feat: Add OCI Gen AI Integration for Direct LLM Support

README_OCI_GENAI.md

@@ -0,0 +1,207 @@
+# OCI Gen AI Integration for Ragas
+
+This contribution adds direct support for Oracle Cloud Infrastructure (OCI) Generative AI models in Ragas, enabling evaluation without requiring LangChain or LlamaIndex.
+
+## 🚀 Features
+
+- **Direct OCI Integration**: Uses OCI Python SDK directly, no LangChain/LlamaIndex dependency
+- **Multiple Model Support**: Works with Cohere, Meta, Mistral, and other OCI Gen AI models
+- **Async Support**: Full async/await support for high-performance evaluation
+- **Error Handling**: Comprehensive error handling and retry mechanisms
+- **Analytics Tracking**: Built-in usage tracking and analytics
+- **Flexible Configuration**: Support for custom OCI configs and endpoints
+
+## 📦 Installation
+
+```bash
+# Install Ragas with OCI support
+pip install ragas[oci]
+
+# Or install OCI SDK separately
+pip install oci>=2.160.1
+```
+
+## 🔧 Quick Start
+
+```python
+from ragas.llms import oci_genai_factory
+from ragas import evaluate
+from datasets import Dataset
+
+# Initialize OCI Gen AI LLM
+llm = oci_genai_factory(
+    model_id="cohere.command",
+    compartment_id="ocid1.compartment.oc1..example"
+)
+
+# Your dataset
+dataset = Dataset.from_dict({
+    "question": ["What is the capital of France?"],
+    "answer": ["Paris"],
+    "contexts": [["France is a country in Europe. Its capital is Paris."]],
+    "ground_truth": ["Paris"]
+})
+
+# Evaluate with OCI Gen AI
+result = evaluate(dataset, llm=llm)
+```
+
+## 🏗️ Architecture
+
+### Files Added/Modified
+
+- `src/ragas/llms/oci_genai_wrapper.py` - Main OCI Gen AI wrapper implementation
+- `src/ragas/llms/__init__.py` - Updated to export OCI Gen AI classes
+- `pyproject.toml` - Added OCI as optional dependency
+- `tests/unit/test_oci_genai_wrapper.py` - Comprehensive test suite
+- `docs/howtos/integrations/oci_genai.md` - Complete documentation
+- `examples/oci_genai_example.py` - Working example script
+
+### Key Components
+
+1. **OCIGenAIWrapper**: Main LLM wrapper class
+2. **oci_genai_factory**: Factory function for easy initialization
+3. **Comprehensive Testing**: Unit tests with mocking
+4. **Documentation**: Complete usage guide and examples
+
+## 🧪 Testing
+
+```bash
+# Run OCI Gen AI tests
+pytest tests/unit/test_oci_genai_wrapper.py -v
+
+# Run example script
+python examples/oci_genai_example.py
+```
+
+## 📚 Documentation
+
+- [Complete Integration Guide](docs/howtos/integrations/oci_genai.md)
+- [OCI Python SDK Documentation](https://docs.oracle.com/en-us/iaas/tools/python/2.160.1/api/generative_ai.html)
+- [Ragas Documentation](https://docs.ragas.io)
+
+## 🔑 Configuration
+
+### OCI Authentication
+
+```python
+# Option 1: Use OCI CLI config
+# oci setup config
+
+# Option 2: Environment variables
+export OCI_CONFIG_FILE=~/.oci/config
+export OCI_PROFILE=DEFAULT
+
+# Option 3: Manual configuration
+config = {
+    "user": "ocid1.user.oc1..example",
+    "key_file": "~/.oci/private_key.pem",
+    "fingerprint": "your_fingerprint",
+    "tenancy": "ocid1.tenancy.oc1..example",
+    "region": "us-ashburn-1"
+}
+```
+
+### Supported Models
+
+- **Cohere**: `cohere.command`, `cohere.command-light`
+- **Meta**: `meta.llama-3-8b`, `meta.llama-3-70b`
+- **Mistral**: `mistral.mistral-7b-instruct`
+- **And more**: Check OCI documentation for latest models
+
+## 🚀 Usage Examples
+
+### Basic Usage
+
+```python
+from ragas.llms import oci_genai_factory
