Update endpoint params and update readme

README.md

@@ -1,15 +1,21 @@
 # Jupyter Coder
 
 This plugin is still in development. To test it, clone this repository first.
-Currently it only supports OPENAI code completion.
+Currently it supports the native jupyter mode of starcoder and Open AI completion API.
 
 ## Installation
 ```bash
-git clone this_repo
+git clone https://github.com/bigcode-project/jupytercoder.git
 ```
 
-Open chrome://extensions/ in your browser and enable developer mode. Then click on "Load unpacked" and select the folder where you cloned this repository.
-Then click on the extension icon to enable it, you will need to enter the bigcode model endpoint url.
+Open chrome://extensions/ in your browser and enable developer mode.
+![devmode](https://user-images.githubusercontent.com/6381544/236060575-1fbb4024-165d-491f-8ae6-450c50b7a66d.png)
+
+Then click on "Load unpacked" and select the folder where you cloned this repository.
+![unpack](https://user-images.githubusercontent.com/6381544/236060695-c432a612-bfeb-4708-909a-f1bb8a64f732.png)
+
+Then click on the extension icon to enable it, you will need to enter the bigcode model endpoint url https://api-inference.huggingface.co/models/bigcode/starcoder/ and your hf readonlys api key. Click save to activate this mode.
+![image](https://user-images.githubusercontent.com/6381544/236060887-5c7fd3b1-d5f7-4b86-8282-8925ed867825.png)
 
 ## Demo
 ```bash

content.js

@@ -89,6 +89,7 @@ async function sendToOtherService(code) {
   }
 
   const prompt = code.replace(/\u200B/g, '')
+  console.log(JSON.stringify(prompt));
   const response = await fetch(url, {
     method: "POST",
     headers: {
@@ -99,17 +100,17 @@ async function sendToOtherService(code) {
       inputs: prompt,
       stream: false,
       parameters: {
-        return_full_text: false
+        return_full_text: false,
+        stop: ["<jupyter_output>"]
       }
     })
   })
   const data = await response.json();
 
-  if (/^\n/.test(data)) {
-    data = data.replace(/^\n/, '');
-  }
-  // 格式处理成可以输出到notebook的字符串
-  return data[0].generated_text;
+  const suggestion = data[0].generated_text;
+
+  // remove end token <jupyter_output> if exists
+  return removeJupyterOutput(suggestion)
 }
 
 
@@ -225,7 +226,7 @@ function getCellContentTextRequiredForOpenAI(activeCell) {
   }
 
   // Iterate through the last 3 cells before the active cell
-  const startIndex = activeCellIndex - 3 < 0 ? 0 : activeCellIndex - 3;
+  const startIndex = 0;
   for (let i = startIndex; i <= activeCellIndex; i++) {
     if(i == activeCellIndex){
       codeContent += leftContext
@@ -308,7 +309,15 @@ function extractTextFromCell(cell) {
   return content_str;
 }
 
+function removeJupyterOutput(str) {
+  const jupyterOutput = '<jupyter_output>';
 
+  if (str.endsWith(jupyterOutput)) {
+    return str.slice(0, -jupyterOutput.length);
+  }
+
+  return str;
+}
 
 // 开始等待动画，有30s等待时间，如果等待时间过了，出现“error”字体，返回两个值如下，接收："const [animationInterval, animationElement] = startWaitingAnimation(activeCall)"
 // 1. animationInterval（interval, 动画计时器），可使用clearInterval(animationInterval)消除动画, 每次请求完毕必须要关掉

examples/starcoder_gpu_usage.ipynb

@@ -0,0 +1,93 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3aa18388",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "50ed5565",
+   "metadata": {},
+   "source": [
+    "read the csv usage_df.csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0997b28d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25867be0",
+   "metadata": {},
+   "source": [
+    "plot the daily usage of month 2022-03"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e7fed4a1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9dd0a765",
+   "metadata": {},
+   "source": [
+    "Calculate the average monthly usage and plot the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e0e304b0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e7e4b2e2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}