Spaces:
Runtime error
Runtime error
File size: 29,209 Bytes
d3ba590 cae655c d3ba590 77aba26 d3ba590 77aba26 d3ba590 cae655c d3ba590 |
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 |
import datetime
import hmac
import os
import uuid
import openai
import requests
import streamlit as st
from azure.cosmos import ContainerProxy, CosmosClient
from bs4 import BeautifulSoup, NavigableString
from dotenv import load_dotenv
from st_copy_to_clipboard import st_copy_to_clipboard
load_dotenv()
def get_related_studies(article: str):
with st.spinner("Extrahiere Studien..."):
url = f'https://serpapi.com/search.json?engine=google_scholar&api_key={os.getenv("SERP_API_KEY")}&as_ylo=2018&q='
url += extract_scholar_query(article).replace('"', "")
try:
response = requests.get(url)
if response.status_code == 200:
data = response.json()
if data.get("organic_results"):
results = []
for result in data["organic_results"]:
if not result.get("title"):
continue
if not result.get("link"):
continue
results.append(
{
"title": result["title"],
"link": result["link"],
}
)
st.session_state["studie_links"] = results
else:
st.session_state["studie_links"] = []
else:
st.session_state["studie_links"] = []
except Exception as e:
print(f"Fehler beim extrahieren der Studien: {str(e)}")
st.error(f"Something went wrong: {str(e)}", icon="🚨")
def get_takeaways(article : str):
openai.api_key = os.environ.get("OPEN_API_KEY")
openai.api_base = os.environ.get("OPEN_API_BASE")
openai.api_type = os.environ.get("OPEN_API_TYPE")
openai.api_version = os.environ.get("OPEN_API_VERSION")
takeaway_query = os.environ.get("takeaway")
with st.spinner("Creating Takeaways"):
try:
res = openai.ChatCompletion.create(
engine="gpt-4-1106",
temperature=0.2,
messages=[
{
"role": "system",
"content": f" The article you have written is as follows: {article}.",
}
],
)
st.session_state["takeaways"] = res["choices"][0]["message"]["content"]
except Exception as e:
print(f"Fehler beim extrahieren der Query: {str(e)}")
st.error(f"Something went wrong: {str(e)}", icon="🚨")
def get_faq(article : str):
openai.api_key = os.environ.get("OPEN_API_KEY")
openai.api_base = os.environ.get("OPEN_API_BASE")
openai.api_type = os.environ.get("OPEN_API_TYPE")
openai.api_version = os.environ.get("OPEN_API_VERSION")
faq_query = os.environ.get("faq")
with st.spinner("Creating FAQ"):
try:
res = openai.ChatCompletion.create(
engine="gpt-4-1106",
temperature=0.2,
messages=[
{
"role": "system",
"content": f" The article you have written is as follows: {article}.",
}
],
)
st.session_state["faq"] = res["choices"][0]["message"]["content"]
except Exception as e:
print(f"Fehler beim extrahieren der Query: {str(e)}")
st.error(f"Something went wrong: {str(e)}", icon="🚨")
def extract_scholar_query(article: str):
openai.api_key = os.environ.get("OPEN_API_KEY")
openai.api_base = os.environ.get("OPEN_API_BASE")
openai.api_type = os.environ.get("OPEN_API_TYPE")
openai.api_version = os.environ.get("OPEN_API_VERSION")
try:
res = openai.ChatCompletion.create(
engine="gpt-4-1106",
temperature=0.2,
messages=[
{
"role": "system",
"content": f"You are a professional journalist whose task is to find related studies based on an article you have written. Please write a query that you would use to search for related studies on Google Scholar. Please make sure that the query is specific enough and cotains a maximum of 4 words. Only include one query in your output. Do not write multiple querys with an AND or OR. The article you have written is as follows: {article}.",
}
],
)
return res["choices"][0]["message"]["content"]
except Exception as e:
print(f"Fehler beim extrahieren der Query: {str(e)}")
st.error(f"Something went wrong: {str(e)}", icon="🚨")
return ""
def create_article(length_option, articles, params, web_page_option):
if length_option == "Kurz":
length = os.environ.get("SHORT_LENGTH")
elif length_option == "Mittel":
length = os.environ.get("MEDIUM_LENGTH")
