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- "source": [
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- "!pip install langchain openai chromadb tiktoken pypdf panel"
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- "cell_type": "code",
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- "execution_count": null,
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i < js_modules.length; i++) {\n var url = js_modules[i];\n if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t on_load();\n\t}\n\tcontinue;\n }\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n element.type = \"module\";\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n if (!js_urls.length && !js_modules.length) {\n on_load()\n }\n };\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/bundled/quillinput/1.3.6/quill.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n var js_modules = [];\n var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/bundled/quillinput/1.3.6/quill.bubble.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/bundled/quillinput/1.3.6/quill.snow.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\"];\n var inline_js = [ function(Bokeh) {\n inject_raw_css(\"\\n .bk.pn-loading.arc:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n background-size: auto calc(min(50%, 400px));\\n }\\n \");\n }, function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n }\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, js_modules, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));",
121
- "application/vnd.holoviews_load.v0+json": ""
122
- },
123
- "metadata": {},
124
- "output_type": "display_data"
125
- },
126
- {
127
- "data": {
128
- "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n function JupyterCommManager() {\n }\n\n JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n comm_manager.register_target(comm_id, function(comm) {\n comm.on_msg(msg_handler);\n });\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n comm.onMsg = msg_handler;\n });\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n console.log(message)\n var content = {data: message.data, comm_id};\n var buffers = []\n for (var buffer of message.buffers || []) {\n buffers.push(new DataView(buffer))\n }\n var metadata = message.metadata || {};\n var msg = {content, buffers, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n })\n }\n }\n\n JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n if (comm_id in window.PyViz.comms) {\n return window.PyViz.comms[comm_id];\n } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n if (msg_handler) {\n comm.on_msg(msg_handler);\n }\n } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n comm.open();\n if (msg_handler) {\n comm.onMsg = msg_handler;\n }\n } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n var comm_promise = google.colab.kernel.comms.open(comm_id)\n comm_promise.then((comm) => {\n window.PyViz.comms[comm_id] = comm;\n if (msg_handler) {\n var messages = comm.messages[Symbol.asyncIterator]();\n function processIteratorResult(result) {\n var message = result.value;\n var content = {data: message.data};\n var metadata = message.metadata || {comm_id};\n var msg = {content, metadata}\n msg_handler(msg);\n return messages.next().then(processIteratorResult);\n }\n return messages.next().then(processIteratorResult);\n }\n }) \n var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n return comm_promise.then((comm) => {\n comm.send(data, metadata, buffers, disposeOnDone);\n });\n };\n var comm = {\n send: sendClosure\n };\n }\n window.PyViz.comms[comm_id] = comm;\n return comm;\n }\n window.PyViz.comm_manager = new JupyterCommManager();\n \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n var div = document.createElement(\"div\");\n var script = document.createElement(\"script\");\n node.appendChild(div);\n node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n var output_area = handle.output_area;\n var output = handle.output;\n if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n return\n }\n var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n if (id !