import gradio as gr import requests import json import os import time from collections import defaultdict from PIL import Image import io BASE_URL = "https://api.jigsawstack.com/v1" headers = { "x-api-key": os.getenv("JIGSAWSTACK_API_KEY") } # Rate limiting configuration request_times = defaultdict(list) MAX_REQUESTS = 20 # Maximum requests per time window TIME_WINDOW = 3600 # Time window in seconds (1 hour) def get_real_ip(request: gr.Request): """Extract real IP address using x-forwarded-for header or fallback""" if not request: return "unknown" forwarded = request.headers.get("x-forwarded-for") if forwarded: ip = forwarded.split(",")[0].strip() # First IP in the list is the client's else: ip = request.client.host # fallback return ip def check_rate_limit(request: gr.Request): """Check if the current request exceeds rate limits""" if not request: return True, "Rate limit check failed - no request info" ip = get_real_ip(request) now = time.time() # Clean up old timestamps outside the time window request_times[ip] = [t for t in request_times[ip] if now - t < TIME_WINDOW] # Check if rate limit exceeded if len(request_times[ip]) >= MAX_REQUESTS: time_remaining = int(TIME_WINDOW - (now - request_times[ip][0])) time_remaining_minutes = round(time_remaining / 60, 1) time_window_minutes = round(TIME_WINDOW / 60, 1) return False, f"Rate limit exceeded. You can make {MAX_REQUESTS} requests per {time_window_minutes} minutes. Try again in {time_remaining_minutes} minutes." # Add current request timestamp request_times[ip].append(now) return True, "" # ----------------- JigsawStack API Wrappers ------------------ def web_ai_search(query, ai_overview, safe_search, spell_check, deep_research, max_depth, max_breadth, max_output_tokens, target_output_tokens, request: gr.Request): rate_limit_ok, rate_limit_msg = check_rate_limit(request) if not rate_limit_ok: return f"❌ {rate_limit_msg}", "", [], "" if not query or not query.strip(): return "❌ Please enter a search query.", "", [], "" payload = { "query": query.strip(), "ai_overview": ai_overview, "safe_search": safe_search, "spell_check": spell_check } if deep_research: payload["deep_research"] = True config = { "max_depth": max_depth if max_depth is not None else 3, "max_breadth": max_breadth if max_breadth is not None else 3, "max_output_tokens": max_output_tokens if max_output_tokens is not None else 32000 } if target_output_tokens is not None and target_output_tokens != "": config["target_output_tokens"] = target_output_tokens payload["deep_research_config"] = config try: response = requests.post(f"{BASE_URL}/web/search", headers=headers, json=payload) if response.status_code != 200: return f"❌ Error: {response.status_code} - {response.text}", "", [], "" result = response.json() if not result.get("success"): return "❌ Search failed.", "", [], "" status = "✅ Search successful!" overview = result.get("ai_overview", "") results = result.get("results", []) # Format results for display formatted_results = [] for r in results: title = r.get("title", "") url = r.get("url", "") snippet = r.get("snippet", "") formatted_results.append(f"{title}\n{url}\n{snippet}") raw_json = json.dumps(result, indent=2) return status, overview, formatted_results, raw_json except Exception as e: return f"❌ Error: {str(e)}", "", [], "" with gr.Blocks() as demo: gr.Markdown("""

🧩 AI Search

Effortlessly search the web and get high-quality results powered by AI.

For more details and API usage, see the documentation.

""") with gr.Row(): with gr.Column(): search_query = gr.Textbox(label="Search Query", placeholder="Type your search here...") ai_overview = gr.Checkbox(label="AI Overview", value=True) safe_search = gr.Dropdown(choices=["moderate", "strict", "off"], value="moderate", label="Safe Search") spell_check = gr.Checkbox(label="Spell Check", value=True) deep_research = gr.Checkbox(label="Deep Research", value=False) with gr.Group(visible=False) as deep_research_group: max_depth = gr.Number(label="Max Depth", value=3, precision=0) max_breadth = gr.Number(label="Max Breadth", value=3, precision=0) max_output_tokens = gr.Number(label="Max Output Tokens", value=32000, precision=0) target_output_tokens = gr.Number(label="Target Output Tokens (optional)", value=None, precision=0) search_btn = gr.Button("🔍 Search") search_clear_btn = gr.Button("Clear") with gr.Column(): search_status = gr.Textbox(label="Status", interactive=False) overview_box = gr.Textbox(label="AI Overview", lines=4, interactive=False) results_box = gr.Dataframe(headers=["Result"], label="Results", interactive=False) search_json_box = gr.Accordion("Raw JSON Response", open=False) with search_json_box: search_json_output = gr.Textbox(show_label=False, lines=20, interactive=False) def toggle_deep_research(checked): return {deep_research_group: gr.update(visible=checked)} deep_research.change(fn=toggle_deep_research, inputs=deep_research, outputs=deep_research_group) def on_search(query, overview, safe, spell, deep, d_depth, d_breadth, d_tokens, d_target, request: gr.Request): return web_ai_search(query, overview, safe, spell, deep, d_depth, d_breadth, d_tokens, d_target, request) search_btn.click(fn=on_search, inputs=[search_query, ai_overview, safe_search, spell_check, deep_research, max_depth, max_breadth, max_output_tokens, target_output_tokens], outputs=[search_status, overview_box, results_box, search_json_output]) def clear_search(): return "", "", [], "" search_clear_btn.click(fn=clear_search, inputs=[], outputs=[search_query, overview_box, results_box, search_json_output]) demo.launch()