feat: cloud PageIndex, streaming query, image improvements, and CI

Author: KylinMountain

.env.example

@@ -0,0 +1,6 @@
+# LLM API key (required)
+OPENAI_API_KEY=sk-your-key-here
+
+# PageIndex Cloud API key (optional, leave empty for local PageIndex)
+# Get your key at https://pageindex.dev
+# PAGEINDEX_API_KEY=your-key-here

.github/workflows/publish.yml

@@ -0,0 +1,27 @@
+name: Publish to PyPI
+
+on:
+  push:
+    tags:
+      - "v*"
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Install build tools
+        run: pip install build
+
+      - name: Build package
+        run: python -m build
+
+      - name: Publish to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1

.gitignore

@@ -13,3 +13,7 @@ venv/
 raw/
 wiki/
 .okb/
+
+# Local only
+docs/
+.claude/

LICENSE

@@ -0,0 +1,190 @@
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README.md

@@ -97,12 +97,14 @@ wiki/
 | | Short documents | Long documents (PDF ≥ 50 pages) |
 |---|---|---|
 | **Convert** | markitdown → Markdown | PageIndex → tree index + summaries |
-| **Images** | Extracted from base64 | Pending PageIndex support |
+| **Images** | Extracted inline (pymupdf) | Extracted by PageIndex |
 | **LLM reads** | Full text | Tree summaries only |
 | **Result** | summary + concepts | summary + concepts |
 
 Short docs are read in full by the LLM. Long PDFs are indexed by PageIndex into a hierarchical tree with summaries — the LLM reads the tree instead of the full text, avoiding context window limits while retaining structural understanding.
 
+> **⚡ PageIndex Cloud API** — By default, PageIndex runs locally. Set `PAGEINDEX_API_KEY` in your `.env` to use [PageIndex Cloud](https://pageindex.ai/) for faster indexing. Get an API key at [pageindex.dev](https://pageindex.dev).
+
 ### The wiki compiles knowledge
 
 When you add a document, the LLM:
@@ -137,6 +139,7 @@ model: gpt-5.4                   # LLM model (any LiteLLM-supported provider)
 api_key_env: OPENAI_API_KEY      # Environment variable for API key
 language: en                      # Wiki output language
 pageindex_threshold: 50           # PDF pages threshold for PageIndex
+pageindex_api_key_env: ""                # Env var name for PageIndex Cloud API key (default: auto-detect PAGEINDEX_API_KEY)
 ```
 
 ### AGENTS.md
@@ -176,8 +179,8 @@ OpenKB's wiki is a directory of Markdown files with `[[wikilinks]]` — Obsidian
 
 ## License
 
-MIT
+Apache 2.0 — see [LICENSE](LICENSE)
 
 ## Acknowledgments
 
-Inspired by [Andrej Karpathy's LLM Wiki pattern](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f). Powered by [PageIndex](https://github.com/VectifyAI/PageIndex).
+Inspired by [Andrej Karpathy's LLM Wiki pattern](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f). Powered by [PageIndex](https://pageindex.ai/).

examples/docs/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf

@@ -102,11 +102,14 @@ def write_file(path: str, content: str) -> str:
         """
         return write_wiki_file(path, content, wiki_root)
 
+    from agents.model_settings import ModelSettings
+
     return Agent(
         name="wiki-compiler",
         instructions=instructions,
         tools=[list_files, read_file, write_file],
         model=model,
+        model_settings=ModelSettings(parallel_tool_calls=False),
     )
 
 
@@ -127,7 +130,8 @@ def build_long_doc_compiler_agent(wiki_root: str, kb_dir: str, model: str, langu
     okb_dir = Path(kb_dir) / ".okb"
     config = load_config(okb_dir / "config.yaml")
     _model = config.get("model", model)
-    pi_api_key = os.environ.get(config.get("pageindex_api_key_env", ""), "")
+    pi_key_env = config.get("pageindex_api_key_env", "") or "PAGEINDEX_API_KEY"
+    pi_api_key = os.environ.get(pi_key_env, "")
     client = PageIndexClient(
         api_key=pi_api_key or None,
         model=_model,
@@ -185,11 +189,14 @@ def get_page_content(doc_id: str, pages: str) -> str:
             parts.append(f"[Page {page_num}]\n{text}")
         return "\n\n".join(parts)
 
+    from agents.model_settings import ModelSettings
+
     return Agent(
         name="wiki-compiler",
         instructions=instructions,
         tools=[list_files, read_file, write_file, get_page_content],
-        model=model,
+        model=_model,
+        model_settings=ModelSettings(parallel_tool_calls=False),
     )