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Chatbot with Python and Open Source LLMs"],"metadata":{"id":"KRHOfJ2NcOTf"}},{"cell_type":"markdown","source":["## Installing required libraries"],"metadata":{"id":"zzdz0TmpCULl"}},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"CKuPN3hMZjlH","executionInfo":{"status":"ok","timestamp":1696090093707,"user_tz":-330,"elapsed":38847,"user":{"displayName":"Tahiyya Khan","userId":"02112400725815246626"}},"outputId":"9fba3327-ee8e-4c4c-bcf6-2dbdfd476f0f"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting huggingface\n","  Downloading huggingface-0.0.1-py3-none-any.whl (2.5 kB)\n","Installing collected packages: huggingface\n","Successfully installed huggingface-0.0.1\n","Collecting transformers\n","  Downloading transformers-4.33.3-py3-none-any.whl (7.6 MB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m42.4 MB/s\u001b[0m eta 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install huggingface\n","!pip install transformers\n","!pip install gradio"]},{"cell_type":"code","source":["# Importing necessary libraries\n","from transformers import AutoTokenizer\n","import gradio as gr\n","from transformers import pipeline\n","\n","model = 'deepset/roberta-base-squad2' # The model used is deepset/roberta-base-squad2\n","tokenizer = AutoTokenizer.from_pretrained(model) # To enable the same tokenization on which the model was trained on"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":177,"referenced_widgets":["d9ec495836c64db79205865211b6dd68","4f892493bc184b8cb3412f392905d41f","4da9ef89818d499babc50709d4febf8a","5d18bb07329b4cf695cc8efc760e560f","85ac664f085e4c48b49fb7d9a717aaed","b4cdc1bada1d4e40a2bb179be8f9f528","419ee8bfb6334bfaab29c179553fc723","1b7366105ca04ddaba7cc522494b3a4a","31cad4f443494f4bbf624dbe0f00129f","415430be381a4faf8bb699a5429d4d76","1046317543aa40518fd48635f6e82681","f4ae6f48c11648e69eb31d2845918fda","59b248f302ba44658e7f026eb2e939ce","bff60ab7072e46e890930b59b8ecc686","71793f00c8b64940a367090e7f5ae2f7","83ec544dfee24110b6ceba7d92bc376f","14371bfeda3a47bb8213b3485d0e948d","80e422e190904d18af849bc6db3f61b2","8e6732bf9ed143628d93f2d016041b5b","cf131f5c1ab848b6a1a10a75627f38e8","5d91a90708c54ac6832949735c540257","cc36b42d98e64e04bf512a55adb5ec98","caccd9a65ca04d7a800ae66dfc45f23a","71e8914f08374a6d8f3f463e9294690b","2814316024034683a4f3e3bb6ef8ee08","2ccfe7eb9741451fa03518c68f140c8a","5d426e14281345748f251feb6a595157","13211fb76dd449acb63689ca3c4f0e8c","5595c0b033e9485fa254f73ea39f8cee","17083c6ff4c0477aa9a97a0b173600fc","ac4e7133491e47cd93e8e1a09e10b13e","953dab331def4c5a93dd31e7c0cee48e","c68ed8ea08844d7394bb5b0179db0d99","f1a688e294f640048fbc683212bf8335","04ee68d8ebf247c8b25dc37e83b213d4","73abfebf7996453eb9424820e82fe40a","f2b666d197284e1ab19cfe9369d962a3","e93d44cd486442bba8c99b610f07c81b","b49d7b1b47974248aa21e82ec9770467","d6f9f123d66e4b25b4376bbcff1cf96d","f4937beb1974413f9ab6a25dc231182f","2e623cf11c17431aaac27633986d8bad","8546299a5a454ba382e235cefc8b3d62","7928a4786b35446ba445646f6212087b","681ac00c0cb04f0aa18a1dce332b643c","51ec51fb0b7149baa14d1c3cc794955e","6b1803a2665641f2a2e1394947e74d5c","a10f535ccb6b46e59ac957ca151d7443","40f4e6d8b3584541949fa9b147893008","dfbe228aab6148ce8a5c5324b8b58cfa","1cac0bf7858b4fdcbf377f5a241f14fc","2983f3c706dc40bba7da69de59b88a3d","a822941fd1114f7abde8c345f250e33d","b7bc6e5143834f47a6e128f0612dc495","b2b186aa85b5401e847d0460ea85dbd4"]},"id":"KsuvHtD5Z6vL","executionInfo":{"status":"ok","timestamp":1696090175523,"user_tz":-330,"elapsed":17677,"user":{"displayName":"Tahiyya Khan","userId":"02112400725815246626"}},"outputId":"799005ee-aafd-4a79-c633-30801fa069d5"},"execution_count":4,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading (…)okenizer_config.json:   0%|          | 0.00/79.