM | BaseLLM,
+    generate_descriptions: bool = True,
 ) -> ChatInputs:
     """
     Generates the ChatInputs required for the crew by analyzing the tasks and agents.
@@ -390,21 +396,28 @@ def generate_crew_chat_inputs(
         crew (Crew): The crew object containing tasks and agents.
         crew_name (str): The name of the crew.
         chat_llm: The chat language model to use for AI calls.
+        generate_descriptions: When True (default), use the LLM to generate
+            input and crew descriptions. When False, skip all LLM calls and
+            return static defaults. Production callers that invoke this at
+            startup should pass ``False`` to avoid blocking on the LLM.
 
     Returns:
         ChatInputs: An object containing the crew's name, description, and input fields.
     """
-    # Extract placeholders from tasks and agents
     required_inputs = fetch_required_inputs(crew)
 
-    # Generate descriptions for each input using AI
     input_fields = []
     for input_name in required_inputs:
-        description = generate_input_description_with_ai(input_name, crew, chat_llm)
+        if generate_descriptions:
+            description = generate_input_description_with_ai(input_name, crew, chat_llm)
+        else:
+            description = DEFAULT_INPUT_DESCRIPTION
         input_fields.append(ChatInputField(name=input_name, description=description))
 
-    # Generate crew description using AI
-    crew_description = generate_crew_description_with_ai(crew, chat_llm)
+    if generate_descriptions:
+        crew_description = generate_crew_description_with_ai(crew, chat_llm)
+    else:
+        crew_description = DEFAULT_CREW_DESCRIPTION
 
     return ChatInputs(
         crew_name=crew_name, crew_description=crew_description, inputs=input_fields
@@ -482,7 +495,15 @@ def generate_input_description_with_ai(
         "Context:\n"
         f"{context}"
     )
-    response = chat_llm.call(messages=[{"role": "user", "content": prompt}])
+    try:
+        response = chat_llm.call(messages=[{"role": "user", "content": prompt}])
+    except Exception as exc:
+        click.secho(
+            f"Warning: failed to generate input description for '{input_name}' "
+            f"({exc}); using default.",
+            fg="yellow",
+        )
+        return DEFAULT_INPUT_DESCRIPTION
     return str(response).strip()
 
 
@@ -532,5 +553,12 @@ def generate_crew_description_with_ai(crew: Crew, chat_llm: LLM | BaseLLM) -> st
         "Context:\n"
         f"{context}"
     )
-    response = chat_llm.call(messages=[{"role": "user", "content": prompt}])
+    try:
+        response = chat_llm.call(messages=[{"role": "user", "content": prompt}])
+    except Exception as exc:
+        click.secho(
+            f"Warning: failed to generate crew description ({exc}); using default.",
+            fg="yellow",
+        )
+        return DEFAULT_CREW_DESCRIPTION
     return str(response).strip()

lib/crewai/tests/cli/test_crew_chat.py

@@ -0,0 +1,116 @@
+"""Tests for ``crewai.cli.crew_chat`` startup-safety helpers."""
+
+from unittest import mock
+
+from crewai.cli.crew_chat import (
+    DEFAULT_CREW_DESCRIPTION,
+    DEFAULT_INPUT_DESCRIPTION,
+    generate_crew_chat_inputs,
+    generate_crew_description_with_ai,
+    generate_input_description_with_ai,
+)
+
+
+def _make_crew(
+    *,
+    task_description: str = "",
+    expected_output: str = "",
+    agent_role: str = "",
+    agent_goal: str = "",
+    agent_backstory: str = "",
+    inputs: set[str] | None = None,
+) -> mock.Mock:
+    task = mock.Mock()
+    task.description = task_description
+    task.expected_output = expected_output
+
+    agent = mock.Mock()
+    agent.role = agent_role
+    agent.goal = agent_goal
+    agent.backstory = agent_backstory
+
+    crew = mock.Mock()
+    crew.tasks = [task]
+    crew.agents = [agent]
+    crew.fetch_inputs = mock.Mock(return_value=inputs or set())
+    return crew
+
+
+def test_generate_input_description_falls_back_on_llm_failure() -> None:
+    crew = _make_crew(task_description="Summarize {topic} for the team.")
+    chat_llm = mock.Mock()
+    chat_llm.call.side_effect = RuntimeError("APIConnectionError")
+
+    description = generate_input_description_with_ai("topic", crew, chat_llm)
+
+    assert description == DEFAULT_INPUT_DESCRIPTION
+    chat_llm.call.assert_called_once()
+
+
+def test_generate_crew_description_falls_back_on_llm_failure() -> None:
+    crew = _make_crew(task_description="Summarize topic for the team.")
+    chat_llm = mock.Mock()
+    chat_llm.call.side_effect = RuntimeError("APIConnectionError")
+
+    description = generate_crew_description_with_ai(crew, chat_llm)
+
+    assert description == DEFAULT_CREW_DESCRIPTION
+    chat_llm.call.assert_called_once()
+
+
+def test_generate_input_description_returns_llm_response_on_success() -> None:
+    crew = _make_crew(task_description="Summarize {topic} for the team.")
+    chat_llm = mock.Mock()
+    chat_llm.call.return_value = "  the subject to summarize  "
+
+    description = generate_input_description_with_ai("topic", crew, chat_llm)
+
+    assert description == "the subject to summarize"
+
+
+def test_generate_crew_chat_inputs_skips_llm_when_descriptions_disabled() -> None:
+    crew = _make_crew(
+        task_description="Summarize {topic} for the team.",
+        inputs={"topic"},
+    )
+    chat_llm = mock.Mock()
+
+    chat_inputs = generate_crew_chat_inputs(
+        crew, "demo-crew", chat_llm, generate_descriptions=False
+    )
+
+    assert chat_inputs.crew_name == "demo-crew"
+    assert chat_inputs.crew_description == DEFAULT_CREW_DESCRIPTION
+    assert len(chat_inputs.inputs) == 1
+    assert chat_inputs.inputs[0].name == "topic"
+    assert chat_inputs.inputs[0].description == DEFAULT_INPUT_DESCRIPTION
+    chat_llm.call.assert_not_called()
+
+
+def test_generate_crew_chat_inputs_uses_llm_by_default() -> None:
+    crew = _make_crew(
+        task_description="Summarize {topic} for the team.",
+        inputs={"topic"},
+    )
+    chat_llm = mock.Mock()
+    chat_llm.call.side_effect = ["the subject to summarize", "summarize topics"]
+
+    chat_inputs = generate_crew_chat_inputs(crew, "demo-crew", chat_llm)
+
+    assert chat_inputs.crew_description == "summarize topics"
+    assert chat_inputs.inputs[0].description == "the subject to summarize"
+    assert chat_llm.call.call_count == 2
+
+
+def test_generate_crew_chat_inputs_falls_back_when_llm_fails_mid_run() -> None:
+    crew = _make_crew(
+        task_description="Summarize {topic} for the team.",
+        inputs={"topic"},
+    )
+    chat_llm = mock.Mock()
+    chat_llm.call.side_effect = RuntimeError("APIConnectionError")
+
+    chat_inputs = generate_crew_chat_inputs(crew, "demo-crew", chat_llm)
+
+    assert chat_inputs.crew_description == DEFAULT_CREW_DESCRIPTION
+    assert chat_inputs.inputs[0].description == DEFAULT_INPUT_DESCRIPTION

uv.lock

@@ -13,7 +13,7 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-04-28T00:00:00Z"
+exclude-newer = "2026-04-27T16:00:00Z"
 
 [manifest]
 members = [