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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)