ISE / app.py
fikird
Complete rewrite of ISE with advanced RAG and OSINT capabilities
48922fa
"""
Intelligent Search Engine with RAG and OSINT capabilities.
"""
import os
import asyncio
import gradio as gr
from engines.search import SearchEngine
from engines.osint import OSINTEngine
from engines.image import ImageEngine
import markdown2
from typing import Dict, Any, List
# Initialize engines
search_engine = SearchEngine()
osint_engine = OSINTEngine()
image_engine = ImageEngine()
def format_search_results(results: Dict[str, Any]) -> str:
"""Format search results with markdown."""
if not results or "answer" not in results:
return "No results found."
formatted = f"### Answer\n{results['answer']}\n\n"
if results.get("sources"):
formatted += "\n### Sources\n"
for i, source in enumerate(results["sources"], 1):
formatted += f"{i}. [{source}]({source})\n"
return formatted
def format_osint_results(results: Dict[str, Any]) -> str:
"""Format OSINT results with markdown."""
formatted = "### OSINT Results\n\n"
if "error" in results:
return f"Error: {results['error']}"
if "found_on" in results:
formatted += "#### Social Media Presence\n"
for platform in results["found_on"]:
formatted += f"- {platform['platform']}: [{platform['url']}]({platform['url']})\n"
if "person_info" in results:
person = results["person_info"]
formatted += f"\n#### Personal Information\n"
formatted += f"- Name: {person.get('name', 'N/A')}\n"
if person.get("age"):
formatted += f"- Age: {person['age']}\n"
if person.get("location"):
formatted += f"- Location: {person['location']}\n"
if person.get("gender"):
formatted += f"- Gender: {person['gender']}\n"
return formatted
async def search_query(query: str) -> str:
"""Handle search queries."""
try:
results = await search_engine.search(query)
return format_search_results(results)
except Exception as e:
return f"Error: {str(e)}"
async def search_username(username: str) -> str:
"""Search for username across platforms."""
try:
results = await osint_engine.search_username(username)
return format_osint_results(results)
except Exception as e:
return f"Error: {str(e)}"
async def search_person(name: str, location: str = "", age: str = "", gender: str = "") -> str:
"""Search for person information."""
try:
age_int = int(age) if age.strip() else None
person = await osint_engine.search_person(
name=name,
location=location if location.strip() else None,
age=age_int,
gender=gender if gender.strip() else None
)
return format_osint_results({"person_info": person.to_dict()})
except Exception as e:
return f"Error: {str(e)}"
async def analyze_image_file(image) -> str:
"""Analyze uploaded image."""
try:
if not image:
return "No image provided."
# Read image data
with open(image.name, "rb") as f:
image_data = f.read()
# Analyze image
results = await image_engine.analyze_image(image_data)
if "error" in results:
return f"Error analyzing image: {results['error']}"
# Format results
formatted = "### Image Analysis Results\n\n"
# Add predictions
formatted += "#### Content Detection\n"
for pred in results["predictions"]:
confidence = pred["confidence"] * 100
formatted += f"- {pred['label']}: {confidence:.1f}%\n"
# Add face detection results
formatted += f"\n#### Face Detection\n"
formatted += f"- Found {len(results['faces'])} faces\n"
# Add metadata
formatted += f"\n#### Image Metadata\n"
metadata = results["metadata"]
formatted += f"- Size: {metadata['width']}x{metadata['height']}\n"
formatted += f"- Format: {metadata['format']}\n"
formatted += f"- Mode: {metadata['mode']}\n"
return formatted
except Exception as e:
return f"Error: {str(e)}"
def create_ui() -> gr.Blocks:
"""Create the Gradio interface."""
with gr.Blocks(title="Intelligent Search Engine", theme=gr.themes.Soft()) as app:
gr.Markdown("""
# πŸ” Intelligent Search Engine
Advanced search engine with RAG and OSINT capabilities.
""")
with gr.Tabs():
# Intelligent Search Tab
with gr.Tab("🌐 Search"):
with gr.Column():
search_input = gr.Textbox(
label="Enter your search query",
placeholder="What would you like to know?"
)
search_button = gr.Button("Search", variant="primary")
search_output = gr.Markdown(label="Results")
search_button.click(
fn=search_query,
inputs=search_input,
outputs=search_output
)
# Username Search Tab
with gr.Tab("πŸ‘€ Username Search"):
with gr.Column():
username_input = gr.Textbox(
label="Enter username",
placeholder="Username to search across platforms"
)
username_button = gr.Button("Search Username", variant="primary")
username_output = gr.Markdown(label="Results")
username_button.click(
fn=search_username,
inputs=username_input,
outputs=username_output
)
# Person Search Tab
with gr.Tab("πŸ‘₯ Person Search"):
with gr.Column():
name_input = gr.Textbox(
label="Full Name",
placeholder="Enter person's name"
)
location_input = gr.Textbox(
label="Location (optional)",
placeholder="City, Country"
)
age_input = gr.Textbox(
label="Age (optional)",
placeholder="Enter age"
)
gender_input = gr.Dropdown(
label="Gender (optional)",
choices=["", "Male", "Female", "Other"]
)
person_button = gr.Button("Search Person", variant="primary")
person_output = gr.Markdown(label="Results")
person_button.click(
fn=search_person,
inputs=[name_input, location_input, age_input, gender_input],
outputs=person_output
)
# Image Analysis Tab
with gr.Tab("πŸ–ΌοΈ Image Analysis"):
with gr.Column():
image_input = gr.File(
label="Upload Image",
file_types=["image"]
)
image_button = gr.Button("Analyze Image", variant="primary")
image_output = gr.Markdown(label="Results")
image_button.click(
fn=analyze_image_file,
inputs=image_input,
outputs=image_output
)
gr.Markdown("""
### πŸ“ Notes
- The search engine uses RAG (Retrieval-Augmented Generation) for intelligent answers
- OSINT capabilities include social media presence, personal information, and image analysis
- All searches are conducted using publicly available information
""")
return app
if __name__ == "__main__":
app = create_ui()
app.launch(share=True)