app.py

import gradio as gr
from langchain import PromptTemplate, OpenAI, LLMChain
from langchain.chains import RetrievalAugmentedGenerationChain
from langchain.tools import GoogleCustomSearchAPIWrapper
from groq import GroqClient

# Initialize Groq client
groq_client = GroqClient(api_key='your_groq_api_key')

# Define function to extract keywords using Groq
def extract_keywords(query):
    response = groq_client.keywords(query)
    keywords = response['keywords']
    return keywords

# Define function to search on noticiasjuridicas.es
def search_noticiasjuridicas(keywords):
    search_query = "site:www.noticiasjuridicas.es " + " ".join(keywords)
    search_tool = GoogleCustomSearchAPIWrapper(api_key="your_google_api_key", search_engine_id="your_search_engine_id")
    results = search_tool(search_query)
    return results

# Define function to generate response using retrieved context
def generate_response(query, context):
    template = """Based on the following information:
    {context}
    
    Here is the response to your query:
    {query}
    
    Response:
    """
    prompt_template = PromptTemplate(template=template, input_variables=["context", "query"])
    llm = OpenAI(model="gpt-4", api_key="your_openai_api_key")
    chain = LLMChain(prompt=prompt_template, llm=llm)
    response = chain.run({"context": context, "query": query})
    return response

# Define the main function for the chatbot
def chatbot(query):
    keywords = extract_keywords(query)
    search_results = search_noticiasjuridicas(keywords)
    context = "\n".join([result['snippet'] for result in search_results['items']])
    response = generate_response(query, context)
    return response

# Create Gradio interface
iface = gr.Interface(
    fn=chatbot,
    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your legal query here..."),
    outputs="text",
    title="Legal Assistant Chatbot",
    description="Ask any legal questions and get answers based on the latest information from noticiasjuridicas.es"
)

# Launch the interface
iface.launch()