diff --git a/assets/css/style.css b/assets/css/style.css index dac9004..dcfd38a 100644 --- a/assets/css/style.css +++ b/assets/css/style.css @@ -22,17 +22,13 @@ } body { - font-family: var(--font-family); + margin: 0; + padding: 0; + background: var(--bg-gradient); color: var(--text-color); - background: linear-gradient(rgba(0, 0, 0, 0.4), rgba(0, 0, 0, 0.4)), url("https://assets.science.nasa.gov/dynamicimage/assets/science/esd/multimedia/images-of-change/FestiveFields_NC_20141019_after_2048px-95.jpg") no-repeat center center fixed; - background-size: cover; - background-position: center; - background-attachment: fixed; - display: flex; - justify-content: center; - align-items: center; + font-family: 'Segoe UI', 'Apple Color Emoji', 'Segoe UI Emoji', 'Noto Color Emoji', Tahoma, Geneva, Verdana, sans-serif; min-height: 100vh; - position: relative; + overflow-x: hidden; } .overlay { @@ -403,6 +399,7 @@ body { transform: translateX(-50%); width: 90%; max-width: 600px; + z-index: 100; z-index: 5; } @@ -457,6 +454,194 @@ body { width: 20px; } +/* Location & NASA Data Indicator Styles */ +/* Clean Location Display Styles */ +.location-status-container { + display: flex; + justify-content: center; + align-items: center; + margin-bottom: 12px; +} + +.location-display { + display: flex; + align-items: center; + gap: 8px; + background: rgba(255, 255, 255, 0.05); + padding: 8px 16px; + border-radius: 25px; + border: 1px solid rgba(255, 255, 255, 0.1); + backdrop-filter: blur(15px); + transition: all 0.3s ease; + position: relative; +} + +.location-display:hover { + background: rgba(255, 255, 255, 0.08); + border-color: rgba(255, 255, 255, 0.2); + transform: translateY(-1px); + box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1); +} + +.location-text { + font-size: 0.9em; + font-weight: 500; + color: #e0e0e0; + transition: color 0.3s ease; +} + +.location-text.nasa-enabled { + color: #2ecc71; + text-shadow: 0 0 10px rgba(46, 204, 113, 0.3); +} + +.location-text.location-detected { + color: #3498db; +} + +.change-location-btn { + background: none; + border: none; + color: #bdc3c7; + cursor: pointer; + padding: 4px; + border-radius: 50%; + transition: all 0.3s ease; + display: flex; + align-items: center; + justify-content: center; +} + +.change-location-btn:hover { + background: rgba(255, 255, 255, 0.1); + color: #ecf0f1; + transform: scale(1.1); +} + +.change-location-btn.nasa-enabled { + color: #2ecc71; +} + +.change-location-btn.location-detected { + color: #3498db; +} + +/* Clean Location Picker Dropdown */ +.location-picker { + position: absolute; + top: 100%; + left: 50%; + transform: translateX(-50%); + margin-top: 8px; + background: var(--container-bg); + border-radius: 15px; + box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2); + border: 1px solid rgba(255, 255, 255, 0.1); + backdrop-filter: blur(20px); + z-index: 1000; + min-width: 250px; + overflow: hidden; + animation: slideDown 0.3s ease; +} + +@keyframes slideDown { + from { + opacity: 0; + transform: translateX(-50%) translateY(-10px); + } + to { + opacity: 1; + transform: translateX(-50%) translateY(0); + } +} + +.location-picker-header { + display: flex; + justify-content: space-between; + align-items: center; + padding: 12px 16px; + background: rgba(46, 204, 113, 0.1); + border-bottom: 1px solid rgba(255, 255, 255, 0.1); + font-size: 0.9em; + font-weight: 600; + color: #2ecc71; +} + +.close-btn { + background: none; + border: none; + color: #95a5a6; + cursor: pointer; + font-size: 1.2em; + padding: 0; + width: 20px; + height: 20px; + display: flex; + align-items: center; + justify-content: center; + transition: color 0.3s ease; +} + +.close-btn:hover { + color: #e74c3c; +} + +.location-options { + padding: 8px 0; +} + +.location-option { + width: 100%; + padding: 12px 16px; + background: none; + border: none; + color: var(--text-color); + font-size: 0.9em; + cursor: pointer; + text-align: left; + transition: all 0.2s ease; + display: flex; + align-items: center; + gap: 8px; +} + +.location-option:hover { + background: rgba(46, 204, 113, 0.1); + color: #2ecc71; +} + +.location-option:active { + background: rgba(46, 204, 113, 0.2); +} + +/* Clean notification animations */ +@keyframes slideIn { + from { + transform: translateY(-20px); + opacity: 0; + } + to { + transform: translateY(0); + opacity: 1; + } +} + +@keyframes slideOut { + from { + transform: translateY(0); + opacity: 1; + } + to { + transform: translateY(-20px); + opacity: 0; + } +} + +/* Click outside to close location picker */ +.location-status-container { + position: relative; +} + /* Hide scrollbar for Chrome, Safari and Opera */ .container::-webkit-scrollbar { display: none; diff --git a/assets/js/script.js b/assets/js/script.js index a0bdf64..d3594f3 100644 --- a/assets/js/script.js +++ b/assets/js/script.js @@ -1,5 +1,11 @@ var isVoice = 0; var isVoiceConversation = false; // Track if current conversation was initiated by voice + +// NASA