aboutsummaryrefslogtreecommitdiff
path: root/gnqa/paper2_eval/src/Vanilla_RAG.ipynb
blob: 52270d6cbd58f8f8fc439a24af4584ad58bb6020 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mz33G3t6gbOl"
      },
      "source": [
        "# RAG\n",
        "\n",
        "Retrieval-Augmented Generation (RAG) is a technique that combines the strengths of pre-trained language models with the ability to retrieve information from a large corpus of documents. RAG **enables the language model to produce more informed, accurate, and contextually relevant answers** than by relying on its pre-trained knowledge alone.\n",
        "\n",
        "At Cohere, all RAG calls come with... **precise citations**! πŸŽ‰\n",
        "The model cites which groups of words, in the RAG chunks, were used to generate the final answer.  \n",
        "These citations make it easy to check where the model’s generated response claims are coming from and they help users gain visibility into the model reasoning.  \n",
        "\n",
        "RAG consists of 3 steps:\n",
        "- Step 1: Indexing and given a user query, retrieve the relevant chunks from the index\n",
        "- Step 2: Optionally, rerank the retrieved chunks\n",
        "- Step 3: Generate the model final answer with **precise citations**, given the retrieved and reranked chunks\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nSB0pnt0gbOo"
      },
      "source": [
        "## Step 0 - Imports & Getting some data\n",
        "\n",
        "In this example, we'll use a recent piece of text, that wasn't in the training data: the Wikipedia page of the movie \"Dune 2\".   \n",
        "\n",
        "In practice, you would typically do RAG on much longer text, that doesn't fit in the context window of the model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H787BXXYvD0a",
        "outputId": "04ef5e04-7760-4d40-deeb-663536b38f20"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "r2r 0.2.59 requires fsspec<2025.0.0,>=2024.6.0, but you have fsspec 2024.2.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n"
          ]
        }
      ],
      "source": [
        "# we'll use Cohere to cover all building blocks of RAG\n",
        "# TODO: upgrade to \"cohere>5\"\n",
        "%pip install \"cohere<5\" --quiet"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rACbepFGgbOo"
      },
      "outputs": [],
      "source": [
        "import cohere\n",
        "API_KEY = \"TyvblqFywENUXIPgS0aT2Z3FdaxStqh6NpMgp4et\" # fill in your Cohere API key here\n",
        "co = cohere.Client(API_KEY)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QdvbqfFrgbOq",
        "outputId": "3882c95c-46bf-4dcc-99a2-453b3c2fc7c4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for wikipedia (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ],
      "source": [
        "# we'll get some wikipedia data\n",
        "!pip install wikipedia --quiet\n",
        "import wikipedia"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xP-bWt9XgbOq",
        "outputId": "72276fb2-0d6b-415d-af74-452a013ae84b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The text has roughly 5323 words.\n"
          ]
        }
      ],
      "source": [
        "# let's get the wikipedia article about Dune Part Two\n",
        "article = wikipedia.page('Dune Part Two')\n",
        "text = article.content\n",
        "print(f\"The text has roughly {len(text.split())} words.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-1aJ7hKGgbOr"
      },
      "source": [
        "## Step 1 - Indexing and given a user query, retrieve the relevant chunks from the index\n",
        "\n",
        "We index the document in a vector database. This requires getting the documents, chunking them, embedding, and indexing them in a vector database. Then we retrieved relevant results based on the users' query.\n",
        "\n",
        "### We split the document into chunks of roughly 512 words"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZUph1JX41665",
        "outputId": "6c63a93f-6999-47af-e704-d4a88727bc75"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m256.9/256.9 kB\u001b[0m \u001b[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m66.6/66.6 kB\u001b[0m \u001b[31m8.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m138.5/138.5 kB\u001b[0m \u001b[31m14.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "# For chunking let's use langchain to help us split the text\n",
        "%pip install -qU langchain-text-splitters --quiet\n",
        "from langchain_text_splitters import RecursiveCharacterTextSplitter"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uhXW7iHC1-Q6",
        "outputId": "d68ac348-4b73-4c6a-a445-6c510bdb0881"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "The text has been broken down in 91 chunks.\n"
          ]
        }
      ],
      "source": [
        "# Create basic configurations to chunk the text\n",
        "text_splitter = RecursiveCharacterTextSplitter(\n",
        "    chunk_size=512,\n",
        "    chunk_overlap=50,\n",
        "    length_function=len,\n",
        "    is_separator_regex=False,\n",
        ")\n",
        "\n",
        "# Split the text into chunks with some overlap\n",
        "chunks_ = text_splitter.create_documents([text])\n",
        "chunks = [c.page_content for c in chunks_]\n",
        "print(f\"The text has been broken down in {len(chunks)} chunks.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P8g0sE2hgbOs"
      },
      "source": [
        "### Embed every text chunk\n",
        "\n",
        "Cohere embeddings are state-of-the-art."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KEarMPEqgbOs",
        "outputId": "7da0e06d-f637-4470-8e01-6de8249be64b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "We just computed 91 embeddings.\n"
          ]
        }
      ],
      "source": [