elif length_option == "Lang":
length = os.environ.get("LONG_LENGTH")
elif length_option == "SEO":
length = os.environ.get("SEO_LENGTH")
elif length_option == "SEO Plus":
length = os.environ.get("SEO_PLUS_LENGTH")
openai.api_key = os.environ.get("OPEN_API_KEY")
openai.api_base = os.environ.get("OPEN_API_BASE")
openai.api_type = os.environ.get("OPEN_API_TYPE")
openai.api_version = os.environ.get("OPEN_API_VERSION")
if web_page_option == "Boulevard":
writing_style = os.environ.get("WRITING_STYLE_HEUTE")
elif web_page_option == "Health Blog":
writing_style = os.environ.get("WRITING_STYLE_GESUND")
elif web_page_option == "Newspaper":
writing_style = os.environ.get("WRITING_STYLE_NEWSPAPER")
elif web_page_option == "Tech/Lifestyle Blog":
writing_style = os.environ.get("WRITING_STYLE_TECH_BLOG")
elif web_page_option == "Public Relations":
writing_style = os.environ.get("WRITING_STYLE_PR")
elif web_page_option == "Sales":
writing_style = os.environ.get("WRITING_STYLE_SALES")
elif web_page_option == "Lifestyle Blog":
writing_style = os.environ.get("WRITING_STYLE_LIFESTYLE")
try:
if len(articles) > 0:
article_string = "; ".join(
f"Artikel {index + 1}: {artikel}"
for index, artikel in enumerate(articles)
)
messages = [
{
"role": "system",
"content": f"You are a professional journalist whose task is to write your own article based on one or more articles. This article should combine the content of the original articles, but have its own writing style, which is as follows: {writing_style} Do not use unusual phrases or neologisms from the original articles.",
},
{"role": "system", "content": f"Source articles: {article_string}"},
{
"role": "system",
"content": f"Please also note the following instructions defined by the user: {params}",
},
{
"role": "system",
"content": f" It is very important that the length of your article you generate should be {length} words long."
}
{
"role": "system",
"content": "Schreibe den Artikel immer in deutscher Sprache.",
},
]
else:
messages = [
{
"role": "system",
"content": f"You are a professional journalist whose task is to write an article based on your own notes. This article should be written in the following writing style: {writing_style} .It is important that the length of your article should be {length} words long.",
},
{
"role": "system",
"content": f"Please write the article based on the following user input: {params}",
},
{
"role": "system",
"content": "Schreibe den Artikel immer in deutscher Sprache.",
},
]
res = openai.ChatCompletion.create(
engine="gpt-35-16k",
temperature=0.4,
max_tokens=8000,
messages=messages,
)
return res["choices"][0]["message"]["content"]
except Exception as e:
print(f"Fehler beim erstellen des artikels: {str(e)}")
st.error(f"Something went wrong: {str(e)}", icon="🚨")
def create_headline(article, web_page_option):
openai.api_key = os.environ.get("OPEN_API_KEY")
openai.api_base = os.environ.get("OPEN_API_BASE")
openai.api_type = os.environ.get("OPEN_API_TYPE")
openai.api_version = os.environ.get("OPEN_API_VERSION")
if web_page_option == "Boulevard":
writing_style = os.environ.get("WRITING_STYLE_HEUTE")
else:
writing_style = os.environ.get("WRITING_STYLE_GESUND")
try:
res = openai.ChatCompletion.create(
engine="gpt-4-1106",
temperature=0.4,
messages=[
{
"role": "system",
"content": f"You are a professional journalist and have the task of generating a headline for an article you have written. I will give you the writing style that was used to create the article as info. Writing style: {writing_style} The headline should be as short as possible, but still capture the essence of the article. It should be a maximum of 10 words long",
},
{"role": "system", "content": f"Source article: {article}"},
{
"role": "system",
"content": "Schreibe die Headline immer in deutscher Sprache.",
},
],
)
return res["choices"][0]["message"]["content"]
except Exception as e:
print(f"Fehler beim erstellen der headline: {str(e)}")
