Docs update

README.md

@@ -6,8 +6,6 @@ Open-source agentic framework for building intelligent research agents using Sch
 
 The library includes extensible tools for search, reasoning, and clarification, real-time streaming responses, OpenAI-compatible REST API. Works with any OpenAI-compatible LLM, including local models for fully private research.
 
-______________________________________________________________________
-
 ## Why use SGR Agent Core?
 
 - **Schema-Guided Reasoning** — SGR combines structured reasoning with flexible tool selection
@@ -17,8 +15,6 @@ ______________________________________________________________________
 - **Real-time Streaming** — Built-in support for streaming responses via SSE
 - **Production Ready** — Battle-tested with comprehensive test coverage and Docker support
 
-______________________________________________________________________
-
 ## Documentation
 
 > **Get started quickly with our documentation:**
@@ -27,25 +23,61 @@ ______________________________________________________________________
 - **[Framework Quick Start Guide](https://vamplabai.github.io/sgr-agent-core/framework/first-steps/)** - Get up and running in minutes
 - **[DeepSearch Service Documentation](https://vamplabai.github.io/sgr-agent-core/sgr-api/SGR-Quick-Start/)** - REST API reference with examples
 
-______________________________________________________________________
-
 ## Quick Start
 
+### Running with Docker
+
+The fastest way to get started is using Docker:
+
+```bash
+# Clone the repository
+git clone https://github.com/vamplabai/sgr-agent-core.git
+cd sgr-agent-core
+
+# Create directories with write permissions for all
+sudo mkdir -p logs reports
+sudo chmod 777 logs reports
+
+# Copy and edit the configuration file
+cp examples/sgr_deep_research/config.yaml.example examples/sgr_deep_research/config.yaml
+# Edit examples/sgr_deep_research/config.yaml and set your API keys:
+# - llm.api_key: Your OpenAI API key
+# - search.tavily_api_key: Your Tavily API key (optional)
+
+# Run the container
+docker run --rm -i \
+  --name sgr-agent \
+  -p 8010:8010 \
+  -v $(pwd)/examples/sgr_deep_research:/app/examples/sgr_deep_research:ro \
+  -v $(pwd)/logs:/app/logs \
+  -v $(pwd)/reports:/app/reports \
+  ghcr.io/vamplabai/sgr-agent-core:latest \
+  --config-file /app/examples/sgr_deep_research/config.yaml \
+  --host 0.0.0.0 \
+  --port 8010
+```
+
+The API server will be available at `http://localhost:8010` with OpenAI-compatible API endpoints. Interactive API documentation (Swagger UI) is available at `http://localhost:8010/docs`.
+
 ### Installation
 
+If you want to use SGR Agent Core as a Python library (framework):
+
 ```bash
 pip install sgr-agent-core
 ```
 
+See the [Installation Guide](https://vamplabai.github.io/sgr-agent-core/getting-started/installation/) for detailed instructions and the [Using as Library](https://vamplabai.github.io/sgr-agent-core/framework/first-steps/) guide to get started.
+
 ### Running Research Agents
 
 The project includes example research agent configurations in the `examples/` directory. To get started with deep research agents:
 
 1. Copy and configure the config file:
 
 ```bash
-cp examples/sgr_deep_research/config.yaml my_config.yaml
-# Edit my_config.yaml and set your API keys:
+cp examples/sgr_deep_research/config.yaml.example examples/sgr_deep_research/config.yaml
+# Edit examples/sgr_deep_research/config.yaml and set your API keys:
 # - llm.api_key: Your OpenAI API key
 # - search.tavily_api_key: Your Tavily API key (optional)
 ```
@@ -56,8 +88,6 @@ cp examples/sgr_deep_research/config.yaml my_config.yaml
 sgr --config-file examples/sgr_deep_research/config.yaml
 ```
 
-The server will start on `http://localhost:8010` with OpenAI-compatible API endpoints.
-
 > **Note:** You can also run the server directly with Python:
 >
 > ```bash
@@ -66,8 +96,6 @@ The server will start on `http://localhost:8010` with OpenAI-compatible API endp
 
 For more examples and detailed usage instructions, see the [examples/](examples/) directory.
 
-______________________________________________________________________
-
 ## Benchmarking
 
 ![SimpleQA Benchmark Comparison](https://github.com/vamplabAI/sgr-agent-core/blob/main/docs/assets/images/simpleqa_benchmark_comparison.png)
@@ -81,8 +109,6 @@ ______________________________________________________________________
 
 More detailed benchmark results are available [here](https://github.com/vamplabAI/sgr-agent-core/blob/main/benchmark/simpleqa_benchmark_results.md).
 
-______________________________________________________________________
-
 ## Open-Source Development Team
 
 *All development is driven by pure enthusiasm and open-source community collaboration. We welcome contributors of all skill levels!*

docs/en/framework/first-steps.md

@@ -1,4 +1,4 @@
-# Quick Start
+# Using as Library
 
 This guide will help you quickly get started with SGR Agent Core as a Python library.
 

docs/en/getting-started/index.md

@@ -15,58 +15,59 @@ The library includes extensible tools for search, reasoning, and clarification,
 
 ## Quick Start
 
-### Installation
+### Running with Docker
 
-Install SGR Agent Core via pip:
+The fastest way to get started is using Docker:
 