        "# Because the texts being embedded are the chunks we are searching over, we set the input type as search_doc\n",
        "model=\"embed-english-v3.0\"\n",
        "response = co.embed(\n",
        "    texts= chunks,\n",
        "    model=model,\n",
        "    input_type=\"search_document\",\n",
        "    embedding_types=['float']\n",
        ")\n",
        "embeddings = response.embeddings.float\n",
        "print(f\"We just computed {len(embeddings)} embeddings.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HM6vKeypgbOs"
      },
      "source": [
        "### Store the embeddings in a vector database\n",
        "\n",
        "We use the simplest vector database ever: a python dictionary using `np.array()`."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "sdW7M8HLvB-9"
      },
      "outputs": [],
      "source": [
        "# We use the simplest vector database ever: a python dictionary\n",
        "!pip install numpy --quiet"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "H2srFH-IgbOs"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "vector_database = {i: np.array(embedding) for i, embedding in enumerate(embeddings)}\n",
        "# { 0: array([...]), 1: array([...]), 2: array([...]), ..., 10: array([...]) }"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q6NGVurZgbOs"
      },
      "source": [
        "## Given a user query, retrieve the relevant chunks from the vector database\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eC05yJQ7jlek"
      },
      "source": [
        "### Define the user question"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Y2HTxspKgbOs"
      },
      "outputs": [],
      "source": [
        "query = \"Name everyone involved in writing the script, directing, and producing 'Dune: Part Two'?\"\n",
        "\n",
        "# Note: the relevant passage in the wikipedia page we're looking for is:\n",
        "# \"[...] Dune: Part Two was originally scheduled to be released on October 20, 2023, but was delayed to November 17, 2023, before moving forward two weeks to November 3, 2023, to adjust to changes in release schedules from other studios. It was later postponed by over four months to March 15, 2024, due to the 2023 Hollywood labor disputes. After the strikes were resolved, the film moved once more up two weeks to March 1, 2024. [...]\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9oULg1tOjjOW"
      },
      "source": [
        "### Embed the user question\n",
        "\n",
        "Cohere embeddings are state-of-the-art."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yrUuS6vXgbOs",
        "outputId": "0c64a930-f817-43c2-d775-1d9145cb304e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "query_embedding:  [-0.068603516, -0.02947998, -0.06274414, -0.015449524, -0.033294678, 0.0056877136, -0.047210693, 0.04714966, -0.024871826, 0.008148193, 0.0770874, 0.023880005, -0.058685303, -0.052520752, 0.012832642, 0.024398804, 0.0053215027, 0.035491943, 0.02961731, -0.0069847107, 0.01083374, -0.0011358261, -0.002199173, 0.018417358, 0.027389526, -0.002691269, -0.026535034, 0.015197754, 0.024368286, 0.03729248, 0.0057754517, -0.02229309, -0.014694214, 0.019989014, -0.0036315918, -0.013793945, 0.02835083, 0.006011963, 0.011428833, 0.008682251, 0.046142578, -0.040039062, -0.032196045, -0.002653122, -0.012580872, -0.0041618347, 0.03111267, -0.016799927, 0.014801025, -0.00030636787, -0.033050537, 0.033966064, -0.016021729, -0.025009155, -0.007534027, -0.017074585, 0.008415222, -0.10620117, 0.019195557, -0.015686035, -0.0043182373, -0.045440674, 0.05404663, 0.030776978, -0.014129639, -0.01499939, -0.007286072, 0.009933472, 0.06390381, 0.02444458, -0.010345459, 0.041931152, 0.032989502, -0.04522705, 0.056610107, 0.0068893433, -0.008911133, 0.012489319, 0.01675415, 0.020065308, 0.018753052, 0.022659302, -0.051849365, -0.04925537, 0.046325684, -0.005268097, 0.0026874542, -0.036712646, 0.009437561, -0.0037841797, -0.01473999, -0.034179688, -0.0011606216, 0.05026245, 0.0020771027, -0.016021729, -0.0044898987, 0.04168701, -0.015205383, 0.019210815, -0.012374878, -0.031311035, 0.03111267, -0.040100098, -0.016479492, 0.020446777, 0.010192871, 0.0037841797, -0.0023765564, 0.015220642, -0.016571045, -0.006454468, 0.037384033, -0.044555664, -0.008262634, 0.019546509, 0.009460449, 0.014701843, 0.02658081, -0.02078247, 0.015571594, 0.013153076, -0.010375977, 0.047912598, 0.005393982, -0.007911682, -0.019378662, 0.023529053, -0.0033550262, -0.04598999, -0.0052871704, 0.040252686, 0.011375427, 0.01550293, -0.004508972, 0.006515503, 0.003370285, -0.022766113, 0.00062561035, -0.0007596016, -0.0015277863, 0.0149002075, 0.061401367, 8.261204e-05, 0.06359863, -0.01537323, 0.007446289, 0.018814087, 0.02507019, 0.024215698, 0.006122589, 0.005886078, -0.03829956, 0.029037476, 0.07720947, 0.016921997, 0.022109985, 0.005958557, 0.028793335, 0.019485474, 0.015174866, 0.026153564, 0.032318115, 0.034210205, 0.027145386, -0.019515991, -0.018661499, 0.020477295, 0.008598328, -0.06573486, -0.037109375, 0.04043579, 0.030471802, -0.0010843277, 0.009757996, 0.026947021, 0.037017822, -0.018234253, -0.0115356445, 0.099365234, 0.027816772, -0.019927979, 0.0020961761, 0.013198853, -0.019073486, 2.7656555e-05, 0.041259766, 0.029510498, -0.016204834, 0.028137207, 0.039489746, 0.034698486, -0.03918457, -0.029418945, 0.02041626, 0.0073432922, -0.018569946, -0.009849548, 0.002861023, 0.030319214, -0.012886047, 0.014671326, -0.035827637, 0.007247925, -0.027709961, -0.022079468, 0.0012960434, 0.015426636, -0.01725769, 0.01525116, 0.025360107, -0.0077400208, -0.039916992, 0.029037476, -0.011154175, 0.007736206, -0.041748047, 0.05343628, 0.007286072, 0.0435791, 0.034301758, -0.047210693, 0.03552246, -0.015327454, 0.029922485, -0.018859863, 0.013053894, -0.028060913, 0.07757568, -0.020462036, 0.070739746, -0.010223389, 0.03604126, 0.02758789, -0.023284912, 0.012184143, 0.029144287, 