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d9ec495836c64db79205865211b6dd68"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)lve/main/config.json:   0%|          | 0.00/571 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f4ae6f48c11648e69eb31d2845918fda"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/vocab.json:   0%|          | 0.00/899k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"caccd9a65ca04d7a800ae66dfc45f23a"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)olve/main/merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f1a688e294f640048fbc683212bf8335"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading (…)cial_tokens_map.json:   0%|          | 0.00/772 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"681ac00c0cb04f0aa18a1dce332b643c"}},"metadata":{}}]},{"cell_type":"code","source":["# Creating a \"question-answering\" Hugging Face pipeline\n","nlp = pipeline(\"question-answering\", model=model, tokenizer=tokenizer)\n","\n","# Sample test cases\n","context = '''My name is RP and I love working on the LLMs and Generative AI\n","and I live in Bangalore\n","'''\n","question = \"what is my name?\"\n","result = nlp(question = question, context=context)\n","result"],"metadata":{"id":"Pj2h27b7rp7G","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1696090335870,"user_tz":-330,"elapsed":3267,"user":{"displayName":"Tahiyya Khan","userId":"02112400725815246626"}},"outputId":"96df8075-110c-4c9d-c5a1-5f99bf246d2a"},"execution_count":8,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'score': 0.8393333554267883, 'start': 11, 'end': 13, 'answer': 'RP'}"]},"metadata":{},"execution_count":8}]},{"cell_type":"code","source":["question = \"what do I love?\"\n","result = nlp(question = question, context=context)\n","result"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"slcPJ-2N3J64","executionInfo":{"status":"ok","timestamp":1696090343584,"user_tz":-330,"elapsed":458,"user":{"displayName":"Tahiyya Khan","userId":"02112400725815246626"}},"outputId":"aa714a7a-33fc-4d19-f5f7-2287b3965ebb"},"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'score': 0.6185383200645447,\n"," 'start': 25,\n"," 'end': 62,\n"," 'answer': 'working on the LLMs and Generative AI'}"]},"metadata":{},"execution_count":9}]},{"cell_type":"markdown","source":["## Chatbot UI 1"],"metadata":{"id":"b2OeVrlCEGPE"}},{"cell_type":"code","source":["# Creating the function tp wrap in Gradio UI\n","def get_answer(context, question):\n","  \"\"\"\n","  Parameters:\n","  context: String containing the context given by user\n","  question: String containing the question asked by user\n","\n","  Returns: String of the answer to the parameter \"question\"\n","  \"\"\"\n","  result = nlp(question = question, context=context)\n","  return result['answer']\n","\n","# Creating the Gradio Chatbot Interface\n","app = gr.Interface(\n","    fn=get_answer,\n","    inputs = ['textbox', 'text'],\n","    outputs = 'textbox',\n","    title = \"Tahiyya Khan's Bot 🤖😊\",\n","    theme = gr.themes.Soft(),\n","    description = 'Provide your context and ask the Chatbot a question to get an answer!')\n","\n","# launching the Chatbot app\n","app.launch(inline=False,share = True)"],"metadata":{"id":"tusAarRidv-u","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1696093681298,"user_tz":-330,"elapsed":3647,"user":{"displayName":"Tahiyya Khan","userId":"02112400725815246626"}},"outputId":"5f669992-5099-446a-da38-13ed3dac9b2c"},"execution_count":42,"outputs":[{"output_type":"stream","name":"stdout","text":["Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n","Running on public URL: https://da79a1a3a465d0d4c2.gradio.live\n","\n","This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"]},{"output_type":"execute_result","data":{"text/plain":[]},"metadata":{},"execution_count":42}]},{"cell_type":"markdown","source":["### Output Screenshot"],"metadata":{"id":"dj8imewZEdqA"}},{"cell_type":"markdown","source":["![02.PNG](data:image/png;base64,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)"],"metadata":{"id":"2HoCviSuEJMY"}},{"cell_type":"markdown","source":["* I have generated a Gradio UI with Soft theme for my chatbot.\n","* I have included two input boxes, one each for context and question."],"metadata":{"id":"czaDfIaREX2i"}},{"cell_type":"markdown","source":["## Chatbot UI 2"],"metadata":{"id":"R9l8kwtAE5TG"}},{"cell_type":"code","source":["with gr.Blocks() as app:\n","    context = gr.Textbox(label=\"Context\")\n","    question = gr.Textbox(label=\"Question\")\n","    output = gr.Textbox(label=\"Answer\")\n","    greet_btn = gr.Button(\"Answer my question\")\n","    greet_btn.click(fn=get_answer, inputs=[context, question], outputs=output, api_name=\"answer\")\n","\n","# launching the Chatbot app\n","app.launch(inline=False,share = True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZdEzBoiK_2uP","executionInfo":{"status":"ok","timestamp":1696094099501,"user_tz":-330,"elapsed":6272,"user":{"displayName":"Tahiyya