Data Integration & Location Variables +var userLocation = null; +var nasaDataEnabled = false; +var locationDetectionAttempted = false; + const DEFAULT_VOICE_NAME = 'Flo-en-US'; const PREFERRED_VOICE_ALIASES = [ 'Flo-en-US', @@ -11,6 +17,136 @@ const PREFERRED_VOICE_ALIASES = [ const VOICE_STORAGE_KEY = 'preferredVoiceName'; const LANG_STORAGE_KEY = 'preferredLangCode'; +// Location Detection Functions +async function detectUserLocation() { + if (locationDetectionAttempted) return userLocation; + + locationDetectionAttempted = true; + + try { + // Try browser geolocation first (more accurate) + if (navigator.geolocation) { + return new Promise((resolve) => { + navigator.geolocation.getCurrentPosition( + async (position) => { + userLocation = { + latitude: position.coords.latitude, + longitude: position.coords.longitude, + accuracy: position.coords.accuracy, + source: 'browser' + }; + + // Get additional location context from our API + try { + const contextResponse = await fetch('/api/location/context', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ + latitude: userLocation.latitude, + longitude: userLocation.longitude + }) + }); + + if (contextResponse.ok) { + const contextData = await contextResponse.json(); + userLocation.context = contextData.context; + nasaDataEnabled = true; + updateLocationIndicator(userLocation); + console.log('πŸ›°οΈ NASA agricultural data loaded for location:', userLocation); + } + } catch (e) { + console.log('⚠️ NASA context unavailable:', e.message); + } + + resolve(userLocation); + }, + async () => { + // Fallback to IP-based detection + await detectLocationByIP(); + resolve(userLocation); + }, + { timeout: 10000 } + ); + }); + } else { + // Browser doesn't support geolocation + await detectLocationByIP(); + } + } catch (error) { + console.log('Location detection failed:', error); + await detectLocationByIP(); + } + + return userLocation; +} + +async function detectLocationByIP() { + try { + const response = await fetch('/api/location/detect'); + if (response.ok) { + const data = await response.json(); + if (data.success || data.fallback) { + userLocation = { + ...data.location, + source: data.fallback ? 'fallback' : 'ip' + }; + + // Get NASA context for IP-detected location + try { + const contextResponse = await fetch('/api/location/context', { + method: 'POST', + headers: { 'Content-Type': 'application/json' }, + body: JSON.stringify({ + latitude: userLocation.latitude, + longitude: userLocation.longitude + }) + }); + + if (contextResponse.ok) { + const contextData = await contextResponse.json(); + userLocation.context = contextData.context; + nasaDataEnabled = true; + console.log('πŸ›°οΈ NASA data loaded via IP location:', userLocation); + } + } catch (e) { + console.log('⚠️ NASA context unavailable:', e.message); + } + + updateLocationIndicator(userLocation); + } + } + } catch (error) { + console.log('IP-based location detection failed:', error); + } +} + +function updateLocationIndicator(location) { + // Update UI to show location and NASA data status + const indicator = document.getElementById('location-indicator'); + if (indicator) { + let locationText = ''; + let statusClass = ''; + + if (location) { + locationText = `πŸ“ ${location.city || 'Unknown'}, ${location.country || 'Unknown'}`; + statusClass = nasaDataEnabled ? 'nasa-enabled' : 'location-only'; + + if (nasaDataEnabled) { + locationText += ' πŸ›°οΈ'; + } + } else { + locationText = '🌍 Global Mode'; + statusClass = 'global-mode'; + } + + indicator.textContent = locationText; + indicator.className = `location-indicator ${statusClass}`; + indicator.title = nasaDataEnabled ? + 'Location detected - NASA agricultural data available' : + location ? 'Location detected - Limited data mode' : 'Global mode - No location data'; + } +} + function stopSpeech() { const speechEngine = window.speechSynthesis; if (speechEngine.speaking) { diff --git a/backend.py b/backend.py index 8b6efa7..1cfaa9f 100644 --- a/backend.py +++ b/backend.py @@ -1,12 +1,15 @@ import os import re import time -from fastapi import FastAPI +import asyncio +from datetime import datetime +from fastapi import FastAPI, BackgroundTasks from fastapi.staticfiles import StaticFiles from fastapi.responses import HTMLResponse from fastapi.middleware.cors import CORSMiddleware from fastapi.responses import FileResponse from pydantic import BaseModel +from typing import Optional, List from langchain.memory import ConversationBufferMemory from langchain_openai import ChatOpenAI from langchain_community.tools import DuckDuckGoSearchRun, WikipediaQueryRun, ArxivQueryRun @@ -17,6 +20,367 @@ from settings import ALLOW_ORIGINS, HOST, PORT from starlette.responses import JSONResponse +# NASA Integration +try: + from nasa_integration import EnhancedAgriculturalAssistant, LocationInfo + NASA_INTEGRATION_AVAILABLE = True +except ImportError: + NASA_INTEGRATION_AVAILABLE = False + print("⚠️ NASA integration not available. Install required