0.023880005, -0.019378662, -0.0051116943, 0.0048675537, 0.01864624, -0.04397583, -0.007598877, 0.0713501, 0.0115737915, 0.002922058, 0.011619568, 0.017364502, 0.031921387, -0.0019664764, -0.008575439, 0.003484726, -0.09466553, 0.03475952, 0.026611328, -0.039520264, -0.0104522705, -0.005443573, -0.008392334, 0.012908936, 0.0043792725, -0.002456665, -0.028396606, -0.02027893, -0.0005569458, 0.027786255, 0.03427124, -0.0062332153, -0.018203735, 0.019241333, 0.07244873, -0.0028057098, 0.01234436, -0.0018787384, -0.027496338, 0.0015287399, -0.004032135, -0.013748169, -0.01878357, 0.0018053055, -0.01159668, 0.028213501, 0.004776001, 0.042388916, 0.0024280548, 0.017471313, -0.038085938, 0.026321411, 0.02973938, 0.06213379, 0.006401062, 0.036102295, -0.028121948, -0.00869751, -0.016693115, 0.029190063, 0.016784668, -0.008628845, 0.0039634705, -0.0035381317, 0.019500732, 0.025009155, -0.04547119, -0.003572464, 0.05215454, 0.067871094, -0.04257202, -0.02293396, -0.027175903, 0.05340576, 0.019226074, 0.039978027, 0.056121826, -0.028320312, -0.020217896, -0.035003662, 0.03225708, 0.028656006, 0.062347412, 0.12915039, -0.0137786865, 0.0022201538, -0.057434082, -0.04397583, -0.049865723, -0.013160706, -0.03353882, 0.006427765, -0.014823914, -0.008201599, -0.036346436, -0.037353516, -0.010528564, -0.015930176, -0.027572632, 0.0074272156, 0.004547119, -0.024414062, -0.018859863, -0.020095825, 0.029632568, -0.00067043304, -0.044036865, -0.0043411255, -0.005256653, -0.019195557, 0.022262573, -0.00020956993, -0.013877869, -0.011108398, -0.020324707, -0.015808105, -0.025039673, -0.009498596, 0.05090332, 0.0046195984, -0.017150879, 0.04309082, -0.029067993, 0.002670288, -0.00026249886, -0.032409668, -0.053100586, 0.012481689, -0.014633179, 0.0013475418, -0.034332275, 0.038330078, 0.014892578, -0.046936035, 0.021591187, -0.020385742, -0.0052604675, 0.02796936, 0.0014333725, 0.012077332, -0.0118255615, -0.005569458, 0.008491516, 0.009841919, 0.0031318665, -0.003408432, -0.007144928, 0.040374756, -0.0038928986, 0.005279541, -0.008415222, 0.031707764, 0.0140686035, -0.015029907, -0.02810669, -0.0078125, -0.030853271, -0.03201294, 0.021316528, -0.036193848, -0.0423584, 0.0072784424, 0.014801025, 0.0019607544, -0.012367249, -0.009056091, -0.021438599, -0.02645874, 0.038726807, -0.007549286, 0.0049591064, 0.019012451, 0.017791748, -0.009185791, 0.04006958, 0.003107071, -0.0075302124, -0.010375977, -0.009246826, -0.02130127, -0.0056762695, -0.0076789856, 0.010009766, -0.010536194, 0.041107178, 0.0021133423, 0.029891968, 0.01626587, 0.042236328, -0.02784729, -0.032836914, 0.0317688, 0.045715332, 0.000116825104, 0.028030396, 0.007205963, 0.012512207, -0.035583496, -0.048034668, -0.023529053, -0.04953003, 0.0345459, -0.048339844, -0.060272217, -0.004512787, 0.04425049, 0.0076141357, 0.029510498, 0.007396698, 0.003353119, -0.038726807, 0.07183838, -0.026901245, -0.023529053, -0.038085938, 0.068725586, 0.018096924, -0.013534546, 0.05883789, -0.016113281, 0.017944336, 0.041046143, 0.022918701, 0.036499023, 0.015296936, -0.04916382, 0.0075683594, -0.011390686, 0.009735107, -0.0070152283, 0.003129959, -0.032562256, 0.0003478527, -0.0036640167, -0.006893158, -0.016098022, -0.034332275, 0.037750244, -0.010269165, 0.016494751, -0.02394104, 0.03753662, -0.022644043, -0.0008234978, 0.001001358, -0.048217773, 0.04989624, 0.0078125, 0.0044937134, 0.027038574, 0.04736328, -0.02973938, -0.011726379, 0.01348114, 0.021408081, 0.00844574, -0.03741455, -0.015686035, -0.040893555, 0.001452446, -0.025405884, 0.07348633, 0.038238525, -0.019958496, 0.023071289, -0.016403198, -0.08105469, 0.0071029663, -0.019088745, 5.8174133e-05, -0.005569458, 0.01399231, 0.02255249, 0.011222839, 0.00028824806, 0.0066184998, 0.0017499924, -0.009864807, -0.0115737915, 0.053100586, 0.0065231323, 0.001865387, -0.026428223, 0.03692627, 0.025390625, 0.022613525, 0.018722534, 0.007675171, -0.03439331, 0.041625977, -0.01789856, -0.041046143, 0.0051460266, 0.04144287, 0.048553467, 0.054595947, -0.01108551, -0.033935547, -0.026275635, -0.0118255615, -0.021362305, -0.009841919, -0.00724411, 0.028900146, 0.009887695, -0.023803711, 0.016311646, 0.018798828, -0.03668213, 0.046844482, 0.010696411, -0.014717102, -0.008110046, -0.004589081, -0.0028076172, -0.050811768, -0.017196655, -0.03491211, 0.0074005127, -0.038909912, 0.032440186, -0.034362793, -0.008682251, 0.032928467, -0.04626465, -0.009666443, 0.018951416, 0.031951904, -0.003791809, 0.02015686, -0.05532837, -0.005683899, -0.00054216385, -0.0034332275, 0.008659363, 0.02130127, -0.038879395, -0.0033397675, -0.03866577, -0.0049934387, 0.017944336, 0.001496315, 0.019485474, -0.004348755, 0.00046491623, 0.0007157326, 0.035614014, -0.027694702, 0.03692627, -0.008491516, 0.0524292, -0.016662598, -0.0017795563, -0.021575928, -0.018753052, -0.049346924, -0.06652832, 0.04272461, 0.03186035, 0.0011978149, 0.03463745, 0.024002075, 0.02607727, 0.020446777, 0.0256958, 0.026855469, 0.0074005127, -0.067993164, 0.017944336, -0.0039482117, 0.05496216, -0.041412354, 0.014175415, 0.02444458, -0.026412964, 0.057403564, -0.026779175, 0.023254395, 0.03945923, 0.033569336, -0.030258179, -0.039093018, -0.036468506, 0.017105103, 0.009635925, 0.025497437, 0.04156494, -0.02571106, -0.0010414124, -0.005630493, -0.016448975, -0.026733398, 0.001326561, -0.042022705, 0.0012521744, -0.041259766, -0.12182617, -0.03857422, 0.12548828, -0.005947113, -0.020736694, -0.0033855438, 0.03778076, -0.033813477, 0.038970947, 0.003921509, 0.011810303, 0.031982422, -0.032562256, -0.002653122, -0.025009155, -0.03805542, -0.016998291, 0.018173218, 0.0158844, 0.0011739731, 0.048217773, -0.020401001, 0.044708252, -0.017318726, 0.014457703, -0.041809082, 0.010543823, 0.041931152, 0.076293945, -0.054779053, 0.060272217, -0.046936035, 0.02949524, 0.00554657, 0.041534424, -0.013046265, -0.056152344, 0.010406494, 0.02973938, -0.023727417, -0.022476196, -0.024734497, -0.013168335, 0.060424805, 0.011787415, 