Add PageIndexClient with agent-based retrieval via OpenAI Agents SDK (#125)

* Add PageIndexClient with retrieve, streaming support and litellm integration
* Add OpenAI agents demo example
* Update README with example agent demo section
* Support separate retrieve_model configuration for index and retrieve

pageindex/__init__.py

@@ -1,2 +1,4 @@
 from .page_index import *
-from .page_index_md import md_to_tree
+from .page_index_md import md_to_tree
+from .retrieve import get_document, get_document_structure, get_page_content
+from .client import PageIndexClient

pageindex/client.py

@@ -0,0 +1,132 @@
+import os
+import uuid
+import json
+import asyncio
+import concurrent.futures
+from pathlib import Path
+
+from .page_index import page_index
+from .page_index_md import md_to_tree
+from .retrieve import get_document, get_document_structure, get_page_content
+from .utils import ConfigLoader
+
+class PageIndexClient:
+    """
+    A client for indexing and retrieving document content.
+    Flow: index() -> get_document() / get_document_structure() / get_page_content()
+
+    For agent-based QA, see examples/openai_agents_demo.py.
+    """
+    def __init__(self, api_key: str = None, model: str = None, retrieve_model: str = None, workspace: str = None):
+        if api_key:
+            os.environ["OPENAI_API_KEY"] = api_key
+        elif not os.getenv("OPENAI_API_KEY") and os.getenv("CHATGPT_API_KEY"):
+            os.environ["OPENAI_API_KEY"] = os.getenv("CHATGPT_API_KEY")
+        self.workspace = Path(workspace).expanduser() if workspace else None
+        overrides = {}
+        if model:
+            overrides["model"] = model
+        if retrieve_model:
+            overrides["retrieve_model"] = retrieve_model
+        opt = ConfigLoader().load(overrides or None)
+        self.model = opt.model
+        self.retrieve_model = opt.retrieve_model or self.model
+        if self.workspace:
+            self.workspace.mkdir(parents=True, exist_ok=True)
+        self.documents = {}
+        if self.workspace:
+            self._load_workspace()
+
+    def index(self, file_path: str, mode: str = "auto") -> str:
+        """Index a document. Returns a document_id."""
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"File not found: {file_path}")
+
+        doc_id = str(uuid.uuid4())
+        ext = os.path.splitext(file_path)[1].lower()
+
+        is_pdf = ext == '.pdf'
+        is_md = ext in ['.md', '.markdown']
+
+        if mode == "pdf" or (mode == "auto" and is_pdf):
+            print(f"Indexing PDF: {file_path}")
+            result = page_index(
+                doc=file_path,
+                model=self.model,
+                if_add_node_summary='yes',
+                if_add_node_text='yes',
+                if_add_node_id='yes',
+                if_add_doc_description='yes'
+            )
+            self.documents[doc_id] = {
+                'id': doc_id,
+                'path': file_path,
+                'type': 'pdf',
+                'structure': result['structure'],
+                'doc_name': result.get('doc_name', ''),
+                'doc_description': result.get('doc_description', '')
+            }
+
+        elif mode == "md" or (mode == "auto" and is_md):
+            print(f"Indexing Markdown: {file_path}")
+            coro = md_to_tree(
+                md_path=file_path,
+                if_thinning=False,
+                if_add_node_summary='yes',
+                summary_token_threshold=200,
+                model=self.model,
+                if_add_doc_description='yes',
+                if_add_node_text='yes',
+                if_add_node_id='yes'
+            )
+            try:
+                asyncio.get_running_loop()
+                with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
+                    result = pool.submit(asyncio.run, coro).result()
+            except RuntimeError:
+                result = asyncio.run(coro)
+            self.documents[doc_id] = {
+                'id': doc_id,
+                'path': file_path,
+                'type': 'md',
+                'structure': result['structure'],
+                'doc_name': result.get('doc_name', ''),
+                'doc_description': result.get('doc_description', '')
+            }
+        else:
+            raise ValueError(f"Unsupported file format for: {file_path}")
+
+        print(f"Indexing complete. Document ID: {doc_id}")
+        if self.workspace:
+            self._save_doc(doc_id)
+        return doc_id
+
+    def _save_doc(self, doc_id: str):
+        path = self.workspace / f"{doc_id}.json"
+        with open(path, "w", encoding="utf-8") as f:
+            json.dump(self.documents[doc_id], f, ensure_ascii=False, indent=2)
+
+    def _load_workspace(self):
+        loaded = 0
+        for path in self.workspace.glob("*.json"):
+            try:
+                with open(path, "r", encoding="utf-8") as f:
+                    doc = json.load(f)
+                self.documents[path.stem] = doc
+                loaded += 1
+            except (json.JSONDecodeError, OSError) as e:
+                print(f"Warning: skipping corrupt workspace file {path.name}: {e}")
+        if loaded:
+            print(f"Loaded {loaded} document(s) from workspace.")
+
+    def get_document(self, doc_id: str) -> str:
+        """Return document metadata JSON."""
+        return get_document(self.documents, doc_id)
+
+    def get_document_structure(self, doc_id: str) -> str:
+        """Return document tree structure JSON (without text fields)."""
+        return get_document_structure(self.documents, doc_id)
+
+    def get_page_content(self, doc_id: str, pages: str) -> str:
+        """Return page content for the given pages string (e.g. '5-7', '3,8', '12')."""
+        return get_page_content(self.documents, doc_id, pages)