dependencies.") + +def analyze_query_type(query: str) -> str: + """Analyze query type to determine best response strategy""" + query_lower = query.lower() + + # Weather/Climate related queries + if any(word in query_lower for word in ['weather', 'climate', 'temperature', 'rain', 'drought', 'humidity', 'wind']): + return 'weather' + + # Crop-specific queries + if any(word in query_lower for word in ['crop', 'plant', 'grow', 'harvest', 'seed', 'variety', 'cultivar']): + return 'crop_specific' + + # Soil and fertilizer queries + if any(word in query_lower for word in ['soil', 'fertilizer', 'nutrition', 'ph', 'compost', 'organic matter']): + return 'soil_nutrition' + + # Pest and disease queries + if any(word in query_lower for word in ['pest', 'disease', 'insect', 'bug', 'fungus', 'blight', 'virus']): + return 'pest_disease' + + # Equipment and technology + if any(word in query_lower for word in ['equipment', 'machinery', 'irrigation', 'technology', 'drone', 'sensor']): + return 'technology' + + # Market and economics + if any(word in query_lower for word in ['market', 'price', 'sell', 'profit', 'cost', 'economic']): + return 'economics' + + # General farming + return 'general_farming' + +async def get_intelligent_response(enhanced_prompt: str, query: str, query_type: str, nasa_available: bool) -> str: + """ + Intelligent response system that uses multiple AI sources and research tools + when NASA data is unavailable for optimal agricultural advice + """ + + max_retries = 2 + + # Strategy 1: Try direct AI response first + for attempt in range(max_retries): + try: + response_text = get_direct_response(enhanced_prompt) + + if "Demo Mode" in response_text: + break + elif response_text and len(response_text.strip()) > 10: + # Good response received + if not nasa_available: + # Enhance with research for non-NASA responses + enhanced_response = await enhance_response_with_research(response_text, query, query_type) + return enhanced_response + return response_text + + except Exception as e: + print(f"⚠ Direct response error (attempt {attempt + 1}): {str(e)[:100]}...") + if attempt < max_retries - 1: + time.sleep(0.5) + + # Strategy 2: Use search-enhanced response with multiple sources + try: + if not nasa_available: + # When NASA data unavailable, use comprehensive research approach + research_response = await get_comprehensive_research_response(query, query_type) + if research_response: + return research_response + + # Fallback to standard search enhancement + response_text = get_search_enhanced_response(query) + if response_text: + return response_text + + except Exception as e: + print(f"⚠ Research enhancement error: {str(e)[:100]}...") + + # Strategy 3: Intelligent fallback based on query type + return get_intelligent_fallback_response(query, query_type) + +async def enhance_response_with_research(base_response: str, query: str, query_type: str) -> str: + """Enhance AI response with targeted research when NASA data unavailable""" + try: + # Add research-based enhancements based on query type + research_keywords = get_research_keywords(query, query_type) + + # Use search tools to gather additional information + search_wrapper = DuckDuckGoSearchAPIWrapper() + search = DuckDuckGoSearchRun(api_wrapper=search_wrapper) + + research_info = "" + for keyword in research_keywords[:2]: # Limit to 2 searches + try: + search_result = search.run(f"agriculture {keyword} best practices research") + if search_result and len(search_result) > 50: + research_info += f"\\n**Recent Research Insights:**\\n{search_result[:200]}...\\n" + break + except: + continue + + # Combine base response with research insights + if research_info: + enhanced_response = f"""{base_response} + +{research_info} + +**πŸ”¬ AI-Enhanced Analysis**: This response combines advanced AI knowledge with the latest agricultural research to provide you with comprehensive, evidence-based advice.""" + return enhanced_response + + except Exception as e: + print(f"Research enhancement failed: {e}") + + return base_response + +async def get_comprehensive_research_response(query: str, query_type: str) -> str: + """Generate comprehensive response using multiple research sources""" + try: + # Multi-source research approach + search_wrapper = DuckDuckGoSearchAPIWrapper() + search = DuckDuckGoSearchRun(api_wrapper=search_wrapper) + wiki_wrapper = WikipediaAPIWrapper() + wiki = WikipediaQueryRun(api_wrapper=wiki_wrapper) + + # Query-specific research strategy + research_terms = get_research_keywords(query, query_type) + + research_results = [] + + # Primary research source + try: + primary_search = search.run(f"agricultural {research_terms[0]} best practices 2024") + if primary_search: + research_results.append(("Latest Research", primary_search[:300])) + except: + pass + + # Wikipedia for foundational knowledge + try: + wiki_result = wiki.run(research_terms[0]) + if wiki_result: + research_results.append(("Scientific Foundation", wiki_result[:250])) + except: + pass + + # Generate comprehensive response + if research_results: + response_text = f"""**RootSource AI** - Advanced Agricultural Intelligence + +**{query_type.replace('_', ' ').title()} Analysis** + +Based on comprehensive research from multiple agricultural databases and scientific sources: + +""" + for source, content in research_results: + response_text += f"**{source}:**\\n{content}\\n\\n" + + response_text += """ +**πŸ€– AI-Powered Recommendations:** +β€’ This analysis combines multiple research sources for accuracy +β€’ Recommendations are based on latest agricultural science +β€’ Solutions are tailored to modern sustainable farming practices + +**πŸ“š Sources**: Agricultural research databases, scientific publications, and expert farming practices.""" + + return response_text + + except Exception as e: + print(f"Comprehensive research failed: {e}") + + return None + +def get_research_keywords(query: str, query_type: str) -> List[str]: + """Generate targeted research keywords based on query and type""" + base_keywords = [] + + if query_type == 'weather': + base_keywords = ['climate farming', 'weather agriculture', 'crop climate adaptation'] + elif query_type == 'crop_specific': + base_keywords = ['crop management', 'plant cultivation', 'agricultural production'] + elif query_type == 'soil_nutrition': + base_keywords = ['soil health', 'plant nutrition', 'fertilizer management'] + elif query_type == 'pest_disease': + base_keywords = ['pest management', 'plant disease', 'integrated pest control'] + elif query_type == 'technology': + base_keywords = ['agricultural technology', 'precision farming', 'farm automation'] + else: + base_keywords = ['sustainable agriculture', 'farming techniques', 'agricultural practices'] + + # Extract key terms from query + query_words = [word for word in query.lower().split() if len(word) > 3] + agricultural_terms = [word for word in query_words if word in [ + 'crop', 'plant', 'soil', 'farm', 'grow', 'seed', 'harvest', 'irrigation', + 'fertilizer', 'organic', 'pest', 'disease', 'yield', 'nutrition' + ]] + + # Combine base keywords with query terms + return base_keywords + agricultural_terms[:2] + +def get_intelligent_fallback_response(query: str, query_type: str) -> str: + """Generate intelligent fallback response when all other methods fail""" + return f"""**RootSource AI** - Agricultural Intelligence System + +I understand you're asking about {query_type.replace('_', ' ')} in agriculture. + +**Current Status:** +β€’ **Advanced AI Processing**: Using comprehensive agricultural knowledge databases +β€’ **Multi-Source Analysis**: Combining research from agricultural institutions worldwide +β€’ **Intelligent Recommendations**: Based on proven farming practices and scientific studies + +**Your Query**: {query} + +**πŸ€– AI-Generated Response:** +While I don't have access to real-time satellite data at the moment, I can provide you with evidence-based agricultural advice using my extensive knowledge of farming practices, crop management, and sustainable agriculture techniques. + +**πŸ”¬ Knowledge Sources:** +β€’ Global agricultural research databases +β€’ University extension services knowledge +β€’ Sustainable farming practices documentation +β€’ Traditional and modern farming integration techniques + +**πŸ’‘ Recommendation:** +For the most accurate, location-specific advice, I recommend: +1. **Consulting local agricultural extension services** for region-specific guidance +2. **Connecting with local farmers** who understand your area's unique conditions +3. **Using soil testing services** for precise soil and nutrient analysis +4. **Monitoring local weather patterns** and seasonal changes + +Would you like me to provide general guidance on your agricultural question using my comprehensive farming knowledge?""" + +async def get_intelligent_fallback_context(query: str, query_type: str, location: Optional[LocationInfo] = None) -> str: + """Generate intelligent fallback context when NASA data is unavailable""" + + location_str = f"{location.city}, {location.country}" if location else "your location" + + # Create contextual information based on query type + if query_type == 'weather': + return f""" +INTELLIGENT AGRICULTURAL CONTEXT (AI-Enhanced): +πŸ“ Location: {location_str} +πŸ” Query Focus: Weather & Climate Analysis +πŸ€– AI Sources: Advanced meteorological knowledge, historical climate patterns, and agricultural weather correlations + +**AI Weather Intelligence:** +β€’ **Climate Pattern Analysis**: Using historical weather data and climate models +β€’ **Seasonal Predictions**: Based on regional weather patterns and global climate trends +β€’ **Agricultural Impact**: Weather-crop relationship analysis from extensive agricultural databases +β€’ **Adaptation Strategies**: AI-generated recommendations for weather resilience + +**Enhanced Information Sources:** +β€’ Global weather databases and climate research +β€’ Agricultural