0.018997192, -0.043426514, -0.00077724457, -0.010154724, 0.017150879, -0.01171875, -0.022476196, 0.0034255981, -0.0026454926, 0.004837036, -0.0043296814, 0.02619934, -0.021560669, -0.039733887, -0.022415161, -0.06817627, -0.023223877, -0.018585205, -0.015319824, 0.012588501, 0.0064353943, -0.013748169, 0.043304443, 0.002626419, -0.029373169, -0.016784668, -0.026184082, 0.05847168, 0.034179688, 0.03842163, -0.05493164, -0.017486572, 0.016540527, 0.03164673, 0.089904785, 0.013534546, -0.07684326, -0.024108887, 0.07434082, 0.030395508, 0.007091522, 0.07373047, 0.012527466, -0.010856628, -0.01828003, -0.045196533, 0.00065279007, -0.0637207, 0.010726929, 0.023880005, -0.0030708313, -0.012298584, 0.027236938, -0.04928589, 0.023071289, 0.008674622, -0.023529053, -0.015838623, -0.010543823, 0.012168884, 0.014854431, -0.05834961, -0.06088257, -0.012313843, 0.035461426, 0.02027893, 0.019348145, -0.014602661, -0.02104187, -0.0309906, 0.001405716, -0.019973755, -0.00157547, -0.003944397, 0.0009326935, -0.02078247, -0.015731812, -0.044433594, 0.03390503, 0.057159424, 0.018585205, -0.023895264, -0.0057029724, 0.0049552917, 0.013412476, 0.022399902, 0.010154724, 0.0519104, 0.06591797, 0.018341064, 0.012161255, -0.05810547, -0.043304443, -0.031173706, 0.0023860931, -0.003944397, 0.11425781, -0.031036377, 0.019989014, -0.038635254, -0.025939941, 0.035064697, 0.041168213, 0.03161621, -0.069885254, -0.04537964, 0.028945923, -0.023162842, 0.019226074, -0.028442383, 0.015594482, -0.019256592, -0.0046463013, 0.034240723, 0.009124756, 0.05718994, 0.031219482, 0.02154541, 0.009590149, 0.00076818466, 0.04849243, -0.029129028, -0.03375244, -0.023391724, -0.028381348, -0.029708862, -0.0132369995, 0.010353088, 0.020263672, -0.030807495, 0.01007843, -0.03704834, 0.023376465, -0.03665161, 0.03741455, 0.015144348, 0.057281494, 0.03137207, 0.048431396, 0.021194458, 0.008110046, -0.03540039, -0.015312195, 0.022384644, 0.0065956116, 0.008056641, 0.0018348694, -0.009246826, 0.030380249, 0.0003862381, 0.0051841736, 0.04486084, 0.017807007, 0.0026130676, 0.07977295, 0.05419922, 0.062194824, 0.02633667, 0.024841309, -0.041625977, -0.005897522, 0.04031372, -0.055908203, 0.0026226044, -0.05340576, -0.05496216, 0.011474609, -0.006954193, -0.013122559, 0.019714355, -0.07159424, 0.031173706, 0.0034255981, -0.0034103394, 0.0440979, 0.011779785, -0.007827759, -0.03173828, -0.020950317, -0.030166626, -0.035308838, 0.030792236, 0.04525757, -0.028701782, -0.011100769, -0.02331543, -0.0357666, -0.025680542, 0.0011911392, 0.01940918, 0.05706787, 0.028381348, 0.007133484, -0.07733154, -0.007686615, 0.03869629, 0.0066833496, 0.008842468, 0.03439331, -0.014282227, 0.0357666, -0.004737854, -0.039794922, -0.0070381165, 0.02670288, 0.0107421875, 0.016189575, -0.06555176, -0.0138549805, 0.0008363724, -0.016693115, 0.006904602, -0.020263672, -0.030426025, 0.008453369, -0.046173096, -0.01802063, -0.013595581, -0.0044288635, -0.0039978027, -0.0044898987, 0.0007619858, 0.003921509, 0.0053977966, 0.020385742, -0.012329102, -0.023803711, -0.0057525635, 0.038330078, -0.014549255, -0.06298828, -0.047607422, 0.039245605, -0.06781006, -0.035217285, -0.009056091, 0.019927979, -0.003932953, -0.020309448, -0.017044067, 0.018127441, -8.624792e-05, -0.043182373, 0.009590149, 0.035308838, 0.031951904, 0.0011615753, -0.042022705, 0.079956055, 0.026687622, 0.013542175, -0.0074157715, -0.00983429, -0.0022563934, 0.07373047, 0.059387207, 0.03488159, 0.0071372986, -0.06427002, -0.0546875, -0.02482605, 0.11071777, -0.021072388, 0.01626587, -0.049713135, 0.061553955, -0.016860962, 0.051971436, -0.012962341, -0.0011711121, -0.014198303, -0.0061149597, -0.005836487, 0.00022387505, -0.027618408, 0.019836426, 0.009933472, 0.02368164, -0.020309448, -0.0049591064, -0.008628845, -0.03253174, -0.017684937, 0.02468872, -0.0023498535, 0.01448822, 0.061920166, 0.031707764, -0.0026416779, -0.040985107, -0.06335449, -0.036071777, 0.05404663, -0.0044136047, -0.0146102905, -0.0033416748, 0.028671265, -0.012771606, -0.0016565323, -0.0038909912, -0.02407837, -0.009857178, 0.0014467239, -0.008720398, -0.006011963, 0.032073975, -0.033325195, 0.014862061, -0.017227173, -0.018753052, -0.0060424805, 0.022567749, -0.017654419, -0.017562866, -0.07244873, -0.0881958, 0.050476074, 0.02609253, -0.032409668, 0.07458496, 0.009399414, 0.009117126, -0.031051636, -0.03451538, -0.004219055, -0.05718994, 0.020080566, -0.025421143, -0.010948181, 0.06341553, -0.009231567, -0.021697998, -0.009719849, 0.012802124, -0.020370483, 0.0034389496, 0.018859863, -0.025680542, 0.0013141632, 0.068603516, -0.021026611, 0.021881104, -0.0395813, -0.0019073486, 0.0056037903, -0.032348633]\n"
          ]
        }
      ],
      "source": [
        "# Because the text being embedded is the search query, we set the input type as search_query\n",
        "response = co.embed(\n",
        "    texts=[query],\n",
        "    model=model,\n",
        "    input_type=\"search_query\",\n",
        "    embedding_types=['float']\n",
        ")\n",
        "query_embedding = response.embeddings.float[0]\n",
        "print(\"query_embedding: \", query_embedding)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8K8B87CGgbOt"
      },
      "source": [
        "### Retrieve the most relevant chunks from the vector database\n",
        "\n",
        "We use cosine similarity to find the most similar chunks"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nik3es32gbOt",