pageindex/config.yaml

@@ -1,5 +1,6 @@
 model: "gpt-4o-2024-11-20"
 # model: "anthropic/claude-sonnet-4-6"
+retrieve_model: "gpt-5.4"  # defaults to model if not set
 toc_check_page_num: 20
 max_page_num_each_node: 10
 max_token_num_each_node: 20000

pageindex/page_index.py

@@ -330,7 +330,7 @@ def toc_transformer(toc_content, model=None):
         if_complete = check_if_toc_transformation_is_complete(toc_content, last_complete, model)
         
 
-    last_complete = json.loads(last_complete)
+    last_complete = extract_json(last_complete)
 
     cleaned_response=convert_page_to_int(last_complete['table_of_contents'])
     return cleaned_response

pageindex/retrieve.py

@@ -0,0 +1,139 @@
+import json
+import PyPDF2
+
+try:
+    from .utils import get_number_of_pages, remove_fields
+except ImportError:
+    from utils import get_number_of_pages, remove_fields
+
+
+# ── Helpers ──────────────────────────────────────────────────────────────────
+
+def _parse_pages(pages: str) -> list[int]:
+    """Parse a pages string like '5-7', '3,8', or '12' into a sorted list of ints."""
+    result = []
+    for part in pages.split(','):
+        part = part.strip()
+        if '-' in part:
+            start, end = int(part.split('-', 1)[0].strip()), int(part.split('-', 1)[1].strip())
+            if start > end:
+                raise ValueError(f"Invalid range '{part}': start must be <= end")
+            result.extend(range(start, end + 1))
+        else:
+            result.append(int(part))
+    return sorted(set(result))
+
+
+def _count_pages(doc_info: dict) -> int:
+    """Return total page count for a document."""
+    if doc_info.get('type') == 'pdf':
+        return get_number_of_pages(doc_info['path'])
+    # For MD, find max line_num across all nodes
+    max_line = 0
+    def _traverse(nodes):
+        nonlocal max_line
+        for node in nodes:
+            ln = node.get('line_num', 0)
+            if ln and ln > max_line:
+                max_line = ln
+            if node.get('nodes'):
+                _traverse(node['nodes'])
+    _traverse(doc_info.get('structure', []))
+    return max_line
+
+
+def _get_pdf_page_content(doc_info: dict, page_nums: list[int]) -> list[dict]:
+    """Extract text for specific PDF pages (1-indexed), opening the PDF once."""
+    path = doc_info['path']
+    with open(path, 'rb') as f:
+        pdf_reader = PyPDF2.PdfReader(f)
+        total = len(pdf_reader.pages)
+        valid_pages = [p for p in page_nums if 1 <= p <= total]
+        return [
+            {'page': p, 'content': pdf_reader.pages[p - 1].extract_text() or ''}
+            for p in valid_pages
+        ]
+
+
+def _get_md_page_content(doc_info: dict, page_nums: list[int]) -> list[dict]:
+    """
+    For Markdown documents, 'pages' are line numbers.
+    Find nodes whose line_num falls within [min(page_nums), max(page_nums)] and return their text.
+    """
+    min_line, max_line = min(page_nums), max(page_nums)
+    results = []
+    seen = set()
+
+    def _traverse(nodes):
+        for node in nodes:
+            ln = node.get('line_num')
+            if ln and min_line <= ln <= max_line and ln not in seen:
+                seen.add(ln)
+                results.append({'page': ln, 'content': node.get('text', '')})
+            if node.get('nodes'):
+                _traverse(node['nodes'])
+
+    _traverse(doc_info.get('structure', []))
+    results.sort(key=lambda x: x['page'])
+    return results
+
+
+# ── Tool functions ────────────────────────────────────────────────────────────
+
+def get_document(documents: dict, doc_id: str) -> str:
+    """Return JSON with document metadata: doc_id, doc_name, doc_description, type, status, page_count (PDF) or line_count (Markdown)."""
+    doc_info = documents.get(doc_id)
+    if not doc_info:
+        return json.dumps({'error': f'Document {doc_id} not found'})
+    result = {
+        'doc_id': doc_id,
+        'doc_name': doc_info.get('doc_name', ''),
+        'doc_description': doc_info.get('doc_description', ''),
+        'type': doc_info.get('type', ''),
+        'status': 'completed',
+    }
+    if doc_info.get('type') == 'pdf':
+        result['page_count'] = _count_pages(doc_info)
+    else:
+        result['line_count'] = _count_pages(doc_info)
+    return json.dumps(result)
+
+
+def get_document_structure(documents: dict, doc_id: str) -> str:
+    """Return tree structure JSON with text fields removed (saves tokens)."""
+    doc_info = documents.get(doc_id)
+    if not doc_info:
+        return json.dumps({'error': f'Document {doc_id} not found'})
+    structure = doc_info.get('structure', [])
+    structure_no_text = remove_fields(structure, fields=['text'])
+    return json.dumps(structure_no_text, ensure_ascii=False)
+
+
+def get_page_content(documents: dict, doc_id: str, pages: str) -> str:
+    """
+    Retrieve page content for a document.
+
+    pages format: '5-7', '3,8', or '12'
+    For PDF: pages are physical page numbers (1-indexed).
+    For Markdown: pages are line numbers corresponding to node headers.
+
+    Returns JSON list of {'page': int, 'content': str}.
+    """
+    doc_info = documents.get(doc_id)
+    if not doc_info:
+        return json.dumps({'error': f'Document {doc_id} not found'})
+
+    try:
+        page_nums = _parse_pages(pages)
+    except (ValueError, AttributeError) as e:
+        return json.dumps({'error': f'Invalid pages format: {pages!r}. Use "5-7", "3,8", or "12". Error: {e}'})
+
+    try:
+        if doc_info.get('type') == 'pdf':
+            content = _get_pdf_page_content(doc_info, page_nums)
+        else:
+            content = _get_md_page_content(doc_info, page_nums)
+    except Exception as e:
+        return json.dumps({'error': f'Failed to read page content: {e}'})
+
+    return json.dumps(content, ensure_ascii=False)