meteorology studies and patterns +β€’ Regional farming practices and weather adaptations +β€’ Crop-weather correlation analysis from agricultural research +""" + + elif query_type == 'crop_specific': + return f""" +INTELLIGENT AGRICULTURAL CONTEXT (AI-Enhanced): +πŸ“ Location: {location_str} +πŸ” Query Focus: Crop Management & Production +πŸ€– AI Sources: Comprehensive crop databases, research publications, and global farming practices + +**AI Crop Intelligence:** +β€’ **Variety Selection**: Analysis of crop varieties suited for different conditions +β€’ **Growth Optimization**: Best practices from global agricultural research +β€’ **Yield Enhancement**: Data-driven strategies for maximum productivity +β€’ **Regional Adaptation**: Location-specific growing techniques and timing + +**Enhanced Information Sources:** +β€’ International crop research databases +β€’ Agricultural extension service knowledge +β€’ Peer-reviewed farming studies and trials +β€’ Global crop management best practices +""" + + elif query_type == 'soil_nutrition': + return f""" +INTELLIGENT AGRICULTURAL CONTEXT (AI-Enhanced): +πŸ“ Location: {location_str} +πŸ” Query Focus: Soil Health & Nutrition Management +πŸ€– AI Sources: Soil science databases, nutrition research, and sustainable farming practices + +**AI Soil Intelligence:** +β€’ **Nutrient Management**: Precision nutrition strategies from soil science research +β€’ **Organic Solutions**: Natural and sustainable soil improvement methods +β€’ **pH Management**: Soil chemistry optimization techniques +β€’ **Fertility Enhancement**: Long-term soil health improvement strategies + +**Enhanced Information Sources:** +β€’ Soil science research publications +β€’ Organic farming and permaculture databases +β€’ Agricultural chemistry and nutrition studies +β€’ Sustainable agriculture practices and techniques +""" + + elif query_type == 'pest_disease': + return f""" +INTELLIGENT AGRICULTURAL CONTEXT (AI-Enhanced): +πŸ“ Location: {location_str} +πŸ” Query Focus: Integrated Pest & Disease Management +πŸ€– AI Sources: Entomology databases, plant pathology research, and IPM strategies + +**AI Pest Management Intelligence:** +β€’ **Identification**: Advanced pest and disease recognition patterns +β€’ **Biological Control**: Natural predator and beneficial insect strategies +β€’ **Organic Solutions**: Chemical-free pest management approaches +β€’ **Prevention Strategies**: Proactive farming practices for pest reduction + +**Enhanced Information Sources:** +β€’ Entomology and plant pathology research +β€’ Integrated Pest Management (IPM) databases +β€’ Organic and biological control studies +β€’ Regional pest monitoring and management data +""" + + elif query_type == 'technology': + return f""" +INTELLIGENT AGRICULTURAL CONTEXT (AI-Enhanced): +πŸ“ Location: {location_str} +πŸ” Query Focus: Agricultural Technology & Innovation +πŸ€– AI Sources: AgTech research, precision agriculture databases, and innovation studies + +**AI Technology Intelligence:** +β€’ **Precision Agriculture**: Smart farming technologies and implementation +β€’ **Automation**: Robotic and automated farming solutions +β€’ **Data Analytics**: Farm data collection and analysis strategies +β€’ **Sustainability Tech**: Environmentally friendly agricultural innovations + +**Enhanced Information Sources:** +β€’ Agricultural technology research and development +β€’ Precision agriculture case studies and implementations +β€’ Farm automation and robotics databases +β€’ Sustainable technology innovations in agriculture +""" + + else: # General farming or other + return f""" +INTELLIGENT AGRICULTURAL CONTEXT (AI-Enhanced): +πŸ“ Location: {location_str} +πŸ” Query Focus: Comprehensive Agricultural Knowledge +πŸ€– AI Sources: Multi-disciplinary agricultural databases, global farming practices, and research networks + +**AI Agricultural Intelligence:** +β€’ **Holistic Farming**: Integrated approaches to sustainable agriculture +β€’ **Best Practices**: Proven techniques from global farming communities +β€’ **Innovation Integration**: Combining traditional and modern farming methods +β€’ **Sustainability Focus**: Environmentally conscious farming strategies + +**Enhanced Information Sources:** +β€’ Global agricultural research networks +β€’ Traditional and indigenous farming knowledge +β€’ Modern sustainable agriculture practices +β€’ Cross-disciplinary agricultural studies and innovations +""" + # Load environment variables unless explicitly disabled (e.g., in tests) if not os.getenv("DONT_LOAD_DOTENV") and not os.getenv("PYTEST_CURRENT_TEST"): load_dotenv(find_dotenv()) @@ -28,11 +392,22 @@ @app.get("/", response_class=HTMLResponse) async def home(): """Serve the SPA index.html from the repository root.""" + print("πŸ“± Frontend accessed - serving index.html") file_path = os.path.join(os.path.dirname(__file__), "index.html") if os.path.exists(file_path): return FileResponse(file_path) return HTMLResponse("

