diff --git a/embedding_cluster/ai_naming.py b/embedding_cluster/ai_naming.py
new file mode 100644
index 0000000..ed62fd2
--- /dev/null
+++ b/embedding_cluster/ai_naming.py
@@ -0,0 +1,111 @@
+from __future__ import annotations
+
+import logging
+
+import litellm
+
+logger = logging.getLogger(__name__)
+
+# Alias for testability (easy to mock)
+litellm_completion = litellm.completion
+
+SYSTEM_PROMPT_TOP_LEVEL = (
+    "Your role is to find a very short (max 5 words), concise name "
+    "for a group of items, one name to rule them all. "
+    "The user will provide a list of item names. Do your best."
+)
+
+SYSTEM_PROMPT_SUB_CLUSTER = (
+    "Your role is to find a very short (max 5 words), concise name "
+    "for a sub-group of items within a larger group called "
+    '"{parent_name}". '
+    "The name should distinguish this sub-group from its siblings "
+    "while relating to the parent theme. The user will provide a "
+    "list of item names. Do your best."
+)
+
+
+def _call_llm(
+    messages: list[dict[str, str]],
+    api_key: str,
+    model: str,
+    base_url: str | None = None,
+    temperature: float = 0.5,
+) -> str:
+    """Call LiteLLM and return the response content."""
+    kwargs: dict[str, object] = {
+        "model": model,
+        "messages": messages,
+        "api_key": api_key,
+        "temperature": temperature,
+    }
+    if base_url:
+        kwargs["api_base"] = base_url
+
+    response = litellm_completion(**kwargs)
+    content: str = response.choices[0].message.content or ""
+    return (content[:30] + "..") if len(content) > 30 else content
+
+
+def get_cluster_name(
+    item_names: list[str],
+    api_key: str,
+    model: str,
+    base_url: str | None = None,
+    temperature: float = 0.5,
+) -> str:
+    """Generate a short name for a cluster of items."""
+    user_content = "\n".join(f"name: {name}" for name in item_names)
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT_TOP_LEVEL},
+        {"role": "user", "content": user_content},
+    ]
+    return _call_llm(messages, api_key, model, base_url, temperature)
+
+
+def get_sub_cluster_name(
+    item_names: list[str],
+    api_key: str,
+    model: str,
+    base_url: str | None = None,
+    temperature: float = 0.5,
+    parent_cluster_name: str | None = None,
+) -> str:
+    """Generate a short name for a sub-cluster."""
+    if parent_cluster_name:
+        system_content = SYSTEM_PROMPT_SUB_CLUSTER.format(
+            parent_name=parent_cluster_name,
+        )
+    else:
+        system_content = SYSTEM_PROMPT_TOP_LEVEL
+
+    user_content = "\n".join(f"name: {name}" for name in item_names)
+    messages = [
+        {"role": "system", "content": system_content},
+        {"role": "user", "content": user_content},
+    ]
+    return _call_llm(messages, api_key, model, base_url, temperature)
+
+
+def test_connection(
+    api_key: str,
+    model: str,
+    base_url: str | None = None,
+) -> tuple[bool, str | None]:
+    """Test LLM connection. Returns (success, error)."""
+    try:
+        kwargs: dict[str, object] = {
+            "model": model,
+            "messages": [{"role": "user", "content": "Say hello"}],
+            "api_key": api_key,
+            "max_tokens": 5,
+        }
+        if base_url:
+            kwargs["api_base"] = base_url
+        litellm_completion(**kwargs)
+        return True, None
+    except Exception as exc:
+        error_msg = str(exc)
+        if api_key and api_key in error_msg:
+            error_msg = error_msg.replace(api_key, "***")
+        return False, error_msg
diff --git a/embedding_cluster/scatter_plot.py b/embedding_cluster/scatter_plot.py
index 532d1f1..13ecedc 100644
--- a/embedding_cluster/scatter_plot.py
+++ b/embedding_cluster/scatter_plot.py
@@ -1,14 +1,12 @@
 from __future__ import annotations
 
 import logging
-import random
 from typing import TYPE_CHECKING, Any
 
 import chromadb
 import numpy as np
 import plotly.graph_objects as go
 from dash import Dash, Input, Output, callback, dcc, html, no_update
-from openai import OpenAI
 from sklearn.cluster import KMeans
 from sklearn.decomposition import PCA
 from sklearn.manifold import TSNE
@@ -71,31 +69,6 @@ def reduce_dimensions(
     return result
 
 
-def gpt_get_cluster_name(info: str, settings: Settings) -> str:
-    openai_client = OpenAI()
-    messages: list[dict[str, str]] = [
-        {
-            "role": "system",
-            "content": (
-                "Your role is to find a very short (max 5 words), concise "
-                "name for a group of items, one name to rule them all. "
-                "the user will provide a list of item names. do your best"
-            ),
-        },
-        {
-            "role": "user",
-            "content": info,
-        },
-    ]
-    completion = openai_client.chat.completions.create(
-        model=settings.gpt_default_model,
-        temperature=settings.gpt_default_temperature,
-        messages=messages,  # type: ignore[arg-type]  # pyright: ignore[reportArgumentType]
-    )
-    content = completion.choices[0].message.content or ""
-    return (content[:30] + "..") if len(content) > 30 else content
-
-
 def load_chromadb_collection(settings: Settings) -> Any:
     chromadb_client: ClientAPI = chromadb.PersistentClient(path="./chromadb")
     collection = chromadb_client.get_or_create_collection(
@@ -201,9 +174,9 @@ def generate_cluster_props(
     num_clusters: int,
     pred_arr: Any,
     collection_content_text_display: list[str],
-    settings: Settings,
     num_products_for_cluster_name: int = 10,
 ) -> tuple[list[list[int]], list[str]]:
+    _ = (collection_content_text_display, num_products_for_cluster_name)
     clusters_indices: list[list[int]] = []
     cluster_names: list[str] = []
     group_index = 1
@@ -211,28 +184,8 @@ def generate_cluster_props(
         curr_cluster_indices = [i for i, x in enumerate(pred_arr) if x == cluster_i]
         clusters_indices.append(curr_cluster_indices)
         logger.info("Generating cluster %d names ...", cluster_i)
-        if settings.gpt_generate_cluster_name is True:
-            random_product_indexes = random.sample(
-                range(0, len(curr_cluster_indices)),
-                min(
-                    num_products_for_cluster_name,
-                    len(curr_cluster_indices),
-                ),
-            )
-            curr_descriptions = ""
-            for product_index in random_product_indexes:
-                idx = curr_cluster_indices[product_index]
-                item = (
-                    collection_content_text_display[idx]
-                    if idx < len(collection_content_text_display)
-                    else f"Item {idx}"
-                )
-                curr_descriptions += f"name: {item} \n"
-            cluster_name = gpt_get_cluster_name(curr_descriptions, settings)
-            cluster_names.append(cluster_name)
-        else:
-            cluster_names.append(f"Group {group_index}")
-            group_index += 1
+        cluster_names.append(f"Group {group_index}")
+        group_index += 1
     return clusters_indices, cluster_names
 
 
@@ -288,7 +241,7 @@ def compute_plot_data(settings: Settings) -> dict[str, Any]:
     )
 
     clusters_indices, cluster_names = generate_cluster_props(
-        num_clusters, pred_arr, collection_content_text_display, settings
+        num_clusters, pred_arr, collection_content_text_display
     )
 
     # Build structured point data
diff --git a/embedding_cluster/server/app.py b/embedding_cluster/server/app.py
index 7a352da..3784879 100644
--- a/embedding_cluster/server/app.py
+++ b/embedding_cluster/server/app.py
@@ -8,6 +8,7 @@
 from fastapi.responses import FileResponse
 from fastapi.staticfiles import StaticFiles
 
+from embedding_cluster.server.routes.ai import router as ai_router
 from embedding_cluster.server.routes.annotations import (
     router as annotations_router,
 )
@@ -43,6 +44,7 @@ def create_app() -> FastAPI:
     async def health_check() -> dict[str, str]:
         return {"status": "ok"}
 
