configuration README.md

README.md

@@ -80,7 +80,7 @@ ollama list
 
 You should see both `llama3.2` and `mxbai-embed-large` in the list of available models.
 
-Note: While Ollama is the default choice for easy setup, KnowLang supports other LLM providers through configuration.
+Note: While Ollama is the default choice for easy setup, KnowLang supports other LLM providers through configuration. See our [Configuration Guide](configuration.md) for using alternative providers like OpenAI or Anthropic.
 
 ## Quick Start
 

configuration.md

@@ -0,0 +1,100 @@
+# Configuration Guide
+
+KnowLang uses [pydantic-settings](https://docs.pydantic.dev/latest/concepts/pydantic_settings/) for configuration management. Settings can be provided through environment variables, `.env` files, or programmatically.
+
+## Quick Start
+
+1. Copy the example configuration:
+```bash
+cp .env.example .env
+```
+
+2. Modify settings as needed in `.env`
+
+## Core Settings
+
+### LLM Settings
+```env
+# Default is Ollama with llama3.2
+LLM__MODEL_NAME=llama3.2
+LLM__MODEL_PROVIDER=ollama
+LLM__API_KEY=your_api_key  # Required for providers like OpenAI
+```
+
+Supported providers:
+- `ollama`: Local models through Ollama
+- `openai`: OpenAI models (requires API key)
+- `anthropic`: Anthropic models (requires API key)
+
+### Embedding Settings
+```env
+# Default is Ollama with mxbai-embed-large
+EMBEDDING__MODEL_NAME=mxbai-embed-large
+EMBEDDING__MODEL_PROVIDER=ollama
+EMBEDDING__API_KEY=your_api_key  # Required for providers like OpenAI
+```
+
+### Database Settings
+```env
+# ChromaDB configuration
+DB__PERSIST_DIRECTORY=./chromadb/mycode
+DB__COLLECTION_NAME=code
+DB__CODEBASE_DIRECTORY=./
+```
+
+### Parser Settings
+```env
+# Language support and file patterns
+PARSER__LANGUAGES='{"python": {"enabled": true, "file_extensions": [".py"]}}'
+PARSER__PATH_PATTERNS='{"include": ["**/*"], "exclude": ["**/venv/**", "**/.git/**"]}'
+```
+
+### Chat Interface Settings
+```env
+CHAT__MAX_CONTEXT_CHUNKS=5
+CHAT__SIMILARITY_THRESHOLD=0.7
+CHAT__INTERFACE_TITLE='Code Repository Q&A Assistant'
+```
+
+## Advanced Configuration
+
+### Using Multiple Models
+
+You can configure different models for different purposes:
+```env
+# Main LLM for responses
+LLM__MODEL_NAME=llama3.2
+LLM__MODEL_PROVIDER=ollama
+
+# Evaluation model
+EVALUATOR__MODEL_NAME=gpt-4
+EVALUATOR__MODEL_PROVIDER=openai
+
+# Embedding model
+EMBEDDING__MODEL_NAME=mxbai-embed-large
+EMBEDDING__MODEL_PROVIDER=ollama
+```
+
+### Reranker Configuration
+```env
+RERANKER__ENABLED=true
+RERANKER__MODEL_NAME=rerank-2
+RERANKER__MODEL_PROVIDER=voyage
+RERANKER__TOP_K=4
+```
+
+### Analytics Integration
+```env
+CHAT_ANALYTICS__ENABLED=true
+CHAT_ANALYTICS__PROVIDER=mixpanel
+CHAT_ANALYTICS__API_KEY=your_api_key
+```
+
+
+## Further Reading
+
+- For detailed settings configuration options, see [pydantic-settings documentation](https://docs.pydantic.dev/latest/concepts/pydantic_settings/)
+- For model-specific configuration, see provider documentation:
+  - [Ollama Models](https://ollama.ai/library)
+  - [OpenAI Models](https://platform.openai.com/docs/models)
+  - [Anthropic Models](https://www.anthropic.com/models)