LLM_translate.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a5b5023-e116-4ef9-9631-09c0e5a0978b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pip install -r requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d75fc1e9-335e-4b41-9164-86fb6392c715",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import boto3\n",
    "import json\n",
    "from datetime import datetime\n",
    "from dynaconf import Dynaconf\n",
    "from evaluate import load\n",
    "from tqdm import tqdm\n",
    "import pandas as pd\n",
    "\n",
    "from src.completion import get_completion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e4b2e69-fe20-4998-8e6e-fe7e8d16ecf8",
   "metadata": {},
   "outputs": [],
   "source": [
    "settings = Dynaconf(settings_files=[\"settings.toml\"], env=\"haiku-3\", environments=True)\n",
    "bedrock_client = boto3.client(service_name = 'bedrock-runtime', region_name = settings.region)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45dc0fa5-067a-48a6-8660-0393ea44e79b",
   "metadata": {},
   "source": [
    "## Translation – spa-eng"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "23a65be5-db37-4456-9fa2-ad4494b62ac1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "eng = []\n",
    "with open('data/spa-eng/eng-10.txt', 'r') as f:\n",
    "    for l in f:\n",
    "        eng.append(l)\n",
    "\n",
    "spa = []\n",
    "with open('data/spa-eng/spa-10.txt', 'r') as f:\n",
    "    for l in f:\n",
    "        spa.append(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d525de3c-8970-43c9-a586-252057810169",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sys_prompt = \"You are a translator from Spanish to English. Only provide the translation.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e5e85e4c-f51a-4a0a-a6bd-e7511a4e19ff",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BLEU Score: 0.5421764828099125\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "# Load BLEU metric\n",
    "bleu = load(\"bleu\")\n",
    "\n",
    "# Generate predictions\n",
    "predictions = [get_completion(src, sys_prompt) for src in tqdm(spa)]\n",
    "\n",
    "# Evaluate with BLEU\n",
    "results = bleu.compute(predictions=predictions, references=eng)\n",
    "print(\"BLEU Score:\", results[\"bleu\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "15c1c2a3-f77d-48d1-af40-9a004b83785d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_27346/4180831044.py:7: FutureWarning: In future versions `DataFrame.to_latex` is expected to utilise the base implementation of `Styler.to_latex` for formatting and rendering. The arguments signature may therefore change. It is recommended instead to use `DataFrame.style.to_latex` which also contains additional functionality.\n",
      "  print(d.to_latex(index=False))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lll}\n",
      "\\toprule\n",
      "                                            source &                                        predictions &                                         references \\\\\n",
      "\\midrule\n",
      "Se divulga un compuesto en donde, A o A represe... & The compound is disclosed where A or A represen... & Disclosed is a compound in which, Aa or Ab repr... \\\\\n",
      "[0036] En los dibujos, los elementos iguales o ... & [0036] In the drawings, equal or equivalent ele... & In the drawings, the same or equivalent element... \\\\\n",
      "La Figura 8 muestra un diagrama de flujo que il... & The Figure 8 shows a flow diagram that illustra... & Fig. 8 shows a flowchart illustrating a method ... \\\\\n",
      "Las bombasde ondas lambda (LW1, LW2, LW3) y el ... & The lambda wave pumps (LW1, LW2, LW3) and the l... & The Lamb-wave pumps (LW1, LW2, LW3) and Lamb-wa... \\\\\n",
      "Se proporcionan mas detalles, por ejemplo, en H... & More details are provided, for example, in Held... & Further details are provided, e.g., by Held et ... \\\\\n",
      "No obstante, se conoce el hecho de que, el carb... & Nevertheless, it is known that activated charco... & However, it is known that active charcoal and t... \\\\\n",
      "Esta eliminación no puede alcanzar el 100\\%, per... & This elimination cannot reach 100\\%, but the obj... & This elimination cannot reach 100\\%, but the aim... \\\\\n",
      "Las condiciones típicas de funcionamiento de la... & The typical operating conditions of the plants ... & Typical operating conditions in the plants of F... \\\\\n",
      "El aparato 10utiliza una lanza flexible 12 cons... & The device 10 uses a flexible lance 12 consisti... & The apparatus 10 utilizes a flexible lance 12 f... \\\\\n",
      "Los derivados de cacao y/o manteca de cacao tam... & The derivatives of cocoa and/or cocoa butter ca... & The derivatives of cocoa and/or cocoa butter ca... \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "d = pd.DataFrame({\n",
    "    \"source\": spa, \n",
    "    \"predictions\": predictions, \n",
    "    \"references\": eng\n",
    "})\n",
    "print(d.to_latex(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "54a5d539-1518-4ee3-8038-532a41c95c39",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "eng = []\n",
    "with open('data/spa-eng/eng-3000.txt', 'r') as f:\n",
    "    for l in f:\n",
    "        eng.append(l)\n",
    "\n",
    "spa = []\n",
    "with open('data/spa-eng/spa-3000.txt', 'r') as f:\n",
    "    for l in f:\n",
    "        spa.append(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36a3cac5-864e-4eb2-8d41-7ca0715ef66d",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
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     ]
    }
   ],
   "source": [
    "# Load BLEU metric\n",
    "bleu = load(\"bleu\")\n",
    "\n",
    "# Generate predictions\n",
    "predictions = [get_completion(src, sys_prompt) for src in tqdm(spa)]\n",
    "\n",
    "# Evaluate with BLEU\n",
    "results = bleu.compute(predictions=predictions, references=eng)\n",
    "print(\"BLEU Score:\", results[\"bleu\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "da3f0865-de39-46dc-ae74-5d7b573b51cc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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