Update README and add env.example file

duttakapil · duttakapil · commit 4830f1999100 · 2025-02-17T23:30:52.000+05:30
diff --git a/.env.example b/.env.example
@@ -0,0 +1,22 @@
+# LLM API Keys
+ANTHROPIC_API_KEY=your_anthropic_api_key_here
+OPENAI_API_KEY=your_openai_api_key_here
+GOOGLE_APPLICATION_CREDENTIALS=path_to_your_google_credentials.json
+AZURE_OPENAI_API_KEY=your_azure_openai_api_key_here
+AZURE_OPENAI_ENDPOINT=your_azure_openai_endpoint_here
+
+# Model Configuration
+DEFAULT_MODEL=claude-3-opus-20240229  # For Anthropic
+# DEFAULT_MODEL=gpt-4-turbo-preview   # For OpenAI
+# DEFAULT_MODEL=gemini-pro           # For Google
+# DEFAULT_MODEL=gpt-4                # For Azure OpenAI
+
+# API Configuration
+MAX_RETRIES=3
+REQUEST_TIMEOUT=30
+TEMPERATURE=0.7
+MAX_TOKENS=1000
+
+# Logging Configuration
+LOG_LEVEL=INFO
+LOG_FILE=llm_patterns.log 
diff --git a/.gitignore b/.gitignore
@@ -1 +1,60 @@
-.DS_Store
+# Cursor Logs
+.cursorlogs
+
+# macOS
+.DS_Store
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual Environment
+venv/
+env/
+ENV/
+.env
+.venv
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Environment Variables
+.env
+.env.local
+.env.*.local
+
+# Logs
+*.log
+logs/
+.cursorlogs
+
+# Testing
+.coverage
+htmlcov/
+.pytest_cache/
+.tox/
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
diff --git a/LICENSE b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 Coderplex Tech
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/README.md b/README.md
@@ -15,55 +15,189 @@ This repository provides:
 
 ### Building Blocks
 
-- **Augmented LLM**: Basic LLM integration with retrieval, tools, and memory
-- **Tool Integration**: Patterns for designing and implementing LLM tools
+- ✅ **Augmented LLM**: Basic LLM integration with retrieval, tools, and memory
+  - Web search, calculator, and weather tools
+  - Memory management
+  - Tool integration framework
 
 ### Workflows
 
-- **Prompt Chaining**: Sequential LLM calls with intermediate processing
-- **Routing**: Input classification and specialized handling
-- **Parallelization**: Concurrent LLM processing with sectioning and voting
-- **Orchestrator-Workers**: Dynamic task decomposition and delegation
-- **Evaluator-Optimizer**: Iterative improvement through feedback loops
+- ✅ **Prompt Chaining**: Sequential LLM calls with intermediate processing
+
+  - Text analysis example
+  - Chain building and execution
+  - Context management
+
+- ✅ **Routing**: Input classification and specialized handling
+
+  - Support ticket routing example
+  - Dynamic route selection
+  - Fallback handling
+
+- ✅ **Parallelization**: Concurrent LLM processing with sectioning and voting
+
+  - Content moderation example
+  - Multiple voting strategies
+  - Result combination
+
+- ✅ **Orchestrator-Workers**: Dynamic task decomposition and delegation
+
+  - Document processing example
+  - Task distribution
+  - Worker management
+
+- ✅ **Evaluator-Optimizer**: Iterative improvement through feedback loops
+  - Code optimization example
+  - Multiple optimization strategies
+  - Progress tracking
 
 ### Agents
 
-- **Autonomous Agents**: Self-directed systems with planning and execution
-- **Domain-Specific Agents**: Implementations for customer support, coding, etc.
+- ✅ **Autonomous Agents**: Self-directed systems with planning and execution
+
+  - Research assistant example
+  - Dynamic planning
+  - Tool utilization
+
+- ✅ **Domain-Specific Agents**: Implementations for specialized domains
+  - Medical diagnosis example
+  - Domain knowledge integration
+  - Constraint enforcement
 
 ## Getting Started
 
-Each pattern includes:
+### Prerequisites
 
-- Architectural overview
-- Implementation examples using different LLM providers:
-  - Anthropic Claude
-  - OpenAI GPT
-  - Google Vertex AI
-  - Azure OpenAI
-- Test cases and example outputs
-- Best practices and common pitfalls
+- Python 3.8+
+- API keys for the LLM provider(s) you want to use
+- Git for version control
 