+    app.include_router(ai_router)
     app.include_router(collections_router)
     app.include_router(csv_router)
     app.include_router(index_router)
diff --git a/embedding_cluster/server/models.py b/embedding_cluster/server/models.py
index 5f42c1f..56dcd22 100644
--- a/embedding_cluster/server/models.py
+++ b/embedding_cluster/server/models.py
@@ -70,9 +70,6 @@ class PlotRequest(BaseModel):
     num_clusters: int = 10
     text_display_fields: list[str] | None = None
     image_field: str | None = None
-    gpt_generate_cluster_name: bool = False
-    gpt_default_model: str = "gpt-3.5-turbo"
-    gpt_default_temperature: float = 0.51
     reduction_algorithm: Literal["tsne", "umap", "pca"] = "tsne"
     tsne_perplexity: float = 30.0
     tsne_learning_rate: str = "auto"
@@ -199,6 +196,7 @@ class SubClusterInfo(BaseModel):
     index: int
     count: int
     color: str
+    name: str | None = None
 
 
 class SubClusterResponse(BaseModel):
@@ -248,3 +246,38 @@ class ClusterAnnotation(BaseModel):
 class AnnotationsResponse(BaseModel):
     job_id: str
     clusters: dict[str, ClusterAnnotation]
+
+
+class AiNamingRequest(BaseModel):
+    job_id: str
+    cluster_indices: list[int]
+    api_key: str
+    model: str
+    base_url: str | None = None
+    temperature: float = 0.5
+
+
+class AiNamingResponse(BaseModel):
+    names: dict[str, str]
+
+
+class AiSubClusterNamingRequest(BaseModel):
+    job_id: str
+    point_ids: list[str]
+    sub_cluster_labels: list[int]
+    api_key: str
+    model: str
+    base_url: str | None = None
+    temperature: float = 0.5
+    parent_cluster_name: str | None = None
+
+
+class AiTestConnectionRequest(BaseModel):
+    api_key: str
+    model: str
+    base_url: str | None = None
+
+
+class AiTestConnectionResponse(BaseModel):
+    success: bool
+    error: str | None = None
diff --git a/embedding_cluster/server/routes/ai.py b/embedding_cluster/server/routes/ai.py
new file mode 100644
index 0000000..bd029fa
--- /dev/null
+++ b/embedding_cluster/server/routes/ai.py
@@ -0,0 +1,160 @@
+from __future__ import annotations
+
+import logging
+import random
+from typing import Any, cast
+
+from fastapi import APIRouter, HTTPException
+
+from embedding_cluster.ai_naming import (
+    get_cluster_name,
+    get_sub_cluster_name,
+)
+from embedding_cluster.ai_naming import (
+    test_connection as ai_test_connection,
+)
+from embedding_cluster.server.models import (
+    AiNamingRequest,
+    AiNamingResponse,
+    AiSubClusterNamingRequest,
+    AiTestConnectionRequest,
+    AiTestConnectionResponse,
+)
+from embedding_cluster.server.tasks import TaskStatus, task_registry
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/ai", tags=["ai"])
+
+MAX_SAMPLE_ITEMS = 10
+
+
+def _get_completed_job(job_id: str) -> dict[str, Any]:
+    task = task_registry.get(job_id)
+    if task is None:
+        raise HTTPException(status_code=404, detail="Job not found")
+    if task.status != TaskStatus.COMPLETED:
+        raise HTTPException(status_code=409, detail="Job not completed")
+    return cast("dict[str, Any]", task.result)
+
+
+def _get_item_names_for_cluster(
+    result: dict[str, Any],
+    cluster_index: int,
+) -> list[str]:
+    points = cast("list[dict[str, Any]]", result["points"])
+    cluster_labels = cast("list[int]", result["cluster_labels"])
+
+    cluster_point_indices = [
+        i for i, label in enumerate(cluster_labels) if label == cluster_index
+    ]
+
+    sample_indices = random.sample(
+        cluster_point_indices,
+        min(MAX_SAMPLE_ITEMS, len(cluster_point_indices)),
+    )
+
+    names: list[str] = []
+    for idx in sample_indices:
+        point = points[idx]
+        metadata = cast("dict[str, Any]", point.get("metadata", {}))
+        name_parts = [str(v) for v in metadata.values()]
+        names.append(
+            ", ".join(name_parts) if name_parts else f"Item {idx}",
+        )
+
+    return names
+
+
+def _get_item_names_for_sub_cluster(
+    result: dict[str, Any],
+    point_ids: list[str],
+    sub_cluster_labels: list[int],
+    sub_cluster_index: int,
+) -> list[str]:
+    points = cast("list[dict[str, Any]]", result["points"])
+    point_id_to_point = {cast("str", p["id"]): p for p in points}
+
+    sub_indices = [
+        i for i, label in enumerate(sub_cluster_labels) if label == sub_cluster_index
+    ]
+
+    sample_indices = random.sample(
+        sub_indices,
+        min(MAX_SAMPLE_ITEMS, len(sub_indices)),
+    )
+
+    names: list[str] = []
+    for idx in sample_indices:
+        pid = point_ids[idx]
+        point = point_id_to_point.get(pid)
+        if point:
+            metadata = cast("dict[str, Any]", point.get("metadata", {}))
+            name_parts = [str(v) for v in metadata.values()]
+            names.append(
+                ", ".join(name_parts) if name_parts else f"Item {pid}",
+            )
+        else:
+            names.append(f"Item {pid}")
+
+    return names
+
+
+@router.post("/name-clusters", response_model=AiNamingResponse)
+async def name_clusters(request: AiNamingRequest) -> AiNamingResponse:
+    result = _get_completed_job(request.job_id)
+
+    names: dict[str, str] = {}
+    for cluster_index in request.cluster_indices:
+        item_names = _get_item_names_for_cluster(result, cluster_index)
+        name = get_cluster_name(
+            item_names=item_names,
+            api_key=request.api_key,
+            model=request.model,
+            base_url=request.base_url,
+            temperature=request.temperature,
+        )
+        names[str(cluster_index)] = name
+
+    return AiNamingResponse(names=names)
+
+
+@router.post("/name-sub-clusters", response_model=AiNamingResponse)
+async def name_sub_clusters(
+    request: AiSubClusterNamingRequest,
+) -> AiNamingResponse:
+    result = _get_completed_job(request.job_id)
+
+    unique_labels = sorted(set(request.sub_cluster_labels))
+    names: dict[str, str] = {}
+
+    for label in unique_labels:
+        item_names = _get_item_names_for_sub_cluster(
+            result,
+            request.point_ids,
+            request.sub_cluster_labels,
+            label,
+        )
+        name = get_sub_cluster_name(
+            item_names=item_names,
+            api_key=request.api_key,
+            model=request.model,
+            base_url=request.base_url,
+            temperature=request.temperature,
+            parent_cluster_name=request.parent_cluster_name,
+        )
+        names[str(label)] = name
+
+    return AiNamingResponse(names=names)
+
+
+@router.post("/test-connection", response_model=AiTestConnectionResponse)
+async def test_connection(
+    request: AiTestConnectionRequest,
+) -> AiTestConnectionResponse:
+    success, error = ai_test_connection(
+        api_key=request.api_key,
+        model=request.model,
+        base_url=request.base_url,
+    )
+    return AiTestConnectionResponse(success=success, error=error)
diff --git a/embedding_cluster/server/routes/plot.py b/embedding_cluster/server/routes/plot.py
index 35da576..5529f96 100644
--- a/embedding_cluster/server/routes/plot.py
+++ b/embedding_cluster/server/routes/plot.py
@@ -43,9 +43,6 @@ async def _run_compute(task_state: TaskState, request: PlotRequest) -> None:
             num_clusters=request.num_clusters,
             text_display_fields=request.text_display_fields,
             image_field=request.image_field,
-            gpt_generate_cluster_name=request.gpt_generate_cluster_name,
-            gpt_default_model=request.gpt_default_model,
-            gpt_default_temperature=request.gpt_default_temperature,
             reduction_algorithm=request.reduction_algorithm,
             tsne_perplexity=request.tsne_perplexity,
             tsne_learning_rate=request.tsne_learning_rate,
diff --git a/embedding_cluster/settings.py b/embedding_cluster/settings.py
index a7677ec..f424f31 100644
--- a/embedding_cluster/settings.py
+++ b/embedding_cluster/settings.py
@@ -75,11 +75,3 @@ class Settings(BaseSettings):
     umap_n_neighbors: int = Field(default=15, description="UMAP number of neighbors")
     umap_min_dist: float = Field(default=0.1, description="UMAP minimum distance")
     umap_metric: str = Field(default="cosine", description="UMAP distance metric")
-
-    gpt_generate_cluster_name: bool = Field(
-        default=False, description="Generate cluster names using GPT"
-    )
-    gpt_default_model: str = Field(default="gpt-3.5-turbo", description="GPT model name")
-    gpt_default_temperature: float = Field(
-        default=0.51, description="GPT model temperature"
-    )
diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx
index c97f470..d6c95a4 100644
--- a/frontend/src/App.tsx
+++ b/frontend/src/App.tsx
@@ -4,6 +4,7 @@ import { useEffect, useRef } from 'react'
 import HomePage from './pages/HomePage'
 import IndexPage from './pages/IndexPage'
 import PlotPage from './pages/PlotPage'
+import SettingsPage from './pages/SettingsPage'
 import { usePlotStore } from './stores/plotStore'
 
