feat(diarization-ui): per-prompt LLM settings with default/custom toggle

Each prompt can override model, thinking, num_ctx, num_predict,
repeat_penalty and repeat_last_n. Default switch uses global settings;
custom values are preserved when switching back to default.

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

app.py

@@ -130,6 +130,19 @@ def init_db():
             )
         except Exception:
             pass
+        for col in [
+            "llm_use_default INTEGER NOT NULL DEFAULT 1",
+            "llm_model TEXT",
+            "llm_think TEXT",
+            "llm_num_ctx TEXT",
+            "llm_num_predict INTEGER",
+            "llm_repeat_penalty REAL",
+            "llm_repeat_last_n INTEGER",
+        ]:
+            try:
+                c.execute(f"ALTER TABLE prompts ADD COLUMN {col}")
+            except Exception:
+                pass
 
         # defaults
         c.execute("INSERT OR IGNORE INTO projects(name, created_at) VALUES (?,?)", ("Default", now_iso()))
@@ -401,17 +414,25 @@ def _process_analysis_job(job_id: int):
             + f"\\nTEXT:\\n{doc['content_md']}\\n"
         )
 
-        num_ctx_setting = get_setting("ollama_num_ctx", "auto")
+        use_default = int(prm["llm_use_default"] if prm["llm_use_default"] is not None else 1)
+        if use_default:
+            model = get_setting("ollama_model", OLLAMA_MODEL)
+            think = get_setting("ollama_think", "true" if OLLAMA_THINK else "false") == "true"
+            num_ctx_setting = get_setting("ollama_num_ctx", "auto")
+            num_predict = int(get_setting("ollama_num_predict", str(OLLAMA_NUM_PREDICT)))
+            repeat_penalty = float(get_setting("ollama_repeat_penalty", "1.15"))
+            repeat_last_n = int(get_setting("ollama_repeat_last_n", "128"))
+        else:
+            model = prm["llm_model"] or get_setting("ollama_model", OLLAMA_MODEL)
+            think = (prm["llm_think"] or get_setting("ollama_think", "true" if OLLAMA_THINK else "false")) == "true"
+            num_ctx_setting = prm["llm_num_ctx"] or get_setting("ollama_num_ctx", "auto")
+            num_predict = int(prm["llm_num_predict"] or get_setting("ollama_num_predict", str(OLLAMA_NUM_PREDICT)))
+            repeat_penalty = float(prm["llm_repeat_penalty"] or get_setting("ollama_repeat_penalty", "1.15"))
+            repeat_last_n = int(prm["llm_repeat_last_n"] or get_setting("ollama_repeat_last_n", "128"))
         num_ctx = _estimate_num_ctx(llm_prompt) if num_ctx_setting == "auto" else int(num_ctx_setting)
         _job_set(job_id, llm_prompt=f"[num_ctx={num_ctx}]\n\n{llm_prompt}")
         with _JOB_STREAM_LOCK:
             _JOB_STREAMS[job_id] = {"thinking": "", "response": ""}
-
-        model = get_setting("ollama_model", OLLAMA_MODEL)
-        think = get_setting("ollama_think", "true" if OLLAMA_THINK else "false") == "true"
-        num_predict = int(get_setting("ollama_num_predict", str(OLLAMA_NUM_PREDICT)))
-        repeat_penalty = float(get_setting("ollama_repeat_penalty", "1.15"))
-        repeat_last_n = int(get_setting("ollama_repeat_last_n", "128"))
         r = requests.post(
             f"{OLLAMA_BASE_URL}/api/generate",
             json={"model": model, "prompt": llm_prompt, "stream": True, "think": think, "options": {
@@ -1224,11 +1245,79 @@ def bulk_delete_documents(ids: List[int] = Form(...)):
     return HTMLResponse("<meta http-equiv='refresh' content='0; url=/library'>")
 