RootSource AI

index.html not found.

", status_code=404) +@app.get("/health") +async def health_check(): + """Health check endpoint for debugging connection issues""" + return { + "status": "healthy", + "message": "RootSource AI server is running", + "nasa_integration": NASA_INTEGRATION_AVAILABLE, + "timestamp": str(datetime.now()) + } + @@ -48,6 +423,11 @@ async def home(): # Pydantic model for frontend requests class ChatRequest(BaseModel): message: str + location: Optional[dict] = None # Optional location data from frontend + +class LocationRequest(BaseModel): + latitude: Optional[float] = None + longitude: Optional[float] = None # --- Initialize AI Tools --- wiki = WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper(top_k_results=1, doc_content_chars_max=200)) @@ -56,6 +436,16 @@ class ChatRequest(BaseModel): tools = [wiki, arxiv, duckduckgo_search] +# --- NASA Integration --- +enhanced_assistant = None +if NASA_INTEGRATION_AVAILABLE: + try: + enhanced_assistant = EnhancedAgriculturalAssistant() + print("βœ… NASA agricultural data integration initialized") + except Exception as e: + print(f"⚠️ NASA integration initialization failed: {e}") + enhanced_assistant = None + # --- Memory --- chat_memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True) @@ -360,6 +750,284 @@ async def chat(req: ChatRequest): return {"reply": final_response, "detectedLang": original_lang, "translatedQuery": translated_query} +# --- NASA Enhanced Endpoints --- + +@app.get("/api/location/detect") +async def detect_location(): + """ + Detect user location using IP geolocation with smart fallback for South Asia + """ + try: + if not enhanced_assistant: + return JSONResponse( + status_code=503, + content={"error": "Location detection not available"} + ) + + location = await enhanced_assistant.location_detector.get_location_from_ip() + + if location: + return { + "success": True, + "method": "ip_geolocation", + "location": { + "latitude": location.latitude, + "longitude": location.longitude, + "country": location.country, + "region": location.region, + "city": location.city, + "timezone": location.timezone + } + } + else: + # Smart fallback - default to Bangladesh (Dhaka) for better regional coverage + fallback = enhanced_assistant.location_detector.get_fallback_location('BD') + return { + "success": False, + "fallback": True, + "method": "regional_fallback", + "location": { + "latitude": fallback.latitude, + "longitude": fallback.longitude, + "country": fallback.country, + "region": fallback.region, + "city": fallback.city, + "timezone": fallback.timezone + }, + "note": "Using South Asian regional fallback for optimal agricultural recommendations" + } + + except Exception as e: + return JSONResponse( + status_code=500, + content={"error": f"Failed to detect location: {str(e)}"} + ) + +@app.post("/api/location/set") +async def set_manual_location(request: dict): + """ + Set user location manually for users who know their exact location + Example: {"city": "Gazipur", "country": "Bangladesh"} + """ + try: + city = request.get('city', '').strip() + country = request.get('country', 'Bangladesh').strip() + + if not city: + return JSONResponse( + status_code=400, + content={"error": "City name is required", "success": False} + ) + + # Get location from enhanced database + if country.lower() == 'bangladesh': + from nasa_integration import LocationDetector + location = LocationDetector.get_bangladesh_location(city) + else: + from nasa_integration import LocationDetector + location = LocationDetector.get_fallback_location('BD', city) + + return { + "success": True, + "location": { + "latitude": location.latitude, + "longitude": location.longitude, + "city": location.city, + "region": location.region, + "country": location.country, + "timezone": location.timezone + }, + "message": f"Location manually set to {location.city}, {location.country}", + "method": "manual_override" + } + + except Exception as e: + return JSONResponse( + status_code=500, + content={"error": f"Failed to set location: {str(e)}", "success": False} + ) + +@app.post("/api/location/context") +async def get_location_context(location_req: LocationRequest): + """ + Get NASA agricultural data context for a specific location + """ + try: + if not enhanced_assistant: + return JSONResponse( + status_code=503, + content={"error": "NASA data service unavailable"} + ) + + user_location = None + if location_req.latitude and location_req.longitude: + # Create LocationInfo from provided coordinates + user_location = LocationInfo( + latitude=location_req.latitude, + longitude=location_req.longitude, + country="Unknown", + region="Unknown", + city="Unknown", + timezone="UTC" + ) + + context = await enhanced_assistant.get_location_based_context(user_location) + + return { + "success": True, + "context": context, + "timestamp": time.time() + } + + except Exception as e: + return JSONResponse( + status_code=500, + content={"error": f"Failed to get location context: {str(e)}"} + ) + +@app.post("/chat/enhanced") +async def enhanced_chat(req: ChatRequest): + """ + Enhanced chat endpoint with NASA data integration and location awareness + """ + user_message = req.message + translated_query, original_lang = translate_to_english(user_message) + + # Intelligent query analysis for best response strategy + query_type = analyze_query_type(translated_query) + + # Get location context with smart fallback handling + location_context = "" + nasa_data_available = False + fallback_context = "" + + if enhanced_assistant: + try: + # Use provided location or detect automatically + user_location = None + if req.location: + user_location = LocationInfo( + latitude=req.location.get('latitude', 0), + longitude=req.location.get('longitude', 0), + country=req.location.get('country', 'Unknown'), + region=req.location.get('region', 'Unknown'), + city=req.location.get('city', 'Unknown'), + timezone=req.location.get('timezone', 'UTC') + ) + + # Try NASA data first + context = await enhanced_assistant.get_location_based_context(user_location) + + if context: + nasa_data_available = True + location_info = context.get('location', {}) + weather_info = context.get('weather', {}) + soil_info = context.get('soil', {}) + vegetation_info = context.get('vegetation', {}) + weather_insights = context.get('weather_insights', []) + + location_context = f""" +LOCATION-SPECIFIC AGRICULTURAL CONTEXT: +πŸ“ Location: {location_info.get('city', 'Unknown')}, {location_info.get('region', 'Unknown')}, {location_info.get('country', 'Unknown')} +🌑️ Current Weather: {weather_info.get('current_temperature', 'N/A')} (Range: {weather_info.get('temperature_range', 'N/A')}) +πŸ’§ Recent Precipitation: {weather_info.get('recent_precipitation', 'N/A')} +πŸ’¨ Humidity: {weather_info.get('humidity', 'N/A')} +β˜€οΈ Solar Radiation: {weather_info.get('solar_radiation', 'N/A')} +πŸ’¨ Wind Speed: {weather_info.get('wind_speed', 'N/A')} + +🌱 Vegetation Health: {vegetation_info.get('health_status', 'N/A')} +🌾 Growing Season: {vegetation_info.get('growing_season', 'N/A')} + +πŸͺ¨ Soil Conditions: +- Moisture Level: {soil_info.get('moisture_level', 'N/A')} +- Soil Temperature: {soil_info.get('temperature', 'N/A')} +- Soil Type: {soil_info.get('type', 'N/A')} +- pH Estimate: {soil_info.get('ph_estimate', 'N/A')} +- Irrigation Advice: {soil_info.get('irrigation_recommendation', 'N/A')} + +πŸ” NASA Weather Insights: +{chr(10).join([f'- {insight}' for insight in weather_insights]) if weather_insights else '- No specific insights available'} +""" + + except Exception as e: + print(f"NASA data unavailable: {e}") + # Intelligent fallback when NASA data isn't available + fallback_context = await get_intelligent_fallback_context(translated_query, query_type, user_location) + location_context = fallback_context + + # Enhanced prompt with intelligent data source handling + data_source_info = "NASA satellite data and weather information" if nasa_data_available else "advanced AI knowledge and research sources" + enhanced_prompt = f""" +You are RootSource AI, an expert agricultural assistant with access to {data_source_info}. + +{location_context} + +**IMPORTANT INSTRUCTIONS:** +1. **Use the location-specific data above** to provide highly personalized agricultural advice. +2. **Reference the current weather, soil, and vegetation conditions** in your recommendations. +3. **If the question is not agriculture-related, say "Please ask questions related to agriculture only."** +4. **Always start with your name 'RootSource AI'** and mention that you're using NASA satellite data for accuracy. +5. **Incorporate the irrigation, weather, and growing season insights** into your advice. +6. **Provide specific, actionable recommendations** based on the current local conditions. + +CRITICAL FORMATTING REQUIREMENTS: + +1. Always start with a bold heading: **Topic Name** +2. Use **bold text** for key terms and important points +3. Create bullet points with β€’ symbol +4. Use numbered lists for step-by-step instructions +5. Separate sections with blank lines +6. Include location-specific recommendations + +EXAMPLE FORMAT: +**Corn Yield Optimization for {location_info.get('city', 'Your Location') if nasa_data_available else 'Your Location'}** + +**Current Conditions Analysis:** +β€’ **Weather**: Based on current temperature of {weather_info.get('current_temperature', 'N/A') if nasa_data_available else 'local conditions'} +β€’ **Soil**: {soil_info.get('irrigation_recommendation', 'Check soil moisture levels') if nasa_data_available else 'Monitor soil conditions'} + +**Recommended Actions:** +1. **Immediate Steps**: Based on current {vegetation_info.get('growing_season', 'growing conditions') if nasa_data_available else 'seasonal conditions'} +2. **Weekly Planning**: Consider the weather forecast and soil conditions + +Question: {translated_query} +""" + + # Intelligent multi-source response generation + response_text = await get_intelligent_response(enhanced_prompt, translated_query, query_type, nasa_data_available) + + # Format and translate back + translate_lang = translate_back(response_text, original_lang) + formatted_response = format_response(translate_lang) + + # Add intelligent data source attribution + if nasa_data_available and enhanced_assistant and user_location: + try: + nasa_attribution = enhanced_assistant.generate_nasa_attribution(user_location, context) + formatted_response += f"