st.error(f"Something went wrong: {str(e)}", icon="🚨")
def extract_text_from_element(element):
# Initialisiere einen leeren Textstring
text_content = ""
# Überprüfe, ob das Element ein <p>, <ul> oder <ol>-Tag ist
if element.name in ["p", "ul", "ol"]:
# Extrahiere den Text des Tags und füge ihn zum Textstring hinzu
text_content += element.get_text() + "\n"
# Überprüfe, ob das Element ein Tag mit Kindern ist (kein Textknoten)
if not isinstance(element, NavigableString):
# Rekursiv durch jedes Child-Element gehen und den Text hinzufügen
for child in element.children:
text_content += extract_text_from_element(child)
return text_content
def get_article_summary(article: str) -> str:
try:
response = requests.post(
os.environ.get("SUMMARY_API"),
headers={
"Content-Type": "application/json",
"Authorization": os.environ.get("SUMMARY_API_KEY"),
"azureml-model-deployment": "heute-summary-api",
},
data={"article": article},
)
response.raise_for_status()
return response.json()["summary"]
except Exception as e:
print(f"Fehler beim erstellen der Zusammenfassung: {str(e)}")
return ""
def extract_article(url):
# Webseite herunterladen
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'
}
response = requests.get(url, headers=headers)
# Überprüfen, ob die Anfrage erfolgreich war (Status-Code 200)
if response.status_code == 200:
# HTML-Inhalt parsen
soup = BeautifulSoup(response.text, "html.parser")
# Finden Sie das <article>-Tag (nehmen Sie an, dass es eins gibt)
article_tag = soup.find("article")
if article_tag:
# Starte die Rekursion für jedes Child-Element des <article>-Tags
extracted_text = extract_text_from_element(article_tag)
stripped_text = filter_empty_lines(extracted_text)
return stripped_text
else:
print("Kein <article>-Tag gefunden.")
return None
else:
# Falls die Anfrage nicht erfolgreich war, eine Fehlermeldung ausgeben
print(f"Fehler: {response.status_code}")
return None
def filter_empty_lines(text):
# Teile den Text in Zeilen auf
lines = text.split("\n")
# Filtere leere Zeilen heraus
non_empty_lines = filter(lambda line: line.strip() != "", lines)
# Verbinde die nicht leeren Zeilen zu einem String
filtered_text = "\n".join(non_empty_lines)
return filtered_text
def extract_article_links(**kwargs):
# print(len(kwargs["links"]))
with st.spinner("Extrahiere..."):
results = []
for link in kwargs["links"]:
results.append(extract_article(link))
st.session_state["extracted_articles"] = results
if st.session_state["process_step"] < 1:
st.session_state["process_step"] += 1
st.session_state["selected_page"] = 1
def extract_article_links_for_heading(**kwargs):
article = extract_article(kwargs["link"])
def finalize_articles():
final_articles = []
for i in range(len(st.session_state["extracted_articles"])):
final_articles.append(st.session_state["final_article_" + str(i + 1)])
st.session_state["final_articles"] = final_articles
if st.session_state["process_step"] < 2:
st.session_state["process_step"] += 1
st.session_state["selected_page"] += 1
def increase_page():
if st.session_state["selected_page"] <= st.session_state["process_step"]:
st.session_state["selected_page"] += 1
def decrease_page():
if st.session_state["selected_page"] > 0:
st.session_state["selected_page"] -= 1
def on_click_handler_generate_article(**kwargs):
with st.spinner("Generiere Artikel..."):
created_article = create_article(
kwargs["length_option"],
kwargs["final_articles"],
kwargs["add_info"],
kwargs["webpage_option"],
)
headline = create_headline(created_article, kwargs["webpage_option"])
db_analytics_item = {
"id": str(uuid.uuid4()),
"oparation": "article_generation",
"timestamp": str(datetime.datetime.now()),
}
client: ContainerProxy = st.session_state["db_container"]
client.create_item(body=db_analytics_item)
st.session_state["generated_article"] = created_article
st.session_state["generated_headline"] = headline
st.session_state["article_summary"] = get_article_summary(created_article)
