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Update demo example paper and polish README

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@ -62,7 +62,7 @@ It simulates how *human experts* navigate and extract knowledge from complex doc
</a>
</div>
### 🎯 Core Features
### 🎯 Core Features
Compared to traditional vector-based RAG, **PageIndex** features:
- **No Vector DB**: Uses document structure and LLM reasoning for retrieval, instead of vector similarity search.
@ -74,7 +74,7 @@ PageIndex powers a reasoning-based RAG system that achieved **state-of-the-art**
### 📍 Explore PageIndex
To learn more, please see a detailed introduction of the [PageIndex framework](https://pageindex.ai/blog/pageindex-intro). Check out this GitHub repo for open-source code, and the [cookbooks](https://docs.pageindex.ai/cookbook), [tutorials](https://docs.pageindex.ai/tutorials), and [blog](https://pageindex.ai/blog) for additional usage guides and examples.
To learn more, please see a detailed introduction of the [PageIndex framework](https://pageindex.ai/blog/pageindex-intro). Check out this GitHub repo for open-source code, and the [cookbooks](https://docs.pageindex.ai/cookbook), [tutorials](https://docs.pageindex.ai/tutorials), and [blog](https://pageindex.ai/blog) for additional usage guides and examples.
The PageIndex service is available as a ChatGPT-style [chat platform](https://chat.pageindex.ai), or can be integrated via [MCP](https://pageindex.ai/mcp) or [API](https://docs.pageindex.ai/quickstart).
@ -101,6 +101,7 @@ The PageIndex service is available as a ChatGPT-style [chat platform](https://ch
---
# 🌲 PageIndex Tree Structure
PageIndex can transform lengthy PDF documents into a semantic **tree structure**, similar to a _"table of contents"_ but optimized for use with Large Language Models (LLMs). It's ideal for: financial reports, regulatory filings, academic textbooks, legal or technical manuals, and any document that exceeds LLM context limits.
Below is an example PageIndex tree structure. Also see more example [documents](https://github.com/VectifyAI/PageIndex/tree/main/tests/pdfs) and generated [tree structures](https://github.com/VectifyAI/PageIndex/tree/main/tests/results).
@ -133,7 +134,7 @@ Below is an example PageIndex tree structure. Also see more example [documents](
...
```
You can generate the PageIndex tree structure with this open-source repo, or use our [API](https://docs.pageindex.ai/quickstart)
You can generate the PageIndex tree structure with this open-source repo, or use our [API](https://docs.pageindex.ai/quickstart).
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@ -149,7 +150,7 @@ pip3 install --upgrade -r requirements.txt
### 2. Set your LLM API key
Create a `.env` file in the root directory with your LLM API key::
Create a `.env` file in the root directory with your LLM API key, with multi-LLM support via [LiteLLM](https://docs.litellm.ai/docs/providers):
```bash
OPENAI_API_KEY=your_openai_key_here
@ -169,7 +170,7 @@ python3 run_pageindex.py --pdf_path /path/to/your/document.pdf
You can customize the processing with additional optional arguments:
```
--model OpenAI model to use (default: gpt-4o-2024-11-20)
--model LLM model to use (default: gpt-4o-2024-11-20)
--toc-check-pages Pages to check for table of contents (default: 20)
--max-pages-per-node Max pages per node (default: 10)
--max-tokens-per-node Max tokens per node (default: 20000)
@ -182,7 +183,7 @@ You can customize the processing with additional optional arguments:
<details>
<summary><strong>Markdown support</strong></summary>
<br>
We also provide markdown support for PageIndex. You can use the `-md_path` flag to generate a tree structure for a markdown file.
We also provide markdown support for PageIndex. You can use the `--md_path` flag to generate a tree structure for a markdown file.
```bash
python3 run_pageindex.py --md_path /path/to/your/document.md
@ -193,7 +194,7 @@ python3 run_pageindex.py --md_path /path/to/your/document.md
### A Complete Agentic RAG Example
For a complete agent-based QA example using the [OpenAI Agents SDK](https://github.com/openai/openai-agents-python), see [`examples/openai_agents_demo.py`](examples/openai_agents_demo.py).
For a complete example on **agentic RAG with PageIndex** (using [OpenAI Agents SDK](https://github.com/openai/openai-agents-python)), see [`examples/openai_agents_demo.py`](examples/openai_agents_demo.py).
```bash
# Install optional dependency