feat: add model override for community labeling

graphify/__main__.py

@@ -2141,8 +2141,10 @@ def main() -> None:
         print("    --graph <path>          path to graph.json (default <path>/graphify-out/graph.json)")
         print("    --no-label              keep 'Community N' placeholders (skip LLM community naming)")
         print("    --backend=<name>        backend to use for community naming (default: auto-detect)")
+        print("    --model=<name>          model to use for community naming")
         print("  label <path>            (re)name communities with the configured LLM backend, regenerate report")
         print("    --backend=<name>        backend to use (default: auto-detect from API keys)")
+        print("    --model=<name>          model to use for community naming")
         print("  query \"<question>\"       BFS traversal of graph.json for a question")
         print("    --dfs                   use depth-first instead of breadth-first")
         print("    --context C             explicit edge-context filter (repeatable)")
@@ -3131,6 +3133,8 @@ def main() -> None:
         no_label = "--no-label" in sys.argv
         _backend_arg = next((a for a in sys.argv if a.startswith("--backend=")), None)
         label_backend = _backend_arg.split("=", 1)[1] if _backend_arg else None
+        _model_arg = next((a for a in sys.argv if a.startswith("--model=")), None)
+        label_model = _model_arg.split("=", 1)[1] if _model_arg else None
         _min_cs_arg = next((a for a in sys.argv if a.startswith("--min-community-size=")), None)
         min_community_size = int(_min_cs_arg.split("=")[1]) if _min_cs_arg else 3
         args = sys.argv[2:]
@@ -3143,6 +3147,14 @@ def main() -> None:
             a = args[i_arg]
             if a == "--graph" and i_arg + 1 < len(args):
                 graph_override = Path(args[i_arg + 1]); i_arg += 2
+            elif a == "--backend" and i_arg + 1 < len(args):
+                label_backend = args[i_arg + 1]; i_arg += 2
+            elif a.startswith("--backend="):
+                label_backend = a.split("=", 1)[1]; i_arg += 1
+            elif a == "--model" and i_arg + 1 < len(args):
+                label_model = args[i_arg + 1]; i_arg += 2
+            elif a.startswith("--model="):
+                label_model = a.split("=", 1)[1]; i_arg += 1
             elif a == "--resolution" and i_arg + 1 < len(args):
                 co_resolution = float(args[i_arg + 1]); i_arg += 2
             elif a.startswith("--resolution="):
@@ -3240,7 +3252,7 @@ def main() -> None:
             # The final labels (LLM or placeholder fallback) are persisted to
             # .graphify_labels.json by the unconditional write below.
             labels, _ = generate_community_labels(
-                G, communities, backend=label_backend, gods=gods
+                G, communities, backend=label_backend, model=label_model, gods=gods
             )
         questions = suggest_questions(G, communities, labels)
         tokens = {"input": 0, "output": 0}

graphify/llm.py

@@ -1716,7 +1716,13 @@ def _merge_into(merged: dict, result: dict) -> None:
     merged["output_tokens"] += result.get("output_tokens", 0)
 
 
-def _call_llm(prompt: str, *, backend: str, max_tokens: int = 200) -> str:
+def _call_llm(
+    prompt: str,
+    *,
+    backend: str,
+    max_tokens: int = 200,
+    model: str | None = None,
+) -> str:
     """Send a plain-text prompt to `backend` and return the model's text reply.
 
     Used by lightweight callers (e.g. `graphify.dedup` LLM tiebreaker) that
@@ -1740,7 +1746,7 @@ def _call_llm(prompt: str, *, backend: str, max_tokens: int = 200) -> str:
         raise ValueError(
             f"No API key for backend '{backend}'. Set {_format_backend_env_keys(backend)}."
         )
-    mdl = _default_model_for_backend(backend)
+    mdl = model or _default_model_for_backend(backend)
 