 
+def _prompt_llm_block(p, def_model, def_think, def_num_ctx, def_num_predict, def_repeat_penalty, def_repeat_last_n):
+    pid = p["id"]
+    use_default = int(p["llm_use_default"]) if p["llm_use_default"] is not None else 1
+    m = p["llm_model"] or def_model
+    th = p["llm_think"] or def_think
+    nc = p["llm_num_ctx"] or def_num_ctx
+    np_ = p["llm_num_predict"] or def_num_predict
+    rp = p["llm_repeat_penalty"] or def_repeat_penalty
+    rn = p["llm_repeat_last_n"] or def_repeat_last_n
+    disabled = "disabled" if use_default else ""
+    opacity = "opacity:.45;pointer-events:none" if use_default else ""
+    ctx_opts = [("auto","Automatisch"), ("4096","4 096"), ("8192","8 192"), ("16384","16 384"),
+                ("32768","32 768"), ("65536","65 536"), ("131072","131 072")]
+    ctx_html = "".join(f"<option value='{v}'{' selected' if v==str(nc) else ''}>{l}</option>" for v,l in ctx_opts)
+    think_checked = "checked" if str(th) == "true" else ""
+    return (
+        f"<hr class='my-3'>"
+        f"<div class='d-flex align-items-center gap-3 mb-2'>"
+        f"  <span class='text-secondary small fw-semibold'><i class='bi bi-robot me-1'></i>KI-Einstellungen</span>"
+        f"  <div class='form-check form-switch mb-0'>"
+        f"    <input class='form-check-input' type='checkbox' role='switch' id='llmdef_{pid}'"
+        f"      onchange='toggleLlmDef({pid},this.checked)' {'checked' if use_default else ''}>"
+        f"    <label class='form-check-label small' for='llmdef_{pid}'>Standard</label>"
+        f"  </div>"
+        f"</div>"
+        f"<input type='hidden' id='llm_use_default_{pid}' name='llm_use_default' value='{use_default}'>"
+        f"<div id='llmfields_{pid}' class='row g-2' style='{opacity}'>"
+        f"  <div class='col-12'>"
+        f"    <label class='form-label small text-secondary mb-1'>Modell</label>"
+        f"    <div class='input-group input-group-sm'>"
+        f"      <input id='llmmodel_{pid}' class='form-control form-control-sm font-monospace' name='llm_model' value='{m}' {disabled}>"
+        f"      <button type='button' class='btn btn-outline-secondary btn-sm' onclick='loadModelsInto(\"llmmodel_{pid}\")' {'disabled' if use_default else ''}>"
+        f"        <i class='bi bi-arrow-clockwise'></i>"
+        f"      </button>"
+        f"    </div>"
+        f"  </div>"
+        f"  <div class='col-6 col-md-3'>"
+        f"    <label class='form-label small text-secondary mb-1'>Kontext</label>"
+        f"    <select class='form-select form-select-sm' name='llm_num_ctx' {disabled}>{ctx_html}</select>"
+        f"  </div>"
+        f"  <div class='col-6 col-md-3'>"
+        f"    <label class='form-label small text-secondary mb-1'>Max. Tokens</label>"
+        f"    <input class='form-control form-control-sm' type='number' name='llm_num_predict' min='256' max='131072' step='256' value='{np_}' {disabled}>"
+        f"  </div>"
+        f"  <div class='col-6 col-md-3'>"
+        f"    <label class='form-label small text-secondary mb-1'>Repeat Penalty</label>"
+        f"    <input class='form-control form-control-sm' type='number' name='llm_repeat_penalty' min='1.0' max='2.0' step='0.01' value='{rp}' {disabled}>"
+        f"  </div>"
+        f"  <div class='col-6 col-md-3'>"
+        f"    <label class='form-label small text-secondary mb-1'>Repeat Last N</label>"
+        f"    <input class='form-control form-control-sm' type='number' name='llm_repeat_last_n' min='0' max='2048' step='1' value='{rn}' {disabled}>"
+        f"  </div>"
+        f"  <div class='col-12'>"
+        f"    <div class='form-check form-switch'>"
+        f"      <input class='form-check-input' type='checkbox' role='switch' id='llmthink_{pid}' name='llm_think' value='true' {think_checked} {disabled}>"
+        f"      <label class='form-check-label small' for='llmthink_{pid}'>Thinking aktivieren</label>"
+        f"    </div>"
+        f"  </div>"
+        f"</div>"
+    )
+
+
 @app.get("/prompts", response_class=HTMLResponse)
 def prompts_page():
     with db() as c:
         prompts = c.execute("SELECT * FROM prompts ORDER BY name").fetchall()
         projects = c.execute("SELECT id,name FROM projects ORDER BY name").fetchall()
+    def_model = get_setting("ollama_model", OLLAMA_MODEL)
+    def_think = get_setting("ollama_think", "true" if OLLAMA_THINK else "false")
+    def_num_ctx = get_setting("ollama_num_ctx", "auto")
+    def_num_predict = get_setting("ollama_num_predict", str(OLLAMA_NUM_PREDICT))
+    def_repeat_penalty = get_setting("ollama_repeat_penalty", "1.15")
+    def_repeat_last_n = get_setting("ollama_repeat_last_n", "128")
 
     project_opts = "".join([f"<option value='{p['name']}'>{p['name']}</option>" for p in projects])
 
