How 0xzee/jev-stock-decision-maker works
JEV is a Streamlit stock-decision demo: users view broad market context, enter a ticker for a fundamentals deep-dive, run a structured 20-question assessment, and ask follow-up questions grounded in the same state document. The sampled code supports separate market-context and ticker-snapshot fetches, state-document construction, and TypeSafe calls; unsampled portions of the data layer may add details not represented here.
Main entry points: app.py Streamlit App · data_fetcher.py Market Context · call_jev.py 20-Question Scoring
Components 9
User Interface
- Streamlit App
app.py
Market Data
- Market Context
data_fetcher.py - Ticker Snapshot
data_fetcher.py - State Document
data_fetcher.py
Decision Analysis
- 20-Question Scoring
call_jev.py - Quick Q&A
call_jev.py
Other components
- Investor
- TypeSafe Jev API
- Yahoo Finance
Connections 16
- Investor → Streamlit App: enters ticker / asks
- Streamlit App → Market Context: requests context
- Market Context → Yahoo Finance: fetches market data
- Market Context → Streamlit App: returns table
- Streamlit App → Ticker Snapshot: requests snapshot
- Ticker Snapshot → Yahoo Finance: fetches ticker data
- Ticker Snapshot → Streamlit App: returns fundamentals
- Streamlit App → State Document: builds state
- State Document → Streamlit App: returns document
- Streamlit App → 20-Question Scoring: requests scoring
- 20-Question Scoring → TypeSafe Jev API: submits questions
- 20-Question Scoring → Streamlit App: returns assessment
- Streamlit App → Quick Q&A: requests answer
- Quick Q&A → TypeSafe Jev API: submits question
- Quick Q&A → Streamlit App: returns answer
- Streamlit App → Investor: displays results