+
+llm = oci_genai_factory(
+    model_id="cohere.command",
+    compartment_id="ocid1.compartment.oc1..example"
+)
+```
+
+### Advanced Configuration
+
+```python
+from ragas.llms import oci_genai_factory
+from ragas.run_config import RunConfig
+
+# Custom configuration
+config = {
+    "user": "ocid1.user.oc1..example",
+    "key_file": "~/.oci/private_key.pem",
+    "fingerprint": "your_fingerprint",
+    "tenancy": "ocid1.tenancy.oc1..example",
+    "region": "us-ashburn-1"
+}
+
+# Custom run configuration
+run_config = RunConfig(timeout=60, max_retries=3)
+
+llm = oci_genai_factory(
+    model_id="cohere.command",
+    compartment_id="ocid1.compartment.oc1..example",
+    config=config,
+    endpoint_id="ocid1.endpoint.oc1..example",  # Optional
+    run_config=run_config
+)
+```
+
+### With Different Models
+
+```python
+# Cohere Command
+llm_cohere = oci_genai_factory(
+    model_id="cohere.command",
+    compartment_id="ocid1.compartment.oc1..example"
+)
+
+# Meta Llama
+llm_llama = oci_genai_factory(
+    model_id="meta.llama-3-8b",
+    compartment_id="ocid1.compartment.oc1..example"
+)
+```
+
+## 🐛 Troubleshooting
+
+### Common Issues
+
+1. **Authentication Errors**: Verify OCI configuration and credentials
+2. **Model Not Found**: Check if model exists in your compartment
+3. **Permission Errors**: Ensure proper IAM policies for Generative AI
+
+### Debug Mode
+
+```python
+import logging
+logging.basicConfig(level=logging.DEBUG)
+
+# Your OCI Gen AI code here
+```
+
+## 🤝 Contributing
+
+This integration follows Ragas patterns and conventions:
+
+- Extends `BaseRagasLLM` abstract class
+- Implements required methods: `generate_text`, `agenerate_text`, `is_finished`
+- Includes comprehensive error handling
+- Provides analytics tracking
+- Follows existing code style and patterns
+
+## 📄 License
+
+This contribution is part of the Ragas project and follows the same license terms.
+
+## 🙏 Acknowledgments
+
+- Oracle Cloud Infrastructure team for the Python SDK
+- Ragas team for the excellent evaluation framework
+- Open source community for inspiration and feedback
+
+---
+
+**Ready to evaluate with OCI Gen AI?** Check out the [complete documentation](docs/howtos/integrations/oci_genai.md) and [example script](examples/oci_genai_example.py)!

docs/howtos/integrations/index.md

@@ -15,6 +15,7 @@ happy to look into it 🙂
 - [LlamaIndex for RAG](./_llamaindex.md) - LlamaIndex is a framework for building RAG applications, more information can be found [here](https://www.llamaindex.ai/).
 - [LlamaIndex for Agents](./llamaindex_agents.md) - LlamaIndex enables building intelligent, semi-autonomous agents, more information can be found [here](https://www.llamaindex.ai/).
 - [LlamaStack](./llama_stack.md) – A unified framework by Meta for building and deploying generative AI apps across local, cloud, and mobile; [docs](https://llama-stack.readthedocs.io/en/latest/)
+- [OCI Gen AI](./oci_genai.md) - Oracle Cloud Infrastructure Generative AI provides access to various LLM models including Cohere, Meta, and Mistral models for RAG evaluation.
 - [R2R](./r2r.md) - R2R is an all-in-one solution for AI Retrieval-Augmented Generation (RAG) with production-ready features, more information can be found [here](https://r2r-docs.sciphi.ai/introduction)
 - [Swarm](./swarm_agent_evaluation.md) - Swarm is a framework for orchestrating multiple AI agents, more information can be found [here](https://github.com/openai/swarm).