From 18a84ef4cbdfd06667c4066724beef8ea0d80aec Mon Sep 17 00:00:00 2001
From: flemming-it <sf@flemming.it>
Date: Tue, 7 Jul 2026 19:18:24 +0200
Subject: [PATCH] fix: clear Ollama-unreachable error naming the endpoint + fix
 hint

Signed-off-by: flemming-it <sf@flemming.it>
---
 src/lib.rs | 31 ++++++++++++++++++++++++++++++-
 1 file changed, 30 insertions(+), 1 deletion(-)

diff --git a/src/lib.rs b/src/lib.rs
index c13d8f1..54d729d 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -35,7 +35,7 @@ pub fn invoke(_ctx: Context, inputs: Inputs) -> Result<Outputs, ModuleError> {
         prompt: &prompt,
     };
     let result = crate::llm::chat_with_identity(&client, &params)
-        .map_err(|e| ModuleError::internal(e.to_string()))?;
+        .map_err(|e| llm_error_to_module_error(e, &endpoint, &model))?;
 
     Ok(Outputs::new()
         .with_text("response", result.response)
@@ -51,6 +51,35 @@ fn payload_text(p: &Payload) -> Option<String> {
     }
 }
 
+/// Turn a transport/protocol error into a message that names the
+/// likely cause and the fix, instead of a raw `ConnectionRefused`.
+/// The endpoint is Ollama-shaped by default, so a connect failure
+/// almost always means Ollama isn't running or the model isn't
+/// pulled.
+fn llm_error_to_module_error(e: crate::llm::LlmError, endpoint: &str, model: &str) -> ModuleError {
+    use crate::llm::LlmError;
+    match e {
+        LlmError::Http(detail) => ModuleError::internal(format!(
+            "LLM endpoint {endpoint} not reachable ({detail}). Is Ollama running? \
+             Start it with `ollama serve`, then pull the model with `ollama pull {model}`. \
+             If the LLM runs elsewhere, set the `endpoint` input to its /api URL."
+        )),
+        LlmError::Status(404) => ModuleError::internal(format!(
+            "LLM endpoint {endpoint} returned 404 for model '{model}' — the model is \
+             likely not pulled. Run `ollama pull {model}` (or check the model name)."
+        )),
+        LlmError::Status(code) => ModuleError::internal(format!(
+            "LLM endpoint {endpoint} returned HTTP {code} for model '{model}'."
+        )),
+        LlmError::Decode(detail) => ModuleError::internal(format!(
+            "LLM response from {endpoint} was not valid Ollama JSON: {detail}"
+        )),
+        LlmError::MissingInput(name) => ModuleError::invalid_input(format!(
+            "missing required input '{name}'"
+        )),
+    }
+}
+
 #[cfg(target_arch = "wasm32")]
 fn make_client() -> WakiClient {
     WakiClient