pip install treedex
# With optional LLM SDK
pip install treedex[gemini]
pip install treedex[openai]
pip install treedex[claude]
pip install treedex[all]

npm install treedex
# With optional LLM SDK
npm install treedex openai
npm install treedex @google/generative-ai
npm install treedex @anthropic-ai/sdk

from treedex import TreeDex, GeminiLLM
llm = GeminiLLM(api_key="YOUR_KEY")
index = TreeDex.from_file("doc.pdf", llm=llm)
result = index.query("What is the main argument?")
print(result.context)
print(result.pages_str) # "pages 5-8, 12-15"

import { TreeDex, GeminiLLM } from "treedex";
const llm = new GeminiLLM("YOUR_KEY");
const index = await TreeDex.fromFile("doc.pdf", llm);
const result = await index.query("What is the main argument?");
console.log(result.context);
console.log(result.pagesStr); // "pages 5-8, 12-15"

from treedex import *
# Google Gemini
llm = GeminiLLM(api_key="YOUR_KEY")
# OpenAI
llm = OpenAILLM(api_key="sk-...")
# Claude
llm = ClaudeLLM(api_key="sk-ant-...")
# Groq (fast inference)
llm = GroqLLM(api_key="gsk_...")
# Together AI
llm = TogetherLLM(api_key="...")
# DeepSeek
llm = DeepSeekLLM(api_key="...")
# OpenRouter (access any model)
llm = OpenRouterLLM(api_key="...")
# Local Ollama
llm = OllamaLLM(model="llama3")
# Any OpenAI-compatible endpoint
llm = OpenAICompatibleLLM(
 base_url="https://your-api.com/v1",
 api_key="...",
 model="model-name",
)

import { /* any backend */ } from "treedex";
// Google Gemini
const llm = new GeminiLLM("YOUR_KEY");
// OpenAI
const llm = new OpenAILLM("sk-...");
// Claude
const llm = new ClaudeLLM("sk-ant-...");
// Groq (fast inference)
const llm = new GroqLLM("gsk_...");
// Together AI
const llm = new TogetherLLM("...");
// DeepSeek
const llm = new DeepSeekLLM("...");
// OpenRouter (access any model)
const llm = new OpenRouterLLM("...");
// Local Ollama
const llm = new OllamaLLM("llama3");
// Any OpenAI-compatible endpoint
const llm = new OpenAICompatibleLLM({
 baseUrl: "https://your-api.com/v1",
 apiKey: "...",
 model: "model-name",
});

from treedex import FunctionLLM
llm = FunctionLLM(lambda p: my_api(p))

import { FunctionLLM } from "treedex";
const llm = new FunctionLLM((p) => myApi(p));

from treedex import BaseLLM
class MyLLM(BaseLLM):
 def generate(self, prompt: str) -> str:
 return my_api_call(prompt)

import { BaseLLM } from "treedex";
class MyLLM extends BaseLLM {
 async generate(prompt: string): Promise<string> {
 return await myApiCall(prompt);
 }
}

# Standard: returns context + page ranges
result = index.query("What is X?")
print(result.context)
# Agentic: returns a direct answer
result = index.query("What is X?", agentic=True)
print(result.answer) # LLM-generated answer
print(result.pages_str) # source pages

// Standard: returns context + page ranges
const result = await index.query("What is X?");
console.log(result.context);
// Agentic: returns a direct answer
const result = await index.query("What is X?", { agentic: true });
console.log(result.answer); // LLM-generated answer
console.log(result.pagesStr); // source pages

# Save
index.save("my_index.json")
# Load
index = TreeDex.load("my_index.json", llm=llm)

// Save
await index.save("my_index.json");
// Load
const index = await TreeDex.load("my_index.json", llm);

pip install -e ".[dev]"
pytest
pytest --cov=treedex
pytest tests/test_core.py -v

npm install
npm test
npm run test:watch
npm run typecheck