 const queryClient = new QueryClient()
@@ -35,6 +36,9 @@ function NavBar() {
               <NavLink to="/plot" className={linkClass}>
                 Plot
               </NavLink>
+              <NavLink to="/settings" className={linkClass}>
+                Settings
+              </NavLink>
             </div>
           </div>
         </div>
@@ -86,6 +90,7 @@ export default function App() {
               <Route path="/" element={<HomePage />} />
               <Route path="/index" element={<IndexPage />} />
               <Route path="/plot" element={<PlotPage />} />
+              <Route path="/settings" element={<SettingsPage />} />
             </Routes>
           </main>
         </div>
diff --git a/frontend/src/api/ai.ts b/frontend/src/api/ai.ts
new file mode 100644
index 0000000..59f57a9
--- /dev/null
+++ b/frontend/src/api/ai.ts
@@ -0,0 +1,58 @@
+import type {
+  AiNamingRequest,
+  AiNamingResponse,
+  AiSubClusterNamingRequest,
+  AiTestConnectionRequest,
+  AiTestConnectionResponse,
+} from "../types";
+import { apiPost } from "./client";
+
+const AI_SETTINGS_KEY = "ai-cluster-naming-settings";
+
+export interface StoredAiSettings {
+  provider: string;
+  model: string;
+  apiKey: string;
+  baseUrl: string;
+  temperature: number;
+}
+
+export const DEFAULT_AI_SETTINGS: StoredAiSettings = {
+  provider: "openai",
+  model: "gpt-4o-mini",
+  apiKey: "",
+  baseUrl: "",
+  temperature: 0.5,
+};
+
+export function loadAiSettings(): StoredAiSettings {
+  try {
+    const raw = localStorage.getItem(AI_SETTINGS_KEY);
+    if (!raw) return { ...DEFAULT_AI_SETTINGS };
+    return { ...DEFAULT_AI_SETTINGS, ...JSON.parse(raw) } as StoredAiSettings;
+  } catch {
+    return { ...DEFAULT_AI_SETTINGS };
+  }
+}
+
+export function saveAiSettings(settings: StoredAiSettings): void {
+  localStorage.setItem(AI_SETTINGS_KEY, JSON.stringify(settings));
+}
+
+export async function testAiConnection(
+  request: AiTestConnectionRequest,
+): Promise<AiTestConnectionResponse> {
+  return apiPost<AiTestConnectionResponse>("/ai/test-connection", request);
+}
+
+export async function nameAiClusters(
+  request: AiNamingRequest,
+): Promise<AiNamingResponse> {
+  return apiPost<AiNamingResponse>("/ai/name-clusters", request);
+}
+
+export async function nameAiSubClusters(
+  request: AiSubClusterNamingRequest,
+): Promise<AiNamingResponse> {
+  return apiPost<AiNamingResponse>("/ai/name-sub-clusters", request);
+}
diff --git a/frontend/src/components/plot/ClusterDetailDrawer.tsx b/frontend/src/components/plot/ClusterDetailDrawer.tsx
index ab7c956..7db58b3 100644
--- a/frontend/src/components/plot/ClusterDetailDrawer.tsx
+++ b/frontend/src/components/plot/ClusterDetailDrawer.tsx
@@ -8,7 +8,8 @@ import {
   subCluster,
   subClusterByPointIds,
 } from '../../api/plot'
-import type { ClusterDetailResponse, SuggestKResponse } from '../../types'
+import { loadAiSettings, nameAiSubClusters } from '../../api/ai'
+import type { ClusterDetailResponse, SubClusterResponse, SuggestKResponse } from '../../types'
 import SelectedPointsDistancePanel from './SelectedPointsDistancePanel'
 
 interface ClusterDetailDrawerProps {
@@ -35,6 +36,9 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail
   const drillIntoSubCluster = usePlotStore((s) => s.drillIntoSubCluster)
   const setIsLoadingDrill = usePlotStore((s) => s.setIsLoadingDrill)
   const isLoadingDrill = usePlotStore((s) => s.isLoadingDrill)
+  const isNamingSubClusters = usePlotStore((s) => s.isNamingSubClusters)
+  const setIsNamingSubClusters = usePlotStore((s) => s.setIsNamingSubClusters)
+  const updateSubClusterNames = usePlotStore((s) => s.updateSubClusterNames)
 
   const [page, setPage] = useState(1)
   const [isEditingName, setIsEditingName] = useState(false)
@@ -100,6 +104,35 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail
     setExpandedSubClusterIndex(null)
   }, [currentLevel?.label])
 
+  const autoNameSubClusters = useCallback(async (
+    data: SubClusterResponse,
+    parentName: string | undefined,
+  ) => {
+    const settings = loadAiSettings()
+    if (!settings.apiKey || !jobId) return
+
+    setIsNamingSubClusters(true)
+    try {
+      const pointIds = data.points.map((p) => p.id)
+      const labels = data.points.map((p) => p.sub_cluster)
+      const response = await nameAiSubClusters({
+        job_id: jobId,
+        point_ids: pointIds,
+        sub_cluster_labels: labels,
+        api_key: settings.apiKey,
+        model: settings.provider ? `${settings.provider}/${settings.model}` : settings.model,
+        base_url: settings.baseUrl || undefined,
+        temperature: settings.temperature,
+        parent_cluster_name: parentName,
+      })
+      updateSubClusterNames(response.names)
+    } catch {
+      // AI naming is best-effort; failures are silent
+    } finally {
+      setIsNamingSubClusters(false)
+    }
+  }, [jobId, setIsNamingSubClusters, updateSubClusterNames])
+
   const handlePageChange = useCallback((newPage: number) => {
     if (clusterIndex == null) return
     setPage(newPage)
@@ -224,12 +257,16 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail
         })
         setSelectedSubClusterIndex(null)
         drillIntoSubCluster(selectedSubCluster, data)
+        const parentLabel = currentLevel.label
+        autoNameSubClusters(data, parentLabel)
       } else {
         const data = await subCluster(jobId, clusterIndex, {
           num_sub_clusters: subClusterK,
         })
         setSelectedSubClusterIndex(null)
         drillIntoCluster(clusterIndex, data)
+        const parentName = annotation?.name ?? cluster?.name
+        autoNameSubClusters(data, parentName)
       }
     } catch {
       setIsLoadingDrill(false)
@@ -245,6 +282,9 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail
     setIsLoadingDrill,
     drillIntoCluster,
     drillIntoSubCluster,
+    autoNameSubClusters,
+    annotation,
+    cluster,
   ])
 
   const handleToggleSubClusterExpanded = useCallback((subClusterIndex: number) => {
@@ -390,7 +430,15 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail
           className="px-4 py-2 border-b border-gray-200 flex-1 min-h-0 overflow-y-auto"
           data-testid="drawer-subcluster-list"
         >
-          <div className="text-xs font-medium text-gray-500 mb-1.5">Current sub-clusters</div>
+          <div className="flex items-center space-x-2 mb-1.5">
+            <span className="text-xs font-medium text-gray-500">Current sub-clusters</span>
+            {isNamingSubClusters && (
+              <div className="flex items-center space-x-1">
+                <div className="animate-spin rounded-full h-3 w-3 border-b-2 border-purple-600" />
+                <span className="text-[10px] text-purple-600">Naming...</span>
+              </div>
+            )}
+          </div>
           <div className="space-y-1">
             {subClusters.map((sc) => {
               const scColor = CLUSTER_COLORS[sc.index % CLUSTER_COLORS.length]
@@ -421,7 +469,7 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail
                         style={{ backgroundColor: scColor }}
                       />
                       <span className="text-xs text-gray-900 font-medium">
-                        Sub {sc.index}
+                        {sc.name || `Sub ${sc.index}`}
                       </span>
                       <span className="text-[10px] text-gray-500 shrink-0">
                         {sc.count} pts
diff --git a/frontend/src/components/plot/ClusterLegend.tsx b/frontend/src/components/plot/ClusterLegend.tsx
index 9f82a50..f836cc5 100644
--- a/frontend/src/components/plot/ClusterLegend.tsx
+++ b/frontend/src/components/plot/ClusterLegend.tsx
@@ -1,5 +1,7 @@
-import { useCallback } from 'react'
+import { useCallback, useState } from 'react'
 import { usePlotStore, CLUSTER_COLORS } from '../../stores/plotStore'
+import { loadAiSettings, nameAiClusters } from '../../api/ai'
+import { updateAnnotation, getAnnotations } from '../../api/plot'
 
 export default function ClusterLegend() {
   const plotData = usePlotStore((state) => state.plotData)
@@ -14,8 +16,14 @@ export default function ClusterLegend() {
   const setSelectedCluster = usePlotStore((state) => state.setSelectedCluster)
   const selectedCluster = usePlotStore((state) => state.selectedCluster)
   const annotations = usePlotStore((state) => state.annotations)
+  const setAnnotations = usePlotStore((state) => state.setAnnotations)
   const drillPath = usePlotStore((state) => state.drillPath)
   const isLoadingDrill = usePlotStore((state) => state.isLoadingDrill)
+  const isNamingClusters = usePlotStore((state) => state.isNamingClusters)
+  const setIsNamingClusters = usePlotStore((state) => state.setIsNamingClusters)
+  const plotJobId = usePlotStore((state) => state.plotJobId)
+
+  const [namingError, setNamingError] = useState<string | null>(null)
 
   const handleClickCluster = useCallback(
     (clusterIndex: number, isSelected: boolean) => {
@@ -24,6 +32,42 @@ export default function ClusterLegend() {
     [setSelectedCluster],
   )
 
