fix: max_tokens CPAM 6000→16000 + diagnostic troncature Ollama

- Argumentation + correction : max_tokens porté à 16000 (num_predict)
- ollama_client : log done_reason=length pour détecter les troncatures serveur
- Résultat live : 1/3 Tier B (dossier 132 passé de C à B, score 5/10)
- Les 2 Tier C restants sont bloqués par hallucination de codes et
  absence de données bio, pas par max_tokens

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/control/cpam_response.py

@@ -126,12 +126,12 @@ def generate_cpam_response(
     prompt, tag_map = _build_cpam_prompt(dossier, controle, sources, extraction)
 
     # 4. Appel LLM — Ollama (rôle cpam) > Haiku fallback
-    result = call_ollama(prompt, temperature=0.1, max_tokens=6000, role="cpam")
+    result = call_ollama(prompt, temperature=0.1, max_tokens=16000, role="cpam")
     if result is not None:
         logger.info("  Contre-argumentation via Ollama")
     else:
         logger.info("  Ollama indisponible → fallback Anthropic Haiku")
-        result = call_anthropic(prompt, temperature=0.1, max_tokens=6000)
+        result = call_anthropic(prompt, temperature=0.1, max_tokens=16000)
         if result is not None:
             logger.info("  Contre-argumentation via Anthropic Haiku")
 
@@ -188,9 +188,9 @@ def generate_cpam_response(
                         validation.get("score_confiance"), len(erreurs_v))
 
         correction_prompt = _build_correction_prompt(prompt, result, validation)
-        corrected = call_ollama(correction_prompt, temperature=0.0, max_tokens=6000, role="cpam")
+        corrected = call_ollama(correction_prompt, temperature=0.0, max_tokens=16000, role="cpam")
         if corrected is None:
-            corrected = call_anthropic(correction_prompt, temperature=0.0, max_tokens=6000)
+            corrected = call_anthropic(correction_prompt, temperature=0.0, max_tokens=16000)
 
         if corrected:
             # Re-valider la correction