        "outputId": "a1c30024-52e1-42c7-8836-a2c590559aca"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "similarity scores:  [0.6953257882233425, 0.3713410510180273, 0.46501499776898964, 0.5448546916785195, 0.4014738351361969, 0.3231420292334584, 0.3179003053384008, 0.42799691553367775, 0.18882594531435784, 0.36868801306504106, 0.3404040737300553, 0.3852837621219358, 0.2600249419491577, 0.3723244353775111, 0.3631492691137214, 0.47574774051439606, 0.40415422750911745, 0.4149923346201023, 0.5014741934381444, 0.3549433331883204, 0.32072714802512714, 0.14770872479410424, 0.585277816615252, 0.6999636953772764, 0.7722295084104617, 0.4895347049465806, 0.5170096485954725, 0.7137817366881455, 0.5224900699612323, 0.5914632581598285, 0.2657897083381463, 0.6462342489537262, 0.6317222315431096, 0.5982303530756702, 0.5138265091630297, 0.41385121172723643, 0.4293941094100836, 0.4173182546482015, 0.42621236706314475, 0.4428474375355954, 0.35058541576139896, 0.3578709652019502, 0.3930157841938308, 0.3564608202848675, 0.23016661533167404, 0.4933441863421645, 0.41037089239250985, 0.39993051898770193, 0.3119997063424595, 0.2677143729521374, 0.3700866951454496, 0.46727994925061545, 0.4393343280374425, 0.42111290117172434, 0.4485349189824285, 0.4710573736688592, 0.24169956903740436, 0.3840442910806355, 0.14284631817675886, 0.5381588054138154, 0.431113882725076, 0.5189547209048608, 0.3950667224233914, 0.32429768756510174, 0.4370358125161736, 0.18727062244331039, 0.5206375682478743, 0.5175737635701252, 0.5326043981628349, 0.45586923626994363, 0.21667338125532032, 0.16459878595959285, 0.22236726481673777, 0.5187259906958807, 0.2884444442338396, 0.286407544555338, 0.2313840178160818, 0.2057731158935257, 0.5973876998341746, 0.42904243401792086, 0.4081217538000544, 0.5330523063972133, 0.45080561486977405, 0.414703452285757, 0.2569028899107211, 0.5087916806929323, 0.14159076456040554, 0.46505779053352697, 0.556364222182839, 0.35464351181035236, 0.40174477023626]\n",
            "Here are the indices of the top 10 chunks after retrieval:  [24 27 23  0 31 32 33 78 29 22]\n",
            "Here are the top 10 chunks after retrieval: \n",
            "== stunt coordinator. Dune: Part Two was produced by Villeneuve, Mary Parent, and Cale Boyter, with Tanya Lapointe, Brian Herbert, Byron Merritt, Kim Herbert, Thomas Tull, Jon Spaihts, Richard P. Rubinstein, John Harrison, and Herbert W. Gain serving as executive producers and Kevin J. Anderson as creative consultant. Legendary CEO Joshua Grode confirmed in April 2019 that they plan to make a sequel, adding that \"there's a logical place to stop the [first] movie before the book is over\".In December 2020,\n",
            "== that.\"On October 26, 2021, Legendary officially greenlit Dune: Part Two, with a spokesperson for the company stating, \"We would not have gotten to this point without the extraordinary vision of Denis and the amazing work of his talented crew, the writers, our stellar cast, our partners at Warner Bros., and of course the fans! Here's to more Dune.\" Production work had occurred back-to-back with the first film, as Villeneuve and his wife Lapointe immediately took a flight to Budapest in order to begin\n",
            "== series. Villeneuve ultimately secured a two-film deal with Warner Bros. Pictures, in the same style as the two-part adaption of Stephen King's It in 2017 and 2019. In January 2019, Joe Walker was confirmed to be serving as the film's editor. Other crew included Brad Riker as supervising art director, Patrice Vermette as production designer, Paul Lambert as visual effects supervisor, Gerd Nefzer as special effects supervisor, and Thomas Struthers as stunt coordinator. Dune: Part Two was produced by\n",
            "== Dune: Part Two is a 2024 American epic science fiction film directed and produced by Denis Villeneuve, who co-wrote the screenplay with Jon Spaihts. The sequel to Dune (2021) adapts the 1965 novel Dune by Frank Herbert and follows Paul Atreides as he unites with the Fremen people of the desert planet Arrakis to wage war against House Harkonnen. TimothΓ©e Chalamet, Rebecca Ferguson, Josh Brolin, Stellan SkarsgΓ₯rd, Dave Bautista, Zendaya, Charlotte Rampling, and Javier Bardem reprise their roles from the first\n",
            "== Eric Roth was hired to co-write the screenplay in April 2017 for the Dune films, and Jon Spaihts was later confirmed to be co-writing the script alongside Roth and Villeneuve. Game of Thrones language creator David Peterson was confirmed to be developing languages for the film in April 2019. Villeneuve and Peterson had created the Chakobsa language, which was used by actors on set. In November 2019, Spaihts stepped down as showrunner for Dune: Prophecy to focus on Dune: Part Two. In June 2020, Greig Fraser\n",
            "== on Dune: Part Two. In June 2020, Greig Fraser said, \"It's a fully formed story in itself with places to go. It's a fully standalone epic film that people will get a lot out of when they see it\". Between the release of Dune and the confirmation of Dune: Part Two, Villeneuve started working the script in a way that production could begin immediately once the film was greenlit. By February 2021, Roth created a full treatment for the sequel, with writing beginning that August. He confirmed that Feyd-Rautha\n",
            "== that August. He confirmed that Feyd-Rautha would appear in the film, and stated he will be a \"very important character\". In March 2022, Villeneuve had mostly finished writing the screenplay. Craig Mazin and Roth wrote additional literary material for the film.Villeneuve stated that the film would continue directly from the first, and specifically described it as being the \"second part.\" He described the film as being an \"epic war movie\", adding that while the first film was more \"contemplative\", the second\n",
            "== On the review aggregator website Rotten Tomatoes, 93% of 378 critics' reviews are positive, with an average rating of 8.4/10. The website's consensus reads: \"Visually thrilling and narratively epic, Dune: Part Two continues Denis Villeneuve's adaptation of the beloved sci-fi series in spectacular form.\" Metacritic, which uses a weighted average, assigned the film a score of 79 out of 100, based on 62 critics, indicating \"generally favorable\" reviews. Audiences surveyed by CinemaScore gave the film an\n",
