added a sample for Monte Carlo Pi estimator

lf-lang · Aug 1, 2024 · 95df969 · 95df969
1 parent a13c0e4
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Showing 3 changed files with 1,595 additions and 18 deletions.
diff --git a/Context_Engineering4LF.ipynb b/Context_Engineering4LF.ipynb
@@ -14,7 +14,7 @@
     "Generate Lingua Franca (LF) code from natural language prompt.\n",
     "\n",
     "## Context\n",
-    "Large Language Models (LLMs) are a powerful tool for generating code. However, LLMs are often trained on standard programming languages like C/C++, Java, Python, and JavaScript. This makes it difficult to generate code in Domain-specific languages like Lingua Franca.\n",
+    "Large Language Models (LLMs) are a powerful tool for generating code. However, LLMs are often trained on standard programming languages like C/C++, Java, Python, or JavaScript. This makes it difficult to generate code in Domain-specific languages like Lingua Franca.\n",
     "\n",
     "This project shows how to curate context to guide the LLM.  We demonstrate the technique by showing how to generate code that uses the Lingua Franca coordination language together with C and Python."
    ]
@@ -49,7 +49,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 125,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -75,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 126,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 127,
+   "execution_count": 3,
    "metadata": {
     "vscode": {
      "languageId": "shellscript"
@@ -187,7 +187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 128,
+   "execution_count": 4,
    "metadata": {
     "vscode": {
      "languageId": "shellscript"
@@ -216,18 +216,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 130,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "LFGPT/without_context/DropSensor_gpt-4o_2.lf\n",
-      "LFGPT/without_context/DropSensor_gpt-3.5-turbo_2.lf\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Initializes an OpenAI client for interacting with the OpenAI API.\n",
     "client = OpenAI()\n",