Add comprehensive agent configuration documentation

docs/user-guide/concepts/experimental/agent-config.md

@@ -0,0 +1,163 @@
+# Agent Configuration [Experimental]
+
+!!! warning "Experimental Feature"
+    This feature is experimental and may change in future versions. Use with caution in production environments.
+
+The experimental `config_to_agent` function provides a simple way to create agents from configuration files or dictionaries.
+
+## Overview
+
+`config_to_agent` allows you to:
+
+- Create agents from JSON files or dictionaries
+- Use a simple functional interface for agent instantiation
+- Support both file paths and dictionary configurations
+- Leverage the Agent class's built-in tool loading capabilities
+
+## Basic Usage
+
+### Dictionary Configuration
+
+```python
+from strands.experimental import config_to_agent
+
+# Create agent from dictionary
+agent = config_to_agent({
+    "model": "us.anthropic.claude-3-5-sonnet-20241022-v2:0",
+    "prompt": "You are a helpful assistant"
+})
+```
+
+### File Configuration
+
+```python
+from strands.experimental import config_to_agent
+
+# Load from JSON file (with or without file:// prefix)
+agent = config_to_agent("/path/to/config.json")
+# or
+agent = config_to_agent("file:///path/to/config.json")
+```
+
+#### Simple Agent Example
+
+```json
+{
+    "prompt": "You are a helpful assistant."
+}
+```
+
+#### Coding Assistant Example
+
+```json
+{
+  "model": "us.anthropic.claude-3-5-sonnet-20241022-v2:0",
+  "prompt": "You are a coding assistant. Help users write, debug, and improve their code. You have access to file operations and can execute shell commands when needed.",
+  "tools": ["strands_tools.file_read", "strands_tools.editor", "strands_tools.shell"]
+}
+```
+
+## Configuration Options
+
+### Supported Keys
+
+- `model`: Model identifier (string) - [[Only supports AWS Bedrock model provider string](../../../quickstart/#using-a-string-model-id)]
+- `prompt`: System prompt for the agent (string)
+- `tools`: List of tool specifications (list of strings)
+- `name`: Agent name (string)
+
+### Tool Loading
+
+The `tools` configuration supports Python-specific tool loading formats:
+
+```json
+{
+  "tools": [
+    "strands_tools.file_read",           // Python module path
+    "my_app.tools.cake_tool",            // Custom module path  
+    "/path/to/another_tool.py",          // File path
+    "my_module.my_tool_function"         // @tool annotated function
+  ]
+}
+```
+
+The Agent class handles all tool loading internally, including:
+
+- Loading from module paths
+- Loading from file paths
+- Error handling for missing tools
+- Tool validation
+
+!!! note "Tool Loading Limitations"
+    Configuration-based agent setup only works for tools that don't require code-based instantiation. For tools that need constructor arguments or complex setup, use the programmatic approach after creating the agent:
+
+    ```python
+    import http.client
+    from sample_module import ToolWithConfigArg
+
+    agent = config_to_agent("config.json")
+    # Add tools that need code-based instantiation
+    agent.process_tools([ToolWithConfigArg(http.client.HTTPSConnection("localhost"))])
+    ```
+
+### Model Configurations
+
+The `model` property uses the [string based model id feature](../../../quickstart/#using-a-string-model-id). You can reference [AWS's Model Id's](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-support.html) to identify a model id to use. If you want to use a different model provider, you can pass in a model as part of the `**kwargs` of the `config_to_agent` function:
+
+```python
+from strands.experimental import config_to_agent
+from strands.models.openai import OpenAIModel
+
+# Create agent from dictionary
+agent = config_to_agent(
+  config={"name": "Data Analyst"},
+  model=OpenAIModel(
+    client_args={
+        "api_key": "<KEY>",
+    },
+    model_id="gpt-4o",
+  )
+)
+```
+
+Additionally, you can override the `agent.model` attribute of an agent to configure a new model provider:
+
+```python
+from strands.experimental import config_to_agent
+from strands.models.openai import OpenAIModel
+
+# Create agent from dictionary
+agent = config_to_agent(
+  config={"name": "Data Analyst"}
+)
+
+agent.model = OpenAIModel(
+  client_args={
+      "api_key": "<KEY>",
+  },
+  model_id="gpt-4o",
+)
+```
+
+## Function Parameters
+
+The `config_to_agent` function accepts:
+
+- `config`: Either a file path (string) or configuration dictionary
+- `**kwargs`: Additional [Agent constructor parameters](../../../../api-reference/agent/#strands.agent.agent.Agent.__init__) that override config values
+
+```python
+# Override config values with valid Agent parameters
+agent = config_to_agent(
+    "/path/to/config.json",
+    name="Data Analyst"
+)
+```
+
+## Best Practices
+
+1. **Override when needed**: Use kwargs to override configuration values dynamically
+2. **Leverage Agent defaults**: Only specify configuration values you want to override
+3. **Use standard tool formats**: Follow Agent class conventions for tool specifications
+4. **Handle errors gracefully**: Catch FileNotFoundError and JSONDecodeError for robust applications
+

mkdocs.yml

@@ -115,6 +115,8 @@ nav:
         - Graph: user-guide/concepts/multi-agent/graph.md
         - Workflow: user-guide/concepts/multi-agent/workflow.md
         - Multi-agent Patterns: user-guide/concepts/multi-agent/multi-agent-patterns.md
+      - Experimental:
+        - AgentConfig: user-guide/concepts/experimental/agent-config.md
     - Safety & Security:
       - Responsible AI: user-guide/safety-security/responsible-ai.md
       - Guardrails: user-guide/safety-security/guardrails.md