            "== theatrical experience is at the very heart of the cinematic language for me.\" With Dune: Part Two being greenlit, Villeneuve said that his primary concern was to complete the filming as soon as possible, with the earliest he expected to start in the last quarter of 2022. However, he noted that production would be facilitated by the work already established on the first film, which would help expedite production.\n",
            "== By November 2016, Legendary Pictures had obtained the film and TV rights for the Dune franchise, based on the eponymous 1965 novel by Frank Herbert. Vice chair of worldwide production for Legendary Mary Parent began discussing with Denis Villeneuve about directing a film adaptation, quickly hiring him after realizing his passion for Dune. By February 2018, Villeneuve was confirmed to be hired as director, and intended to adapt the novel as a two-part film series. Villeneuve ultimately secured a two-film\n"
          ]
        }
      ],
      "source": [
        "def cosine_similarity(a, b):\n",
        "    return np.dot(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))\n",
        "\n",
        "# Calculate similarity between the user question & each chunk\n",
        "similarities = [cosine_similarity(query_embedding, chunk) for chunk in embeddings]\n",
        "print(\"similarity scores: \", similarities)\n",
        "\n",
        "# Get indices of the top 10 most similar chunks\n",
        "sorted_indices = np.argsort(similarities)[::-1]\n",
        "\n",
        "# Keep only the top 10 indices\n",
        "top_indices = sorted_indices[:10]\n",
        "print(\"Here are the indices of the top 10 chunks after retrieval: \", top_indices)\n",
        "\n",
        "# Retrieve the top 10 most similar chunks\n",
        "top_chunks_after_retrieval = [chunks[i] for i in top_indices]\n",
        "print(\"Here are the top 10 chunks after retrieval: \")\n",
        "for t in top_chunks_after_retrieval:\n",
        "    print(\"== \" + t)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qzcpds3VgbOt"
      },
      "source": [
        "## Step 2 - Rerank the chunks retrieved from the vector database\n",
        "\n",
        "We rerank the 10 chunks retrieved from the vector database. Reranking boosts retrieval accuracy.\n",
        "\n",
        "Reranking lets us go from 10 chunks retrieved from the vector database, to the 3 most relevant chunks."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2J4LywVygbOt",
        "outputId": "7a4c89bf-fc5e-409f-9304-fce006b9d8bf"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Here are the top 3 chunks after rerank: \n",
            "== Dune: Part Two is a 2024 American epic science fiction film directed and produced by Denis Villeneuve, who co-wrote the screenplay with Jon Spaihts. The sequel to Dune (2021) adapts the 1965 novel Dune by Frank Herbert and follows Paul Atreides as he unites with the Fremen people of the desert planet Arrakis to wage war against House Harkonnen. TimothΓ©e Chalamet, Rebecca Ferguson, Josh Brolin, Stellan SkarsgΓ₯rd, Dave Bautista, Zendaya, Charlotte Rampling, and Javier Bardem reprise their roles from the first\n",
            "== stunt coordinator. Dune: Part Two was produced by Villeneuve, Mary Parent, and Cale Boyter, with Tanya Lapointe, Brian Herbert, Byron Merritt, Kim Herbert, Thomas Tull, Jon Spaihts, Richard P. Rubinstein, John Harrison, and Herbert W. Gain serving as executive producers and Kevin J. Anderson as creative consultant. Legendary CEO Joshua Grode confirmed in April 2019 that they plan to make a sequel, adding that \"there's a logical place to stop the [first] movie before the book is over\".In December 2020,\n",
            "== series. Villeneuve ultimately secured a two-film deal with Warner Bros. Pictures, in the same style as the two-part adaption of Stephen King's It in 2017 and 2019. In January 2019, Joe Walker was confirmed to be serving as the film's editor. Other crew included Brad Riker as supervising art director, Patrice Vermette as production designer, Paul Lambert as visual effects supervisor, Gerd Nefzer as special effects supervisor, and Thomas Struthers as stunt coordinator. Dune: Part Two was produced by\n"
          ]
        }
      ],
      "source": [
        "response = co.rerank(\n",
        "    query=query,\n",
        "    documents=top_chunks_after_retrieval,\n",
        "    top_n=3,\n",
        "    model=\"rerank-english-v2.0\",\n",
        ")\n",
        "\n",
        "top_chunks_after_rerank = [result.document['text'] for result in response]\n",
        "print(\"Here are the top 3 chunks after rerank: \")\n",
        "for t in top_chunks_after_rerank:\n",
        "    print(\"== \" + t)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KuPL0VUXgbOt"
      },
      "source": [
        "## Step 3 - Generate the model final answer, given the retrieved and reranked chunks"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oCNXWH8GgbOt"
      },
      "outputs": [],
      "source": [
        "# preamble containing instructions about the task and the desired style for the output.\n",
        "preamble = \"\"\"\n",
        "## Task & Context\n",
        "You help people answer their questions and other requests interactively. You will be asked a very wide array of requests on all kinds of topics. You will be equipped with a wide range of search engines or similar tools to help you, which you use to research your answer. You should focus on serving the user's needs as best you can, which will be wide-ranging.\n",
        "\n",
        "## Style Guide\n",
        "Unless the user asks for a different style of answer, you should answer in full sentences, using proper grammar and spelling.\n",
        "\"\"\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BevatShtgbOt",