Khan","userId":"02112400725815246626"}},"outputId":"be575b3d-162c-48e4-81db-e895595102f0"},"execution_count":43,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'targets': [(312, 'click')],\n"," 'inputs': [309, 310],\n"," 'outputs': [311],\n"," 'backend_fn': True,\n"," 'js': None,\n"," 'queue': None,\n"," 'api_name': 'answer',\n"," 'scroll_to_output': False,\n"," 'show_progress': 'full',\n"," 'every': None,\n"," 'batch': False,\n"," 'max_batch_size': 4,\n"," 'cancels': [],\n"," 'types': {'continuous': False, 'generator': False},\n"," 'collects_event_data': False,\n"," 'trigger_after': None,\n"," 'trigger_only_on_success': False}"]},"metadata":{},"execution_count":43},{"output_type":"stream","name":"stdout","text":["Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n","Running on public URL: https://4f92cbb81688f60f35.gradio.live\n","\n","This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"]},{"output_type":"execute_result","data":{"text/plain":[]},"metadata":{},"execution_count":43}]},{"cell_type":"markdown","source":["### Output Screenshot"],"metadata":{"id":"rpFemsbZFUuV"}},{"cell_type":"markdown","source":["![01.PNG](data:image/png;base64,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)"],"metadata":{"id":"rxQRrcTnE8_P"}},{"cell_type":"markdown","source":["* I have generated a Gradio UI with the concept of Blocks for my next chatbot.\n","* I have included two input boxes, one each for context and question and an output box."],"metadata":{"id":"oQPZAfLIE9c4"}},{"cell_type":"code","source":["%%shell\n","jupyter nbconvert --to html Assignment2_Chatbot_with_LLM.ipynb"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"ylTUXpBzHJUo","executionInfo":{"status":"error","timestamp":1696094566311,"user_tz":-330,"elapsed":4439,"user":{"displayName":"Tahiyya Khan","userId":"02112400725815246626"}},"outputId":"2099beed-db0c-46b5-e49c-f07c0b9cc47b"},"execution_count":44,"outputs":[{"output_type":"stream","name":"stdout","text":["[NbConvertApp] Converting notebook Assignment2_Chatbot_with_LLM.ipynb to html\n","Traceback (most recent call last):\n","  File \"/usr/local/bin/jupyter-nbconvert\", line 8, in <module>\n","    sys.exit(main())\n","  File \"/usr/local/lib/python3.10/dist-packages/jupyter_core/application.py\", line 285, in launch_instance\n","    return super().launch_instance(argv=argv, **kwargs)\n","  File \"/usr/local/lib/python3.10/dist-packages/traitlets/config/application.py\", line 992, in launch_instance\n","    app.start()\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/nbconvertapp.py\", line 423, in start\n","    self.convert_notebooks()\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/nbconvertapp.py\", line 597, in convert_notebooks\n","    self.convert_single_notebook(notebook_filename)\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/nbconvertapp.py\", line 560, in convert_single_notebook\n","    output, resources = self.export_single_notebook(\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/nbconvertapp.py\", line 488, in export_single_notebook\n","    output, resources = self.exporter.from_filename(\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/exporters/exporter.py\", line 189, in from_filename\n","    return self.from_file(f, resources=resources, **kw)\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/exporters/exporter.py\", line 206, in from_file\n","    return self.from_notebook_node(\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/exporters/html.py\", line 223, in from_notebook_node\n","    return super().from_notebook_node(nb, resources, **kw)\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/exporters/templateexporter.py\", line 413, in from_notebook_node\n","    output = self.template.render(nb=nb_copy, resources=resources)\n","  File \"/usr/local/lib/python3.10/dist-packages/jinja2/environment.py\", line 1301, in render\n","    self.environment.handle_exception()\n","  File \"/usr/local/lib/python3.10/dist-packages/jinja2/environment.py\", line 936, in handle_exception\n","    raise rewrite_traceback_stack(source=source)\n","  File \"/usr/local/share/jupyter/nbconvert/templates/lab/index.html.j2\", line 3, in top-level template code\n","    {% from 'jupyter_widgets.html.j2' import