inital commit for yellowhammer jupyter assistant

examples/001-getting-started.ipynb

@@ -123,7 +123,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.10.9"
   }
  },
  "nbformat": 4,

examples/Demo.ipynb

@@ -0,0 +1,133 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "2671fc38-c9ca-49ef-948a-abb7815ca2b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%reload_ext yellowhammer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "32c5ffc5-ea83-458c-8e5a-75bb15da8a2d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os, getpass\n",
+    "os.environ['LLM_PROVIDER'] = \"OPENAI\"\n",
+    "os.environ['LLM_API_KEY'] = getpass.getpass(\"Enter your LLM API key\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "2f61e78f-b8a3-4f0c-b5e4-503af30019f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.environ[\"DATALAB_API_KEY\"] = getpass.getpass(\"Enter your Datalab API key\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f44cabeb-58ef-4ccd-86d7-5cb04a3f8643",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "Datalab is a data management platform designed for scientists and researchers to manage their experimental data efficiently. It allows users to organize, analyze, and visualize their data through a structured interface. Datalab uses the concept of \"data blocks\" to handle files associated with samples, enabling users to parse data according to scientific schemas and create plots for better data interpretation. The platform also provides an API for programmatic access, allowing users to automate tasks such as data entry, file uploads, and data analysis."
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%llm\n",
+    "What is datalab?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d10442e5-7c5c-40cd-becf-9c2e9a79fd45",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "To create a new sample in Datalab with the specified ID, name, and formula, we will use the `create_item` method of the `DatalabClient`. This method requires the item ID, item type, and the data that matches the schema for samples. In this case, we will set the `item_id` to 'llm-test3', the `name` to 'virtual sample', and the `chemform` to 'RbCl'."
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%%llm\n",
+    "Create a sample with ID llm-test3, sample name \"virtual sample\", formula RbCl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "33c0e59e-586d-48f3-aa5f-f6fa743dcc96",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/yue/Library/CloudStorage/OneDrive-Personal/code/yellowhammer/.venv/lib/python3.10/site-packages/datalab_api/_base.py:165: UserWarning: Found API URL https://demo-api.datalab-org.io in HTML meta tag. Creating client with this URL instead.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datalab_api import DatalabClient\n",
+    "import os\n",
+    "with DatalabClient(\"https://demo.datalab-org.io\") as client:\n",
+    "    json_data = {\n",
+    "        \"name\": \"virtual sample\",\n",
+    "        \"chemform\": \"RbCl\"\n",
+    "    }\n",
+    "    client.create_item(item_id=\"llm-test3\", item_type=\"samples\", item_data=json_data)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "yellowhammer",
+   "language": "python",
+   "name": "yellowhammer"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

pyproject.toml

@@ -8,6 +8,7 @@ dependencies = [
     "datalab-api>=0.2.4",
     "jupyter-ai>=2.24.1",
     "jupyterlab>=4.2.5",
+    "langchain>=0.2.16",
     "langchain-anthropic>=0.1.23",
     "langchain-openai>=0.1.25",
     "notebook>=7.2.2",

src/yellowhammer/__init__.py

@@ -6,3 +6,14 @@
     __version__ = "develop"
 
 __all__ = ("__version__",)
+
+
+from .magics import datalabMagics
+
+def load_ipython_extension(ipython):
+    """
+    Any module file that define a function named `load_ipython_extension`
+    can be loaded via `%load_ext module.path` or be configured to be
+    autoloaded by IPython at startup time.
+    """
+    ipython.register_magics(datalabMagics)