socratic-nexus 0.4.0

Universal LLM client for production - works with Claude, GPT-4, Gemini, Llama, and any LLM. Built-in integrations with Openclaw, LangChain, and LangGraph.

Socratic Nexus

A universal LLM client library providing unified access to multiple AI providers with a consistent interface.

Features

• Multi-Provider Support: Works with Anthropic (Claude), OpenAI (GPT-4), Google (Gemini), Ollama, and HuggingFace
• Unified Interface: Consistent API across all providers
• Async/Sync Support: Full async/await support with optional synchronous API
• Production Ready: 70%+ test coverage, comprehensive error handling
• Token Tracking: Built-in token usage monitoring and cost estimation
• Caching: Intelligent response caching with optional Redis support
• Type Safe: Full type hints with mypy support
• No Lock-in: Easy to switch between providers without code changes

Installation

Basic Installation

pip install socratic-nexus

With Specific Providers

# Claude/Anthropic
pip install socratic-nexus[anthropic]

# OpenAI
pip install socratic-nexus[openai]

# Google Gemini
pip install socratic-nexus[google]

# Ollama (local LLMs)
pip install socratic-nexus[ollama]

# All providers
pip install socratic-nexus[all]

With Integrations

# LangChain support
pip install socratic-nexus[langchain]

# Everything
pip install socratic-nexus[full]

Quick Start

Using Claude (Anthropic)

from socratic_nexus.clients import ClaudeClient

# Initialize with API key
client = ClaudeClient(api_key="sk-ant-...")

# Generate a response
response = client.generate_response(
    "Explain quantum computing in simple terms"
)
print(response)

# Generate code
code = client.generate_code(
    "Create a Python function to calculate fibonacci numbers"
)
print(code)

# Extract insights
insights = client.extract_insights(
    "Why is photosynthesis important for Earth's ecosystem?",
    project_name="biology_study"
)
print(insights)

Using OpenAI (GPT-4)

from socratic_nexus.clients import OpenAIClient

client = OpenAIClient(api_key="sk-...")

response = client.generate_response(
    "What are the key principles of machine learning?"
)
print(response)

Using Google Gemini

from socratic_nexus.clients import GoogleClient

client = GoogleClient(api_key="...")

response = client.generate_response(
    "Explain blockchain technology"
)
print(response)

Using Ollama (Local Models)

from socratic_nexus.clients import OllamaClient

# Ollama runs locally, no API key needed
client = OllamaClient(base_url="http://localhost:11434")

response = client.generate_response(
    "What is the capital of France?"
)
print(response)

Async Usage

import asyncio
from socratic_nexus.clients import ClaudeClient

async def main():
    client = ClaudeClient(api_key="sk-ant-...")

    response = await client.generate_response_async(
        "Explain the theory of relativity"
    )
    print(response)

asyncio.run(main())

Core Clients

ClaudeClient

Anthropic's Claude model with specialized methods:

• generate_response() - General text generation
• generate_code() - Code generation
• extract_insights() - Extract key insights
• generate_documentation() - Create documentation
• generate_business_plan() - Business planning
• generate_curriculum() - Learning curriculum design
• generate_research_protocol() - Research methodology
• And 10+ more specialized generators

OpenAIClient

OpenAI's GPT models with:

• Cost calculation based on token usage
• Support for GPT-4, GPT-4 Turbo, GPT-3.5
• Configurable temperature and parameters

GoogleClient

Google's Gemini models with:

• Multi-modal support
• Advanced safety settings
• Model variant selection (pro, pro-vision)

OllamaClient

Local LLM support for:

• Running models locally without API keys
• Custom model selection
• Development and testing without cloud costs

Architecture

Socratic-nexus follows a layered architecture:

Application Code
       ↓
   Client Layer (ClaudeClient, OpenAIClient, etc.)
       ↓
   Provider Abstraction Layer
       ↓
   Provider-Specific Implementations
       ↓
   External LLM APIs

Each client:

• Handles provider-specific authentication
• Normalizes request/response formats
• Manages async/sync variants
• Tracks token usage and costs
• Implements caching and retry logic

See ARCHITECTURE.md for detailed architecture documentation.

API Reference

Base Client Interface

All clients implement these core methods:

# Generate a response to a prompt
response = client.generate_response(
    prompt: str,
    max_tokens: int = 1024,
    temperature: float = 0.7
) -> str

# Generate code from specifications
code = client.generate_code(
    specification: str,
    language: str = "python"
) -> str

# Extract key insights from text
insights = client.extract_insights(
    text: str,
    project: Optional[ProjectContext] = None
) -> str

# Async variants
response = await client.generate_response_async(...)
code = await client.generate_code_async(...)
insights = await client.extract_insights_async(...)

Token Usage Tracking

Each response includes token usage information:

from socratic_nexus.clients import ClaudeClient

client = ClaudeClient(api_key="sk-ant-...")
response = client.generate_response("Your prompt here")

# Token information available in response metadata
print(f"Input tokens: {response.metadata.input_tokens}")
print(f"Output tokens: {response.metadata.output_tokens}")
print(f"Estimated cost: ${response.metadata.cost_usd}")

See docs/API_REFERENCE.md for complete API documentation.

Configuration

Environment Variables

Set provider API keys via environment variables:

export ANTHROPIC_API_KEY="sk-ant-..."
export OPENAI_API_KEY="sk-..."
export GOOGLE_API_KEY="..."

Then initialize clients without explicit keys:

from socratic_nexus.clients import ClaudeClient

# Reads from ANTHROPIC_API_KEY
client = ClaudeClient()

Client Configuration

from socratic_nexus.clients import ClaudeClient

client = ClaudeClient(
    api_key="sk-ant-...",
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    temperature=0.7,
    timeout=30
)

Error Handling

from socratic_nexus.clients import ClaudeClient
from anthropic import APIError

try:
    client = ClaudeClient(api_key="invalid-key")
    response = client.generate_response("Test prompt")
except APIError as e:
    print(f"API Error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")

Testing

Run the test suite:

pytest tests/

With coverage:

pytest --cov=socratic_nexus tests/

Run specific test categories:

# Unit tests only
pytest -m unit

# Integration tests (requires API keys)
pytest -m integration

Performance

• Response Caching: Configurable in-memory caching
• Async Support: Non-blocking API calls for high concurrency
• Connection Pooling: Efficient HTTP connection management
• Retry Logic: Automatic retry with exponential backoff

Typical response times (with caching disabled):

• Claude: 1-5s per request
• GPT-4: 1-3s per request
• Gemini: 500ms-2s per request
• Ollama (local): 100ms-1s per request

Security

• API Key Protection: Never logged or cached
• HTTPS Only: All communication encrypted
• No Request Logging: Sensitive data not persisted
• Input Validation: All requests validated before sending

For security issues, please see SECURITY.md.

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Ensure all tests pass and coverage remains above 70%
5. Submit a pull request

See CONTRIBUTING.md for detailed guidelines.

License

MIT License - See LICENSE file for details.

Support

• Documentation: docs/
• API Reference: docs/API_REFERENCE.md
• Quickstart Guide: docs/quickstart.md
• GitHub Issues: Report bugs
• Discussions: Ask questions

Roadmap

• Support for additional providers (Cohere, Together AI, etc.)
• Function calling for all providers
• Streaming response support
• Advanced RAG integration
• Cost optimization features
• Rate limiting and quota management

Changelog

See CHANGELOG.md for release notes and version history.

Related Projects

• Socratic Nexus Agents - Agent framework built on socratic-nexus
• Socratic RAG - Retrieval-augmented generation
• Socratic Analyzer - Quality analysis and evaluation

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