== undefined) {\n var nchildren = toinsert.length;\n var html_node = toinsert[nchildren-1].children[0];\n html_node.innerHTML = output.data[HTML_MIME_TYPE];\n var scripts = [];\n var nodelist = html_node.querySelectorAll(\"script\");\n for (var i in nodelist) {\n if (nodelist.hasOwnProperty(i)) {\n scripts.push(nodelist[i])\n }\n }\n\n scripts.forEach( function (oldScript) {\n var newScript = document.createElement(\"script\");\n var attrs = [];\n var nodemap = oldScript.attributes;\n for (var j in nodemap) {\n if (nodemap.hasOwnProperty(j)) {\n attrs.push(nodemap[j])\n }\n }\n attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n oldScript.parentNode.replaceChild(newScript, oldScript);\n });\n if (JS_MIME_TYPE in output.data) {\n toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n }\n output_area._hv_plot_id = id;\n if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n window.PyViz.plot_index[id] = Bokeh.index[id];\n } else {\n window.PyViz.plot_index[id] = null;\n }\n } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n var bk_div = document.createElement(\"div\");\n bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n var script_attrs = bk_div.children[0].attributes;\n for (var i = 0; i < script_attrs.length; i++) {\n toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n }\n // store reference to server id on output_area\n output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n var id = handle.cell.output_area._hv_plot_id;\n var server_id = handle.cell.output_area._bokeh_server_id;\n if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n if (server_id !== null) {\n comm.send({event_type: 'server_delete', 'id': server_id});\n return;\n } else if (comm !== null) {\n comm.send({event_type: 'delete', 'id': id});\n }\n delete PyViz.plot_index[id];\n if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n var doc = window.Bokeh.index[id].model.document\n doc.clear();\n const i = window.Bokeh.documents.indexOf(doc);\n if (i > -1) {\n window.Bokeh.documents.splice(i, 1);\n }\n }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n delete PyViz.comms[\"hv-extension-comm\"];\n window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n handle_clear_output(event, {cell: {output_area: handle.output_area}})\n handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n function append_mime(data, metadata, element) {\n // create a DOM node to render to\n var toinsert = this.create_output_subarea(\n metadata,\n CLASS_NAME,\n EXEC_MIME_TYPE\n );\n this.keyboard_manager.register_events(toinsert);\n // Render to node\n var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n render(props, toinsert[0]);\n element.append(toinsert);\n return toinsert\n }\n\n events.on('output_added.OutputArea', handle_add_output);\n events.on('output_updated.OutputArea', handle_update_output);\n events.on('clear_output.CodeCell', handle_clear_output);\n events.on('delete.Cell', handle_clear_output);\n events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n safe: true,\n index: 0\n });\n}\n\nif (window.Jupyter !== undefined) {\n try {\n var events = require('base/js/events');\n var OutputArea = require('notebook/js/outputarea').OutputArea;\n if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n register_renderer(events, OutputArea);\n }\n } catch(err) {\n }\n}\n",
129
- "application/vnd.holoviews_load.v0+json": ""
130
- },
131
- "metadata": {},
132
- "output_type": "display_data"
133
- },
134
- {
135
- "data": {
136
- "text/html": [
137
- "<style>.bk-root, .bk-root .bk:before, .bk-root .bk:after {\n",
138
- " font-family: var(--jp-ui-font-size1);\n",
139
- " font-size: var(--jp-ui-font-size1);\n",
140
- " color: var(--jp-ui-font-color1);\n",
141
- "}\n",
142
- "</style>"
143
- ]
144
- },
145
- "metadata": {},
146
- "output_type": "display_data"
147
- }
148
- ],
149
- "source": [
150
- "import os \n",
151
- "from langchain.chains import RetrievalQA\n",
152
- "from langchain.llms import OpenAI\n",
153
- "from langchain.document_loaders import TextLoader\n",
154
- "from langchain.document_loaders import PyPDFLoader\n",
155
- "from langchain.indexes import VectorstoreIndexCreator\n",
156
- "from langchain.text_splitter import CharacterTextSplitter\n",
157
- "from langchain.embeddings import OpenAIEmbeddings\n",
158
- "from langchain.vectorstores import Chroma\n",
159
- "import panel as pn\n",
160
- "import tempfile"
161
- ]
162
- },
163
- {
164
- "cell_type": "code",
165
- "execution_count": null,
166
- "id": "9d891458",
167
- "metadata": {},
168
- "outputs": [],
169
- "source": [
170