+  const handleNameWithAi = useCallback(async () => {
+    if (!plotData || !plotJobId || isNamingClusters) return
+
+    const settings = loadAiSettings()
+    if (!settings.apiKey) {
+      setNamingError('Configure AI settings first (Settings page)')
+      return
+    }
+
+    setIsNamingClusters(true)
+    setNamingError(null)
+
+    try {
+      const clusterIndices = plotData.clusters.map((c) => c.index)
+      const response = await nameAiClusters({
+        job_id: plotJobId,
+        cluster_indices: clusterIndices,
+        api_key: settings.apiKey,
+        model: settings.provider ? `${settings.provider}/${settings.model}` : settings.model,
+        base_url: settings.baseUrl || undefined,
+        temperature: settings.temperature,
+      })
+
+      for (const [indexStr, name] of Object.entries(response.names)) {
+        await updateAnnotation(plotJobId, Number(indexStr), { name })
+      }
+
+      const updated = await getAnnotations(plotJobId)
+      setAnnotations(updated)
+    } catch (err) {
+      setNamingError(err instanceof Error ? err.message : 'AI naming failed')
+    } finally {
+      setIsNamingClusters(false)
+    }
+  }, [plotData, plotJobId, isNamingClusters, setIsNamingClusters, setAnnotations])
+
   if (!plotData) return null
 
   const handleShowAll = () => resetVisibleClusters(plotData.clusters.length)
@@ -56,12 +100,33 @@ export default function ClusterLegend() {
             Show All
           </button>
         ) : (
-          <button
-            onClick={handleShowAll}
-            className="text-xs text-blue-600 hover:text-blue-800"
-          >
-            Show All
-          </button>
+          <>
+            <button
+              onClick={handleShowAll}
+              className="text-xs text-blue-600 hover:text-blue-800"
+            >
+              Show All
+            </button>
+            <button
+              onClick={handleNameWithAi}
+              disabled={isNamingClusters || !plotJobId}
+              className="text-xs text-purple-600 hover:text-purple-800 disabled:opacity-50 flex items-center space-x-1"
+              title="Name clusters using AI (configure in Settings)"
+              data-testid="name-with-ai-button"
+            >
+              {isNamingClusters ? (
+                <div className="animate-spin rounded-full h-3 w-3 border-b-2 border-purple-600" />
+              ) : (
+                <svg xmlns="http://www.w3.org/2000/svg" width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
+                  <path d="M12 2l2.09 6.26L20 10l-5.91 1.74L12 18l-2.09-6.26L4 10l5.91-1.74z" />
+                </svg>
+              )}
+              <span>Name with AI</span>
+            </button>
+            {namingError && (
+              <span className="text-xs text-red-500">{namingError}</span>
+            )}
+          </>
         )}
         {isLoadingDrill && (
           <div className="animate-spin rounded-full h-3 w-3 border-b-2 border-blue-600" />
@@ -118,7 +183,7 @@ export default function ClusterLegend() {
                     />
                     <div className="text-xs text-left">
                       <div className={`font-medium ${isVisible ? 'text-gray-900' : 'text-gray-500 line-through'}`}>
-                        Sub {sc.index}
+                        {sc.name || `Sub ${sc.index}`}
                       </div>
                       <div className="text-gray-500 text-[10px]">
                         {sc.count} points
diff --git a/frontend/src/components/plot/PlotControls.tsx b/frontend/src/components/plot/PlotControls.tsx
index c02d164..92a0e69 100644
--- a/frontend/src/components/plot/PlotControls.tsx
+++ b/frontend/src/components/plot/PlotControls.tsx
@@ -36,10 +36,6 @@ export default function PlotControls({ onCompute, isComputing }: PlotControlsPro
   const [numClusters, setNumClusters] = useState(10)
   const [textDisplayFields, setTextDisplayFields] = useState<string[]>([])
   const [imageField, setImageField] = useState('')
-  const [gptEnabled, setGptEnabled] = useState(false)
-  const [gptModel, setGptModel] = useState('gpt-3.5-turbo')
-  const [gptTemperature, setGptTemperature] = useState(0.51)
-
   const {
     renderMode, setRenderMode, pointSize, setPointSize,
     reductionAlgorithm, setReductionAlgorithm,
@@ -100,9 +96,6 @@ export default function PlotControls({ onCompute, isComputing }: PlotControlsPro
       num_clusters: numClusters,
       text_display_fields: textDisplayFields,
       image_field: imageField || undefined,
-      gpt_generate_cluster_name: gptEnabled,
-      gpt_default_model: gptEnabled ? gptModel : undefined,
-      gpt_default_temperature: gptEnabled ? gptTemperature : undefined,
       reduction_algorithm: reductionAlgorithm,
       ...(reductionAlgorithm === 'tsne' && {
         tsne_perplexity: tsnePerplexity,
@@ -320,51 +313,6 @@ export default function PlotControls({ onCompute, isComputing }: PlotControlsPro
             </div>
           </CollapsibleSection>
 
