Structsense getting started

docs/structsense_getting_started.md

@@ -47,6 +47,13 @@ export EXTERNAL_PDF_EXTRACTION_SERVICE=True
 ```
 > The external API is assumed public (no auth) for now.
 
+### LLM
+#### LLM for Agents
+We are using OpenRouter to access models like GPT for agents. However, Ollama can also serve as a substitute for OpenRouter when using open-source models such as Llama.
+
+#### Embedding configuration
+In our default setup, Ollama is used for embedding generation. You can also use other models via OpenRouter for this purpose.
+
 <!--Running -->
 
 ## Running
@@ -82,7 +89,6 @@ Disabled by default. Enable with:
 The `docker/` directory contains **Docker Compose** files for running the following components:
 
 - **Grobid** – for PDF extraction
-- **Ollama** – In our setup, Ollama is used for embedding generation. However, it can also serve as a substitute for OpenRouter when using open-source models such as Llama for agents. OpenRouter, on the other hand, provides access to various proprietary models like GPT.
 - **Weaviate** – In our StructSense architecture, Weaviate acts as the vector database responsible for storing the ontology, effectively serving as the Ontology database.
 
 These Compose files allow you to quickly stand up a complete local **StructSense** stack.

docs/structsense_overview.md

@@ -14,4 +14,9 @@ It orchestrates specialized agents to collaborate, align to schemas/ontologies,
 ## Architecture
 ![StructSense Architecture](images/structsense_arch.png)
 
+## Quickstart
+
+```bash
+pip install structsense
+```