-## Usage
+### Installation
 
-Navigate to the specific pattern you're interested in:
+1. Clone the repository:
 
 ```bash
-examples/
-  workflows/prompt-chaining/  # For prompt chaining examples
-  agents/autonomous-agent/    # For autonomous agent examples
+git clone https://github.com/coderplex-tech/building-with-llms.git
+cd building-with-llms
 ```
 
-Each example contains a standalone implementation that you can run with your API keys.
+2. Create and activate a virtual environment:
 
-## Prerequisites:
+```bash
+python -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+```
 
-- Python 3.8+
-- API keys for the LLM provider(s) you want to use
+3. Install dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+4. Set up environment variables:
+
+```bash
+cp .env.example .env
+# Edit .env with your API keys and configuration
+```
+
+### Running Examples
+
+Each pattern includes standalone examples that demonstrate its usage. Here's how to run them:
+
+1. **Building Blocks**:
+
+```bash
+# Augmented LLM example
+python -m building-block.augmented-llm.examples.basic_usage
+```
+
+2. **Workflows**:
+
+```bash
+# Prompt Chaining
+python -m workflows.prompt-chaining.examples.text_analysis
+
+# Routing
+python -m workflows.routing.examples.support_routing
+
+# Parallelization
+python -m workflows.parallelization.examples.content_moderation
+
+# Orchestrator-Workers
+python -m workflows.orchestrator-workers.examples.document_processing
+
+# Evaluator-Optimizer
+python -m workflows.evaluator-optimizer.examples.code_optimization
+```
+
+3. **Agents**:
+
+```bash
+# Autonomous Agent
+python -m agents.autonomous-agent.examples.research_assistant
+
+# Domain-Specific Agent
+python -m agents.domain-specific.examples.medical_assistant
+```
+
+### Directory Structure
+
+```
+├── building-block/
+│   └── augmented-llm/          # Basic LLM integration
+├── workflows/
+│   ├── prompt-chaining/        # Sequential processing
+│   ├── routing/                # Input classification
+│   ├── parallelization/        # Concurrent processing
+│   ├── orchestrator-workers/   # Task decomposition
+│   └── evaluator-optimizer/    # Iterative improvement
+├── agents/
+│   ├── autonomous-agent/       # Self-directed systems
+│   └── domain-specific/        # Specialized agents
+├── requirements.txt            # Project dependencies
+├── .env.example               # Example environment variables
+└── README.md                  # This file
+```
+
+## Implementation Details
+
+Each pattern is implemented with:
+
+- Core classes and interfaces
+- Example implementations
+- Comprehensive documentation
+- Unit tests (coming soon)
+- Best practices and usage guidelines
+
+### Current Features
+
+- Multiple LLM provider support (Anthropic, OpenAI, etc.)
+- Async/await for efficient processing
+- Type hints and Pydantic models
+- Error handling and retries
+- Detailed logging
+- Configuration management
+
+### Coming Soon
+
+- Additional examples for each pattern
+- Integration tests
+- Performance benchmarks
+- CI/CD pipeline
+- Docker containerization
+- API documentation
 
 ## Contributing
 
-We welcome contributions! Please see our Contributing Guide for details.
+We welcome contributions! Here's how you can help:
+
+1. Fork the repository
+2. Create a feature branch
+3. Make your changes
+4. Submit a pull request
+
+Please ensure your code follows our style guide and includes appropriate tests and documentation.
 
 ## Why Native Implementations?
 
@@ -76,6 +210,17 @@ While frameworks like LangChain can be useful, we believe building directly with
 
 ## Resources
 
-- Architecture Decision Records
-- Pattern Documentation
-- Implementation Guides
+- 📚 [Pattern Documentation](./docs)
+- 🔧 [Implementation Guides](./guides)
+- 📊 [Architecture Decision Records](./adr)
+- 🧪 [Example Collection](./examples)
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## Acknowledgments
+
+- Thanks to all contributors
+- Inspired by software architecture patterns and LLM best practices
+- Built with modern Python async/await patterns
