Require user API key for pipeline + generated-page summaries; keep secret for demo summaries; add OpenAI key guide link

api.py

@@ -93,13 +93,28 @@ class ClassifyPayload(BaseModel):
     api_key: Optional[str] = None
 
 
-def _resolve_api_key(supplied: Optional[str]) -> str:
-    key = (supplied or "").strip() or os.environ.get("OPENAI_API_KEY", "").strip()
+def _resolve_api_key(
+    supplied: Optional[str], allow_secret_fallback: bool = True
+) -> str:
+    """Resolve the OpenAI key to use for a request.
+
+    When ``allow_secret_fallback`` is True (the demo's summary feature), an
+    empty supplied key falls back to the server's ``OPENAI_API_KEY`` secret.
+    When False (the user-driven classification pipeline and summaries on a
+    generated page), only the user-supplied key is accepted — the server
+    secret is never used, so the caller must provide their own key.
+    """
+    supplied_key = (supplied or "").strip()
+    if allow_secret_fallback:
+        key = supplied_key or os.environ.get("OPENAI_API_KEY", "").strip()
+    else:
+        key = supplied_key
     if not key:
-        raise HTTPException(
-            status_code=400,
-            detail="No OpenAI API key available — none supplied and OPENAI_API_KEY is unset.",
-        )
+        if allow_secret_fallback:
+            detail = "No OpenAI API key available — none supplied and OPENAI_API_KEY is unset."
+        else:
+            detail = "An OpenAI API key is required for this request. Please provide your own key."
+        raise HTTPException(status_code=400, detail=detail)
     return key
 
 @app.post("/prepare")
@@ -158,7 +173,9 @@ async def classify_article(payload: ClassifyPayload, background_tasks: Backgroun
     Start classification in the background and return immediately.
     Uses the flexible-linker pipeline + OpenAI Batch API (single batch).
     """
-    api_key = _resolve_api_key(payload.api_key)
+    # The classification pipeline runs on the user's own key — never the
+    # server secret. The demo path doesn't hit /classify at all.
+    api_key = _resolve_api_key(payload.api_key, allow_secret_fallback=False)
     model_name = payload.model or "gpt-5-mini"
 
     df, title = fetch_revision_history(payload.article)
@@ -571,6 +588,11 @@ class SummarizePayload(BaseModel):
     section_ids: Optional[List[int]] = None  # grouped_idx values; None = all sections
     api_key: Optional[str] = None
     model: Optional[str] = "gpt-5.4"
+    # Whether this summary may use the server's OPENAI_API_KEY secret. True
+    # only for the demo pages (their summaries run on the provided secret key).
+    # False for summaries on a user-generated page or an uploaded CSV, which
+    # must run on the user's own key.
+    use_server_key: bool = False
     # When the dataset lives only in the user's browser (CSV they uploaded),
     # the frontend filters rows itself and sends just the matching explanation
     # snippets here. If provided, the server skips its own dataset lookup.
@@ -1043,7 +1065,13 @@ async def summarize_edits(payload: SummarizePayload) -> Dict[str, Any]:
 
     try:
         import openai
-        client = openai.OpenAI(api_key=_resolve_api_key(payload.api_key))
+        # Demo summaries fall back to the server secret; summaries on a
+        # user-generated page or uploaded CSV require the user's own key.
+        client = openai.OpenAI(
+            api_key=_resolve_api_key(
+                payload.api_key, allow_secret_fallback=payload.use_server_key
+            )
+        )
         completion = client.chat.completions.create(
             model="gpt-5.4",
             messages=[

frontend_build/asset-manifest.json

@@ -1,7 +1,7 @@
 {
   "files": {
     "main.css": "/static/css/main.ccff2033.css",
-    "main.js": "/static/js/main.65a51a7c.js",
+    "main.js": "/static/js/main.8068e73f.js",
     "static/js/206.b8423ec3.chunk.js": "/static/js/206.b8423ec3.chunk.js",
     "static/media/KaTeX_AMS-Regular.ttf": "/static/media/KaTeX_AMS-Regular.853be92419a6c3766b9a.ttf",
     "static/media/KaTeX_Main-Regular.ttf": "/static/media/KaTeX_Main-Regular.9eba1d77abcf2aa6e94e.ttf",
@@ -67,6 +67,6 @@
   },
   "entrypoints": [
     "static/css/main.ccff2033.css",
-    "static/js/main.65a51a7c.js"
+    "static/js/main.8068e73f.js"
   ]
 }

frontend_build/index.html

@@ -1 +1 @@
-<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#0e7490"/><meta name="description" content="Wikistar — understand how scientific revisions evolve over time for a specific Wikipedia page."/><link rel="apple-touch-icon" href="/wikistar-192.png"/><link rel="manifest" href="/manifest.json"/><title>Wikistar — Wikipedia Edit History Explorer</title><script defer="defer" src="/static/js/main.65a51a7c.js"></script><link href="/static/css/main.ccff2033.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
+<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#0e7490"/><meta name="description" content="Wikistar — understand how scientific revisions evolve over time for a specific Wikipedia page."/><link rel="apple-touch-icon" href="/wikistar-192.png"/><link rel="manifest" href="/manifest.json"/><title>Wikistar — Wikipedia Edit History Explorer</title><script defer="defer" src="/static/js/main.8068e73f.js"></script><link href="/static/css/main.ccff2033.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>