     if backend == "claude":
         try:
@@ -1769,8 +1775,11 @@ def _call_llm(prompt: str, *, backend: str, max_tokens: int = 200) -> str:
                 raise RuntimeError("Claude Code CLI not found on $PATH")
         elif shutil.which("claude") is None:
             raise RuntimeError("Claude Code CLI not found on $PATH")
+        cli_args = [claude_cmd, "-p", "--output-format", "json", "--no-session-persistence"]
+        if model is not None:
+            cli_args.extend(["--model", mdl])
         proc = subprocess.run(
-            [claude_cmd, "-p", "--output-format", "json", "--no-session-persistence"],
+            cli_args,
             input=prompt,
             capture_output=True,
             text=True,
@@ -2033,6 +2042,7 @@ def label_communities(
     communities,
     *,
     backend: str,
+    model: str | None = None,
     gods=None,
     max_communities: int | None = None,
     top_k: int = _LABEL_TOP_K,
@@ -2084,7 +2094,10 @@ def label_communities(
         # _resolve_max_tokens so GRAPHIFY_MAX_OUTPUT_TOKENS applies here too (#1200).
         max_tokens = _resolve_max_tokens(min(64 + 24 * len(batch_cids), 8192))
         try:
-            text = _call_llm(prompt, backend=backend, max_tokens=max_tokens)
+            call_kwargs = {"backend": backend, "max_tokens": max_tokens}
+            if model is not None:
+                call_kwargs["model"] = model
+            text = _call_llm(prompt, **call_kwargs)
             parsed = _parse_label_response(text, batch_cids)
             labels.update(parsed)
             written += len(parsed)
@@ -2109,6 +2122,7 @@ def generate_community_labels(
     communities,
     *,
     backend: str | None = None,
+    model: str | None = None,
     gods=None,
     quiet: bool = False,
 ) -> tuple[dict[int, str], str]:
@@ -2130,7 +2144,7 @@ def generate_community_labels(
             )
         return _placeholder_community_labels(communities), "placeholder"
     try:
-        labels = label_communities(G, communities, backend=backend, gods=gods)
+        labels = label_communities(G, communities, backend=backend, model=model, gods=gods)
         return labels, "llm"
     except Exception as exc:
         if not quiet:

tests/test_labeling.py

@@ -3,6 +3,9 @@
 Backend calls are mocked - no network. Covers the happy path, partial replies,
 malformed replies, and the no-backend fallback.
 """
+import json
+import sys
+
 import networkx as nx
 import pytest
 
@@ -40,6 +43,71 @@ def test_label_communities_happy_path(monkeypatch):
     assert captured["backend"] == "gemini"
 
 
+def test_label_communities_passes_model_override(monkeypatch):
+    G, communities = _graph()
+    captured = {}
+
+    def fake_call(prompt, *, backend, max_tokens=200, model=None):
+        captured["backend"] = backend
+        captured["model"] = model
+        return '{"0": "Order Management", "1": "Payment Flow"}'
+
+    monkeypatch.setattr("graphify.llm._call_llm", fake_call)
+    labels = label_communities(
+        G,
+        communities,
+        backend="gemini",
+        model="gemini-3.1-flash-lite",
+    )
+
+    assert labels == {0: "Order Management", 1: "Payment Flow"}
+    assert captured == {"backend": "gemini", "model": "gemini-3.1-flash-lite"}
+
+
+def test_label_cli_passes_model_override(tmp_path, monkeypatch):
+    import graphify.__main__ as cli
+
+    out = tmp_path / "graphify-out"
+    out.mkdir()
+    graph = {
+        "directed": False,
+        "multigraph": False,
+        "nodes": [
+            {"id": "n1", "label": "OrderService", "community": 0},
+        ],
+        "links": [],
+    }
+    (out / "graph.json").write_text(json.dumps(graph), encoding="utf-8")
+
+    captured = {}
+
+    def fake_generate(G, communities, *, backend=None, model=None, gods=None, quiet=False):
+        captured["backend"] = backend
+        captured["model"] = model
+        return {0: "Orders"}, "llm"
+
+    monkeypatch.setattr("graphify.llm.generate_community_labels", fake_generate)
+    monkeypatch.setattr("graphify.export.to_html", lambda *args, **kwargs: None)
+    monkeypatch.setattr(
+        sys,
+        "argv",
+        [
+            "graphify",
+            "label",
+            str(tmp_path),
+            "--backend",
+            "gemini",
+            "--model",
+            "gemini-3.1-flash-lite",
+            "--no-viz",
+        ],
+    )
+
+    cli.main()
+
+    assert captured == {"backend": "gemini", "model": "gemini-3.1-flash-lite"}
+
+
 def test_label_communities_partial_reply_fills_placeholder(monkeypatch):
     G, communities = _graph()
     monkeypatch.setattr("graphify.llm._call_llm",