Add config.yaml example file

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Ruben Lucas 2025-04-16 11:11:56 +02:00
parent 498b06bb3b
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# Define your application settings here.
chat_backend: local # Select the primary chat backend (azure, openai, google_vertex, aws, local)
emb_backend: local # Select the primary embedding backend (azure, openai, google_vertex, aws, local, huggingface)
use_conditional_graph: false # Use a conditional RAG model with historical chat context, or a non-conditional model without access to the current conversation
# --- Provider Specific Settings ---
azure:
openai_api_key: "your_openai_api_key"
llm_endpoint: "https://example.openai.azure.com"
llm_deployment_name: "gpt-4o-mini"
llm_api_version: "2025-01-01-preview"
emb_endpoint: "https://example.openai.azure.com" # Can be same as LLM endpoint
emb_deployment_name: "text-embedding-3-large"
emb_api_version: "2023-05-15"
openai:
openai_api_key: "your_openai_api_key"
chat_model: "gpt-4o-mini"
emb_model: "text-embedding-3-large"
google_vertex:
project_id: "your_gcp_project_id"
location: "europe-west4"
chat_model: "gemini-pro"
emb_model: "textembedding-gecko@001"
aws:
region: "us-east-1"
credentials: "PATH_TO_YOUR_CREDENTIALS_FILE.json"
local: # Settings for local models (e.g., Ollama)
chat_model: "llama3.1:8b"
emb_model: "llama3.1:8b"
huggingface: # Settings specific to HuggingFace embedding backend
emb_model: "sentence-transformers/paraphrase-MiniLM-L12-v2"
# --- Data Processing Settings ---
pdf:
# List of paths to PDF files or folders containing PDFs.
# Pydantic converts these strings to pathlib.Path objects.
data:
- "C:/path/folder"
unstructured: false # Use the unstructured PDF loader?
chunk_size: 1000
chunk_overlap: 200
add_start_index: false
web:
# List of URLs to scrape for data.
data:
- "https://www.example.nl/subdomain"
chunk_size: 200
chroma_db:
location: "/app/data/vector_database" # Override default DB path (default: '.chroma_db')
reset: True # Reset the database on startup? (default: false)