Merge branch 'main' into selectspeakertransforms

autogen/agentchat/contrib/capabilities/transforms.py

@@ -53,13 +53,16 @@ class MessageHistoryLimiter:
     It trims the conversation history by removing older messages, retaining only the most recent messages.
     """
 
-    def __init__(self, max_messages: Optional[int] = None):
+    def __init__(self, max_messages: Optional[int] = None, keep_first_message: bool = False):
         """
         Args:
             max_messages Optional[int]: Maximum number of messages to keep in the context. Must be greater than 0 if not None.
+            keep_first_message bool: Whether to keep the original first message in the conversation history.
+                Defaults to False.
         """
         self._validate_max_messages(max_messages)
         self._max_messages = max_messages
+        self._keep_first_message = keep_first_message
 
     def apply_transform(self, messages: List[Dict]) -> List[Dict]:
         """Truncates the conversation history to the specified maximum number of messages.
@@ -75,10 +78,31 @@ def apply_transform(self, messages: List[Dict]) -> List[Dict]:
             List[Dict]: A new list containing the most recent messages up to the specified maximum.
         """
 
-        if self._max_messages is None:
+        if self._max_messages is None or len(messages) <= self._max_messages:
             return messages
 
-        return messages[-self._max_messages :]
+        truncated_messages = []
+        remaining_count = self._max_messages
+
+        # Start with the first message if we need to keep it
+        if self._keep_first_message:
+            truncated_messages = [messages[0]]
+            remaining_count -= 1
+
+        # Loop through messages in reverse
+        for i in range(len(messages) - 1, 0, -1):
+            if remaining_count > 1:
+                truncated_messages.insert(1 if self._keep_first_message else 0, messages[i])
+            if remaining_count == 1:
+                # If there's only 1 slot left and it's a 'tools' message, ignore it.
+                if messages[i].get("role") != "tool":
+                    truncated_messages.insert(1, messages[i])
+
+            remaining_count -= 1
+            if remaining_count == 0:
+                break
+
+        return truncated_messages
 
     def get_logs(self, pre_transform_messages: List[Dict], post_transform_messages: List[Dict]) -> Tuple[str, bool]:
         pre_transform_messages_len = len(pre_transform_messages)

autogen/agentchat/conversable_agent.py

@@ -377,9 +377,9 @@ def replace_reply_func(self, old_reply_func: Callable, new_reply_func: Callable)
                 f["reply_func"] = new_reply_func
 
     @staticmethod
-    def _summary_from_nested_chats(
+    def _get_chats_to_run(
         chat_queue: List[Dict[str, Any]], recipient: Agent, messages: Union[str, Callable], sender: Agent, config: Any
-    ) -> Tuple[bool, str]:
+    ) -> List[Dict[str, Any]]:
         """A simple chat reply function.
         This function initiate one or a sequence of chats between the "recipient" and the agents in the
         chat_queue.
@@ -406,22 +406,59 @@ def _summary_from_nested_chats(
             if message:
                 current_c["message"] = message
                 chat_to_run.append(current_c)
+        return chat_to_run
+
+    @staticmethod
+    def _summary_from_nested_chats(
+        chat_queue: List[Dict[str, Any]], recipient: Agent, messages: Union[str, Callable], sender: Agent, config: Any
+    ) -> Tuple[bool, Union[str, None]]:
+        """A simple chat reply function.
+        This function initiate one or a sequence of chats between the "recipient" and the agents in the
+        chat_queue.
+
+        It extracts and returns a summary from the nested chat based on the "summary_method" in each chat in chat_queue.
+
+        Returns:
+            Tuple[bool, str]: A tuple where the first element indicates the completion of the chat, and the second element contains the summary of the last chat if any chats were initiated.
+        """
+        chat_to_run = ConversableAgent._get_chats_to_run(chat_queue, recipient, messages, sender, config)
         if not chat_to_run:
             return True, None
         res = initiate_chats(chat_to_run)
         return True, res[-1].summary
 
