golden-jatayu
Divya Rajput# JATAYU Backend Architecture Generate a production-ready backend using Python FastAPI. Architecture: ## APIs POST /upload POST /analyze POST /chat GET /mission/{id} GET /report/{id} ## AI Agents IntentAgent MetadataAgent RouterAgent FusionAgent RSVQAAgent CDVQAAgent GeoReasonAgent SITREPAgent ## Context Engine Every mission creates a unique Mission ID. Store: * image paths * metadata * CRS * timestamps * previous queries * GeoJSON * flood masks ## Router Logic If 1 image → RSVQA If Optical + SAR → Fusion If Before + After → CDVQA ## Outputs Return JSON containing: * summary * confidence * area_km2 * gps_coordinates * geojson_path * execution_trace Generate clean modular folder structure and FastAPI routes. Design a LangGraph multi-agent workflow for JATAYU. Agents: Intent Agent Metadata Agent Router Agent Optical-SAR Fusion Agent Change Detection Agent GeoReason Agent SITREP Agent The router must decide the workflow based on: * number of images * modality * timestamps * user query Generate an execution graph and state schema. Output should be explainable and auditable. givme mea full working website
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Project Tasks
79 planning tasksGenerate system requirement document
Generate personas & user flows
Create flow for Remote Sensing Analyst
Create flow for Field Officer
Create flow for Data Scientist
Landing
Landing / Hero Workflow
Landing / Navigation
Landing / Features And Capabilities
Landing / Header
Landing / Use Cases
Landing / Hero
Landing / Primary Action
Landing / Workflow
Landing / Capabilities
Landing / CTA
Landing / Footer
Retry First Page
Header
Footer
Navigation
Login
Login / Navigation
Login / Workflow Diagram
Login / Auth Panel
Login / Footer
Dashboard
Dashboard / Navigation
Dashboard / Hero
Dashboard / Mission Summary
Dashboard / Active Missions List
Dashboard / Quick Actions
Dashboard / Footer
Missions
Missions / Navigation
Missions / Page Header
Missions / Table
Missions / Footer
Upload
Upload / Navigation
Upload / Hero
Upload / Form And Progress
Upload / Footer
Mission Details
Mission Details / Navigation
Mission Details / Metadata Panel
Mission Details / Progress Timeline
Mission Details / Validation Workflow
Mission Details / Data Inventory
Mission Details / Footer
Chat
Chat / Navigation
Chat / Interface
Chat / Footer
Analysis
Analysis / Navigation
Analysis / Workflow
Analysis / Status
Analysis / Footer
Results
Results / Navigation
Results / Summary
Results / Metrics
Results / JSON
Results / Execution Trace
Results / Actions
Results / Footer
Map
Map / Navigation
Map / Overlay Controls
Map / Container
Map / Footer
Reports
Reports / Navigation
Reports / Header
Reports / Grid
Reports / Footer
Architecture
Workspace task plan
JATAYU: Multimodal Remote Sensing Vision-Language Assistant
Transform satellite imagery into actionable insights using natural language.
JATAYU coordinates a multi-agent architecture that interprets natural-language queries, validates image metadata, and routes each mission to the right specialist model. A single image is analyzed by the RSVQA agent, optical and SAR pairs are fused for robust detection, and before/after pairs are assessed for change. Every mission produces an explainable, auditable JSON output with GPS coordinates, GeoJSON polygons, and a full execution trace.
Intent & Metadata → Router → RSVQA / Fusion / CDVQA → GeoReason → SITREP
ROUTER AGENT
Selects the correct specialist workflow based on image count, modality, and timestamps.
Multi-Agent Architecture
Workflow & Agent Responsibilities
golden-jatayu routes every mission through a chain of specialist agents. Each agent owns one responsibility, from interpreting a query to compiling the final report, keeping the full analysis path explainable and auditable end to end.
Intent Agent
Step 01
Interprets natural-language queries submitted through the chat interface and maps them to the correct analysis workflow.
Metadata Agent
Step 02
Validates GeoTIFF metadata, including coordinate reference system (CRS) and timestamps, before analysis begins.
Router Agent
Step 03
Selects the appropriate downstream workflow based on image count, modality, timestamps, and the parsed user query.
Fusion Agent
Step 04
Performs optical-SAR image fusion, combining both modalities for reliable flood and terrain detection.
RSVQA Agent
Step 05
Executes visual question answering on a single image to answer queries about the observed scene.
CDVQA Agent
Step 06
Conducts change-detection visual question answering on before-and-after image pairs to identify changes over time.