-          {/* GPT Settings */}
-          <CollapsibleSection title="GPT Cluster Naming" defaultOpen={false}>
-            <div className="space-y-1.5">
-              <div className="flex items-center">
-                <input
-                  type="checkbox"
-                  id="gpt-enabled"
-                  aria-label="GPT Cluster Naming"
-                  checked={gptEnabled}
-                  onChange={(e) => setGptEnabled(e.target.checked)}
-                  className="mr-2"
-                />
-                <label htmlFor="gpt-enabled" className="text-xs font-medium text-gray-600 cursor-pointer">
-                  Enable
-                </label>
-              </div>
-
-              {gptEnabled && (
-                <div className="pl-6 space-y-2">
-                  <div>
-                    <label className="block text-xs text-gray-500">Model</label>
-                    <input
-                      type="text"
-                      value={gptModel}
-                      onChange={(e) => setGptModel(e.target.value)}
-                      className="w-full border border-gray-300 rounded px-2 py-1 text-sm"
-                    />
-                  </div>
-                  <div>
-                    <label className="block text-xs text-gray-500">Temperature: {gptTemperature}</label>
-                    <input
-                      type="number"
-                      step="0.1"
-                      min="0"
-                      max="1"
-                      value={gptTemperature}
-                      onChange={(e) => setGptTemperature(Number(e.target.value))}
-                      className="w-full border border-gray-300 rounded px-2 py-1 text-sm"
-                    />
-                  </div>
-                </div>
-              )}
-            </div>
-          </CollapsibleSection>
-
           {/* Rendering (Render Mode + Point Size) */}
           <CollapsibleSection title="Rendering" defaultOpen={false}>
             <div className="space-y-1.5">
diff --git a/frontend/src/pages/SettingsPage.tsx b/frontend/src/pages/SettingsPage.tsx
new file mode 100644
index 0000000..1de00cf
--- /dev/null
+++ b/frontend/src/pages/SettingsPage.tsx
@@ -0,0 +1,200 @@
+import { useState, useEffect } from 'react';
+import type { StoredAiSettings } from '../api/ai';
+import {
+  loadAiSettings,
+  saveAiSettings,
+  testAiConnection,
+  DEFAULT_AI_SETTINGS,
+} from '../api/ai';
+
+export default function SettingsPage() {
+  const [settings, setSettings] = useState<StoredAiSettings>(DEFAULT_AI_SETTINGS);
+  const [isSaved, setIsSaved] = useState(false);
+  const [testStatus, setTestStatus] = useState<'idle' | 'testing' | 'success' | 'error'>('idle');
+  const [testMessage, setTestMessage] = useState('');
+  const [showApiKey, setShowApiKey] = useState(false);
+
+  useEffect(() => {
+    setSettings(loadAiSettings());
+  }, []);
+
+  const handleChange = (field: keyof StoredAiSettings, value: string | number) => {
+    setSettings((prev) => ({ ...prev, [field]: value }));
+    setIsSaved(false);
+    setTestStatus('idle');
+  };
+
+  const handleSave = () => {
+    saveAiSettings(settings);
+    setIsSaved(true);
+    setTimeout(() => setIsSaved(false), 3000);
+  };
+
+  const handleTestConnection = async () => {
+    setTestStatus('testing');
+    setTestMessage('');
+    try {
+      const result = await testAiConnection({
+        api_key: settings.apiKey,
+        model: settings.model,
+        base_url: settings.baseUrl || undefined,
+      });
+
+      if (result.success) {
+        setTestStatus('success');
+        setTestMessage('Connection successful!');
+      } else {
+        setTestStatus('error');
+        setTestMessage(result.error || 'Connection failed.');
+      }
+    } catch (err: unknown) {
+      setTestStatus('error');
+      const msg = err instanceof Error ? err.message : 'Unknown error occurred.';
+      setTestMessage(`Failed to test connection: ${msg}`);
+    }
+  };
+
+  return (
+    <div className="p-6 max-w-7xl mx-auto">
+      <div className="mb-6 border-b pb-4 border-gray-200">
+        <h1 className="text-3xl font-bold mb-2 text-gray-900">AI Settings</h1>
+        <p className="text-gray-500 text-lg">
+          Configure AI provider for cluster naming
+        </p>
+      </div>
+
+      <div className="bg-white rounded-lg shadow border border-gray-200 p-6 max-w-2xl">
+        <div className="space-y-6">
+          <div>
+            <label className="block text-sm font-medium text-gray-700 mb-1">
+              Provider
+            </label>
+            <input
+              type="text"
+              value={settings.provider}
+              onChange={(e) => handleChange('provider', e.target.value)}
+              className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border"
+              placeholder="e.g. openai"
+            />
+          </div>
+
+          <div>
+            <label className="block text-sm font-medium text-gray-700 mb-1">
+              Model
+            </label>
+            <input
+              type="text"
+              value={settings.model}
+              onChange={(e) => handleChange('model', e.target.value)}
+              className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border"
+              placeholder="e.g. gpt-4o-mini"
+            />
+          </div>
+
+          <div>
+            <label className="block text-sm font-medium text-gray-700 mb-1">
+              API Key
+            </label>
+            <div className="relative">
+              <input
+                type={showApiKey ? 'text' : 'password'}
+                value={settings.apiKey}
+                onChange={(e) => handleChange('apiKey', e.target.value)}
+                className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border pr-10"
+                placeholder="sk-..."
+              />
+              <button
+                type="button"
+                onClick={() => setShowApiKey(!showApiKey)}
+                className="absolute inset-y-0 right-0 px-3 flex items-center text-sm text-gray-500 hover:text-gray-700 focus:outline-none"
+              >
+                {showApiKey ? 'Hide' : 'Show'}
+              </button>
+            </div>
+          </div>
+
+          <div>
+            <label className="block text-sm font-medium text-gray-700 mb-1">
+              Base URL <span className="text-gray-400 font-normal">(Optional)</span>
+            </label>
+            <input
+              type="text"
+              value={settings.baseUrl}
+              onChange={(e) => handleChange('baseUrl', e.target.value)}
+              className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border"
+              placeholder="e.g. https://api.openai.com/v1"
+            />
+          </div>
+
+          <div>
+            <label className="block text-sm font-medium text-gray-700 mb-1">
+              Temperature
+            </label>
+            <input
+              type="number"
+              step="0.1"
+              min="0"
+              max="1"
+              value={settings.temperature}
+              onChange={(e) => handleChange('temperature', parseFloat(e.target.value))}
+              className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border"
+            />
+          </div>
+
+          <div className="pt-4 flex items-center justify-between border-t border-gray-200">
+            <div className="flex items-center space-x-4">
+              <button
+                type="button"
+                onClick={() => { void handleTestConnection(); }}
+                disabled={testStatus === 'testing' || !settings.apiKey}
+                className="inline-flex items-center px-4 py-2 border border-gray-300 shadow-sm text-sm font-medium rounded-md text-gray-700 bg-white hover:bg-gray-50 focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-blue-500 disabled:opacity-50 disabled:cursor-not-allowed transition-colors"
+              >
+                {testStatus === 'testing' ? (
+                  <>
+                    <svg className="animate-spin -ml-1 mr-2 h-4 w-4 text-gray-700" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24">
+                      <circle className="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" strokeWidth="4"></circle>
+                      <path className="opacity-75" fill="currentColor" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path>
+                    </svg>
+                    Testing...
+                  </>
+                ) : (
+                  'Test Connection'
+                )}
+              </button>
+
+              {testStatus === 'success' && (
+                <span className="flex items-center text-sm text-green-600 font-medium">
+                  <svg className="mr-1.5 h-5 w-5" fill="currentColor" viewBox="0 0 20 20">
+                    <path fillRule="evenodd" d="M10 18a8 8 0 100-16 8 8 0 000 16zm3.707-9.293a1 1 0 00-1.414-1.414L9 10.586 7.707 9.293a1 1 0 00-1.414 1.414l2 2a1 1 0 001.414 0l4-4z" clipRule="evenodd" />
+                  </svg>
+                  {testMessage}
+                </span>
+              )}
+
+              {testStatus === 'error' && (
+                <span className="text-sm text-red-600 font-medium max-w-xs break-words">
+                  {testMessage}
+                </span>
+              )}
+            </div>
+
+            <div className="flex items-center space-x-3">
+              {isSaved && (
+                <span className="text-sm text-green-600 transition-opacity duration-300">
+                  Settings saved!
+                </span>
+              )}
+              <button
+                type="button"
+                onClick={handleSave}
+                className="inline-flex justify-center py-2 px-4 border border-transparent shadow-sm text-sm font-medium rounded-md text-white bg-blue-600 hover:bg-blue-700 focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-blue-500 transition-colors"
+              >
+                Save
+              </button>
+            </div>
+          </div>
+        </div>
+      </div>
+    </div>
+  );
+}
diff --git a/frontend/src/stores/plotStore.ts b/frontend/src/stores/plotStore.ts
index c0f144e..2b19d74 100644
--- a/frontend/src/stores/plotStore.ts
+++ b/frontend/src/stores/plotStore.ts
@@ -27,6 +27,8 @@ interface PlotState {
   drillPath: DrillLevel[]
   subClusterColorMap: Map<string, number> | null
   isLoadingDrill: boolean
+  isNamingClusters: boolean
+  isNamingSubClusters: boolean
   imageField: string | null
   plotJobId: string | null
   plotCollectionName: string | null
@@ -61,6 +63,9 @@ interface PlotState {
   navigateBack: () => void
   resetDrill: () => void
   setIsLoadingDrill: (loading: boolean) => void
+  setIsNamingClusters: (loading: boolean) => void
+  setIsNamingSubClusters: (loading: boolean) => void
+  updateSubClusterNames: (names: Record<string, string>) => void
   isolateCluster: (index: number) => void
   toggleSubCluster: (index: number) => void
   isolateSubCluster: (index: number) => void
@@ -121,6 +126,8 @@ export const usePlotStore = create<PlotState>((set) => ({
   drillPath: [],
   subClusterColorMap: null,
   isLoadingDrill: false,
+  isNamingClusters: false,
+  isNamingSubClusters: false,
   imageField: null,
   plotJobId: null,
   plotCollectionName: null,
@@ -247,6 +254,25 @@ export const usePlotStore = create<PlotState>((set) => ({
 
   setIsLoadingDrill: (loading) => set({ isLoadingDrill: loading }),
 
+  setIsNamingClusters: (loading) => set({ isNamingClusters: loading }),
+  setIsNamingSubClusters: (loading) => set({ isNamingSubClusters: loading }),
+
+  updateSubClusterNames: (names) =>
+    set((state) => {
+      if (state.drillPath.length === 0) return {}
+      const newPath = [...state.drillPath]
+      const currentLevel = { ...newPath[newPath.length - 1] }
+      currentLevel.subClusterData = {
+        ...currentLevel.subClusterData,
+        sub_clusters: currentLevel.subClusterData.sub_clusters.map((sc) => ({
+          ...sc,
+          name: names[String(sc.index)] ?? sc.name,
+        })),
+      }
+      newPath[newPath.length - 1] = currentLevel
+      return { drillPath: newPath }
+    }),
+
   isolateCluster: (index) =>
     set(() => ({ visibleClusters: new Set([index]) })),
 
diff --git a/frontend/src/types/index.ts b/frontend/src/types/index.ts
index 75eec4c..a05c3fe 100644
--- a/frontend/src/types/index.ts
+++ b/frontend/src/types/index.ts
@@ -65,9 +65,6 @@ export interface PlotRequest {
   num_clusters?: number
   text_display_fields?: string[]
   image_field?: string
-  gpt_generate_cluster_name?: boolean
-  gpt_default_model?: string
-  gpt_default_temperature?: number
   reduction_algorithm?: ReductionAlgorithm
   tsne_perplexity?: number
   tsne_learning_rate?: string
@@ -184,6 +181,7 @@ export interface SubClusterInfo {
   index: number;
   count: number;
   color: string;
+  name?: string;
 }
 
