Update app.py

app.py

@@ -1,227 +1,52 @@
 import gradio as gr
 import requests
-from bs4 import BeautifulSoup
-from urllib.parse import urljoin
 import os
 import json
-import pandas as pd
-from io import StringIO
 import google.generativeai as genai
 
 # Load environment variables
 genai.configure(api_key=os.environ["geminiapikey"])
-api_key = os.environ.get('GROQ_API_KEY')
 read_key = os.environ.get('HF_TOKEN', None)
 
-# Initialize Groq client
-if api_key:
-    from groq import Client as GroqClient
-    client = GroqClient(api_key=api_key)
-else:
-    client = None
-
-# Use Llama 3 70B powered by Groq for answering
-def ask_llm(ort):
-    if not client:
-        return "Groq API key not set."
+custom_css = ".md{height:450px}"
+
+def predict(prompt):
+    # Create the model
+    generation_config = {
+        "temperature": 1,
+        "top_p": 0.95,
+        "top_k": 40,
+        "max_output_tokens": 8192,
+        "response_mime_type": "text/plain",
+    }
+
+    model = genai.GenerativeModel(
+        model_name="gemini-2.0-flash-exp",
+        generation_config=generation_config,
+    )
+
+    chat_session = model.start_chat(
+        history=[
+        ]
+    )
     
-    try:
-        completion = client.chat.completions.create(
-            model="llama3-70b-8192",
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant."},
-                {"role": "user", "content": f"{ort}. \n instruction: antworte kurz und knapp. antworte immer auf deutsch"}
-            ],
-        )
-        return completion.choices[0].message.content
-    except Exception as e:
-        return f"Error in response generation: {str(e)}"
-
-def parse_links_and_content(ort):
-    base_url = "https://vereine-in-deutschland.net"
-    all_links = []
-    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:
-                links = [urljoin(base_url, a['href']) for a in target_div.find_all('a', href=True)]
-                texts = [a.text for a in target_div.find_all('a', href=True)]
-                all_links.extend(links)
-                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 = all_links[0::2]
-    all_links_text = all_links_text[0::2]
-
-    return all_links_text, all_links
-
-def extract_vereinsname(url):
-    parts = url.split('/')
-    vereinsname = parts[-1]
-    vereinsname = vereinsname.replace("-", " ")
-    return vereinsname
-
-def scrape_links(links):
-    details = []
-    for link in links:
-        try:
-            response = requests.get(link)
-            response.raise_for_status()
-            soup = BeautifulSoup(response.content, 'html.parser')
-            target_nav = soup.select_one('.nav')
-            parts = link.split('/')
-            
-            # Log the URL and its parts for debugging
-            print(f"Processing URL: {link}")
-            print(f"URL parts: {parts}")
-            
-            # Extract the name of the Verein from the URL
-            vereinsname = parts[-1] if parts[-1] else parts[-2]  # Fallback to the second-to-last part if the last part is empty
-            texte = target_nav.text.strip()
-            texte = texte.replace("Amtsgericht: Schweinfurt", "")
-            texte = texte.replace("Adresse folgt", "")
-            texte = texte.replace("Adresse", "Adresse:")
-            texte = texte.replace("Kontakt", "Email:")
-            texte = texte.replace("Noch keine Daten vorhanden", "")
-
-            if target_nav:
-                details.append(f"Verein: {vereinsname} {texte}")
-            else:
-                details.append(f"Verein: {vereinsname} - No contact information found")
-        except Exception as e:
-            details.append(f"Error: {str(e)}")
-
-    return details
-
-def save_to_csv(data, filename):
-    keys = data[0].keys() if data else []
-    with open(filename, 'w', newline='', encoding='utf-8') as output_file:
-        dict_writer = csv.DictWriter(output_file, fieldnames=keys)
-        dict_writer.writeheader()
-        dict_writer.writerows(data)
-
-# Clear output
-def clear():
-    return "", ""
-
-def load_data():
-    return df
+    response = chat_session.send_message(prompt)   
+    return response.text
 
