Configure clinical assistant reasoning profile

src/routes/clinicalAssistant.js

@@ -36,6 +36,7 @@ var {
 var {
   buildSystemPrompt,
   buildUserPrompt,
+  assistantGenerationOptions,
   finalizeAssistantAnswer
 } = require('../utils/clinicalAnswer');
 
@@ -182,12 +183,17 @@ router.post('/clinical-assistant/chat', async function(req, res) {
     var prepared = await prepareAssistantChat(req.body);
     if (prepared.direct) return res.json(prepared.direct);
 
-    var ai = await callAI(prepared.messages, {
+    var ai = await callAI(prepared.messages, assistantGenerationOptions({
       model: prepared.chatModel || undefined,
       temperature: 0.15,
       maxTokens: 2600
+    }));
+    var finalized = await finalizeAssistantAnswer(ai, {
+      messages: prepared.messages,
+      chatModel: prepared.chatModel,
+      callAI: callAI,
+      generationOptions: assistantGenerationOptions({ temperature: 0.15 })
     });
-    var finalized = await finalizeAssistantAnswer(ai, { messages: prepared.messages, chatModel: prepared.chatModel, callAI: callAI });
     var answer = finalized.answer;
     ai = finalized.ai;
 
@@ -237,11 +243,11 @@ router.post('/clinical-assistant/chat/stream', async function(req, res) {
     sendEvent('sources', { sources: safeSources, search: prepared.search });
     sendEvent('status', { message: 'Generating answer...' });
 
-    var ai = await callAIStream(prepared.messages, {
+    var ai = await callAIStream(prepared.messages, assistantGenerationOptions({
       model: prepared.chatModel || undefined,
       temperature: 0.15,
       maxTokens: 2600
-    }, function(delta) {
+    }), function(delta) {
       sendEvent('token', { token: delta });
     });
 
@@ -249,6 +255,7 @@ router.post('/clinical-assistant/chat/stream', async function(req, res) {
       messages: prepared.messages,
       chatModel: prepared.chatModel,
       callAI: callAI,
+      generationOptions: assistantGenerationOptions({ temperature: 0.15 }),
       streamed: true,
       onRegenerating: function() { sendEvent('status', { message: 'Completing answer...' }); }
     });
@@ -467,11 +474,11 @@ async function rewriteSearchQuery(message, history, chatModel) {
       role: 'user',
       content: 'Conversation:\n' + hist + '\n\nLatest user question:\n' + message + '\n\nStandalone search query:'
     }
-  ], {
+  ], assistantGenerationOptions({
     model: chatModel || undefined,
     temperature: 0,
     maxTokens: 80
-  });
+  }));
   var rewritten = String(ai.content || '').replace(/^['"]|['"]$/g, '').replace(/\s+/g, ' ').trim();
   if (!rewritten || rewritten.length < 6 || rewritten.length > 300) return message;
   if (/^(yes|no|maybe|i don'?t know)$/i.test(rewritten)) return message;

src/utils/ai.js

@@ -7,6 +7,7 @@
 const { OpenAI } = require('openai');
 const { DEFAULT_MODEL, FALLBACK_MODEL, getBedrockModelId, getBedrockMaxOut } = require('./models');
 const logger = require('./logger');
+const { resolveGenerationOptions } = require('./generationOptions');
 
 var activeProvider = process.env.AI_PROVIDER || (process.env.LITELLM_API_BASE ? 'litellm' : 'openrouter');
 
@@ -367,15 +368,21 @@ async function callVertex(messages, model, temperature, maxTokens) {
 // ============================================================
 // CALL LITELLM (OpenAI-compatible proxy)
 // ============================================================
-async function callLiteLLM(messages, model, temperature, maxTokens) {
+function addReasoningOptions(request, generation) {
+  if (generation.reasoningEffort != null) request.reasoning_effort = generation.reasoningEffort;
+  if (generation.reasoningFormat != null) request.reasoning_format = generation.reasoningFormat;
+  return request;
+}
+
+async function callLiteLLM(messages, model, temperature, maxTokens, generation) {
   if (!litellmClient) throw new Error('LiteLLM not configured. Set LITELLM_API_BASE in .env');
 
-  var completion = await litellmClient.chat.completions.create({
+  var completion = await litellmClient.chat.completions.create(addReasoningOptions({
     model: model,
     messages: messages,
     temperature: temperature,
     max_tokens: maxTokens
-  });
+  }, generation || {}));
 
   return {
     success: true,
@@ -421,8 +428,9 @@ async function callAIStream(messages, options, onToken) {
   options = options || {};
   var requestedModel = options.model;
   var model = await resolveModel(requestedModel);
-  var temperature = options.temperature || 0.3;
+  var generation = resolveGenerationOptions(options);
-  var maxTokens = options.maxTokens || 4000;
+  var temperature = generation.temperature;
+  var maxTokens = generation.maxTokens;
   var startTime = Date.now();
   await assertModelAllowed(model, options);
 