@@ -1264,6 +1353,7 @@ def prompts_page():
             f"<textarea id='prompt_text_{p['id']}' class='form-control' name='prompt' style='min-height:110px; resize:vertical'>{p['prompt']}</textarea>"
             f"</div>"
             f"</div>"
+            + _prompt_llm_block(p, def_model, def_think, def_num_ctx, def_num_predict, def_repeat_penalty, def_repeat_last_n) +
             f"<div class='mt-3 d-flex flex-wrap gap-2'>"
             f"<button class='btn btn-primary btn-sm' type='submit'><i class='bi bi-check2-circle'></i> Speichern</button>"
             f"<button class='btn btn-outline-secondary btn-sm' type='button' onclick='previewPrompt({p['id']})'><i class='bi bi-eye'></i> Anzeigen</button>"
@@ -1387,6 +1477,58 @@ document.addEventListener('DOMContentLoaded', () => {{
   const el = document.getElementById('promptEditorModal');
   if(el) el.addEventListener('hide.bs.modal', syncPromptEditorBack);
 }});
+
+const _llmDefaults = {{
+  model: {json.dumps(def_model)},
+  think: {json.dumps(def_think)},
+  num_ctx: {json.dumps(def_num_ctx)},
+  num_predict: {json.dumps(def_num_predict)},
+  repeat_penalty: {json.dumps(def_repeat_penalty)},
+  repeat_last_n: {json.dumps(def_repeat_last_n)},
+}};
+
+function toggleLlmDef(pid, isDefault) {{
+  document.getElementById('llm_use_default_' + pid).value = isDefault ? '1' : '0';
+  const wrap = document.getElementById('llmfields_' + pid);
+  const inputs = wrap.querySelectorAll('input,select,button');
+  if (isDefault) {{
+    wrap.style.opacity = '.45';
+    wrap.style.pointerEvents = 'none';
+    inputs.forEach(el => el.disabled = true);
+  }} else {{
+    wrap.style.opacity = '';
+    wrap.style.pointerEvents = '';
+    inputs.forEach(el => el.disabled = false);
+    // pre-fill from defaults if field is empty
+    const modelInp = document.getElementById('llmmodel_' + pid);
+    if (modelInp && !modelInp.value) modelInp.value = _llmDefaults.model;
+  }}
+}}
+
+async function loadModelsInto(inputId) {{
+  const inp = document.getElementById(inputId);
+  if (!inp) return;
+  const btn = inp.nextElementSibling;
+  if (btn) btn.disabled = true;
+  try {{
+    const res = await fetch('/settings/models');
+    const data = await res.json();
+    if (!data.ok || !data.models.length) {{
+      alert('Keine Modelle gefunden: ' + (data.error || ''));
+      return;
+    }}
+    const current = inp.value.trim();
+    const v = await window.uiSelect('Modell wählen',
+      data.models.map(m => ({{value: m, label: m}})),
+      '– Modell auswählen –'
+    );
+    if (v) inp.value = v;
+  }} catch(e) {{
+    alert('Fehler: ' + e);
+  }} finally {{
+    if (btn) btn.disabled = false;
+  }}
+}}
 </script>
 """
     return layout("Prompts & Projekte", body)
@@ -1412,9 +1554,36 @@ def prompt_add(name: str = Form(...), prompt: str = Form(...)):
 
 
 @app.post("/prompts/update", response_class=HTMLResponse)
-def prompt_update(id: int = Form(...), name: str = Form(...), prompt: str = Form(...)):
+def prompt_update(
+    id: int = Form(...),
+    name: str = Form(...),
+    prompt: str = Form(...),
+    llm_use_default: int = Form(1),
+    llm_model: Optional[str] = Form(None),
+    llm_think: Optional[str] = Form(None),
+    llm_num_ctx: Optional[str] = Form(None),
+    llm_num_predict: Optional[str] = Form(None),
+    llm_repeat_penalty: Optional[str] = Form(None),
+    llm_repeat_last_n: Optional[str] = Form(None),
+):
     with db() as c:
-        c.execute("UPDATE prompts SET name=?, prompt=?, updated_at=? WHERE id=?", (name.strip(), prompt.strip(), now_iso(), id))
+        c.execute(
+            """UPDATE prompts SET name=?, prompt=?, updated_at=?,
+               llm_use_default=?, llm_model=?, llm_think=?,
+               llm_num_ctx=?, llm_num_predict=?, llm_repeat_penalty=?, llm_repeat_last_n=?
+               WHERE id=?""",
+            (
+                name.strip(), prompt.strip(), now_iso(),
+                llm_use_default,
+                (llm_model or "").strip() or None,
+                "true" if llm_think == "true" else "false",
+                (llm_num_ctx or "auto").strip(),
+                int(float(llm_num_predict)) if llm_num_predict else None,
+                float(llm_repeat_penalty) if llm_repeat_penalty else None,
+                int(float(llm_repeat_last_n)) if llm_repeat_last_n else None,
+                id,
+            ),
+        )
     return HTMLResponse("<meta http-equiv='refresh' content='0; url=/prompts'>")