 export interface SubClusterResponse {
@@ -235,3 +233,47 @@ export interface AnnotationsResponse {
   job_id: string;
   clusters: Record<string, ClusterAnnotation>;
 }
+
+// AI Naming
+export interface AiSettings {
+  provider: string;
+  model: string;
+  apiKey: string;
+  baseUrl: string;
+  temperature: number;
+}
+
+export interface AiNamingRequest {
+  job_id: string;
+  cluster_indices: number[];
+  api_key: string;
+  model: string;
+  base_url?: string;
+  temperature?: number;
+}
+
+export interface AiNamingResponse {
+  names: Record<string, string>;
+}
+
+export interface AiSubClusterNamingRequest {
+  job_id: string;
+  point_ids: string[];
+  sub_cluster_labels: number[];
+  api_key: string;
+  model: string;
+  base_url?: string;
+  temperature?: number;
+  parent_cluster_name?: string;
+}
+
+export interface AiTestConnectionRequest {
+  api_key: string;
+  model: string;
+  base_url?: string;
+}
+
+export interface AiTestConnectionResponse {
+  success: boolean;
+  error: string | null;
+}
diff --git a/pyproject.toml b/pyproject.toml
index 61f6c42..553ee41 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,7 +15,7 @@ dependencies = [
     "dash>=3.4,<4",
     "plotly>=6.5,<7",
     "aiohttp>=3.11,<4",
-    "openai>=1.60,<2",
+    "litellm>=1.65,<2",
     "scikit-learn>=1.6,<2",
     "numpy>=2.2,<3",
     "Pillow>=11,<12",
@@ -83,7 +83,7 @@ module = [
     "plotly.*",
     "sklearn.*",
     "PIL.*",
-    "openai.*",
+    "litellm.*",
     "aiohttp.*",
     "umap.*",
 ]
diff --git a/tests/test_ai_naming.py b/tests/test_ai_naming.py
new file mode 100644
index 0000000..1bc308a
--- /dev/null
+++ b/tests/test_ai_naming.py
@@ -0,0 +1,198 @@
+from __future__ import annotations
+
+from unittest.mock import MagicMock, patch
+
+
+class TestGetClusterName:
+    def test_returns_short_name(self) -> None:
+        from embedding_cluster.ai_naming import get_cluster_name
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = "Athletic Footwear"
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ):
+            result = get_cluster_name(
+                item_names=["Running Shoes", "Basketball Sneakers"],
+                api_key="test-key",
+                model="gpt-4o-mini",
+            )
+
+        assert result == "Athletic Footwear"
+
+    def test_truncates_long_name(self) -> None:
+        from embedding_cluster.ai_naming import get_cluster_name
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = "A" * 50
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ):
+            result = get_cluster_name(
+                item_names=["item1"],
+                api_key="test-key",
+                model="gpt-4o-mini",
+            )
+
+        assert len(result) == 32  # 30 chars + ".."
+
+    def test_none_content_returns_empty(self) -> None:
+        from embedding_cluster.ai_naming import get_cluster_name
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = None
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ):
+            result = get_cluster_name(
+                item_names=["item1"],
+                api_key="test-key",
+                model="gpt-4o-mini",
+            )
+
+        assert result == ""
+
+    def test_passes_base_url(self) -> None:
+        from embedding_cluster.ai_naming import get_cluster_name
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = "Name"
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ) as mock_completion:
+            get_cluster_name(
+                item_names=["item1"],
+                api_key="test-key",
+                model="gpt-4o-mini",
+                base_url="http://localhost:11434",
+            )
+
+        mock_completion.assert_called_once()
+        call_kwargs = mock_completion.call_args[1]
+        assert call_kwargs["api_base"] == "http://localhost:11434"
+
+    def test_passes_temperature(self) -> None:
+        from embedding_cluster.ai_naming import get_cluster_name
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = "Name"
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ) as mock_completion:
+            get_cluster_name(
+                item_names=["item1"],
+                api_key="test-key",
+                model="gpt-4o-mini",
+                temperature=0.7,
+            )
+
+        mock_completion.assert_called_once()
+        call_kwargs = mock_completion.call_args[1]
+        assert call_kwargs["temperature"] == 0.7
+
+
+class TestGetSubClusterName:
+    def test_includes_parent_context(self) -> None:
+        from embedding_cluster.ai_naming import get_sub_cluster_name
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = "Running Shoes"
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ) as mock_completion:
+            result = get_sub_cluster_name(
+                item_names=["Nike Air Max", "Adidas Ultraboost"],
+                api_key="test-key",
+                model="gpt-4o-mini",
+                parent_cluster_name="Athletic Footwear",
+            )
+
+        assert result == "Running Shoes"
+        call_kwargs = mock_completion.call_args[1]
+        system_msg = call_kwargs["messages"][0]["content"]
+        assert "Athletic Footwear" in system_msg
+
+    def test_without_parent_name_uses_default_prompt(self) -> None:
+        from embedding_cluster.ai_naming import get_sub_cluster_name
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = "Sub Name"
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ) as mock_completion:
+            result = get_sub_cluster_name(
+                item_names=["item1"],
+                api_key="test-key",
+                model="gpt-4o-mini",
+            )
+
+        assert result == "Sub Name"
+        call_kwargs = mock_completion.call_args[1]
+        system_msg = call_kwargs["messages"][0]["content"]
+        assert "sub-group" not in system_msg
+
+
+class TestTestConnection:
+    def test_success(self) -> None:
+        from embedding_cluster.ai_naming import test_connection
+
+        mock_response = MagicMock()
+        mock_choice = MagicMock()
+        mock_choice.message.content = "Hello"
+        mock_response.choices = [mock_choice]
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=mock_response,
+        ):
+            success, error = test_connection(
+                api_key="test-key",
+                model="gpt-4o-mini",
+            )
+
+        assert success is True
+        assert error is None
+
+    def test_failure_redacts_key(self) -> None:
+        from embedding_cluster.ai_naming import test_connection
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            side_effect=Exception("Invalid API key: sk-1234567890abcdef"),
+        ):
+            success, error = test_connection(
+                api_key="sk-1234567890abcdef",
+                model="gpt-4o-mini",
+            )
+
+        assert success is False
+        assert error is not None
+        assert "sk-1234567890abcdef" not in error
diff --git a/tests/test_scatter_plot.py b/tests/test_scatter_plot.py
index 6e8128e..2e1227b 100644
--- a/tests/test_scatter_plot.py
+++ b/tests/test_scatter_plot.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from typing import cast
 from unittest.mock import MagicMock, patch
 
 import numpy as np
@@ -50,10 +51,9 @@ def test_custom_separator(self) -> None:
 
 
 class TestGenerateClusterProps:
-    def test_without_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None:
+    def test_without_gpt(self) -> None:
         from embedding_cluster.scatter_plot import generate_cluster_props
 
-        settings = Settings()
         pred_arr = [0, 0, 1, 1, 2]
         text_display = ["a", "b", "c", "d", "e"]
 
@@ -61,7 +61,6 @@ def test_without_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None:
             num_clusters=3,
             pred_arr=pred_arr,
             collection_content_text_display=text_display,
-            settings=settings,
         )
 
         assert len(clusters_indices) == 3
@@ -71,83 +70,6 @@ def test_without_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None:
         assert clusters_indices[2] == [4]
         assert cluster_names == ["Group 1", "Group 2", "Group 3"]
 
-    def test_with_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None:
-        from embedding_cluster.scatter_plot import generate_cluster_props
-
-        monkeypatch.setenv("GPT_GENERATE_CLUSTER_NAME", "true")
-        settings = Settings()
-        pred_arr = [0, 0]
-        text_display = ["item1", "item2"]
-
-        with patch(
-            "embedding_cluster.scatter_plot.gpt_get_cluster_name",
-            return_value="Cool Group",
-        ):
-            _clusters_indices, cluster_names = generate_cluster_props(
-                num_clusters=1,
-                pred_arr=pred_arr,
-                collection_content_text_display=text_display,
-                settings=settings,
-            )
-
-        assert cluster_names == ["Cool Group"]
-
-
-class TestGptGetClusterName:
-    def test_gpt_get_cluster_name(self) -> None:
-        from embedding_cluster.scatter_plot import gpt_get_cluster_name
-
-        settings = Settings()
-
-        with patch("embedding_cluster.scatter_plot.OpenAI") as mock_openai_cls:
-            mock_client = MagicMock()
-            mock_openai_cls.return_value = mock_client
-            mock_completion = MagicMock()
-            mock_choice = MagicMock()
-            mock_choice.message.content = "Fashion Items"
-            mock_completion.choices = [mock_choice]
-            mock_client.chat.completions.create.return_value = mock_completion
-
-            result = gpt_get_cluster_name("item1\nitem2", settings)
-
-        assert result == "Fashion Items"
-
-    def test_gpt_truncates_long_name(self) -> None:
-        from embedding_cluster.scatter_plot import gpt_get_cluster_name
-
-        settings = Settings()
-
-        with patch("embedding_cluster.scatter_plot.OpenAI") as mock_openai_cls:
-            mock_client = MagicMock()
-            mock_openai_cls.return_value = mock_client
-            mock_completion = MagicMock()
-            mock_choice = MagicMock()
-            mock_choice.message.content = "A" * 50
-            mock_completion.choices = [mock_choice]
-            mock_client.chat.completions.create.return_value = mock_completion
-
-            result = gpt_get_cluster_name("info", settings)
-
-        assert len(result) == 32  # 30 chars + ".."
-
-    def test_gpt_none_content(self) -> None:
-        from embedding_cluster.scatter_plot import gpt_get_cluster_name
-
-        settings = Settings()
-
-        with patch("embedding_cluster.scatter_plot.OpenAI") as mock_openai_cls:
-            mock_client = MagicMock()
-            mock_openai_cls.return_value = mock_client
-            mock_completion = MagicMock()
-            mock_choice = MagicMock()
-            mock_choice.message.content = None
-            mock_completion.choices = [mock_choice]
-            mock_client.chat.completions.create.return_value = mock_completion
-
-            result = gpt_get_cluster_name("info", settings)
-
-        assert result == ""
-
 
