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import gradio as gr | |
import requests | |
from bs4 import BeautifulSoup | |
from gradio_client import Client | |
from urllib.parse import urljoin | |
import pandas as pd | |
from io import StringIO | |
import json | |
import groq | |
import os | |
google_api_key = os.getenv('google_search') | |
API_URL = "https://blavken-flowiseblav.hf.space/api/v1/prediction/fbc118dc-ec00-4b59-acff-600648958be3" | |
api_key = os.getenv('groq') | |
client = groq.Client(api_key=api_key) | |
custom_css = """ | |
#md { | |
height: 200px; | |
font-size: 30px; | |
background: #121212; | |
padding: 20px; | |
color: white; | |
border: 1 px solid white; | |
font-size:10px; | |
} | |
""" | |
def perplexica_search(payloads): | |
client = Client("mgokg/PerplexicaApi") | |
result = client.predict( | |
prompt=f"{payloads}", | |
optimization_mode="balanced", | |
api_name="/question" | |
) | |
return result | |
def query(payload): | |
response = requests.post(API_URL, json=payload) | |
return response.json() | |
def google_search(payloads): | |
output = query({ | |
"question": f"{payloads}", | |
}) | |
#search_query = f"{payloads} antworte kurz und knapp. antworte auf deutsch. du findest die antwort hier:\n {output}" | |
texte="" | |
for o in output: | |
texte +=o | |
return output | |
scheme = """ | |
{"name":"","email":"","website":""} | |
""" | |
def llama(messages): | |
client = Client("mgokg/selenium-screenshot-gradio") | |
result = client.predict( | |
message=f"{messages}", | |
api_name="/predict" | |
) | |
return result | |
client = Client("AiActivity/AI-Assistant") | |
result = client.predict( | |
message={"text":f"instruction: return a valid json object only, no comments or explanaition, fill in the missing information. use this json scheme.\n {scheme}\n leave blank if information is not verfügbar. here is the information for the values:\n{message}","files":[]}, | |
api_name="/chat" | |
) | |
print(result) | |
def llm(message): | |
message = f'return a json object with the keys: name,email,phone,website \n the values can be found here, leave blank if value is not available:\n {message} \n return a json object only. no text, no explanaition' | |
try: | |
completion = client.chat.completions.create( | |
model="llama3-70b-8192", | |
messages=[ | |
{"role": "system", "content": "You are a helpful assistant."}, | |
{"role": "user", "content": f"{message}"} | |
], | |
) | |
return completion.choices[0].message.content | |
except Exception as e: | |
return f"Error in response generation: {str(e)}" | |
def qwen(jsondata): | |
client = Client("Qwen/Qwen2.5-72B-Instruct") | |
result = client.predict( | |
query= f'return a json object with the keys: name,email,phone,website for each verein \n the values can be found here, leave blank if value is not available:\n {jsondata} \n return a json object only. no text, no explanaition', | |
history=[], | |
system="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.", | |
api_name="/model_chat" | |
) | |
return result | |
def list_of_clubs(ort): | |
base_url = "https://vereine-in-deutschland.net" | |
all_links_text = [] | |
initial_url = f"{base_url}/vereine/Bayern/{ort}" | |
try: | |
response = requests.get(initial_url) | |
response.raise_for_status() | |
soup = BeautifulSoup(response.content, 'html.parser') | |
# Determine the last page | |
link_element = soup.select_one('li.page-item:nth-child(8) > a:nth-child(1)') | |
last_page = 10 | |
if link_element and 'href' in link_element.attrs: | |
href = link_element['href'] | |
last_page = int(href.split('/')[-1]) | |
# Loop through all pages and collect links | |
for page_number in range(1, last_page + 1): | |
page_url = f"{base_url}/vereine/Bayern/{ort}/p/{page_number}" | |
response = requests.get(page_url) | |
response.raise_for_status() | |
soup = BeautifulSoup(response.content, 'html.parser') | |
target_div = soup.select_one('div.row-cols-1:nth-child(4)') | |
if target_div: | |
texts = [a.text for a in target_div.find_all('a', href=True)] | |
all_links_text.extend(texts) | |
else: | |
print(f"Target div not found on page {page_number}") | |
except Exception as e: | |
return str(e), [] | |
all_links_text = all_links_text[0::2] | |
return all_links_text | |
def process_ort(ort): | |
links_text = list_of_clubs(ort) | |
#return links_text | |
vereine = [] | |
for verein in links_text: | |
prompt=f"{verein}", | |
result = llama(prompt) | |
vereine.append(result) | |
print(result) | |
#data = json.loads(vereine) | |
#df = pd.DataFrame(vereine) | |
return vereine | |
for verein in links_text: | |
client = Client("mgokg/gemini-2.0-flash-exp") | |
result = client.predict( | |
prompt=f"impressum {verein}", | |
api_name="/perform_search" | |
) | |
#json_object = llm(result) | |
""" | |
headers = { | |
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" | |
} | |
url = f"https://www.google.com/search?q=impressum {verein}" | |
response = requests.get(url, headers=headers) | |
soup = BeautifulSoup(response.content, 'html.parser') | |
impressum_div = soup.find('body') | |
contact_detailes = impressum_div.text | |
json_object = llm(contact_detailes) | |
""" | |
vereine.append(result) | |
#dicts = [json.loads(item) for item in vereine] | |
#df = pd.DataFrame(dicts) | |
#return df | |
return vereine | |
# Create the Gradio interface | |
with gr.Blocks(css=custom_css) as demo: | |
with gr.Row(): | |
#details_output = gr.DataFrame(label="Ausgabe", elem_id="md") | |
details_output = gr.Textbox(label="Ausgabe") | |
with gr.Row(): | |
ort_input = gr.Textbox(label="Ort eingeben", placeholder="ask anything...") | |
with gr.Row(): | |
button = gr.Button("Senden") | |
# Connect the button to the function | |
button.click(fn=process_ort, inputs=ort_input, outputs=details_output) | |
# Launch the Gradio application | |
demo.launch() | |