if st.session_state["process_step"] < 3:
st.session_state["process_step"] += 1
st.session_state["selected_page"] += 1
def on_click_handler_generate_generate_article_keywords(**kwargs):
with st.spinner("Generiere Artikel..."):
created_article = create_article(
kwargs["length_option"],
"",
kwargs["artikel_input"],
kwargs["webpage_option"],
)
headline = create_headline(created_article, kwargs["webpage_option"])
summary = get_article_summary(created_article)
db_analytics_item = {
"id": str(uuid.uuid4()),
"oparation": "article_generation",
"timestamp": str(datetime.datetime.now()),
}
client: ContainerProxy = st.session_state["db_container"]
client.create_item(body=db_analytics_item)
st.session_state["generated_article"] = created_article
st.session_state["generated_headline"] = headline
st.session_state["article_summary"] = summary
def reset_session_state():
st.session_state["extracted_articles"] = []
st.session_state["article_links"] = []
st.session_state["final_articles"] = []
st.session_state["process_step"] = 0
st.session_state["selected_page"] = 0
st.session_state["generated_article"] = ""
st.session_state["studie_links"] = []
st.session_state["article_summary"] = ""
if "extracted_articles" not in st.session_state:
st.session_state["extracted_articles"] = []
if "article_links" not in st.session_state:
st.session_state["article_links"] = []
if "final_articles" not in st.session_state:
st.session_state["final_articles"] = []
if "process_step" not in st.session_state:
st.session_state["process_step"] = 0
if "selected_page" not in st.session_state:
st.session_state["selected_page"] = 0
if "generated_article" not in st.session_state:
st.session_state["generated_article"] = ""
if "function_state" not in st.session_state:
st.session_state["function_state"] = True
if "generated_headline" not in st.session_state:
st.session_state["generated_headline"] = ""
if "webpage_option" not in st.session_state:
st.session_state["webpage_option"] = "Boulevard"
if "studie_links" not in st.session_state:
st.session_state["studie_links"] = []
if "db_container" not in st.session_state:
client = (
CosmosClient(os.environ["DB_ENDPOINT"], os.environ["DB_KEY"])
.get_database_client(os.environ["DB_NAME"])
.get_container_client("tina-analytics")
)
db_analytics_item = {
"id": str(uuid.uuid4()),
"oparation": "page_load",
"timestamp": str(datetime.datetime.now()),
}
client.create_item(body=db_analytics_item)
st.session_state["db_container"] = client
if "article_summary" not in st.session_state:
st.session_state["article_summary"] = ""
PROCESS_STEPS = [
"Artikel Extraktion",
"Artikel Finalisierung",
"Artikel Generierung",
"Artikel Ausgabe",
]
# def check_password():
# """Returns `True` if the user had the correct password."""
# def password_entered():
# """Checks whether a password entered by the user is correct."""
# if hmac.compare_digest(
# st.session_state["password"], os.environ.get("PASSWORD")
# ):
# st.session_state["password_correct"] = True
# del st.session_state["password"] # Don't store the password.
# else:
# st.session_state["password_correct"] = False
# # Return True if the password is validated.
# if st.session_state.get("password_correct", False):
# return True
# # Show input for password.
# st.text_input(
# "Password", type="password", on_change=password_entered, key="password"
# )
# if "password_correct" in st.session_state:
# st.error("😕 Password incorrect")
# return False
# if not check_password():
# st.stop() # Do not continue if check_password is not True.
col1, col2 = st.columns([2, 1])
col1.title("TINA")
col2.image("tensora_logo.png")
st.radio(
"Wähle den Schreibstil für Artikel aus",
[
"Boulevard",
"Health Blog",
"Newspaper",
"Tech/Lifestyle Blog",
"Public Relations",
"Sales",
"Lifestyle Blog",
],
key="webpage_option",
)
with st.sidebar:
st.title("Funktions Auswahl")
st.write("Hier kannst Du zwischen der Art der Artikelgenerierung wählen.")