 class TestLoadChromadbCollection:
     def test_load(self) -> None:
@@ -690,8 +612,8 @@ def test_points_aligned_with_cluster_labels(self) -> None:
         endpoint to return items from the wrong cluster.
         """
         result = self._run_compute(self._make_settings(), n_points=6)
-        points = result["points"]
-        labels = result["cluster_labels"]
+        points = cast("list[dict[str, object]]", result["points"])
+        labels = cast("list[int]", result["cluster_labels"])
         assert len(points) == len(labels)
         for i, (point, label) in enumerate(zip(points, labels, strict=True)):
             assert point["cluster"] == label, (
@@ -706,7 +628,7 @@ def test_points_preserve_original_id_order(self) -> None:
         index-based lookup in cluster-detail and sub-cluster endpoints.
         """
         result = self._run_compute(self._make_settings(), n_points=6)
-        points = result["points"]
+        points = cast("list[dict[str, object]]", result["points"])
         expected_ids = [str(i) for i in range(6)]
         actual_ids = [p["id"] for p in points]
         assert actual_ids == expected_ids
diff --git a/tests/test_server_ai.py b/tests/test_server_ai.py
new file mode 100644
index 0000000..1c8ca1f
--- /dev/null
+++ b/tests/test_server_ai.py
@@ -0,0 +1,351 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, cast
+from unittest.mock import MagicMock, patch
+
+import pytest
+from fastapi import status
+from httpx import ASGITransport, AsyncClient
+
+if TYPE_CHECKING:
+    from fastapi import FastAPI
+
+from embedding_cluster.server.app import create_app
+from embedding_cluster.server.tasks import TaskStatus, task_registry
+
+
+@pytest.fixture
+def app() -> FastAPI:
+    return create_app()
+
+
+@pytest.fixture
+def completed_job() -> str:
+    """Create a completed job in the task registry and return its ID."""
+    task = task_registry.create()
+    task.status = TaskStatus.COMPLETED
+    task.result = {
+        "points": [
+            {
+                "id": "p1",
+                "x": 1.0,
+                "y": 2.0,
+                "z": 3.0,
+                "cluster": 0,
+                "metadata": {"name": "Running Shoes"},
+            },
+            {
+                "id": "p2",
+                "x": 4.0,
+                "y": 5.0,
+                "z": 6.0,
+                "cluster": 0,
+                "metadata": {"name": "Basketball Sneakers"},
+            },
+            {
+                "id": "p3",
+                "x": 7.0,
+                "y": 8.0,
+                "z": 9.0,
+                "cluster": 1,
+                "metadata": {"name": "Summer Dress"},
+            },
+        ],
+        "cluster_labels": [0, 0, 1],
+        "clusters": [
+            {"index": 0, "name": "Group 1", "color": "#ff0000", "count": 2},
+            {"index": 1, "name": "Group 2", "color": "#00ff00", "count": 1},
+        ],
+        "total_points": 3,
+    }
+    return task.job_id
+
+
+def _mock_llm_response(content: str = "Athletic Footwear") -> MagicMock:
+    mock_response = MagicMock()
+    mock_choice = MagicMock()
+    mock_choice.message.content = content
+    mock_response.choices = [mock_choice]
+    return mock_response
+
+
+class TestNameClusters:
+    @pytest.mark.asyncio
+    async def test_names_clusters_successfully(
+        self, app: FastAPI, completed_job: str
+    ) -> None:
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=_mock_llm_response("Athletic Footwear"),
+        ):
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                response = await client.post(
+                    "/api/ai/name-clusters",
+                    json={
+                        "job_id": completed_job,
+                        "cluster_indices": [0],
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                    },
+                )
+
+        assert response.status_code == status.HTTP_200_OK
+        data = cast("dict[str, object]", response.json())
+        names = cast("dict[str, str]", data["names"])
+        assert "0" in names
+        assert names["0"] == "Athletic Footwear"
+
+    @pytest.mark.asyncio
+    async def test_names_multiple_clusters(
+        self, app: FastAPI, completed_job: str
+    ) -> None:
+        call_count = 0
+
+        def side_effect(**kwargs: object) -> MagicMock:
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                return _mock_llm_response("Athletic Footwear")
+            return _mock_llm_response("Fashion Dresses")
+
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            side_effect=side_effect,
+        ):
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                response = await client.post(
+                    "/api/ai/name-clusters",
+                    json={
+                        "job_id": completed_job,
+                        "cluster_indices": [0, 1],
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                    },
+                )
+
+        assert response.status_code == status.HTTP_200_OK
+        data = cast("dict[str, object]", response.json())
+        names = cast("dict[str, str]", data["names"])
+        assert "0" in names
+        assert "1" in names
+
+    @pytest.mark.asyncio
+    async def test_job_not_found(self, app: FastAPI) -> None:
+        async with AsyncClient(
+            transport=ASGITransport(app=app), base_url="http://test"
+        ) as client:
+            response = await client.post(
+                "/api/ai/name-clusters",
+                json={
+                    "job_id": "nonexistent-id",
+                    "cluster_indices": [0],
+                    "api_key": "test-key",
+                    "model": "gpt-4o-mini",
+                },
+            )
+
+        assert response.status_code == status.HTTP_404_NOT_FOUND
+
+    @pytest.mark.asyncio
+    async def test_job_not_completed(self, app: FastAPI) -> None:
+        task = task_registry.create()
+        task.status = TaskStatus.RUNNING
+
+        async with AsyncClient(
+            transport=ASGITransport(app=app), base_url="http://test"
+        ) as client:
+            response = await client.post(
+                "/api/ai/name-clusters",
+                json={
+                    "job_id": task.job_id,
+                    "cluster_indices": [0],
+                    "api_key": "test-key",
+                    "model": "gpt-4o-mini",
+                },
+            )
+
+        assert response.status_code == status.HTTP_409_CONFLICT
+
+    @pytest.mark.asyncio
+    async def test_passes_optional_params(self, app: FastAPI, completed_job: str) -> None:
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=_mock_llm_response("Name"),
+        ) as mock_completion:
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                await client.post(
+                    "/api/ai/name-clusters",
+                    json={
+                        "job_id": completed_job,
+                        "cluster_indices": [0],
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                        "base_url": "http://localhost:11434",
+                        "temperature": 0.8,
+                    },
+                )
+
+        call_kwargs = mock_completion.call_args[1]
+        assert call_kwargs["api_base"] == "http://localhost:11434"
+        assert call_kwargs["temperature"] == 0.8
+
+
+class TestNameSubClusters:
+    @pytest.mark.asyncio
+    async def test_names_sub_clusters_successfully(
+        self, app: FastAPI, completed_job: str
+    ) -> None:
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=_mock_llm_response("Running Shoes"),
+        ):
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                response = await client.post(
+                    "/api/ai/name-sub-clusters",
+                    json={
+                        "job_id": completed_job,
+                        "point_ids": ["p1", "p2"],
+                        "sub_cluster_labels": [0, 1],
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                    },
+                )
+
+        assert response.status_code == status.HTTP_200_OK
+        data = cast("dict[str, object]", response.json())
+        names = cast("dict[str, str]", data["names"])
+        assert "0" in names
+        assert "1" in names
+
+    @pytest.mark.asyncio
+    async def test_with_parent_cluster_name(
+        self, app: FastAPI, completed_job: str
+    ) -> None:
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=_mock_llm_response("Running Shoes"),
+        ) as mock_completion:
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                await client.post(
+                    "/api/ai/name-sub-clusters",
+                    json={
+                        "job_id": completed_job,
+                        "point_ids": ["p1"],
+                        "sub_cluster_labels": [0],
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                        "parent_cluster_name": "Athletic Footwear",
+                    },
+                )
+
+        call_kwargs = mock_completion.call_args[1]
+        system_msg = call_kwargs["messages"][0]["content"]
+        assert "Athletic Footwear" in system_msg
+
+    @pytest.mark.asyncio
+    async def test_job_not_found(self, app: FastAPI) -> None:
+        async with AsyncClient(
+            transport=ASGITransport(app=app), base_url="http://test"
+        ) as client:
+            response = await client.post(
+                "/api/ai/name-sub-clusters",
+                json={
+                    "job_id": "nonexistent-id",
+                    "point_ids": ["p1"],
+                    "sub_cluster_labels": [0],
+                    "api_key": "test-key",
+                    "model": "gpt-4o-mini",
+                },
+            )
+
+        assert response.status_code == status.HTTP_404_NOT_FOUND
+
+
+class TestTestConnection:
+    @pytest.mark.asyncio
+    async def test_successful_connection(self, app: FastAPI) -> None:
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=_mock_llm_response("Hello"),
+        ):
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                response = await client.post(
+                    "/api/ai/test-connection",
+                    json={
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                    },
+                )
+
+        assert response.status_code == status.HTTP_200_OK
+        data = cast("dict[str, object]", response.json())
+        assert data["success"] is True
+        assert data["error"] is None
+
+    @pytest.mark.asyncio
+    async def test_failed_connection(self, app: FastAPI) -> None:
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            side_effect=Exception("Connection refused"),
+        ):
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                response = await client.post(
+                    "/api/ai/test-connection",
+                    json={
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                    },
+                )
+
+        assert response.status_code == status.HTTP_200_OK
+        data = cast("dict[str, object]", response.json())
+        assert data["success"] is False
+        assert data["error"] is not None
+        assert "Connection refused" in cast("str", data["error"])
+
+    @pytest.mark.asyncio
+    async def test_with_base_url(self, app: FastAPI) -> None:
+        with patch(
+            "embedding_cluster.ai_naming.litellm_completion",
+            return_value=_mock_llm_response("Hello"),
+        ) as mock_completion:
+            async with AsyncClient(
+                transport=ASGITransport(app=app), base_url="http://test"
+            ) as client:
+                await client.post(
+                    "/api/ai/test-connection",
+                    json={
+                        "api_key": "test-key",
+                        "model": "gpt-4o-mini",
+                        "base_url": "http://localhost:11434",
+                    },
+                )
+
+        call_kwargs = mock_completion.call_args[1]
+        assert call_kwargs["api_base"] == "http://localhost:11434"
+
+    @pytest.mark.asyncio
+    async def test_missing_required_fields(self, app: FastAPI) -> None:
+        async with AsyncClient(
+            transport=ASGITransport(app=app), base_url="http://test"
+        ) as client:
+            response = await client.post(
+                "/api/ai/test-connection",
+                json={},
+            )
+
+        assert response.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY
diff --git a/tests/test_server_plot.py b/tests/test_server_plot.py
index 4aa1d76..7f0bb25 100644
--- a/tests/test_server_plot.py
+++ b/tests/test_server_plot.py
@@ -241,9 +241,6 @@ async def test_compute_with_all_fields(app: FastAPI, mock_compute: None) -> None
                 "num_clusters": 5,
                 "text_display_fields": ["name", "description"],
                 "image_field": "imageUrl",
-                "gpt_generate_cluster_name": True,
-                "gpt_default_model": "gpt-4",
-                "gpt_default_temperature": 0.7,
             },
         )
 