+    @staticmethod
+    async def _a_summary_from_nested_chats(
+        chat_queue: List[Dict[str, Any]], recipient: Agent, messages: Union[str, Callable], sender: Agent, config: Any
+    ) -> Tuple[bool, Union[str, None]]:
+        """A simple chat reply function.
+        This function initiate one or a sequence of chats between the "recipient" and the agents in the
+        chat_queue.
+
+        It extracts and returns a summary from the nested chat based on the "summary_method" in each chat in chat_queue.
+
+        Returns:
+            Tuple[bool, str]: A tuple where the first element indicates the completion of the chat, and the second element contains the summary of the last chat if any chats were initiated.
+        """
+        chat_to_run = ConversableAgent._get_chats_to_run(chat_queue, recipient, messages, sender, config)
+        if not chat_to_run:
+            return True, None
+        res = await a_initiate_chats(chat_to_run)
+        index_of_last_chat = chat_to_run[-1]["chat_id"]
+        return True, res[index_of_last_chat].summary
+
     def register_nested_chats(
         self,
         chat_queue: List[Dict[str, Any]],
         trigger: Union[Type[Agent], str, Agent, Callable[[Agent], bool], List],
         reply_func_from_nested_chats: Union[str, Callable] = "summary_from_nested_chats",
         position: int = 2,
+        use_async: Union[bool, None] = None,
         **kwargs,
     ) -> None:
         """Register a nested chat reply function.
         Args:
-            chat_queue (list): a list of chat objects to be initiated.
+            chat_queue (list): a list of chat objects to be initiated. If use_async is used, then all messages in chat_queue must have a chat-id associated with them.
             trigger (Agent class, str, Agent instance, callable, or list): refer to `register_reply` for details.
             reply_func_from_nested_chats (Callable, str): the reply function for the nested chat.
                 The function takes a chat_queue for nested chat, recipient agent, a list of messages, a sender agent and a config as input and returns a reply message.
@@ -436,15 +473,33 @@ def reply_func_from_nested_chats(
             ) -> Tuple[bool, Union[str, Dict, None]]:
             ```
             position (int): Ref to `register_reply` for details. Default to 2. It means we first check the termination and human reply, then check the registered nested chat reply.
+            use_async: Uses a_initiate_chats internally to start nested chats. If the original chat is initiated with a_initiate_chats, you may set this to true so nested chats do not run in sync.
             kwargs: Ref to `register_reply` for details.
         """
-        if reply_func_from_nested_chats == "summary_from_nested_chats":
-            reply_func_from_nested_chats = self._summary_from_nested_chats
-        if not callable(reply_func_from_nested_chats):
-            raise ValueError("reply_func_from_nested_chats must be a callable")
+        if use_async:
+            for chat in chat_queue:
+                if chat.get("chat_id") is None:
+                    raise ValueError("chat_id is required for async nested chats")
+
+        if use_async:
+            if reply_func_from_nested_chats == "summary_from_nested_chats":
+                reply_func_from_nested_chats = self._a_summary_from_nested_chats
+            if not callable(reply_func_from_nested_chats) or not inspect.iscoroutinefunction(
+                reply_func_from_nested_chats
+            ):
+                raise ValueError("reply_func_from_nested_chats must be a callable and a coroutine")
 
-        def wrapped_reply_func(recipient, messages=None, sender=None, config=None):
-            return reply_func_from_nested_chats(chat_queue, recipient, messages, sender, config)
+            async def wrapped_reply_func(recipient, messages=None, sender=None, config=None):
+                return await reply_func_from_nested_chats(chat_queue, recipient, messages, sender, config)
+
+        else:
+            if reply_func_from_nested_chats == "summary_from_nested_chats":
+                reply_func_from_nested_chats = self._summary_from_nested_chats
+            if not callable(reply_func_from_nested_chats):
+                raise ValueError("reply_func_from_nested_chats must be a callable")
+
+            def wrapped_reply_func(recipient, messages=None, sender=None, config=None):
+                return reply_func_from_nested_chats(chat_queue, recipient, messages, sender, config)
 
         functools.update_wrapper(wrapped_reply_func, reply_func_from_nested_chats)
 
@@ -454,7 +509,9 @@ def wrapped_reply_func(recipient, messages=None, sender=None, config=None):
             position,
             kwargs.get("config"),
             kwargs.get("reset_config"),
-            ignore_async_in_sync_chat=kwargs.get("ignore_async_in_sync_chat"),
+            ignore_async_in_sync_chat=(
+                not use_async if use_async is not None else kwargs.get("ignore_async_in_sync_chat")
+            ),
         )
 