@@ -443,13 +451,13 @@ async function callAIStream(messages, options, onToken) {
 
   var content = '';
   var finishReason = null;
-  var stream = await client.chat.completions.create({
+  var stream = await client.chat.completions.create(addReasoningOptions({
     model: model,
     messages: messages,
     temperature: temperature,
     max_tokens: maxTokens,
     stream: true
-  });
+  }, generation));
   for await (var part of stream) {
     var choice = part && part.choices && part.choices[0] ? part.choices[0] : null;
     if (choice && choice.finish_reason) finishReason = choice.finish_reason;
@@ -470,8 +478,9 @@ async function callAI(messages, options) {
   options = options || {};
   var requestedModel = options.model;
   var model = await resolveModel(requestedModel);
-  var temperature = options.temperature || 0.3;
+  var generation = resolveGenerationOptions(options);
-  var maxTokens = options.maxTokens || 4000;
+  var temperature = generation.temperature;
+  var maxTokens = generation.maxTokens;
   var startTime = Date.now();
 
   // Server-side whitelist: reject any model the operator hasn't enabled.
@@ -492,7 +501,7 @@ async function callAI(messages, options) {
     } else if (activeProvider === 'vertex' && vertexClient) {
       result = await callVertex(messages, model, temperature, maxTokens);
     } else if (activeProvider === 'litellm' && litellmClient) {
-      result = await callLiteLLM(messages, model, temperature, maxTokens);
+      result = await callLiteLLM(messages, model, temperature, maxTokens, generation);
     } else if (openrouter) {
       result = await callOpenRouter(messages, model, temperature, maxTokens);
     } else {
@@ -552,7 +561,7 @@ async function callAI(messages, options) {
       if (activeProvider === 'litellm' && model !== FALLBACK_MODEL && litellmClient) {
         logger.warn('Trying fallback model on LiteLLM: ' + FALLBACK_MODEL);
         try {
-          var litellmFallback = await callLiteLLM(messages, FALLBACK_MODEL, temperature, maxTokens);
+          var litellmFallback = await callLiteLLM(messages, FALLBACK_MODEL, temperature, maxTokens, generation);
           litellmFallback.fallback = true;
           litellmFallback.duration = Date.now() - startTime;
           logger.info('LiteLLM fallback success', { model: FALLBACK_MODEL });

src/utils/clinicalAnswer.js

@@ -9,17 +9,23 @@ function buildUserPrompt(question, context, history, searchQuery) {
   return 'Question:\n' + question + searchNote + '\n\nRecent conversation, if relevant:\n' + (hist || 'None') + '\n\nRetrieved sources:\n' + context + '\n\nWrite the answer now. If the question is a short misspelled or partial term and the sources point to a likely concept, answer the likely concept rather than asking for clarification.';
 }
 
+function assistantGenerationOptions(overrides) {
+  return Object.assign({
+    reasoningEffort: 'low',
+    reasoningFormat: 'hidden'
+  }, overrides || {});
+}
+
 async function finalizeAssistantAnswer(ai, options) {
   options = options || {};
   var answer = stripModelSourcesSection(String(ai && ai.content || '').trim());
   if (shouldRegenerateTruncatedAnswer(answer, ai && ai.finishReason) && typeof options.callAI === 'function') {
     console.warn('[clinical-assistant] answer looked truncated; regenerating final answer', { finishReason: ai && ai.finishReason, chars: answer.length, streamed: Boolean(options.streamed) });
     if (typeof options.onRegenerating === 'function') options.onRegenerating();
-    var completed = await options.callAI(options.messages, {
+    var completed = await options.callAI(options.messages, Object.assign({}, options.generationOptions || {}, {
       model: options.chatModel || undefined,
-      temperature: 0.15,
       maxTokens: 5000
-    });
+    }));
     answer = stripModelSourcesSection(String(completed.content || '').trim()) || answer;
     ai.model = completed.model || ai.model;
     ai.provider = completed.provider || ai.provider;
@@ -60,6 +66,7 @@ function shouldRegenerateTruncatedAnswer(answer, finishReason) {
 module.exports = {
   buildSystemPrompt: buildSystemPrompt,
   buildUserPrompt: buildUserPrompt,
+  assistantGenerationOptions: assistantGenerationOptions,
   finalizeAssistantAnswer: finalizeAssistantAnswer,
   stripModelSourcesSection: stripModelSourcesSection,
   shouldRegenerateTruncatedAnswer: shouldRegenerateTruncatedAnswer

src/utils/generationOptions.js

@@ -0,0 +1,11 @@
+function resolveGenerationOptions(options) {
+  options = options || {};
+  return {
+    temperature: options.temperature ?? 0.3,
+    maxTokens: options.maxTokens ?? 4000,
+    reasoningEffort: options.reasoningEffort,
+    reasoningFormat: options.reasoningFormat
+  };
+}
+
+module.exports = { resolveGenerationOptions };

test/clinical-generation-options.test.js

@@ -0,0 +1,19 @@
+const test = require('node:test');
+const assert = require('node:assert/strict');
+
+const { assistantGenerationOptions } = require('../src/utils/clinicalAnswer');
+const { resolveGenerationOptions } = require('../src/utils/generationOptions');
+
+test('clinical assistant profile requests low reasoning without exposing it', () => {
+  assert.deepEqual(assistantGenerationOptions({ temperature: 0, maxTokens: 80 }), {
+    reasoningEffort: 'low',
+    reasoningFormat: 'hidden',
+    temperature: 0,
+    maxTokens: 80
+  });
+});
+
+test('generation defaults preserve an explicit zero temperature', () => {
+  assert.equal(resolveGenerationOptions({ temperature: 0 }).temperature, 0);
+  assert.equal(resolveGenerationOptions({}).temperature, 0.3);
+});