pageindex/utils.py

@@ -1,6 +1,7 @@
 import litellm
 import logging
 import os
+import textwrap
 from datetime import datetime
 import time
 import json
@@ -29,6 +30,8 @@ def count_tokens(text, model=None):
 
 
 def llm_completion(model, prompt, chat_history=None, return_finish_reason=False):
+    if model:
+        model = model.removeprefix("litellm/")
     max_retries = 10
     messages = list(chat_history) + [{"role": "user", "content": prompt}] if chat_history else [{"role": "user", "content": prompt}]
     for i in range(max_retries):
@@ -57,6 +60,8 @@ def llm_completion(model, prompt, chat_history=None, return_finish_reason=False)
 
 
 async def llm_acompletion(model, prompt):
+    if model:
+        model = model.removeprefix("litellm/")
     max_retries = 10
     messages = [{"role": "user", "content": prompt}]
     for i in range(max_retries):
@@ -678,3 +683,28 @@ class ConfigLoader:
         self._validate_keys(user_dict)
         merged = {**self._default_dict, **user_dict}
         return config(**merged)
+
+def create_node_mapping(tree):
+    """Create a flat dict mapping node_id to node for quick lookup."""
+    mapping = {}
+    def _traverse(nodes):
+        for node in nodes:
+            if node.get('node_id'):
+                mapping[node['node_id']] = node
+            if node.get('nodes'):
+                _traverse(node['nodes'])
+    _traverse(tree)
+    return mapping
+
+def print_tree(tree, indent=0):
+    for node in tree:
+        summary = node.get('summary') or node.get('prefix_summary', '')
+        summary_str = f"  —  {summary[:60]}..." if summary else ""
+        print('  ' * indent + f"[{node.get('node_id', '?')}] {node.get('title', '')}{summary_str}")
+        if node.get('nodes'):
+            print_tree(node['nodes'], indent + 1)
+
+def print_wrapped(text, width=100):
+    for line in text.splitlines():
+        print(textwrap.fill(line, width=width))
+