st.button(
"Artikel Generierung mit Links",
key="article_gen_btn",
use_container_width=True,
on_click=lambda: st.session_state.update({"function_state": True}),
)
st.button(
"Artikel Generierung mit Stichpunkten",
key="headline_gen_btn",
use_container_width=True,
on_click=lambda: st.session_state.update({"function_state": False}),
)
if st.session_state["function_state"]:
tab_col1, tab_col2, tab_col3, tab_col4 = st.columns([1, 1, 1, 1])
tab_col1.button(
"Artikel Extraktion",
key="tab1",
use_container_width=True,
on_click=lambda: st.session_state.update({"selected_page": 0}),
disabled=st.session_state["selected_page"] == 0,
)
tab_col2.button(
"Artikel Finalisierung",
key="tab2",
use_container_width=True,
on_click=lambda: st.session_state.update({"selected_page": 1}),
disabled=st.session_state["process_step"] < 1
or st.session_state["selected_page"] == 1,
)
tab_col3.button(
"Artikel Generierung",
key="tab3",
use_container_width=True,
on_click=lambda: st.session_state.update({"selected_page": 2}),
disabled=st.session_state["process_step"] < 2
or st.session_state["selected_page"] == 2,
)
tab_col4.button(
"Artikel Ausgabe",
key="tab4",
use_container_width=True,
on_click=lambda: st.session_state.update({"selected_page": 3}),
disabled=st.session_state["process_step"] < 3
or st.session_state["selected_page"] == 3,
)
nav_col1, nav_col2, nav_col3 = st.columns([1, 4, 1])
nav_col1.button(
"◀️",
key="nav1",
use_container_width=True,
on_click=decrease_page,
disabled=st.session_state["selected_page"] == 0,
)
nav_col2.markdown(
f"<div style='text-align: center;'>{PROCESS_STEPS[st.session_state['selected_page']]}</div>",
unsafe_allow_html=True,
)
nav_col3.button(
"▶️",
key="nav2",
use_container_width=True,
on_click=increase_page,
disabled=st.session_state["selected_page"] == st.session_state["process_step"],
)
if st.session_state["selected_page"] == 0:
st.write(
"Bitte gebe die Links der Artikel ein, welche Du extrahiert haben möchtest."
)
st.text_input(
"Gebe den "
+ str(len(st.session_state["article_links"]) + 1)
+ ". Link ein:",
key="link_input_" + str(len(st.session_state["article_links"]) + 1),
)
if st.session_state[
"link_input_" + str(len(st.session_state["article_links"]) + 1)
]:
st.session_state["article_links"].append(
st.session_state[
"link_input_" + str(len(st.session_state["article_links"]) + 1)
]
)
st.rerun()
for i in range(len(st.session_state["article_links"])):
st.write(f"Link nr. {i+1}:\n\n{st.session_state['article_links'][i]}")
if len(st.session_state["article_links"]) > 0:
try:
st.button(
"Extrahiere Artikel",
on_click=extract_article_links,
kwargs={"links": st.session_state["article_links"]},
)
except Exception as e:
print(f"Fehler beim extrahieren der artikel: {str(e)}")
st.error(
f"Du hast einen oder mehrere Links nicht in dem korrekten Format angegeben. Bitte Lade die Seite neu und benutze korrekte Links: {str(e)}",
icon="🚨",
)
elif st.session_state["selected_page"] == 1:
st.write(
"Hier kannst Du die extrahierten Artikel ansehen und bei Bedarf anpassen."