diff --git a/tests/test_settings.py b/tests/test_settings.py
index 8d7dfed..6befd5f 100644
--- a/tests/test_settings.py
+++ b/tests/test_settings.py
@@ -36,12 +36,6 @@ def test_default_none_fields(self) -> None:
         assert s.image_field is None
         assert s.id_field is None
 
-    def test_default_gpt_settings(self) -> None:
-        s = Settings()
-        assert s.gpt_generate_cluster_name is False
-        assert s.gpt_default_model == "gpt-3.5-turbo"
-        assert s.gpt_default_temperature == pytest.approx(0.51)
-
     def test_default_model_names(self) -> None:
         s = Settings()
         assert s.image_model_name == "openai/clip-vit-base-patch32"
@@ -86,11 +80,6 @@ def test_text_display_fields_from_env(self, monkeypatch: pytest.MonkeyPatch) ->
         s = Settings()
         assert s.text_display_fields == ["productDisplayName"]
 
-    def test_boolean_field_from_env(self, monkeypatch: pytest.MonkeyPatch) -> None:
-        monkeypatch.setenv("GPT_GENERATE_CLUSTER_NAME", "true")
-        s = Settings()
-        assert s.gpt_generate_cluster_name is True
-
     def test_start_end_lines_from_env(self, monkeypatch: pytest.MonkeyPatch) -> None:
         monkeypatch.setenv("INDEX_START_LINE", "5")
         monkeypatch.setenv("INDEX_END_LINE", "100")
diff --git a/uv.lock b/uv.lock
index db32f7a..ad1128b 100644
--- a/uv.lock
+++ b/uv.lock
@@ -366,8 +366,8 @@ dependencies = [
     { name = "chromadb", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
     { name = "dash", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
     { name = "fastapi", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "litellm", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
     { name = "numpy", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
-    { name = "openai", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
     { name = "pillow", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
     { name = "plotly", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
     { name = "pydantic", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
@@ -402,9 +402,9 @@ requires-dist = [
     { name = "dash", specifier = ">=3.4,<4" },
     { name = "fastapi", specifier = ">=0.115,<1" },
     { name = "httpx", marker = "extra == 'dev'", specifier = ">=0.28,<1" },
+    { name = "litellm", specifier = ">=1.65,<2" },
     { name = "mypy", marker = "extra == 'dev'", specifier = ">=1.14,<2" },
     { name = "numpy", specifier = ">=2.2,<3" },
-    { name = "openai", specifier = ">=1.60,<2" },
     { name = "pillow", specifier = ">=11,<12" },
     { name = "plotly", specifier = ">=6.5,<7" },
     { name = "pre-commit", marker = "extra == 'dev'", specifier = ">=4,<5" },
@@ -441,6 +441,24 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/9e/dd/d0ee25348ac58245ee9f90b6f3cbb666bf01f69be7e0911f9851bddbda16/fastapi-0.129.0-py3-none-any.whl", hash = "sha256:b4946880e48f462692b31c083be0432275cbfb6e2274566b1be91479cc1a84ec", size = 102950, upload-time = "2026-02-12T13:54:54.528Z" },
 ]
 
+[[package]]
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+version = "0.14.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/c3/7d/d9daedf0f2ebcacd20d599928f8913e9d2aea1d56d2d355a93bfa2b611d7/fastuuid-0.14.0.tar.gz", hash = "sha256:178947fc2f995b38497a74172adee64fdeb8b7ec18f2a5934d037641ba265d26", size = 18232, upload-time = "2025-10-19T22:19:22.402Z" }
+wheels = [
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+    { url = "https://files.pythonhosted.org/packages/53/b0/a4b03ff5d00f563cc7546b933c28cb3f2a07344b2aec5834e874f7d44143/fastuuid-0.14.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:9bd57289daf7b153bfa3e8013446aa144ce5e8c825e9e366d455155ede5ea2dc", size = 262024, upload-time = "2025-10-19T22:30:25.482Z" },
+    { url = "https://files.pythonhosted.org/packages/9c/6d/64aee0a0f6a58eeabadd582e55d0d7d70258ffdd01d093b30c53d668303b/fastuuid-0.14.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ac60fc860cdf3c3f327374db87ab8e064c86566ca8c49d2e30df15eda1b0c2d5", size = 251679, upload-time = "2025-10-19T22:36:14.096Z" },
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+    { url = "https://files.pythonhosted.org/packages/16/c9/8c7660d1fe3862e3f8acabd9be7fc9ad71eb270f1c65cce9a2b7a31329ab/fastuuid-0.14.0-cp314-cp314-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:b852a870a61cfc26c884af205d502881a2e59cc07076b60ab4a951cc0c94d1ad", size = 510600, upload-time = "2025-10-19T22:43:44.17Z" },
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+    { url = "https://files.pythonhosted.org/packages/ef/33/4105ca574f6ded0af6a797d39add041bcfb468a1255fbbe82fcb6f592da2/fastuuid-0.14.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a8a0dfea3972200f72d4c7df02c8ac70bad1bb4c58d7e0ec1e6f341679073a7f", size = 278283, upload-time = "2025-10-19T22:29:02.812Z" },
+    { url = "https://files.pythonhosted.org/packages/e0/c8/2ce1c78f983a2c4987ea865d9516dbdfb141a120fd3abb977ae6f02ba7ca/fastuuid-0.14.0-cp314-cp314-musllinux_1_1_x86_64.whl", hash = "sha256:ec27778c6ca3393ef662e2762dba8af13f4ec1aaa32d08d77f71f2a70ae9feb8", size = 450837, upload-time = "2025-10-19T22:34:37.178Z" },
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+
 [[package]]
 name = "filelock"
 version = "3.24.3"
@@ -733,6 +751,33 @@ wheels = [
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 ]
 
+[[package]]
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+version = "4.26.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "attrs", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
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+    { name = "referencing", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "rpds-py", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+]
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+wheels = [
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+]
+
+[[package]]
+name = "jsonschema-specifications"
+version = "2025.9.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "referencing", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/19/74/a633ee74eb36c44aa6d1095e7cc5569bebf04342ee146178e2d36600708b/jsonschema_specifications-2025.9.1.tar.gz", hash = "sha256:b540987f239e745613c7a9176f3edb72b832a4ac465cf02712288397832b5e8d", size = 32855, upload-time = "2025-09-08T01:34:59.186Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl", hash = "sha256:98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe", size = 18437, upload-time = "2025-09-08T01:34:57.871Z" },
+]
+
 [[package]]
 name = "kubernetes"
 version = "35.0.0"
@@ -773,6 +818,29 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/2b/39/191d3d28abc26c9099b19852e6c99f7f6d400b82fa5a4e80291bd3803e19/librt-0.8.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:cc3656283d11540ab0ea01978378e73e10002145117055e03722417aeab30994", size = 263001, upload-time = "2026-02-17T16:12:43.627Z" },
 ]
 
+[[package]]
+name = "litellm"
+version = "1.82.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiohttp", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "click", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "fastuuid", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "httpx", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "importlib-metadata", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "jinja2", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "jsonschema", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "openai", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "pydantic", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "python-dotenv", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "tiktoken", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "tokenizers", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+]
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+wheels = [
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+]
+
 [[package]]
 name = "llvmlite"
 version = "0.46.0"
@@ -1176,7 +1244,7 @@ wheels = [
 
 [[package]]
 name = "openai"
-version = "1.109.1"
+version = "2.30.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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@@ -1188,9 +1256,9 @@ dependencies = [
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+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "attrs", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+    { name = "rpds-py", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or sys_platform == 'darwin'" },
+]
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+wheels = [
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 version = "2026.1.15"
@@ -1773,6 +1854,30 @@ wheels = [
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