        "outputId": "af71f4a9-787a-4ee3-9598-20692fb3bf16"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Final answer:\n",
            "Here are the key crew members involved in 'Dune: Part Two':\n",
            "\n",
            "- Denis Villeneuve: director and producer\n",
            "- Jon Spaihts: co-writer of the screenplay\n",
            "- Mary Parent and Cale Boyter: producers \n",
            "- Tanya Lapointe, Brian Herbert, Byron Merritt, Kim Herbert, Thomas Tull, Richard P. Rubinstein, John Harrison, Herbert W. Gain and Kevin J. Anderson: executive producers \n",
            "- Joe Walker: editor\n",
            "- Brad Riker: supervising art director\n",
            "- Patrice Vermette: production designer\n",
            "- Paul Lambert: visual effects supervisor\n",
            "- Gerd Nefzer: special effects supervisor\n",
            "- Thomas Struthers: stunt coordinator. \n",
            "\n",
            "A number of crew members from the first film returned for the sequel, which is set to be released in 2024.\n"
          ]
        }
      ],
      "source": [
        "# retrieved documents\n",
        "documents = [\n",
        "    {\"title\": \"chunk 0\", \"snippet\": top_chunks_after_rerank[0]},\n",
        "    {\"title\": \"chunk 1\", \"snippet\": top_chunks_after_rerank[1]},\n",
        "    {\"title\": \"chunk 2\", \"snippet\": top_chunks_after_rerank[2]},\n",
        "  ]\n",
        "\n",
        "# get model response\n",
        "response = co.chat(\n",
        "  message=query,\n",
        "  documents=documents,\n",
        "  preamble=preamble,\n",
        "  model=\"command-r\",\n",
        "  temperature=0.3\n",
        ")\n",
        "\n",
        "print(\"Final answer:\")\n",
        "print(response.text)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "20wcn-EjlXZd"
      },
      "source": [
        "Note: this is indeed the answer you'd expect, and here was the passage of text in wikipedia explaining it!\n",
        "\n",
        "\" [...] Dune: Part Two was originally scheduled to be released on October 20, 2023, but was delayed to November 17, 2023, before moving forward two weeks to November 3, 2023, to adjust to changes in release schedules from other studios. It was later postponed by over four months to March 15, 2024, due to the 2023 Hollywood labor disputes. After the strikes were resolved, the film moved once more up two weeks to March 1, 2024. [...]\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RoSVDXSsgbOt"
      },
      "source": [
        "## Bonus: Citations come for free with Cohere! πŸŽ‰\n",
        "\n",
        "At Cohere, all RAG calls come with... precise citations! πŸŽ‰\n",
        "The model cites which groups of words, in the RAG chunks, were used to generate the final answer.  \n",
        "These citations make it easy to check where the model’s generated response claims are coming from.  \n",
        "They help users gain visibility into the model reasoning, and sanity check the final model generation.  \n",
        "These citations are optional β€” you can decide to ignore them.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BVTuQdmDgbOt",
        "outputId": "f843b262-d8bb-45ba-cbfb-9915da104eda"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Citations that support the final answer:\n",
            "{'start': 63, 'end': 79, 'text': 'Denis Villeneuve', 'document_ids': ['doc_0']}\n",
            "{'start': 81, 'end': 102, 'text': 'director and producer', 'document_ids': ['doc_0']}\n",
            "{'start': 105, 'end': 116, 'text': 'Jon Spaihts', 'document_ids': ['doc_0']}\n",
            "{'start': 118, 'end': 145, 'text': 'co-writer of the screenplay', 'document_ids': ['doc_0']}\n",
            "{'start': 148, 'end': 159, 'text': 'Mary Parent', 'document_ids': ['doc_1']}\n",
            "{'start': 164, 'end': 175, 'text': 'Cale Boyter', 'document_ids': ['doc_1']}\n",
            "{'start': 177, 'end': 186, 'text': 'producers', 'document_ids': ['doc_1']}\n",
            "{'start': 190, 'end': 204, 'text': 'Tanya Lapointe', 'document_ids': ['doc_1']}\n",
            "{'start': 206, 'end': 219, 'text': 'Brian Herbert', 'document_ids': ['doc_1']}\n",
            "{'start': 221, 'end': 234, 'text': 'Byron Merritt', 'document_ids': ['doc_1']}\n",
            "{'start': 236, 'end': 247, 'text': 'Kim Herbert', 'document_ids': ['doc_1']}\n",
            "{'start': 249, 'end': 260, 'text': 'Thomas Tull', 'document_ids': ['doc_1']}\n",
            "{'start': 262, 'end': 283, 'text': 'Richard P. Rubinstein', 'document_ids': ['doc_1']}\n",
            "{'start': 285, 'end': 298, 'text': 'John Harrison', 'document_ids': ['doc_1']}\n",
            "{'start': 300, 'end': 315, 'text': 'Herbert W. Gain', 'document_ids': ['doc_1']}\n",
            "{'start': 320, 'end': 337, 'text': 'Kevin J. Anderson', 'document_ids': ['doc_1']}\n",
            "{'start': 339, 'end': 358, 'text': 'executive producers', 'document_ids': ['doc_1']}\n",
            "{'start': 362, 'end': 372, 'text': 'Joe Walker', 'document_ids': ['doc_2']}\n",
            "{'start': 374, 'end': 380, 'text': 'editor', 'document_ids': ['doc_2']}\n",
            "{'start': 383, 'end': 393, 'text': 'Brad Riker', 'document_ids': ['doc_2']}\n",
            "{'start': 395, 'end': 419, 'text': 'supervising art director', 'document_ids': ['doc_2']}\n",
            "{'start': 422, 'end': 438, 'text': 'Patrice Vermette', 'document_ids': ['doc_2']}\n",
            "{'start': 440, 'end': 459, 'text': 'production designer', 'document_ids': ['doc_2']}\n",
            "{'start': 462, 'end': 474, 'text': 'Paul Lambert', 'document_ids': ['doc_2']}\n",
            "{'start': 476, 'end': 501, 'text': 'visual effects supervisor', 'document_ids': ['doc_2']}\n",
            "{'start': 504, 'end': 515, 'text': 'Gerd Nefzer', 'document_ids': ['doc_2']}\n",
            "{'start': 517, 'end': 543, 'text': 'special effects supervisor', 'document_ids': ['doc_2']}\n",
