feat: add Ollama/local LLM provider support

Add Ollama as a third AI provider option alongside Anthropic and OpenAI.
Uses the OpenAI-compatible API endpoint that Ollama exposes, configured
via OLLAMA_URL and OLLAMA_MODEL env vars. Provider selection is now
tenant-aware via DB settings, with env var fallback.

- New provider type 'ollama' in AIProvider union
- Tenant-aware getModelForTenant() reads AI config from tenant settings jsonb
- Admin settings UI on /einstellungen for provider/model selection
- API route GET/PATCH /api/settings/ai for tenant AI config
- Updated all AI call sites (analysis, structured-analysis, contracts)

Co-Authored-By: Paperclip <noreply@paperclip.ing>

src/app/(dashboard)/einstellungen/ai-settings.tsx

@@ -0,0 +1,141 @@
+'use client';
+
+import { useEffect, useState } from 'react';
+
+interface AISettings {
+  provider: string;
+  model: string;
+  ollamaUrl: string;
+  ollamaModel: string;
+}
+
+export default function AISettingsForm() {
+  const [settings, setSettings] = useState<AISettings>({
+    provider: 'anthropic',
+    model: '',
+    ollamaUrl: 'http://localhost:11434',
+    ollamaModel: 'llama3',
+  });
+  const [saving, setSaving] = useState(false);
+  const [message, setMessage] = useState<{ type: 'success' | 'error'; text: string } | null>(null);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    fetch('/api/settings/ai')
+      .then((r) => r.json())
+      .then((data) => {
+        setSettings(data);
+        setLoading(false);
+      })
+      .catch(() => setLoading(false));
+  }, []);
+
+  async function handleSubmit(e: React.FormEvent) {
+    e.preventDefault();
+    setSaving(true);
+    setMessage(null);
+
+    try {
+      const res = await fetch('/api/settings/ai', {
+        method: 'PATCH',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify(settings),
+      });
+
+      if (res.ok) {
+        setMessage({ type: 'success', text: 'AI-Einstellungen gespeichert.' });
+      } else {
+        const data = await res.json();
+        setMessage({ type: 'error', text: data.error ?? 'Fehler beim Speichern.' });
+      }
+    } catch {
+      setMessage({ type: 'error', text: 'Netzwerkfehler.' });
+    } finally {
+      setSaving(false);
+    }
+  }
+
+  if (loading) {
+    return (
+      <div className="bg-card-bg border border-card-border rounded-xl p-6">
+        <p className="text-sm text-muted">Lade AI-Einstellungen...</p>
+      </div>
+    );
+  }
+
+  return (
+    <form onSubmit={handleSubmit} className="bg-card-bg border border-card-border rounded-xl p-6">
+      <h3 className="text-sm font-semibold text-foreground mb-4">AI-Provider</h3>
+
+      <div className="space-y-4">
+        <div>
+          <label className="block text-sm text-muted mb-1">Provider</label>
+          <select
+            value={settings.provider}
+            onChange={(e) => setSettings({ ...settings, provider: e.target.value })}
+            className="w-full rounded-lg border border-card-border bg-background px-3 py-2 text-sm text-foreground"
+          >
+            <option value="anthropic">Anthropic (Claude)</option>
+            <option value="openai">OpenAI (GPT)</option>
+            <option value="ollama">Ollama (Lokal)</option>
+          </select>
+        </div>
+
+        {settings.provider !== 'ollama' && (
+          <div>
+            <label className="block text-sm text-muted mb-1">Modell (optional)</label>
+            <input
+              type="text"
+              value={settings.model}
+              onChange={(e) => setSettings({ ...settings, model: e.target.value })}
+              placeholder={settings.provider === 'anthropic' ? 'claude-sonnet-4-20250514' : 'gpt-4o'}
+              className="w-full rounded-lg border border-card-border bg-background px-3 py-2 text-sm text-foreground placeholder:text-muted/50"
+            />
+          </div>
+        )}
+
+        {settings.provider === 'ollama' && (
+          <>
+            <div>
+              <label className="block text-sm text-muted mb-1">Ollama URL</label>
+              <input
+                type="text"
+                value={settings.ollamaUrl}
+                onChange={(e) => setSettings({ ...settings, ollamaUrl: e.target.value })}
+                placeholder="http://localhost:11434"
+                className="w-full rounded-lg border border-card-border bg-background px-3 py-2 text-sm text-foreground placeholder:text-muted/50"
+              />
+            </div>
+            <div>
+              <label className="block text-sm text-muted mb-1">Ollama Modell</label>
+              <input
+                type="text"
+                value={settings.ollamaModel}
+                onChange={(e) => setSettings({ ...settings, ollamaModel: e.target.value })}
+                placeholder="llama3"
+                className="w-full rounded-lg border border-card-border bg-background px-3 py-2 text-sm text-foreground placeholder:text-muted/50"
+              />
+            </div>
+            <p className="text-xs text-muted">
+              Ollama muss lokal oder auf dem Server laufen. Die OpenAI-kompatible API wird verwendet.
+            </p>
+          </>
+        )}
+      </div>
+
+      {message && (
+        <p className={`mt-3 text-sm ${message.type === 'success' ? 'text-green-500' : 'text-red-500'}`}>
+          {message.text}
+        </p>
+      )}
+
+      <button
+        type="submit"
+        disabled={saving}
+        className="mt-4 rounded-lg bg-primary px-4 py-2 text-sm font-medium text-white hover:bg-primary/90 disabled:opacity-50"
+      >
+        {saving ? 'Speichern...' : 'Speichern'}
+      </button>
+    </form>
+  );
+}