jupyter_widgets %}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/lab/base.html.j2\", line 2, in top-level template code\n","    {% from 'celltags.j2' import celltags %}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/display_priority.j2\", line 1, in top-level template code\n","    {%- extends 'base/null.j2' -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 26, in top-level template code\n","    {%- block body -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 29, in block 'body'\n","    {%- block body_loop -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 31, in block 'body_loop'\n","    {%- block any_cell scoped -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 34, in block 'any_cell'\n","    {%- block codecell scoped -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/lab/base.html.j2\", line 12, in block 'codecell'\n","    {{ super() }}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 44, in block 'codecell'\n","    {%- block output_group -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/lab/base.html.j2\", line 38, in block 'output_group'\n","    {{ super() }}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 48, in block 'output_group'\n","    {%- block outputs scoped -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/lab/base.html.j2\", line 44, in block 'outputs'\n","    {{ super() }}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 50, in block 'outputs'\n","    {%- block output scoped -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/lab/base.html.j2\", line 87, in block 'output'\n","    {{ super() }}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 67, in block 'output'\n","    {%- block display_data scoped -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/null.j2\", line 68, in block 'display_data'\n","    {%- block data_priority scoped -%}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/lab/base.html.j2\", line 126, in block 'data_priority'\n","    {{ super() }}\n","  File \"/usr/local/share/jupyter/nbconvert/templates/base/display_priority.j2\", line 7, in block 'data_priority'\n","    {%- for type in output.data | filter_data_type -%}\n","  File \"/usr/local/lib/python3.10/dist-packages/nbconvert/filters/widgetsdatatypefilter.py\", line 57, in __call__\n","    metadata[\"widgets\"][WIDGET_STATE_MIMETYPE][\"state\"]\n","KeyError: 'state'\n"]},{"output_type":"error","ename":"CalledProcessError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mCalledProcessError\u001b[0m                        Traceback (most recent call last)","\u001b[0;32m<ipython-input-44-63be0cc1e1fe>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_cell_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'shell'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'jupyter nbconvert --to html Assignment2_Chatbot_with_LLM.ipynb\\n'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/google/colab/_shell.py\u001b[0m in \u001b[0;36mrun_cell_magic\u001b[0;34m(self, magic_name, line, cell)\u001b[0m\n\u001b[1;32m    332\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    333\u001b[0m       \u001b[0mcell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m' '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 334\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_cell_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmagic_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mline\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    335\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    336\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_cell_magic\u001b[0;34m(self, magic_name, line, cell)\u001b[0m\n\u001b[1;32m   2471\u001b[0m             \u001b[0;32mwith\u001b[0m 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137\u001b[0;31m       raise subprocess.CalledProcessError(\n\u001b[0m\u001b[1;32m    138\u001b[0m           \u001b[0mreturncode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreturncode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcmd\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    139\u001b[0m       )\n","\u001b[0;31mCalledProcessError\u001b[0m: Command 'jupyter nbconvert --to html Assignment2_Chatbot_with_LLM.ipynb\n' returned non-zero exit status 1."]}]},{"cell_type":"code","source":[],"metadata":{"id":"l4dwQLhCHSFv"},"execution_count":null,"outputs":[]}]}