How rchava25/devops works
The clearest runnable product in the sampled source is a Streamlit travel-agent chat app: a user asks about destinations or weather, a LangGraph agent consults an LLM, and tool requests are dispatched and returned to the agent before the response is displayed. The tree also contains a separate static website and contact handler. No README or website-page source was provided, so those components and their wiring are represented conservatively; deployment artifacts are not connected to runtime behavior.
Main entry points: travelagent2.py Agent node · contact.php Contact handler · index.html Home page · portfolio-details.html Portfolio page
Components 16
Travel chat
- Chat interface
travelagent2.py - LangGraph app
travelagent2.py - Agent node
travelagent2.py - Ollama model
- Tool dispatcher
travelagent2.py - Destination lookup
travelagent2.py - Weather lookup
travelagent2.py - Conversation memory
travelagent2.py
Website
- Home page
website/index.html - Portfolio page
website/portfolio-details.html - Services page
website/service-details.html - Starter page
website/starter-page.html
Contact handling
- Contact handler
website/forms/contact.php
Other components
- Traveler
- Website visitor
- Email recipient
Connections 15
- Traveler → Chat interface: asks
- Chat interface → LangGraph app: streams request
- LangGraph app → Agent node: runs
- Agent node → Ollama model: invokes
- Ollama model → Agent node: returns response
- Agent node → Tool dispatcher: dispatches calls
- Tool dispatcher → Destination lookup: calls
- Tool dispatcher → Weather lookup: calls
- Tool dispatcher → Agent node: returns results
- LangGraph app → Conversation memory: checkpoints state
- Website visitor → Home page: requests
- Website visitor → Portfolio page: requests
- Website visitor → Services page: requests
- Website visitor → Starter page: requests
- Contact handler → Email recipient: sends message