src/chatbot/README.md

metadata

title: AI Chatbot
emoji: 🤖
colorFrom: pink
colorTo: yellow
sdk: docker
sdk_version: 0.0.1
app_file: app.py
pinned: false
license: mit
tags:
  - text-generation
  - agentic-ai
  - openai-sdk
short_description: An Experimental Agentic Chatbot (uses OpenAI Agent SDK)

AI Chatbot

This is an experimental chatbot for chatting with AI. It is equipped with agents & tools to give you realtime data from the web. It uses OpenAI - SDK and OpenAI - Agents...

Features

• Predefined prompts for quick analysis
• Chat interface with AI responses
• Enter key support and responsive design
• Latest messages appear on top

Usage

1. Type a message or select a predefined prompt
2. Press Enter or click Send
3. AI responses appear instantly in the chat interface

Supported APIs

• OpenAI
• Google
• GROQ
• SERPER
• News API

Notes

• Make sure your API keys are configured in the Space secrets
• Built using Streamlit and deployed as a Docker Space

References

https://openai.github.io/openai-agents-python/

https://github.com/openai/openai-agents-python/tree/main/examples/mcp

Project Folder Structure

chatbot/
├── app.py                    # Main Streamlit chatbot interface
├── appagents/
│   ├── __init__.py               # Package initialization
│   ├── OrchestratorAgent.py      # Main orchestrator - coordinates all agents
│   ├── FinancialAgent.py         # Financial data and analysis agent
│   ├── NewsAgent.py              # News retrieval and summarization agent
│   ├── SearchAgent.py            # General web search agent
│   └── InputValidationAgent.py   # Input validation and sanitization agent
├── core/
│   ├── __init__.py               # Package initialization
│   └── logger.py                 # Centralized logging configuration
├── tools/
│   ├── __init__.py               # Package initialization
│   ├── google_tools.py           # Google search API wrapper
│   ├── yahoo_tools.py            # Yahoo Finance API wrapper
│   ├── news_tools.py             # News API wrapper
│   └── time_tools.py             # Time-related utility functions
├── prompts/
│   ├── economic_news.txt         # Prompt for economic news analysis
│   ├── market_sentiment.txt      # Prompt for market sentiment analysis
│   ├── news_headlines.txt        # Prompt for news headline summarization
│   ├── trade_recommendation.txt  # Prompt for trade recommendations
│   └── upcoming_earnings.txt     # Prompt for upcoming earnings alerts
├── Dockerfile                     # Docker configuration for container deployment
├── pyproject.toml                 # Project metadata and dependencies (copied from root)
├── uv.lock                        # Locked dependency versions (copied from root)
├── README.md                      # Project documentation
└── run.py                         # Script to run the application locally

File Descriptions

UI Layer

• app.py - Main Streamlit chatbot interface that provides:
  • Chat message display with user and AI messages
  • Text input for user queries
  • Predefined prompt buttons for quick analysis
  • Real-time AI responses
  • Support for Enter key submission
  • Responsive design with latest messages appearing first

Agents (appagents/)

• OrchestratorAgent.py - Main orchestrator that:

  • Coordinates communication between all specialized agents
  • Routes user queries to appropriate agents
  • Manages conversation flow and context
  • Integrates tool responses

• FinancialAgent.py - Financial data and analysis:

  • Retrieves stock prices and financial metrics
  • Performs financial analysis using Yahoo Finance API
  • Provides market insights and recommendations
  • Integrates with yahoo_tools for data fetching

• NewsAgent.py - News retrieval and summarization:

  • Fetches latest news articles
  • Summarizes news content
  • Integrates with News API for real-time updates
  • Provides news-based market insights

• SearchAgent.py - General web search:

  • Performs web searches for general queries
  • Integrates with Google Search / Serper API
  • Returns relevant search results
  • Supports multi-source data gathering

• InputValidationAgent.py - Input validation:

  • Sanitizes user input
  • Validates query format and content
  • Prevents malicious inputs
  • Ensures appropriate content

Core Utilities (core/)

• logger.py - Centralized logging configuration:
  • Provides consistent logging across agents
  • Handles different log levels
  • Formats log messages for clarity

Tools (tools/)

• google_tools.py - Google Search API wrapper:

  • Executes web searches via Google Search / Serper API
  • Parses and returns search results
  • Handles API authentication

• yahoo_tools.py - Yahoo Finance API integration:

  • Retrieves stock price data
  • Fetches financial metrics and indicators
  • Provides historical price data
  • Returns earnings information

• news_tools.py - News API integration:

  • Fetches latest news articles
  • Filters news by category and keywords
  • Returns news headlines and summaries
  • Provides market-related news feeds

• time_tools.py - Time utility functions:

  • Provides current time information
  • Formats timestamps
  • Handles timezone conversions

Prompts (prompts/)

Predefined prompts for specialized analysis:

• economic_news.txt - Analyzes economic news and implications
• market_sentiment.txt - Analyzes market sentiment trends
• news_headlines.txt - Summarizes and explains news headlines
• trade_recommendation.txt - Provides trading recommendations
• upcoming_earnings.txt - Alerts about upcoming earnings reports

Configuration Files

• Dockerfile - Container deployment:

  • Builds Docker image with Python 3.12
  • Installs dependencies using uv
  • Sets up Streamlit server on port 8501
  • Configures PYTHONPATH for module imports

• pyproject.toml - Project metadata:

  • Package name: "agents"
  • Python version requirement: 3.12
  • Lists all dependencies (OpenAI, LangChain, Streamlit, etc.)

• uv.lock - Dependency lock file:

  • Ensures reproducible builds
  • Pins exact versions of all dependencies

Key Technologies

Component	Technology	Purpose
LLM Framework	OpenAI Agents	Multi-agent orchestration
Chat Interface	Streamlit	User interaction and display
Web Search	Google Search / Serper API	Web search results
Financial Data	Yahoo Finance API	Stock prices and metrics
News Data	News API	Latest news articles
Async Operations	AsyncIO	Parallel agent execution
Dependencies	UV	Fast Python package management
Containerization	Docker	Cloud deployment

Predefined Prompts

The chatbot includes quick-access buttons for common analysis:

1. Economic News - Analyzes current economic trends and news
2. Market Sentiment - Provides market sentiment analysis
3. News Headlines - Summarizes latest news headlines
4. Trade Recommendation - Suggests trading strategies
5. Upcoming Earnings - Lists upcoming company earnings

Running Locally

# Install dependencies
uv sync

# Set environment variables defined in .env.name file
export OPENAI_API_KEY="your-key"
export SERPER_API_KEY="your-key"
export NEWS_API_KEY="your-key"

# Run the Streamlit app (from the root)
python run.py chatbot

Deployment

The project is deployed on Hugging Face Spaces as a Docker container:

• Space: https://huggingface.co/spaces/mishrabp/chatbot-app
• URL: https://mishrabp-chatbot-app.hf.space
• Trigger: Automatic deployment on push to main branch
• Configuration: .github/workflows/chatbot-app-hf.yml