Update Jan's chat window instructions and add new notebook on using Open Interpreter to talk to your database.

Author: MikeBirdTech

examples/jan_computer_control.ipynb

@@ -55,7 +55,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Go to the chat window to start a new thread.\n",
+    "Go to Jan's chat window to start a new thread.\n",
     "\n",
     "Set `Model` to an OpenAI model. \n",
     "\n",

examples/talk_to_your_database.ipynb

@@ -0,0 +1,156 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Use Open Interpreter to talk to your database"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "> Note: Open Interpreter should ideally be limited to read-only actions on your database. If write operations are necessary, use a copy of your data to protect against unexpected changes from the AI model. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "vscode": {
+     "languageId": "plaintext"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "Set up a profile with:\n",
+    "- Database credentials\n",
+    "- Connection string\n",
+    "\n",
+    "Here is an example for a PostgreSQL database:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from interpreter import interpreter\n",
+    "import os\n",
+    "\n",
+    "# Use environment variables for database connection or update defaults with your credentials\n",
+    "db_user = os.environ.get(\"DB_USER\", \"user\")\n",
+    "db_host = os.environ.get(\"DB_HOST\", \"localhost\")\n",
+    "db_port = os.environ.get(\"DB_PORT\", \"5432\")\n",
+    "db_name = os.environ.get(\"DB_NAME\", \"demo_database\")\n",
+    "db_password = os.environ.get(\"DB_PASSWORD\", \"\")\n",
+    "\n",
+    "# Construct connection string with optional password\n",
+    "if db_password and db_password.strip():\n",
+    "    connection_string = (\n",
+    "        f\"postgresql://{db_user}:{db_password}@{db_host}:{db_port}/{db_name}\"\n",
+    "    )\n",
+    "else:\n",
+    "    connection_string = f\"postgresql://{db_user}@{db_host}:{db_port}/{db_name}\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Configure your instance of Open Interpreter.\n",
+    "\n",
+    "\n",
+    "This example uses a local model served by Ollama but you can use a hosted model:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# LLM settings\n",
+    "interpreter.llm.model = \"ollama/llama3.1\"\n",
+    "interpreter.llm.supports_functions = False\n",
+    "interpreter.llm.execution_instructions = False\n",
+    "interpreter.llm.max_tokens = 1000\n",
+    "interpreter.llm.context_window = 7000\n",
+    "interpreter.llm.load() \n",
+    "\n",
+    "# Computer settings\n",
+    "interpreter.computer.import_computer_api = False\n",
+    "\n",
+    "# Misc settings\n",
+    "interpreter.auto_run = False\n",
+    "interpreter.offline = True"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Set the custom instructions to maximize performance."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Custom Instructions\n",
+    "interpreter.custom_instructions = f\"\"\"\n",
+    "    You are a SQL master and are the oracle of database knowledge. You are obsessed with SQL. You only want to discuss SQL. SQL is life.\n",
+    "    Recap the plan before answering the user's query.\n",
+    "    You will connect to a PostgreSQL database, with the connection string {connection_string}.\n",
+    "    Remember to only query the {db_name} database.\n",
+    "    Execute valid SQL commands to satisfy the user's query.\n",
+    "    Write all code in a full Python script. When you have to re-write code, redo the entire script.\n",
+    "    Execute the script to get the answer for the user's query.\n",
+    "    **YOU CAN EXECUTE SQL COMMANDS IN A PYTHON SCRIPT.***\n",
+    "    Get the schema of '{db_name}' before writing any other SQL commands. It is important to know the tables. This will let you know what commands are correct.\n",
+    "    Only use real column names.\n",
+    "    ***You ARE fully capable of executing SQL commands.***\n",
+    "    Be VERY clear about the answer to the user's query. They don't understand technical jargon so make it very clear and direct.\n",
+    "    You should respond in a very concise way.\n",
+    "    You can do it, I believe in you.\n",
+    "    \"\"\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "Save the profile in the `profiles` directory.\n",
+    "\n",
+    "Once you are happy with your profile, test it on a test table/database. \n",
+    "\n",
+    "Run the following in your terminal:\n",
+    "\n",
+    "`interpreter --profile <name-of-profile.py>`\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Iterate on the profile until you are happy with the performance. \n",
+    "\n",
+    "Remember to use the right LLM for the job. Larger models tend to have better reasoning.\n",
+    "\n",
+    "If you want to share your profile with the community, please open a PR."
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}