- "pn.extension('texteditor', template=\"bootstrap\", sizing_mode='stretch_width')\n",
171
- "pn.state.template.param.update(\n",
172
- " main_max_width=\"690px\",\n",
173
- " header_background=\"#F08080\",\n",
174
- ")"
175
- ]
176
- },
177
- {
178
- "cell_type": "code",
179
- "execution_count": 3,
180
- "id": "fcd48f62",
181
- "metadata": {},
182
- "outputs": [],
183
- "source": [
184
- "file_input = pn.widgets.FileInput(width=300)\n",
185
- "\n",
186
- "openaikey = pn.widgets.PasswordInput(\n",
187
- " value=\"\", placeholder=\"Enter your OpenAI API Key here...\", width=300\n",
188
- ")\n",
189
- "prompt = pn.widgets.TextEditor(\n",
190
- " value=\"\", placeholder=\"Enter your questions here...\", height=160, toolbar=False\n",
191
- ")\n",
192
- "run_button = pn.widgets.Button(name=\"Run!\")\n",
193
- "\n",
194
- "select_k = pn.widgets.IntSlider(\n",
195
- " name=\"Number of relevant chunks\", start=1, end=5, step=1, value=2\n",
196
- ")\n",
197
- "select_chain_type = pn.widgets.RadioButtonGroup(\n",
198
- " name='Chain type', \n",
199
- " options=['stuff', 'map_reduce', \"refine\", \"map_rerank\"]\n",
200
- ")\n",
201
- "\n",
202
- "widgets = pn.Row(\n",
203
- " pn.Column(prompt, run_button, margin=5),\n",
204
- " pn.Card(\n",
205
- " \"Chain type:\",\n",
206
- " pn.Column(select_chain_type, select_k),\n",
207
- " title=\"Advanced settings\", margin=10\n",
208
- " ), width=600\n",
209
- ")"
210
- ]
211
- },
212
- {
213
- "cell_type": "code",
214
- "execution_count": 4,
215
- "id": "dd7114ba",
216
- "metadata": {},
217
- "outputs": [],
218
- "source": [
219
- "def qa(file, query, chain_type, k):\n",
220
- " # load document\n",
221
- " loader = PyPDFLoader(file)\n",
222
- " documents = loader.load()\n",
223
- " # split the documents into chunks\n",
224
- " text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
225
- " texts = text_splitter.split_documents(documents)\n",
226
- " # select which embeddings we want to use\n",
227
- " embeddings = OpenAIEmbeddings()\n",
228
- " # create the vectorestore to use as the index\n",
229
- " db = Chroma.from_documents(texts, embeddings)\n",
230
- " # expose this index in a retriever interface\n",
231
- " retriever = db.as_retriever(search_type=\"similarity\", search_kwargs={\"k\": k})\n",
232
- " # create a chain to answer questions \n",
233
- " qa = RetrievalQA.from_chain_type(\n",
234
- " llm=OpenAI(), chain_type=chain_type, retriever=retriever, return_source_documents=True)\n",
235
- " result = qa({\"query\": query})\n",
236
- " print(result['result'])\n",
237
- " return result"
238
- ]
239
- },
240
- {
241
- "cell_type": "code",
242
- "execution_count": 6,
243
- "id": "8ef4ae70",
244
- "metadata": {},
245
- "outputs": [],
246
- "source": [
247
- "convos = [] # store all panel objects in a list\n",
248
- "\n",
249
- "def qa_result(_):\n",
250
- " os.environ[\"OPENAI_API_KEY\"] = openaikey.value\n",
251
- " \n",
252
- " # save pdf file to a temp file \n",
253
- " if file_input.value is not None:\n",
254
- " file_input.save(\"/.cache/temp.pdf\")\n",
255
- " \n",
256
- " prompt_text = prompt.value\n",
257
- " if prompt_text:\n",
258
- " result = qa(file=\"/.cache/temp.pdf\", query=prompt_text, chain_type=select_chain_type.value, k=select_k.value)\n",
259
- " convos.extend([\n",
260
- " pn.Row(\n",
261
- " pn.panel(\"\\U0001F60A\", width=10),\n",
262
- " prompt_text,\n",
263
- " width=600\n",
264
- " ),\n",
265
- " pn.Row(\n",
266
- " pn.panel(\"\\U0001F916\", width=10),\n",
267
- " pn.Column(\n",
268
- " result[\"result\"],\n",
269
- " \"Relevant source text:\",\n",
270
- " pn.pane.Markdown('\\n--------------------------------------------------------------------\\n'.join(doc.page_content for doc in result[\"source_documents\"]))\n",
271
- " )\n",
272
- " )\n",
273
- " ])\n",
274
- " #return convos\n",
275
- " return pn.Column(*convos, margin=15, width=575, min_height=400)"
276
- ]
277
- },
278
- {
279
- "cell_type": "code",
280
- "execution_count": 7,
281
- "id": "6a682e65",
282
- "metadata": {
283
- "scrolled": true
284
- },
285
- "outputs": [],
286
- "source": [
287
- "qa_interactive = pn.panel(\n",
288
- " pn.bind(qa_result, run_button),\n",
289
- " loading_indicator=True,\n",
290
- ")"
291
- ]
292
- },
293
- {
294
- "cell_type": "code",
295
- "execution_count": 8,
296
- "id": "4258f908",
297
- "metadata": {},
298
- "outputs": [],
299
- "source": [
