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import os
import httpx
from dotenv import load_dotenv
import gradio as gr
from phi.agent import Agent
from phi.model.groq import Groq
from phi.storage.agent.postgres import PgAgentStorage
from phi.knowledge.pdf import PDFUrlKnowledgeBase
from phi.vectordb.pgvector import PgVector, SearchType
from phi.embedder.google import GeminiEmbedder
# Load environment variables
load_dotenv()
os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")
# HTTP client
client = httpx.Client(timeout=httpx.Timeout(60.0))
# Database connection
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai?connect_timeout=60"
# Gradio processing function
def summarize_pdf(pdf_url):
try:
# Set up the knowledge base
knowledge_base = PDFUrlKnowledgeBase(
urls=[pdf_url],
vector_db=PgVector(
table_name="recipies1",
db_url=db_url,
embedder=GeminiEmbedder(dimensions=768),
search_type=SearchType.hybrid,
)
)
# Load and upsert the knowledge base
knowledge_base.load(recreate=True, upsert=True)
# Set up storage and agent
storage = PgAgentStorage(table_name="pdf-assistant1", db_url=db_url)
agent = Agent(
model=Groq(id="llama-3.3-70b-versatile"),
knowledge=knowledge_base,
storage=storage,
)
# Generate summary
response = agent.run("Summarize the document within 5000 tokens!")
return response.content
except Exception as e:
return f"An error occurred: {e}"
# Gradio interface
iface = gr.Interface(
fn=summarize_pdf,
inputs=gr.Textbox(
label="PDF URL",
placeholder="Enter the URL of a PDF document...",
lines=1
),
outputs=gr.Textbox(
label="Output Summary",
placeholder="The summary will appear here...",
lines=15
),
examples=[
["https://www.joghat.org/uploads/2024-vol-7-issue-1-full-text-405.pdf"]
],
description="Enter a PDF URL to generate a concise summary of the document.",
title="PDF Summarizer"
)
# Launch the interface
iface.launch(share=True, debug=True)
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