src/app/(dashboard)/einstellungen/page.tsx

@@ -4,6 +4,7 @@ import { hasPermission } from '@/lib/auth/rbac';
 import { db } from '@/lib/db';
 import { tenants, users } from '@/lib/db/schema';
 import { eq } from 'drizzle-orm';
+import AISettingsForm from './ai-settings';
 
 const ROLE_LABELS: Record<string, string> = {
   admin: 'Administrator',
@@ -70,6 +71,8 @@ export default async function EinstellungenPage() {
         </div>
       </div>
 
+      {isAdmin && <AISettingsForm />}
+
       {isAdmin && tenantUsers.length > 0 && (
         <div className="bg-card-bg border border-card-border rounded-xl p-6">
           <h3 className="text-sm font-semibold text-foreground mb-4">Benutzer</h3>

src/app/api/settings/ai/route.ts

@@ -0,0 +1,66 @@
+// GET  /api/settings/ai — Read current AI provider settings for tenant
+// PATCH /api/settings/ai — Update AI provider settings (admin only)
+
+import { db } from '@/lib/db';
+import { tenants } from '@/lib/db/schema';
+import { eq } from 'drizzle-orm';
+import { requirePermission } from '@/lib/auth/rbac';
+import type { AIProvider } from '@/lib/ai/providers';
+
+const VALID_PROVIDERS = new Set<AIProvider>(['anthropic', 'openai', 'ollama']);
+
+export async function GET() {
+  const auth = await requirePermission('settings:manage');
+  if ('response' in auth) return auth.response;
+
+  const [tenant] = await db
+    .select({ settings: tenants.settings })
+    .from(tenants)
+    .where(eq(tenants.id, auth.ctx.tenantId))
+    .limit(1);
+
+  const settings = tenant?.settings ?? {};
+  return Response.json({
+    provider: (settings.aiProvider as string) ?? process.env.AI_PROVIDER ?? 'anthropic',
+    model: (settings.aiModel as string) ?? process.env.AI_MODEL ?? '',
+    ollamaUrl: (settings.ollamaUrl as string) ?? process.env.OLLAMA_URL ?? 'http://localhost:11434',
+    ollamaModel: (settings.ollamaModel as string) ?? process.env.OLLAMA_MODEL ?? 'llama3',
+  });
+}
+
+export async function PATCH(request: Request) {
+  const auth = await requirePermission('settings:manage');
+  if ('response' in auth) return auth.response;
+
+  const body = await request.json();
+  const { provider, model, ollamaUrl, ollamaModel } = body;
+
+  if (provider && !VALID_PROVIDERS.has(provider)) {
+    return Response.json(
+      { error: `Ungültiger Provider. Erlaubt: ${[...VALID_PROVIDERS].join(', ')}` },
+      { status: 400 },
+    );
+  }
+
+  const [tenant] = await db
+    .select({ settings: tenants.settings })
+    .from(tenants)
+    .where(eq(tenants.id, auth.ctx.tenantId))
+    .limit(1);
+
+  const current = (tenant?.settings ?? {}) as Record<string, unknown>;
+  const updated = {
+    ...current,
+    ...(provider !== undefined && { aiProvider: provider }),
+    ...(model !== undefined && { aiModel: model }),
+    ...(ollamaUrl !== undefined && { ollamaUrl }),
+    ...(ollamaModel !== undefined && { ollamaModel }),
+  };
+
+  await db
+    .update(tenants)
+    .set({ settings: updated, updatedAt: new Date() })
+    .where(eq(tenants.id, auth.ctx.tenantId));
+
+  return Response.json({ ok: true });
+}

