- Moved handoff example scripts to a new directory structure for better organisation.
- Updated paths to reflect the new locations of the files.
This change aims to enhance the clarity and maintainability of the codebase.
- simple_input.py: Basic user input example
- medium_complexity_input.py: Multiple inputs with tools and context
- advanced_dynamic_input.py: Class-based system with conditional logic
- environment_variable_input.py: Combining env vars with user input
- streamlit_ui_input.py: Web-based UI for dynamic input
These examples demonstrate various approaches to handling dynamic user input in PraisonAI agents.
Closes#66
Co-authored-by: Mervin Praison <[email protected]>
- 01_basic_state_management.py: Demonstrates fundamental state operations
- 02_state_in_tool_functions.py: Shows state usage within tool functions
- 03_conditional_task_execution.py: Illustrates conditional task flow based on state
- 04_session_state_persistence.py: Shows how to save/restore workflow state
- 05_loop_control_with_state.py: Demonstrates state-controlled loops and iterations
- 06_advanced_state_operations.py: Covers complex state scenarios and patterns
Each example is fully working with detailed documentation and real-world use cases.
Co-authored-by: Mervin Praison <[email protected]>
- Enhanced Session class to support remote agent URLs
- Added agent_url parameter for direct agent connectivity
- Implemented HTTP client for remote agent communication
- Added connection testing and validation
- Provided send_message() alias for Google ADK compatibility
- Created comprehensive examples and documentation
- Maintained full backward compatibility
- Added proper error handling for remote operations
Fixes#630
Co-authored-by: MervinPraison <[email protected]>
- Fix SQLite query compatibility in session state restoration
- Add type safety to increment_state and improve append_to_state
- Change API from session.create_agent() to session.Agent() (backward compatible)
- Clean up code style: remove unused imports, trailing whitespace, fix f-strings
- Fix missing limit parameter in search_knowledge method
- Update examples to use new API
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: MervinPraison <[email protected]>
Add minimal enhancements to PraisonAI's existing stateful capabilities:
- Add Session helper class for unified session management
- Add 9 convenience methods to PraisonAIAgents for enhanced state management
- Add comprehensive stateful agents documentation with examples
- Add 3 practical examples demonstrating session, workflow, and memory capabilities
- Maintain backward compatibility - all existing code continues to work
The implementation leverages existing robust infrastructure (Memory, Agent, Process classes)
rather than duplicating functionality, providing better developer experience through
improved APIs and documentation.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <[email protected]>
Fixes#289 - Multi-agent context issue
This solution demonstrates how to solve the domain context problem where tools
default to "example.com" instead of user-specified domains. Uses 4 existing
PraisonAI features:
1. Custom tool wrappers with domain injection
2. Agent instructions with domain context
3. Task context parameter for domain info
4. Shared memory for context persistence
Key benefits:
- No core SDK changes required
- Uses only existing framework features
- Multi-layer context reliability
- 100% backward compatible
- Works for hierarchical and other processes
Co-authored-by: MervinPraison <[email protected]>
This commit deletes the outdated test_approval_basic.py file, which contained basic tests for the human approval system. The tests are no longer necessary as the functionality has been integrated into other components.
Files modified:
- Deleted test_approval_basic.py
- Add graph memory configuration support to Memory class
- Enhanced Knowledge class with graph store support
- Added optional graph dependency group in pyproject.toml
- Comprehensive examples demonstrating graph memory usage
- Maintained full backward compatibility
- Added test scripts to verify implementation
Supports Neo4j and Memgraph as graph store providers.
Install with: pip install "praisonaiagents[graph]"
Co-authored-by: MervinPraison <[email protected]>
This commit provides working examples and comprehensive documentation for using MCP tools with Streamlit, without modifying core MCP implementation.
Key fixes:
- Proper session state management to prevent agent re-initialization
- Use standard LLM format instead of provider/model format
- Comprehensive error handling and user feedback
- Working examples with troubleshooting guidance
Files added:
- examples/python/ui/mcp-streamlit-airbnb.py - Complete working Streamlit app
- examples/python/ui/mcp-streamlit-simple.py - Simple fixed version of original code
- docs/ui/streamlit/mcp-streamlit.mdx - Comprehensive documentation and troubleshooting
The root issue was improper usage patterns in Streamlit, not the core MCP implementation.
Co-authored-by: MervinPraison <[email protected]>
🤖 Generated with [Claude Code](https://claude.ai/code)
- Multi-agent system with 6 specialized research agents
- Customizable parameters for company, geography, industry, and sections
- YAML configuration for easy setup and customization
- FastAPI integration with async job processing and REST API
- Professional report generation suitable for business decision-making
- Jupyter notebook with multiple implementation examples
- Complete documentation and usage guidelines
Addresses issue #18 - Secondary market research agent with customization
Co-authored-by: MervinPraison <[email protected]>
- Add simple CSV URL processor for basic use cases
- Add comprehensive CSV processing with 4 different methods
- Add complete documentation with setup and troubleshooting
- Address GitHub issue #23: "How to pass in a CSV file"
- Support sequential processing of URLs and other CSV data
- Include validation, error handling, and multiple processing patterns
Co-authored-by: MervinPraison <[email protected]>
- Add comprehensive camera integration examples in examples/python/camera/
- camera-basic.py: Single frame capture and analysis
- camera-continuous.py: Continuous monitoring system
- camera-multi-agent.py: Multi-agent parallel analysis
- camera-video-analysis.py: Video recording and temporal analysis
- README.md: Complete documentation for all examples
- Add camera integration documentation in docs/features/camera-integration.mdx
- Complete integration patterns and use cases
- Configuration options and best practices
- Troubleshooting guide and security considerations
- Links to example code
- Update docs/mint.json to include camera integration in navigation
Addresses issue #238 regarding multimodel agent camera input
Co-authored-by: MervinPraison <[email protected]>
- Implement SearxNG search tool following PraisonAI patterns
- Add comprehensive documentation with setup instructions
- Include working examples for both tools and agents
- Support configurable SearxNG URL and search parameters
- Integrate with existing tools registry and documentation
- Provide privacy-focused alternative to traditional search engines
Addresses issue #337
Co-authored-by: MervinPraison <[email protected]>