GeoReason Agent
Step 07
Converts image pixel coordinates into GPS coordinates and generates GeoJSON polygons for detected areas.
SITREP Agent
Step 08
Compiles analytical results, maps, confidence scores, and damage statistics into a professional PDF and GeoJSON report.
Platform Capabilities
Capabilities & Supported Outputs
golden-jatayu combines multimodal image ingestion, multi-agent analysis, and auditable geospatial outputs across every mission.
Image Upload
- GeoTIFF
- Optical
- SAR
- Multiple modalities
Accepts georeferenced imagery with embedded CRS metadata
Multi-Agent Analysis
- Optical-SAR fusion
- Change detection
- Visual question answering
Router Agent selects the workflow based on modality and query
Natural-Language Interface
- Conversational query input
- Intent recognition
Submit queries in plain language via the Chat interface
Geospatial Output
- GPS coordinates
- GeoJSON polygons
GeoReason Agent converts image pixels to geographic coordinates
Report Generation
- PDF reports
- JSON summaries
SITREP Agent compiles findings into structured documents
Execution Trace
- Auditable steps
- Explainable outputs
Every mission response includes a full execution trace
Mission ID Tracking
- Persistent mission history
- Query log
Each mission is assigned a unique, trackable identifier
Ready to explore satellite insights?
Sign in to upload imagery, run multi-agent analysis, and generate auditable geospatial reports.
For Data Scientists, Field Officers, and Remote Sensing Analysts.
LoginJATAYU: Multimodal Remote Sensing Vision-Language Assistant
Transform satellite imagery into actionable insights using natural language.
JATAYU coordinates a multi-agent architecture that interprets natural-language queries, validates image metadata, and routes each mission to the right specialist model. A single image is analyzed by the RSVQA agent, optical and SAR pairs are fused for robust detection, and before/after pairs are assessed for change. Every mission produces an explainable, auditable JSON output with GPS coordinates, GeoJSON polygons, and a full execution trace.
Intent & Metadata → Router → RSVQA / Fusion / CDVQA → GeoReason → SITREP
ROUTER AGENT
Selects the correct specialist workflow based on image count, modality, and timestamps.
Multi-Agent Architecture
Workflow & Agent Responsibilities
golden-jatayu routes every mission through a chain of specialist agents. Each agent owns one responsibility, from interpreting a query to compiling the final report, keeping the full analysis path explainable and auditable end to end.
Intent Agent
Step 01
Interprets natural-language queries submitted through the chat interface and maps them to the correct analysis workflow.
Metadata Agent
Step 02
Validates GeoTIFF metadata, including coordinate reference system (CRS) and timestamps, before analysis begins.
Router Agent
Step 03
Selects the appropriate downstream workflow based on image count, modality, timestamps, and the parsed user query.
Fusion Agent
Step 04
Performs optical-SAR image fusion, combining both modalities for reliable flood and terrain detection.
RSVQA Agent
Step 05
Executes visual question answering on a single image to answer queries about the observed scene.
CDVQA Agent
Step 06
Conducts change-detection visual question answering on before-and-after image pairs to identify changes over time.
GeoReason Agent
Step 07
Converts image pixel coordinates into GPS coordinates and generates GeoJSON polygons for detected areas.
SITREP Agent
Step 08
Compiles analytical results, maps, confidence scores, and damage statistics into a professional PDF and GeoJSON report.
Platform Capabilities
Capabilities & Supported Outputs
golden-jatayu combines multimodal image ingestion, multi-agent analysis, and auditable geospatial outputs across every mission.
Image Upload
- GeoTIFF
- Optical
- SAR
- Multiple modalities
Accepts georeferenced imagery with embedded CRS metadata
Multi-Agent Analysis
- Optical-SAR fusion
- Change detection
- Visual question answering
Router Agent selects the workflow based on modality and query
Natural-Language Interface
- Conversational query input
- Intent recognition
Submit queries in plain language via the Chat interface
Geospatial Output
- GPS coordinates
- GeoJSON polygons
GeoReason Agent converts image pixels to geographic coordinates
Report Generation
- PDF reports
- JSON summaries
SITREP Agent compiles findings into structured documents
Execution Trace
- Auditable steps
- Explainable outputs
Every mission response includes a full execution trace
Mission ID Tracking
- Persistent mission history
- Query log
Each mission is assigned a unique, trackable identifier
Ready to explore satellite insights?
Sign in to upload imagery, run multi-agent analysis, and generate auditable geospatial reports.
For Data Scientists, Field Officers, and Remote Sensing Analysts.
Login
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