import os
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_core.prompts import PromptTemplate
from langchain_core.output_parsers import StrOutputParser
import gradio as gr

# loading api key
os.environ["GOOGLE_API_KEY"] = os.environ.get("GOOGLE_API_KEY")

# loading model, here i am using Google model, because huggingFace model is not working for me, due to api issue.
model = ChatGoogleGenerativeAI(
    model="models/gemini-1.5-flash-latest",
    temperature=0.5
)

# Creating a simple template
template = PromptTemplate(
    template="Generate 5 interesting facts about {topic}",
    input_variables=["topic"]
)

parser = StrOutputParser()
chain = template | model | parser

# gradio code
def generate_facts(topic):
    try:
        return chain.invoke({'topic': topic})
    except Exception as e:
        return f"Error: {e}"

iface = gr.Interface(
    fn=generate_facts,
    inputs=gr.Textbox(label="Enter Topic"),
    outputs=gr.Textbox(label="5 Interesting Facts"),
    title="Fact Generator using Gemini"
)

if __name__ == "__main__":
    iface.launch()