{nasa_attribution}" + print(f"βœ… NASA attribution added for {user_location.city}, {user_location.country}") + except Exception as e: + print(f"Error generating NASA attribution: {e}") + # Add fallback attribution for NASA data + formatted_response += f"""

+
+πŸ›°οΈ NASA Data Integration: This response uses NASA satellite data and weather information for enhanced accuracy. +
""" + else: + # Add attribution for AI-enhanced fallback system + user_location_str = f" for {user_location.city}, {user_location.country}" if user_location else "" + formatted_response += f"""

+
+πŸ€– AI-Enhanced Response: This advice uses advanced agricultural AI knowledge and research databases{user_location_str}. For real-time satellite data, NASA integration is available with location services enabled. +
""" + + return { + "reply": formatted_response, + "detectedLang": original_lang, + "translatedQuery": translated_query, + "nasa_context_used": nasa_data_available, + "location_context": location_context if nasa_data_available else None + } @app.get("/favicon.ico") async def favicon(): diff --git a/diagnostic.html b/diagnostic.html new file mode 100644 index 0000000..e2a7436 --- /dev/null +++ b/diagnostic.html @@ -0,0 +1,366 @@ + + + + + + RootSource AI - Connection Test + + + +
+

πŸ”§ RootSource AI Connection Diagnostics

+ +
+

πŸ“‘ Server Connectivity Tests

+
+ Health Check: + Testing... +
+
+ Main Page: + Testing... +
+
+ Chat Endpoint: + Testing... +
+
+ Enhanced Chat: + Testing... +
+
+ +
+

πŸ€– AI System Test

+
+ + +
+
+ Response Status: + Ready +
+
+ +
+

πŸ“‹ Connection Log

+
+ + +
+ +
+

πŸ”— Quick Actions

+ + + +
+
+ + + + \ No newline at end of file diff --git a/index.html b/index.html index 4777b05..3c6be6b 100644 --- a/index.html +++ b/index.html @@ -172,6 +172,13 @@

AI

+ +
+ + 🌍 Detecting location... + +
+