TheSethRose Agent-Chat .cursorrules file for Python (stars: 18)

# Custom Cursor Rules for Phidata Agent running Llama-3.1-Nemotron-70B-Instruct

# General Instructions
general:
  preserve_comments: true   # Preserve comments unless removal is explicitly requested
  version_in_requirements: false   # Do not include specific versions in requirements.txt


# Documentation for Imports
import_statement_validation:
  # Validate that current imports are correct as the documentation is incorrect
  ensure_correct: true
  feedback: "Current phidata documentation has incorrect imports; current imports are correct."
  sources:
    - "https://github.com/phidatahq/phidata"

# Python Best Practices
python_guidelines:
  - Follow PEP 8 style guidelines
  - Use type annotations for all functions
  - Implement proper error handling using try-except blocks
  - Use descriptive variable names reflecting the data or function description

# Pydantic Model Rules
pydantic:
  - Ensure BaseModel usage and proper validation of data models

# Phidata Usage
phidata_guidelines:
  # Validate correct implementation of phi modules
  - Ensure correct integration with Phi's agent and model setup
sources:
  - "https://github.com/phidatahq/phidata"

# Phidata Playground Integration
playground_integration:
  # Instructions for enabling additional functionality in the playground:
  functionalities:
    enable_knowledge_base:
      - task: "Uncomment import for PDFUrlKnowledgeBase and LanceDb, SearchType"
      - task: "Uncomment the knowledge_base initialization in the __init__ method"
      - task: "Set `enable_rag` and `search_knowledge` to True in the Agent initialization"
      - task: "Add `knowledge=knowledge_base` to the Agent initialization"
      - task: "Install required packages: `pip install lancedb tantivy`"
    integrate_database:
      - task: "Create and implement `integrate_with_database` method"
      - task: "Add necessary database connection logic and queries"
      - task: "Install required database package (e.g., `pip install psycopg2-binary` for PostgreSQL)"
    integrate_external_api:
      - task: "Create and implement `integrate_with_api` method"
      - task: "Use the requests library for API calls"
      - task: "Install requests: `pip install requests`"
    add_custom_tool:
      - task: "Create `integrate_with_custom_tool` method"
      - task: "Create a new tool class inheriting from `phi.tools.base.Tool`"
      - task: "Add the tool to the tools list in Agent initialization"
    sources:
        - "https://github.com/phidatahq/phidata"

# LLaMa 3.1 Model Usage
model_specifics:
  llama_usage:
    - Model work is via API; validate API connections for compliance with NVIDIA LLaMa structure and usage benchmarks
    - Ensure compatibility with NVIDIA NeMo framework deployment using prebuilt containers with required hardware and software setups
    - Be aware of inference capabilities: up to 128k input tokens and generating up to 4k tokens
    - Reference performance benchmarks (Arena Hard, AlpacaEval 2 LC) when optimizing or updating model configurations

  # Reward Model Integration
  reward_model_integration:
    - Verify usage and effectiveness of the associated reward model (Llama-3.1-Nemotron-70B-Reward) for improving alignment with human preferences
    - Ensure RLHF approach aligns with safe response rejection capabilities in the associated reward model (e.g., 94% or above on RewardBench)

  # Interactive Components
  interactive_usage:
    - Utilize tools available in Phidata for interactive engagements and functionality expansion
    - Leverage instructions based on Llama's strengths: reasoning, markdown formatting, structured outputs

  source:
    - "Source repository for Phidata: https://github.com/phidatahq/phidata"
    - "Model information source: https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
    - "HelpSteer2-Preference dataset: https://huggingface.co/datasets/nvidia/HelpSteer2"
    - "Reward model information: https://huggingface.co/nvidia/Llama-3.1-Nemotron-70B-Reward"
    - "NVIDIA NeMo deployment guide: https://build.nvidia.com/nvidia/llama-3_1-nemotron-70b-instruct"

# User Preferences
user_preferences:
  # Comments can only be changed with explicit permission from the user
  comments_modification: false