docs: update docs

- Update doc layout
- Add syntax highlight support

docs/howto/persist-messages.md

@@ -0,0 +1 @@
+# Persist Messages

docs/howto/retrieval.md

@@ -0,0 +1 @@
+# Enhance TableGPT Agent with RAG

docs/index.md

@@ -9,14 +9,19 @@ tablegpt-agent is a pre-built agent for [TableGPT2 (huggingface)](https://huggin
 
 ## Table Of Contents
 
-1. [Tutorials](tutorials.md)
-2. [How-To Guides](how-to-guides.md)
-3. [Reference](reference.md)
-4. [Explanation](explanation.md)
+<!-- mkdocs requires 4 space to intent the list -->
+- Tutorials
+    - [Quickstart](tutorials/quickstart.md)
+    - [Chat on Tabular Data](tutorials/table-chat.md)
+- How-To Guides
+    - [Enhance TableGPT Agent with RAG](howto/retrieval.md)
+    - [Persist Messages](howto/persist-messages.md)
+- [Reference](reference.md)
+- [Explanation](explanation.md)
 
 ## Contributing
 
-For more information on how to contribute, see [here](https://github.com/tablegpt/tablegpt-agent/blob/main/CONTRIBUTING.md).
+Thank you for your interest in TableGPT Agent. For more information on contributing, please see [the contributing guide](https://github.com/tablegpt/tablegpt-agent/blob/main/CONTRIBUTING.md).
 
 ## Acknowledgements
 

docs/tutorials/quickstart.md

@@ -0,0 +1,125 @@
+# Quickstart
+
+## Installation
+
+To install `tablegpt-agent`, use the following command:
+
+```sh
+pip install tablegpt-agent
+```
+
+This package depends on [pybox](https://github.com/edwardzjl/pybox), a Python code sandbox delegator. By default, `pybox` operates in an in-cluster mode. If you wish to run `tablegpt-agent` in a local environment, you need to install an optional dependency:
+
+```sh
+pip install pppybox[local]
+```
+
+## Setup LLM Service
+
+Before using `tablegpt-agent`, ensure that you have an OpenAI-compatible server set up to host TableGPT2. We recommend using [vllm](https://github.com/vllm-project/vllm) for this:
+
+```sh
+python -m vllm.entrypoints.openai.api_server --served-model-name TableGPT2-7B --model path/to/weights
+```
+
+> **Note:** For production environments, it's important to optimize the vllm server configuration. For details, refer to the [vllm documentation on server configuration](https://docs.vllm.ai/en/v0.6.0/serving/openai_compatible_server.html#command-line-arguments-for-the-server).
+
+## Chat with TableGPT Agent
+
+To create a `TablegptAgent`, you'll need both `LLM` and `PyBoxManager` components:
+
+```pycon
+>>> from langchain_openai import ChatOpenAI
+>>> from pybox import LocalPyBoxManager
+>>> from tablegpt.agent import create_tablegpt_graph
+
+>>> llm = ChatOpenAI(openai_api_base="YOUR_VLLM_URL", openai_api_key="whatever", model_name="TableGPT2-7B")
+>>> pybox_manager = LocalPyBoxManager()
+
+>>> agent = create_tablegpt_graph(
+...     llm=llm,
+...     pybox_manager=pybox_manager,
+... )
+```
+
+To interact with the agent:
+
+```pycon
+>>> import asyncio
+>>> from datetime import date
+>>> from langchain_core.messages import HumanMessage
+
+>>> message = HumanMessage(content="Hi")
+
+>>> _input = {
+...     "messages": [message],
+...     "parent_id": "some-parent-id",
+...     "date": date.today(),
+... }
+
+>>> response = asyncio.run(agent.ainvoke(_input))
+>>> print(response["messages"])
+[HumanMessage(content='Hi', additional_kwargs={}, response_metadata={}, id='7da7e51c-0ad0-4481-aa22-54acce6a82d7'), AIMessage(content="Hello! How can I assist you with your data analysis today? Do you have a dataset you'd like to work with?", additional_kwargs={'parent_id': 'some-parent-id'}, response_metadata={}, id='43df249b-9c61-44bc-a535-eb33f9efaa9e')]
+```
+
+You can get more detailed outputs with the `astream_events` method:
+
+```pycon
+>>> async for event in agent.astream_events(
+...     input=_input,
+...     version="v2",
+... ):
+...     # We ignore irrelevant events here.
+...     if event["event"] == "on_chat_model_end":
+...         print(event["data"]["output"])
+content="Hello! How can I assist you with your data analysis today? Do you have a specific dataset or problem in mind that you'd like to work on?" additional_kwargs={} response_metadata={'finish_reason': 'stop', 'model_name': 'TableGPT2-7B'} id='run-677d42b7-ae79-4695-8e54-1b02fab07427'
+```
+
+<details>
+
+<summary>Full code</summary>
+
+```python
+import asyncio
+from datetime import date
+
+from langchain_core.messages import HumanMessage
+from langchain_openai import ChatOpenAI
+from pybox import LocalPyBoxManager
+from tablegpt.agent import create_tablegpt_graph
+
+
+# tablegpt-agent fully supports async invocation
+async def main() -> None:
+    llm = ChatOpenAI(openai_api_base="YOUR_VLLM_URL", openai_api_key="whatever", model_name="TableGPT2-7B")
+
+    # Use local pybox manager for development and testing
+    pybox_manager = LocalPyBoxManager()
+
+    agent = create_tablegpt_graph(
+        llm=llm,
+        pybox_manager=pybox_manager,
+    )
+
+    message = HumanMessage(content="Hi")
+    _input = {
+        "messages": [message],
+        "parent_id": "some-parent-id",
+        "date": date.today(),  # noqa: DTZ011
+    }
+
+    # response = await agent.ainvoke(_input)
+    # print(response["messages"])
+
+    # More details can be obtained through the astream_events method
+    async for event in agent.astream_events(
+        input=_input,
+        version="v2",
+    ):
+        print(event)  # noqa: T201
+
+
+asyncio.run(main())
+```
+
+</details>