This is a Javascript-based log viewer for MAVLink telemetry and dataflash logs with an AI-powered analysis chatbot. Live demo here.

Agentic Chatbot Backend Demo Video: Link

• You can checkout the Readme file in the 'backend' directory - Link

• Intelligent Analysis: Ask natural language questions about your flight data
• Real-time Streaming: Get responses as they're generated with WebSocket streaming
• Comprehensive Insights: Analyze altitude, battery, GPS, RC signals, speed, and anomalies
• Export Conversations: Download chat history in TXT, JSON, or CSV formats
• Session Management: Secure, isolated analysis sessions for each uploaded log

Example Questions:

• "What was the maximum altitude reached?"
• "Were there any GPS signal dropouts?"
• "Give me a complete flight summary"
• "What about the RC signal loss?"

# install dependencies
npm install

# serve with hot reload at localhost:8080
npm run dev

# build for production with minification
npm run build

# run unit tests
npm run unit

# run e2e tests
npm run e2e

# run all tests
npm test

To enable the AI chat features, you'll need to set up the backend:

# Navigate to backend directory
cd backend

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Set up environment variables (requires OpenAI API key)
cp .env.example .env
# Edit .env file with your OpenAI API key

# Start backend server
python main.py

The backend will run on http://localhost:8000. The frontend will automatically connect to it for AI chat features.

Frontend Configuration: You can configure the backend URL by setting the VUE_APP_BACKEND_URL environment variable:

# For development
export VUE_APP_BACKEND_URL=http://localhost:8000

# Then start frontend
npm run dev

1. Upload a Log File: Drag and drop or browse for your MAVLink log file (.bin, .log, .tlog, .ulg)
2. Start Chatting: Ask questions about your flight data in natural language
3. Real-time Responses: Watch as the AI analyzes your data and responds in real-time
4. Export Results: Download your conversation and analysis results for documentation

Supported Log Formats:

• MAVLink Binary Logs (.bin)
• MAVLink Text Logs (.tlog/.log)
• ULog Format (.ulg) - PX4 format (limited support, .bin/.tlog recommended)

• The entire chat (during the session) can be downloaded by clicking on the "Download" button below the chatbox.

• 3D Flight Visualization: Interactive 3D flight path visualization with Cesium
• Advanced Plotting: Multi-parameter telemetry plotting with time-series analysis
• Data Export: Export flight data and visualizations
• File Management: Upload and manage multiple log files
• Expression Editor: Custom data expressions and calculations

• Drag & Drop Upload: Easy log file uploading with visual feedback
• Natural Language Queries: Ask questions in plain English about your flight
• Real-time Streaming: See AI responses generated in real-time
• Quick Questions: Pre-defined common questions for fast analysis
• Analysis Cards: Structured display of flight analysis results
• Chat History Export: Download conversations in multiple formats (TXT, JSON, CSV)
• Session Management: Isolated analysis sessions with automatic cleanup
• Connection Status: Visual indicators for WebSocket and REST API connectivity

• Vue.js 2: Progressive JavaScript framework
• Bootstrap Vue: Responsive UI components
• Cesium: 3D geospatial visualization
• Plotly.js: Interactive charting and plotting
• Axios: HTTP client for API communication
• WebSocket: Real-time bidirectional communication

• (for more details - please checkout the Readme file in the 'backend' directory.)

• 🛰 MAVLink – Lightweight messaging protocol for communicating with drones; used as the telemetry data standard for parsing .tlog files.

• 🧠 OpenAI (GPT-4o, ada-002) – Powering the agent’s reasoning (gpt-4o) and semantic memory embeddings (text-embedding-ada-002) for both planning and answer generation.

• 🦜 LangChain – Used for tool abstraction, agent orchestration (BaseTool, ChatOpenAI), and memory integration (Buffer, FAISS, Entity, CombinedMemory).

• ⚡ FastAPI – Fast, async-ready Python web framework powering the backend API and WebSocket chat streaming.

• 🔍 FAISS (Facebook AI Similarity Search) – High-performance similarity search for time-weighted memory retrieval and context-aware long-term recall.

• 📈 pandas & numpy – Backbone of all telemetry data processing, statistical analysis, and time-series metric computation.

• 🧰 scikit-learn (IsolationForest) – Used for anomaly detection in UAV signal metrics (e.g., voltage drops, GPS fix instability, RC link losses).

• 📚 Pydantic – For request/response validation and serialization in FastAPI endpoints.

• 🌐 HTTPX – Async HTTP client for OpenAI API calls, streaming completions, and retry-resilient embedding generation.

• 🧪 watchfiles – Dev-time hot-reloading of FastAPI and agent modules with minimal latency.

• 🔧 dotenv & os – For clean environment management and configuration loading across API and agent layers.

• 🔄 LangGraph – Graph-based agentic planning and execution pipeline with support for conditional branching (StateGraph, ainvoke).

• 🗃 JSON & Regex – Used extensively for prompt I/O extraction, sanitization, and handling LangChain tool JSON parsing.

• 🧼 Uvicorn – ASGI server for running FastAPI with support for auto-reloading, WebSockets, and streaming endpoints.

# Build Docker Image
docker build -t <your username>/uavlogviewer .

# Run Docker Image
docker run -p 8080:8080 -d <your username>/uavlogviewer

# View Running Containers
docker ps

# View Container Log
docker logs <container id>

# Navigate to localhost:8080 in your web browser