src/lib/ai/analysis.ts

@@ -1,7 +1,7 @@
 // Core analysis service — orchestrates norm/decision lookup, prompt assembly, and AI generation
 
 import { streamText, generateText } from 'ai';
-import { getModel, getProvider } from './providers';
+import { getModelForTenant } from './providers';
 import { SYSTEM_PROMPTS, buildContextBlock, type AnalysisModeKey } from './prompts';
 import { ANALYSIS_MODES } from './modes';
 import { AnalyseMode } from '@/types';
@@ -108,7 +108,7 @@ export async function runAnalysis(input: AnalysisInput) {
 
   const contextBlock = buildContextBlock(normContext, decisionContext);
 
-  const model = getModel();
+  const { model, provider, modelId } = await getModelForTenant(input.tenantId);
 
   // Create the analysis record (status: in_progress)
   const [analysis] = await db
@@ -121,8 +121,8 @@ export async function runAnalysis(input: AnalysisInput) {
       status: 'in_progress',
       title: input.title,
       query: input.query,
-      aiProvider: getProvider(),
-      aiModel: process.env.AI_MODEL ?? 'default',
+      aiProvider: provider,
+      aiModel: modelId,
       sources: {
         normIds: normContext.map((n) => n.id),
         decisionIds: decisionContext.map((d) => d.id),
@@ -182,7 +182,7 @@ export async function runAnalysisSync(input: AnalysisInput) {
     ? `${contextBlock}\n\n---\n\n## Rechtsfrage\n\n${input.query}`
     : input.query;
 
-  const model = getModel();
+  const { model, provider, modelId } = await getModelForTenant(input.tenantId);
 
   const [analysis] = await db
     .insert(analyses)
@@ -194,8 +194,8 @@ export async function runAnalysisSync(input: AnalysisInput) {
       status: 'in_progress',
       title: input.title,
       query: input.query,
-      aiProvider: getProvider(),
-      aiModel: process.env.AI_MODEL ?? 'default',
+      aiProvider: provider,
+      aiModel: modelId,
       sources: {
         normIds: normContext.map((n) => n.id),
         decisionIds: decisionContext.map((d) => d.id),

src/lib/ai/providers/index.ts

@@ -1,31 +1,69 @@
 // AI Provider abstraction via Vercel AI SDK v6
-// Supports: Anthropic, OpenAI — selected via AI_PROVIDER env var
+// Supports: Anthropic, OpenAI, Ollama — selected via AI_PROVIDER env var or tenant settings
 
 import { anthropic } from '@ai-sdk/anthropic';
-import { openai } from '@ai-sdk/openai';
+import { createOpenAI, openai } from '@ai-sdk/openai';
 import type { LanguageModel } from 'ai';
+import { db } from '@/lib/db';
+import { tenants } from '@/lib/db/schema';
+import { eq } from 'drizzle-orm';
 
-export type AIProvider = 'anthropic' | 'openai';
+export type AIProvider = 'anthropic' | 'openai' | 'ollama';
 
 const DEFAULT_MODELS: Record<AIProvider, string> = {
   anthropic: 'claude-sonnet-4-20250514',
   openai: 'gpt-4o',
+  ollama: 'llama3',
 };
 
 export function getProvider(): AIProvider {
   const p = process.env.AI_PROVIDER;
   if (p === 'openai') return 'openai';
+  if (p === 'ollama') return 'ollama';
   return 'anthropic';
 }
 
