Merge pull request #138 from bassilkhilo/allow-agent-name-as-string-i…

…n-swarm-results

Modified swarm_translation to check if agent is str, if so, get agent…

autogen/agentchat/contrib/swarm_agent.py

@@ -122,6 +122,17 @@ def swarm_transition(last_speaker: SwarmAgent, groupchat: GroupChat):
         if tool_execution._next_agent is not None:
             next_agent = tool_execution._next_agent
             tool_execution._next_agent = None
+
+            # Check for string, access agent from group chat.
+
+            if isinstance(next_agent, str):
+                if next_agent in swarm_agent_names:
+                    next_agent = groupchat.agent_by_name(name=next_agent)
+                else:
+                    raise ValueError(
+                        f"No agent found with the name '{next_agent}'. Ensure the agent exists in the swarm."
+                    )
+
             return next_agent
 
         # get the last swarm agent
@@ -228,7 +239,7 @@ class SwarmResult(BaseModel):
     """
 
     values: str = ""
-    agent: Optional["SwarmAgent"] = None
+    agent: Optional[Union["SwarmAgent", str]] = None
     context_variables: Dict[str, Any] = {}
 
     class Config:  # Add this inner class

test/agentchat/contrib/test_swarm.py

@@ -461,5 +461,103 @@ def test_initialization():
         )
 
 
+def test_string_agent_params_for_transfer():
+    """Test that string agent parameters are handled correctly without using real LLMs."""
+    # Define test configuration
+    testing_llm_config = {
+        "config_list": [
+            {
+                "model": "gpt-4o",
+                "api_key": "SAMPLE_API_KEY",
+            }
+        ]
+    }
+
+    # Define a simple function for testing
+    def hello_world(context_variables: dict) -> SwarmResult:
+        value = "Hello, World!"
+        return SwarmResult(values=value, context_variables=context_variables, agent="agent_2")
+
+    # Create SwarmAgent instances
+    agent_1 = SwarmAgent(
+        name="agent_1",
+        system_message="Your task is to call hello_world() function.",
+        llm_config=testing_llm_config,
+        functions=[hello_world],
+    )
+    agent_2 = SwarmAgent(
+        name="agent_2",
+        system_message="Your task is to let the user know what the previous agent said.",
+        llm_config=testing_llm_config,
+    )
+
+    # Mock LLM responses
+    def mock_generate_oai_reply_agent1(*args, **kwargs):
+        return True, {
+            "role": "assistant",
+            "name": "agent_1",
+            "tool_calls": [{"type": "function", "function": {"name": "hello_world", "arguments": "{}"}}],
+            "content": "I will call the hello_world function.",
+        }
+
+    def mock_generate_oai_reply_agent2(*args, **kwargs):
+        return True, {
+            "role": "assistant",
+            "name": "agent_2",
+            "content": "The previous agent called hello_world and got: Hello, World!",
+        }
+
+    # Register mock responses
+    agent_1.register_reply([ConversableAgent, None], mock_generate_oai_reply_agent1)
+    agent_2.register_reply([ConversableAgent, None], mock_generate_oai_reply_agent2)
+
+    # Initiate the swarm chat
+    chat_result, final_context, last_active_agent = initiate_swarm_chat(
+        initial_agent=agent_1,
+        agents=[agent_1, agent_2],
+        context_variables={},
+        messages="Begin by calling the hello_world() function.",
+        after_work=AFTER_WORK(AfterWorkOption.TERMINATE),
+        max_rounds=5,
+    )
+
+    # Assertions to verify the behavior
+    assert chat_result.chat_history[3]["name"] == "agent_2"
+    assert last_active_agent.name == "agent_2"
+
+    # Define a simple function for testing
+    def hello_world(context_variables: dict) -> SwarmResult:
+        value = "Hello, World!"
+        return SwarmResult(values=value, context_variables=context_variables, agent="agent_unknown")
+
+    agent_1 = SwarmAgent(
+        name="agent_1",
+        system_message="Your task is to call hello_world() function.",
+        llm_config=testing_llm_config,
+        functions=[hello_world],
+    )
+    agent_2 = SwarmAgent(
+        name="agent_2",
+        system_message="Your task is to let the user know what the previous agent said.",
+        llm_config=testing_llm_config,
+    )
+
+    # Register mock responses
+    agent_1.register_reply([ConversableAgent, None], mock_generate_oai_reply_agent1)
+    agent_2.register_reply([ConversableAgent, None], mock_generate_oai_reply_agent2)
+
+    with pytest.raises(
+        ValueError, match="No agent found with the name 'agent_unknown'. Ensure the agent exists in the swarm."
+    ):
+        chat_result, final_context, last_active_agent = initiate_swarm_chat(
+            initial_agent=agent_1,
+            agents=[agent_1, agent_2],
+            context_variables={},
+            messages="Begin by calling the hello_world() function.",
+            after_work=AFTER_WORK(AfterWorkOption.TERMINATE),
+            max_rounds=5,
+        )
+
+
 if __name__ == "__main__":
     pytest.main([__file__])

website/docs/topics/swarm.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Swarm Ochestration\n",
+    "# Swarm Orchestration\n",
     "\n",
     "With AG2, you can initiate a Swarm Chat similar to OpenAI's [Swarm](https://github.com/openai/swarm). This orchestration offers two main features:\n",
     "\n",