 # Create the Gradio interface
-with gr.Blocks() as demo:
-    gr.Markdown("[Download](https://specialist-it.de/verein.csv)")
+with gr.Blocks(css=custom_css) as demo:
     with gr.Row():
-        ort_input = gr.Textbox(label="Ort", placeholder="Gib den Namen des Ortes ein")
+        ort_input = gr.Textbox(label="prompt", placeholder="Gib den Namen des Ortes ein")
     with gr.Row():
-        details_output = gr.Markdown(label="Ausgabe",)        
+        details_output = gr.Markdown(label="answer",elem_id="md")        
         #details_output = gr.Textbox(label="Ausgabe", value = f"\n\n\n\n")
-
-    def process_ort(ort):
-        links_text, links = parse_links_and_content(ort)
-        #return links_text
-        kontakt = []
-
-        # Create the model
-        generation_config = {
-          "temperature": 1,
-          "top_p": 0.95,
-          "top_k": 40,
-          "max_output_tokens": 8192,
-          "response_mime_type": "text/plain",
-        }
-
-        model = genai.GenerativeModel(
-          model_name="gemini-2.0-flash-exp",
-          generation_config=generation_config,
-        )
-
-        chat_session = model.start_chat(
-          history=[
-          ]
-        )
-
-         
-        json_schema ='{"vereinsname": "", "email": "", "adresse": "","telefon": ""}'
-        response = chat_session.send_message(f"return a valid json object with contact details for each verein \n {links_text}")
-        #response.text = response.text.replace("```json", "")
-        #response.text = response.text.replace("```", "")
-        #kontakt.append(response.text)
-            
-        return response.text
-        
-        for verein in links_text:
-            json_schema ='{"vereinsname": "", "email": "", "adresse": "","telefon": ""}'
-            response = chat_session.send_message(f"return a valid json object with kontakdaten für {verein}. here is the json schema: {json_schema}")
-            #response.text = response.text.replace("```json", "")
-            #response.text = response.text.replace("```", "")
-            kontakt.append(response.text)
-            
-        return kontakt
-        
-        contact_details = scrape_links(links)
         
-        from gradio_client import Client
-        
-
-        qwen_client = Client("Qwen/Qwen2.5-72B-Instruct")
-        result = qwen_client.predict(
-            query=f"return a valid json objects with contact details foreach verein. return the generated json only \n {contact_details}",
-            history=[],
-            system="you are a expert for json data and your job is to extract information from text and return a valid json object only. no text no explanations. reverse all email adresses. example: reverse ed.nesuahsgnitle-vs@dnatsrov to [email protected]. replace all dashes from vereinsname with a whitespace",     
-            api_name="/model_chat"
-        )
-
-        json_data = result[1][0][1]
-        json_data = json_data.replace("```json", "")
-        json_data = json_data.replace("```", "")
-        
-        # Convert JSON string to Python dictionary
-        data_dict = json.loads(json_data)
-
-        # Convert dictionary to DataFrame
-        df = pd.DataFrame(data_dict)
-        # DataFrame in eine CSV-Datei konvertieren
-        #df.to_csv('daten.csv', index=False)
-        # DataFrame in eine CSV-Variable konvertieren
-        csv_buffer = StringIO()
-        df.to_csv(csv_buffer, index=False)
-        csv_data = csv_buffer.getvalue()
-
-        print(csv_data)
-        #return csv_data
-        return df
-
     with gr.Row():
         clearbutton = gr.Button("Clear")  
         button = gr.Button("Senden")    
 
     # Connect the button to the function
-    button.click(fn=process_ort, inputs=ort_input, outputs=details_output)
+    button.click(fn=predict, inputs=ort_input, outputs=details_output)
     clearbutton.click(fn=clear, inputs=[], outputs=details_output)
 
 # Launch the Gradio application