            "{'start': 546, 'end': 562, 'text': 'Thomas Struthers', 'document_ids': ['doc_2']}\n",
            "{'start': 564, 'end': 582, 'text': 'stunt coordinator.', 'document_ids': ['doc_2']}\n",
            "{'start': 686, 'end': 691, 'text': '2024.', 'document_ids': ['doc_0']}\n"
          ]
        }
      ],
      "source": [
        "print(\"Citations that support the final answer:\")\n",
        "for cite in response.citations:\n",
        "  print(cite)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IueXaIJggbOu",
        "outputId": "c816af51-74be-42c9-e94e-9820bbf95f79"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Here are the key crew members involved in 'Dune: Part Two':\n",
            "\n",
            "- **Denis Villeneuve**[1]: **director and producer**[1]\n",
            "- **Jon Spaihts**[1]: **co-writer of the screenplay**[1]\n",
            "- **Mary Parent**[2] and **Cale Boyter**[2]: **producers**[2] \n",
            "- **Tanya Lapointe**[2], **Brian Herbert**[2], **Byron Merritt**[2], **Kim Herbert**[2], **Thomas Tull**[2], **Richard P. Rubinstein**[2], **John Harrison**[2], **Herbert W. Gain**[2] and **Kevin J. Anderson**[2]: **executive producers**[2] \n",
            "- **Joe Walker**[3]: **editor**[3]\n",
            "- **Brad Riker**[3]: **supervising art director**[3]\n",
            "- **Patrice Vermette**[3]: **production designer**[3]\n",
            "- **Paul Lambert**[3]: **visual effects supervisor**[3]\n",
            "- **Gerd Nefzer**[3]: **special effects supervisor**[3]\n",
            "- **Thomas Struthers**[3]: **stunt coordinator.**[3] \n",
            "\n",
            "A number of crew members from the first film returned for the sequel, which is set to be released in **2024.**[1]\n",
            "\n",
            "[1] source: \"Dune: Part Two is a 2024 American epic science fiction film directed and produced by Denis Villeneuve, who co-wrote the screenplay with Jon Spaihts. The sequel to Dune (2021) adapts the 1965 novel Dune by Frank Herbert and follows Paul Atreides as he unites with the Fremen people of the desert planet Arrakis to wage war against House Harkonnen. TimothΓ©e Chalamet, Rebecca Ferguson, Josh Brolin, Stellan SkarsgΓ₯rd, Dave Bautista, Zendaya, Charlotte Rampling, and Javier Bardem reprise their roles from the first\"\n",
            "[2] source: \"stunt coordinator. Dune: Part Two was produced by Villeneuve, Mary Parent, and Cale Boyter, with Tanya Lapointe, Brian Herbert, Byron Merritt, Kim Herbert, Thomas Tull, Jon Spaihts, Richard P. Rubinstein, John Harrison, and Herbert W. Gain serving as executive producers and Kevin J. Anderson as creative consultant. Legendary CEO Joshua Grode confirmed in April 2019 that they plan to make a sequel, adding that \"there's a logical place to stop the [first] movie before the book is over\".In December 2020,\"\n",
            "[3] source: \"series. Villeneuve ultimately secured a two-film deal with Warner Bros. Pictures, in the same style as the two-part adaption of Stephen King's It in 2017 and 2019. In January 2019, Joe Walker was confirmed to be serving as the film's editor. Other crew included Brad Riker as supervising art director, Patrice Vermette as production designer, Paul Lambert as visual effects supervisor, Gerd Nefzer as special effects supervisor, and Thomas Struthers as stunt coordinator. Dune: Part Two was produced by\"\n"
          ]
        }
      ],
      "source": [
        "def insert_citations_in_order(text, citations):\n",
        "    \"\"\"\n",
        "    A helper function to pretty print citations.\n",
        "    \"\"\"\n",
        "    offset = 0\n",
        "    document_id_to_number = {}\n",
        "    citation_number = 0\n",
        "    modified_citations = []\n",
        "\n",
        "    # Process citations, assigning numbers based on unique document_ids\n",
        "    for citation in citations:\n",
        "        citation_numbers = []\n",
        "        for document_id in sorted(citation[\"document_ids\"]):\n",
        "            if document_id not in document_id_to_number:\n",
        "                citation_number += 1  # Increment for a new document_id\n",
        "                document_id_to_number[document_id] = citation_number\n",
        "            citation_numbers.append(document_id_to_number[document_id])\n",
        "\n",
        "        # Adjust start/end with offset\n",
        "        start, end = citation['start'] + offset, citation['end'] + offset\n",
        "        placeholder = ''.join([f'[{number}]' for number in citation_numbers])\n",
        "        # Bold the cited text and append the placeholder\n",
        "        modification = f'**{text[start:end]}**{placeholder}'\n",
        "        # Replace the cited text with its bolded version + placeholder\n",
        "        text = text[:start] + modification + text[end:]\n",
        "        # Update the offset for subsequent replacements\n",
        "        offset += len(modification) - (end - start)\n",
        "\n",
        "    # Prepare citations for listing at the bottom, ensuring unique document_ids are listed once\n",
        "    unique_citations = {number: doc_id for doc_id, number in document_id_to_number.items()}\n",
        "    citation_list = '\\n'.join([f'[{doc_id}] source: \"{documents[doc_id - 1][\"snippet\"]}\"' for doc_id, number in sorted(unique_citations.items(), key=lambda item: item[1])])\n",
        "    text_with_citations = f'{text}\\n\\n{citation_list}'\n",
        "\n",
        "    return text_with_citations\n",
        "\n",
        "\n",
        "print(insert_citations_in_order(response.text, response.citations))\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Kp4c_HkYIEn_"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.10.12"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}