+function buildModel(provider: AIProvider, modelId: string, ollamaUrl?: string): LanguageModel {
+  switch (provider) {
+    case 'anthropic':
+      return anthropic(modelId);
+    case 'openai':
+      return openai(modelId);
+    case 'ollama': {
+      const baseURL = ollamaUrl ?? process.env.OLLAMA_URL ?? 'http://localhost:11434';
+      const ollama = createOpenAI({
+        baseURL: `${baseURL}/v1`,
+        apiKey: 'ollama',
+      });
+      return ollama(modelId);
+    }
+  }
+}
+
 export function getModel(provider?: AIProvider, modelId?: string): LanguageModel {
   const p = provider ?? getProvider();
   const id = modelId ?? process.env.AI_MODEL ?? DEFAULT_MODELS[p];
-
-  switch (p) {
-    case 'anthropic':
-      return anthropic(id);
-    case 'openai':
-      return openai(id);
-  }
+  return buildModel(p, id);
+}
+
+/** Tenant-aware model getter: reads AI settings from tenant DB, falls back to env vars. */
+export async function getModelForTenant(tenantId: string): Promise<{ model: LanguageModel; provider: AIProvider; modelId: string }> {
+  const [tenant] = await db
+    .select({ settings: tenants.settings })
+    .from(tenants)
+    .where(eq(tenants.id, tenantId))
+    .limit(1);
+
+  const s = tenant?.settings as Record<string, string> | undefined;
+  const provider: AIProvider = (['anthropic', 'openai', 'ollama'].includes(s?.aiProvider ?? '') ? s!.aiProvider : getProvider()) as AIProvider;
+
+  let modelId: string;
+  if (provider === 'ollama') {
+    modelId = s?.ollamaModel ?? process.env.OLLAMA_MODEL ?? DEFAULT_MODELS.ollama;
+  } else {
+    modelId = s?.aiModel || process.env.AI_MODEL || DEFAULT_MODELS[provider];
+  }
+
+  const ollamaUrl = s?.ollamaUrl;
+  return { model: buildModel(provider, modelId, ollamaUrl), provider, modelId };
 }

src/lib/ai/structured-analysis.ts

@@ -2,7 +2,7 @@
 // Returns structured data for frontend consumption with Quellenrang integration
 
 import { generateText } from 'ai';
-import { getModel, getProvider } from './providers';
+import { getModelForTenant } from './providers';
 import { SYSTEM_PROMPTS, buildContextBlock, type AnalysisModeKey } from './prompts';
 import { ANALYSIS_MODES } from './modes';
 import { STRUCTURED_OUTPUT_INSTRUCTION, type StructuredAnalysisOutput } from './structured-output';
@@ -135,7 +135,7 @@ export async function runStructuredAnalysis(
   // Add structured output instruction to system prompt
   const systemPrompt = SYSTEM_PROMPTS[systemPromptKey] + STRUCTURED_OUTPUT_INSTRUCTION;
 
-  const model = getModel();
+  const { model, provider, modelId } = await getModelForTenant(input.tenantId);
 
   // Create analysis record
   const [analysis] = await db
@@ -148,8 +148,8 @@ export async function runStructuredAnalysis(
       status: 'in_progress',
       title: input.title,
       query: input.query,
-      aiProvider: getProvider(),
-      aiModel: process.env.AI_MODEL ?? 'default',
+      aiProvider: provider,
+      aiModel: modelId,
       sources: {
         normIds: normContext.map((n) => n.id),
         decisionIds: decisionContext.map((d) => d.id),

src/lib/contracts/index.ts

@@ -11,7 +11,7 @@ import {
 } from '@/lib/db/schema';
 import { eq, and, desc } from 'drizzle-orm';
 import { generateText } from 'ai';
-import { getModel } from '@/lib/ai/providers';
+import { getModelForTenant } from '@/lib/ai/providers';
 
 const ALLOWED_MIME_TYPES = new Set([
   'application/pdf',
@@ -208,7 +208,7 @@ export async function analyzeContractClauses(tenantId: string, documentId: strin
         .join('\n\n')
     : 'Keine Standardklauseln verfügbar.';
 
-  const model = getModel();
+  const { model } = await getModelForTenant(tenantId);
 
   const { text: analysisResult } = await generateText({
     model,