 ```bash
-pip install sgr-agent-core
+# Clone the repository
+git clone https://github.com/vamplabai/sgr-agent-core.git
+cd sgr-agent-core
+
+# Create directories with write permissions for all
+sudo mkdir -p logs reports
+sudo chmod 777 logs reports
+
+# Copy and edit the configuration file
+cp examples/sgr_deep_research/config.yaml.example examples/sgr_deep_research/config.yaml
+# Edit examples/sgr_deep_research/config.yaml and set your API keys
+
+# Run the container
+docker run --rm -i \
+  --name sgr-agent \
+  -p 8010:8010 \
+  -v $(pwd)/examples/sgr_deep_research:/app/examples/sgr_deep_research:ro \
+  -v $(pwd)/logs:/app/logs \
+  -v $(pwd)/reports:/app/reports \
+  ghcr.io/vamplabai/sgr-agent-core:latest \
+  --config-file /app/examples/sgr_deep_research/config.yaml \
+  --host 0.0.0.0 \
+  --port 8010
 ```
 
-Or use Docker:
+The API server will be available at `http://localhost:8010`. Interactive API documentation (Swagger UI) is available at `http://localhost:8010/docs`.
+
+### Installation
+
+If you want to use SGR Agent Core as a Python library (framework):
 
 ```bash
-docker pull ghcr.io/vamplabai/sgr-agent-core:latest
+pip install sgr-agent-core
 ```
 
-See the [Installation Guide](installation.md) for detailed instructions.
-
-### Quick Example
-
-```python
-import asyncio
-from sgr_agent_core import AgentDefinition, AgentFactory
-from sgr_agent_core.agents import SGRToolCallingAgent
-import sgr_agent_core.tools as tools
-
-async def main():
-    agent_def = AgentDefinition(
-        name="my_agent",
-        base_class=SGRToolCallingAgent,
-        tools=[tools.GeneratePlanTool, tools.FinalAnswerTool],
-        llm={
-            "api_key": "your-api-key",
-            "base_url": "https://api.openai.com/v1",
-        },
-    )
-
-    agent = await AgentFactory.create(
-        agent_def=agent_def,
-        task_messages=[{"role": "user", "content": "Research AI trends"}],
-    )
-
-    result = await agent.execute()
-    print(result)
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
+See the [Installation Guide](installation.md) for detailed instructions and the [Using as Library](../framework/first-steps.md) guide to get started.
+
+### Next Steps
+
+- **[Using as Library](../framework/first-steps.md)** — Learn how to use SGR Agent Core as a Python library
+- **[API Server Quick Start](../sgr-api/SGR-Quick-Start.md)** — Get started with the REST API service
 
 ## Documentation
 
 - **[Installation](installation.md)** — Detailed installation instructions for pip and Docker
 - **[Agent Core Framework](../framework/main-concepts.md)** — Understand the core concepts and architecture
-- **[SGR API Service](../sgr-api/SGR-Quick-Start.md)** — Get started with the REST API service
+- **[Using as Library](../framework/first-steps.md)** — Learn how to use SGR Agent Core as a Python library
+- **[API Server Quick Start](../sgr-api/SGR-Quick-Start.md)** — Get started with the REST API service
 
 ## Contact & Community
 

docs/en/getting-started/installation.md

@@ -114,7 +114,7 @@ services:
 docker-compose up -d
 ```
 
-The API server will be available at `http://localhost:8010`.
+The API server will be available at `http://localhost:8010`. Interactive API documentation (Swagger UI) is available at `http://localhost:8010/docs`.
 
 ### Building from Source