From d517a3fdf65092dea26feb37c6d622705f07be02 Mon Sep 17 00:00:00 2001
From: Daniel <danitex@danvics.com>
Date: Sun, 13 Sep 2026 06:41:49 +0200
Subject: [PATCH] fix: an empty model reply is logged with its finish reason,
 and a pool batch that gets one is retried once
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Two batches in five came back as a 200 with an empty message — nothing in
the gateway log, nothing in ours. callLiteLLM now says when that happens
(finish reason, completion tokens, whether the tokens went into reasoning),
and the starter-question build tries such a batch once more instead of
writing the category off.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Dv6sqaY6Vq3ChZHMem3cnU
---
 src/utils/ai.js                 | 16 +++++++++++++---
 src/utils/clinicalPromptPool.js |  9 ++++++++-
 2 files changed, 21 insertions(+), 4 deletions(-)

diff --git a/src/utils/ai.js b/src/utils/ai.js
index 81cd75e6..7cbc48ee 100644
--- a/src/utils/ai.js
+++ b/src/utils/ai.js
@@ -366,14 +366,24 @@ async function callLiteLLM(messages, model, temperature, maxTokens, generation)
     max_tokens: maxTokens
   }, generation || {}), generation));
 
+  var choice = completion.choices[0];
+  // An empty reply with a 200 is the one failure nothing else reports: the
+  // gateway is happy, the caller gets '' and a JSON task keeps nothing. Say
+  // what the model said about it — the finish reason and whether the tokens
+  // went into reasoning instead of the answer.
+  if (!choice.message.content && !choice.message.tool_calls) {
+    var reasoningChars = String(choice.message.reasoning_content || choice.message.reasoning || '').length;
+    console.warn('[ai] empty reply from ' + model + ': finish_reason=' + (choice.finish_reason || '?') +
+      ' completion_tokens=' + (completion.usage && completion.usage.completion_tokens) + ' reasoning_chars=' + reasoningChars);
+  }
   return {
     success: true,
-    content: completion.choices[0].message.content,
-    ...(completion.choices[0].message.tool_calls ? { toolCalls: completion.choices[0].message.tool_calls } : {}),
+    content: choice.message.content,
+    ...(choice.message.tool_calls ? { toolCalls: choice.message.tool_calls } : {}),
     model: model,
     provider: 'litellm',
     usage: completion.usage || null,
-    finishReason: completion.choices[0].finish_reason || null
+    finishReason: choice.finish_reason || null
   };
 }
 
diff --git a/src/utils/clinicalPromptPool.js b/src/utils/clinicalPromptPool.js
index bed5a653..dcb468e9 100644
--- a/src/utils/clinicalPromptPool.js
+++ b/src/utils/clinicalPromptPool.js
@@ -360,7 +360,14 @@ function createClinicalPromptPool(opts) {
         });
         var parsed = parseJsonObject(String(ai.content || ''));
         var offered = Array.isArray(parsed.questions) ? parsed.questions.length : 0;
-        if (!offered) console.warn('[clinical-assistant] prompt pool ' + item.category + ' batch ' + (i + 1) + ': nothing parseable in ' + String(ai.content || '').length + ' chars');
+        if (!offered) {
+          // The model answers a JSON task with an empty message now and then —
+          // two batches in five came back with nothing. One more try with the
+          // same snippets is cheap and usually enough.
+          console.warn('[clinical-assistant] prompt pool ' + item.category + ' batch ' + (i + 1) + ': nothing parseable in ' + String(ai.content || '').length + ' chars (finish ' + (ai.finishReason || '?') + '); retrying once');
+          i--; batches++; if (batches > 12) break;
+          continue;
+        }
         else if (parsed.truncated) console.warn('[clinical-assistant] prompt pool ' + item.category + ' batch ' + (i + 1) + ': reply was cut off; ' + offered + ' questions salvaged');
         categoryExamples = normalizeGeneratedExamples(categoryExamples.concat(parsed.questions || []), item).slice(0, item.quota);
       }