)
for i, article in enumerate(st.session_state["extracted_articles"]):
with st.expander(f"Artikel {i+1}"):
if article:
st.text_area(
"Editiere die Artikel, falls nötig:",
value=article,
key="final_article_" + str(i + 1),
height=500,
)
else:
st.info(
"Die Webseite des Artikels blockiert das automatische extrahieren von Artikeln. Wenn Du den Artikel dennoch benutzen möchtest, dann kannst Du diesen kopieren und einfügen.",
icon="ℹ️",
)
st.text_area(
"Füge den Artikel ein, falls nötig:",
value=article,
key="final_article_" + str(i + 1),
height=500,
)
st.button("Artikel finalisieren", on_click=finalize_articles)
elif st.session_state["selected_page"] == 2:
for i in range(len(st.session_state["final_articles"])):
if st.session_state["final_articles"][i]:
with st.expander("Artikel " + str(i + 1)):
st.write(st.session_state["final_articles"][i])
if len(st.session_state["final_articles"]) > 0:
st.write("Benutzte Artikel:")
for i, link in enumerate(st.session_state["article_links"]):
st.write(f"Link {i+1}: {link}")
st.text_area(
"Füge weitere Informationen für den Prompt hinzu, falls nötig:",
key="add_info",
)
st.write("Artikellänge")
st.radio("Optionen", ["Kurz", "Mittel", "Lang", "SEO", "SEO Plus"], key="length_option")
st.button(
"Artikel generieren",
key="article_btn",
on_click=on_click_handler_generate_article,
kwargs={
"length_option": st.session_state["length_option"],
"final_articles": st.session_state["final_articles"],
"add_info": st.session_state["add_info"],
"webpage_option": st.session_state["webpage_option"],
},
)
elif st.session_state["selected_page"] == 3:
st.write(f"**{st.session_state['generated_headline']}**")
st.write(st.session_state["generated_article"])
st.write("**Zusammenfassung:**")
st.write(st.session_state["article_summary"])
st.write("Kopieren Sie den Artikel: ")
st_copy_to_clipboard(
st.session_state["generated_headline"]
+ "\n"
+ st.session_state["generated_article"]
)
if st.session_state["studie_links"]:
st.write("Hier sind einige Studien, die relevant sein könnten:")
for result in st.session_state["studie_links"]:
st.write(f"- [{result['title']}]({result['link']})")
else:
st.write("Keine relevanten Studien gefunden.")
if "takeaways" in st.session_state:
st.write("Hier sind einige Takeaways die wichtig sein könnten:")
st.write(st.session_state["takeaways"])
if "faq" in st.session_state:
st.write("Hier sind FAQs zu dem Artikel:")
st.write(st.session_state["faq"])
st.button(
"Relevante Studien finden",
on_click=get_related_studies,
args=(st.session_state["generated_article"],),
)
st.button("Key Takeaways generieren", on_click=lambda: get_takeaways(st.session_state["generated_article"]))
st.button("FAQ generieren", on_click=lambda: get_faq(st.session_state["generated_article"]))
st.button(
"Neuen Artikel generieren", key="reset_btn", on_click=reset_session_state
)
else:
st.write(
"Bitte trage die Stichpunkte ein, die Du in den Artikel einbauen möchtest. Der Textinput ist essenziell für die Generierung des Artikels."
)
st.text_area(label="Artikel input:", key="keyword_article_input")
st.write("Artikellänge")
st.radio("Optionen", ["Kurz", "Mittel", "Lang", "SEO", "SEO Plus"], key="length_option")
st.button(
"Artikel generieren",
key="article_btn",
on_click=on_click_handler_generate_generate_article_keywords,
kwargs={
"length_option": st.session_state["length_option"],
"artikel_input": st.session_state["keyword_article_input"],
"webpage_option": st.session_state["webpage_option"],
},
)
if st.session_state["generated_article"] and st.session_state["generated_headline"]:
st.write(f"**{st.session_state['generated_headline']}**")
st.write(st.session_state["generated_article"])
st.write("**Zusammenfassung:**")
st.write(st.session_state["article_summary"])
st.write("Kopieren Sie den Artikel: ")
st_copy_to_clipboard(
st.session_state["generated_headline"]
+ "\n"
+ st.session_state["generated_article"]
)
if st.session_state["studie_links"]:
st.write("Hier sind einige Studien, die relevant sein könnten:")
for result in st.session_state["studie_links"]:
st.write(f"- [{result['title']}]({result['link']})")
# else:
# st.write("Keine relevanten Studien gefunden.")
st.button(
"Relevante Studien finden",
on_click=get_related_studies,
args=(st.session_state["generated_article"],),
)
st.button(
"Neuen Artikel generieren", key="reset_btn", on_click=reset_session_state
)
|