300
- "output = pn.WidgetBox('*Output will show up here:*', qa_interactive, width=630, scroll=True)"
301
- ]
302
- },
303
- {
304
- "cell_type": "code",
305
- "execution_count": 9,
306
- "id": "42a031d1",
307
- "metadata": {
308
- "scrolled": true
309
- },
310
- "outputs": [
311
- {
312
- "data": {},
313
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326
- " var render_items = [{\"docid\":\"d0252f16-7a5e-460a-82c3-6b7db2f9af2a\",\"root_ids\":[\"1005\"],\"roots\":{\"1005\":\"c2b6d391-2418-4059-a838-b20218c1be11\"}}];\n",
327
- " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
328
- " for (const render_item of render_items) {\n",
329
- " for (const root_id of render_item.root_ids) {\n",
330
- "\tconst id_el = document.getElementById(root_id)\n",
331
- "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
332
- "\t const root_el = id_el.children[0]\n",
333
- "\t root_el.id = root_el.id + '-rendered'\n",
334
- "\t}\n",
335
- " }\n",
336
- " }\n",
337
- " }\n",
338
- " if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined) {\n",
339
- " embed_document(root);\n",
340
- " } else {\n",
341
- " var attempts = 0;\n",
342
- " var timer = setInterval(function(root) {\n",
343
- " if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined) {\n",
344
- " clearInterval(timer);\n",
345
- " embed_document(root);\n",
346
- " } else if (document.readyState == \"complete\") {\n",
347
- " attempts++;\n",
348
- " if (attempts > 200) {\n",
349
- " clearInterval(timer);\n",
350
- " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
351
- " }\n",
352
- " }\n",
353
- " }, 25, root)\n",
354
- " }\n",
355
- "})(window);</script>"
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- ],
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- "text/plain": [
358
- "Column(sizing_mode='stretch_width')\n",
359
- " [0] Markdown(str, sizing_mode='stretch_width')\n",
360
- " [1] Row(sizing_mode='stretch_width')\n",
361
- " [0] FileInput(width=300)\n",
362
- " [1] PasswordInput(placeholder='Enter your OpenAI A..., width=300)\n",
363
- " [2] WidgetBox(scroll=True, width=630)\n",
364
- " [0] Markdown(str, sizing_mode='stretch_width')\n",
365
- " [1] ParamFunction(function, _pane=Column, loading_indicator=True, sizing_mode='stretch_width')\n",
366
- " [3] Row(width=600)\n",
367
- " [0] Column(margin=5, sizing_mode='stretch_width')\n",
368
- " [0] TextEditor(height=160, placeholder='Enter your questions h..., sizing_mode='stretch_width', toolbar=False)\n",
369
- " [1] Button(name='Run!', sizing_mode='stretch_width')\n",
370
- " [1] Card(margin=10, sizing_mode='stretch_width', title='Advanced settings')\n",
371
- " [0] Column(sizing_mode='stretch_width')\n",
372
- " [0] Markdown(str, sizing_mode='stretch_width')\n",
373
- " [1] RadioButtonGroup(name='Chain type', options=['stuff', 'map_reduce', ...], sizing_mode='stretch_width', value='stuff')\n",
374
- " [2] IntSlider(end=5, name='Number of relevant c..., sizing_mode='stretch_width', start=1, value=2)"
375
- ]
376
- },
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- "execution_count": 9,
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- "application/vnd.holoviews_exec.v0+json": {
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- "id": "1005"
381
- }
382
- },
383
- "output_type": "execute_result"
384
- }
385
- ],
386
- "source": [
387
- "# layout\n",
388
- "pn.Column(\n",
389
- " pn.pane.Markdown(\"\"\"\n",
390
- " ## \\U0001F60A! Question Answering with your PDF file\n",
391
- " \n",
392
- " 1) Upload a PDF. 2) Enter OpenAI API key. This costs $. Set up billing at [OpenAI](https://platform.openai.com/account). 3) Type a question and click \"Run\".\n",
393
- " \n",
394
- " \"\"\"),\n",
395
- " pn.Row(file_input,openaikey),\n",
396
- " output,\n",
397
- " widgets\n",
398
- "\n",
399
- ").servable()"
400
- ]
401
- }
402
- ],
403
- "metadata": {
404
- "kernelspec": {
405
- "display_name": "Python 3 (ipykernel)",
406
- "language": "python",
407
- "name": "python3"
408
- },
409
- "language_info": {
410
- "codemirror_mode": {
411
- "name": "ipython",
412
- "version": 3
413
- },
414
- "file_extension": ".py",
415
- "mimetype": "text/x-python",
416
- "name": "python",
417
- "nbconvert_exporter": "python",
418
- "pygments_lexer": "ipython3",
419
- "version": "3.10.10"
420
- }
421
- },
422
- "nbformat": 4,
423
- "nbformat_minor": 5
424
- }