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Browse files- 4_lab4.ipynb +7 -15
- app.py +8 -1
4_lab4.ipynb
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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{
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" if text:\n",
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" linkedin += text\n",
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"\n",
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"
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"resume = \"\"\n",
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"for page in
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" text = page.extract_text()\n",
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" if text:\n",
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" resume += text\n",
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:
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"* To create a public link, set `share=True` in `launch()`.\n"
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]
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"data": {
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"text/html": [
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"<div><iframe src=\"http://127.0.0.1:
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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"data": {
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"text/plain": []
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"execution_count":
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"metadata": {},
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"output_type": "execute_result"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Tool called: record_user_details\n",
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"Push: Recording interest from Jen with email [email protected] and notes Interested in getting in touch.\n"
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]
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}
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],
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"source": [
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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" if text:\n",
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" linkedin += text\n",
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"\n",
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"reader2 = PdfReader(\"me/resume.pdf\")\n",
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"resume = \"\"\n",
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"for page in reader2.pages:\n",
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" text = page.extract_text()\n",
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" if text:\n",
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" resume += text\n",
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},
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:7862\n",
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"* To create a public link, set `share=True` in `launch()`.\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div><iframe src=\"http://127.0.0.1:7862/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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"data": {
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"text/plain": []
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"execution_count": 22,
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"metadata": {},
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"output_type": "execute_result"
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"source": [
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app.py
CHANGED
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from dotenv import load_dotenv
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from openai import OpenAI
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import json
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def __init__(self):
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self.openai = OpenAI()
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self.name = "
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reader = PdfReader("me/linkedin.pdf")
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self.linkedin = ""
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for page in reader.pages:
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text = page.extract_text()
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if text:
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self.linkedin += text
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with open("me/summary.txt", "r", encoding="utf-8") as f:
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self.summary = f.read()
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from dotenv import load_dotenv
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from openai import OpenAI
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import json
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def __init__(self):
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self.openai = OpenAI()
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self.name = "Filipa Lobão"
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reader = PdfReader("me/linkedin.pdf")
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self.linkedin = ""
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for page in reader.pages:
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text = page.extract_text()
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if text:
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self.linkedin += text
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reader2 = PdfReader("me/resume.pdf")
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self.resume = ""
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for page in reader2.pages:
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text = page.extract_text()
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if text:
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self.resume += text
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with open("me/summary.txt", "r", encoding="utf-8") as f:
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self.summary = f.read()
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