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import gradio as gr
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin
def parse_links(prompt):
#anfrage ='fill in the missing contact information. do not reference the json object. do not use html tags inside the json object. it must be valid json. do not return explanaitons or any other text. thanks for your efforts:)'
try:
url = "http://specialist-it.de:3001/api/search"
payload = {
"chatModel": {
"provider": "groq",
"model": "mixtral-8x7b-32768"
},
"embeddingModel": {
"provider": "local",
"model": "xenova-bge-small-en-v1.5"
},
"optimizationMode": "balanced",
"focusMode": "webSearch",
"query": f"{prompt}. outputformat=json",
"history": [
["human", "Hi, how are you?"],
["assistant", "I am doing well, how can I help you today?"]
]
}
headers = {
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
# Parse the JSON response
#data = response.json()
# Extract the message
#ergebnis = data.get('message')
#return ergebnis
return response.json().get('message')
# Rückgabe als Dictionary, um es mit gr.JSON kompatibel zu machen
#return {"body_text": body_text}
except requests.RequestException as e:
return {"error": str(e)}
except Exception as e:
return {"error": str(e)}
# Erstelle die Gradio-Schnittstelle
with gr.Blocks() as demo:
gr.Markdown("# Perplexica WebSearch")
ort_input = gr.Textbox(label="Prompt", placeholder="prompt", value="contact details Aero Club Bamberg e.v.")
links_output = gr.Textbox(label="Antwort")
# Button zum Starten der Parsung
button = gr.Button("senden")
# Verbinde den Button mit der Funktion
button.click(fn=parse_links, inputs=ort_input, outputs=links_output)
demo.launch() |