     @property

autogen/agentchat/groupchat.py

@@ -986,6 +986,7 @@ def __init__(
         # Store groupchat
         self._groupchat = groupchat
 
+        self._last_speaker = None
         self._silent = silent
 
         # Order of register_reply is important.
@@ -1027,6 +1028,52 @@ def _prepare_chat(
             if (recipient != agent or prepare_recipient) and isinstance(agent, ConversableAgent):
                 agent._prepare_chat(self, clear_history, False, reply_at_receive)
 
+    @property
+    def last_speaker(self) -> Agent:
+        """Return the agent who sent the last message to group chat manager.
+
+        In a group chat, an agent will always send a message to the group chat manager, and the group chat manager will
+        send the message to all other agents in the group chat. So, when an agent receives a message, it will always be
+        from the group chat manager. With this property, the agent receiving the message can know who actually sent the
+        message.
+
+        Example:
+        ```python
+        from autogen import ConversableAgent
+        from autogen import GroupChat, GroupChatManager
+
+
+        def print_messages(recipient, messages, sender, config):
+            # Print the message immediately
+            print(
+                f"Sender: {sender.name} | Recipient: {recipient.name} | Message: {messages[-1].get('content')}"
+            )
+            print(f"Real Sender: {sender.last_speaker.name}")
+            assert sender.last_speaker.name in messages[-1].get("content")
+            return False, None  # Required to ensure the agent communication flow continues
+
+
+        agent_a = ConversableAgent("agent A", default_auto_reply="I'm agent A.")
+        agent_b = ConversableAgent("agent B", default_auto_reply="I'm agent B.")
+        agent_c = ConversableAgent("agent C", default_auto_reply="I'm agent C.")
+        for agent in [agent_a, agent_b, agent_c]:
+            agent.register_reply(
+                [ConversableAgent, None], reply_func=print_messages, config=None
+            )
+        group_chat = GroupChat(
+            [agent_a, agent_b, agent_c],
+            messages=[],
+            max_round=6,
+            speaker_selection_method="random",
+            allow_repeat_speaker=True,
+        )
+        chat_manager = GroupChatManager(group_chat)
+        groupchat_result = agent_a.initiate_chat(
+            chat_manager, message="Hi, there, I'm agent A."
+        )
+        """
+        return self._last_speaker
+
     def run_chat(
         self,
         messages: Optional[List[Dict]] = None,
@@ -1055,6 +1102,7 @@ def run_chat(
                 a.previous_cache = a.client_cache
                 a.client_cache = self.client_cache
         for i in range(groupchat.max_round):
+            self._last_speaker = speaker
             groupchat.append(message, speaker)
             # broadcast the message to all agents except the speaker
             for agent in groupchat.agents:

autogen/oai/client.py

@@ -457,10 +457,13 @@ def _configure_azure_openai(self, config: Dict[str, Any], openai_config: Dict[st
     def _configure_openai_config_for_bedrock(self, config: Dict[str, Any], openai_config: Dict[str, Any]) -> None:
         """Update openai_config with AWS credentials from config."""
         required_keys = ["aws_access_key", "aws_secret_key", "aws_region"]
-
+        optional_keys = ["aws_session_token"]
         for key in required_keys:
             if key in config:
                 openai_config[key] = config[key]
+        for key in optional_keys:
+            if key in config:
+                openai_config[key] = config[key]
 
     def _register_default_client(self, config: Dict[str, Any], openai_config: Dict[str, Any]) -> None:
         """Create a client with the given config to override openai_config,

dotnet/AutoGen.sln

@@ -68,6 +68,12 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AutoGen.OpenAI.Sample", "sa
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AutoGen.WebAPI.Sample", "sample\AutoGen.WebAPI.Sample\AutoGen.WebAPI.Sample.csproj", "{12079C18-A519-403F-BBFD-200A36A0C083}"
 EndProject
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AutoGen.AzureAIInference", "src\AutoGen.AzureAIInference\AutoGen.AzureAIInference.csproj", "{5C45981D-1319-4C25-935C-83D411CB28DF}"
+EndProject
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "AutoGen.AzureAIInference.Tests", "test\AutoGen.AzureAIInference.Tests\AutoGen.AzureAIInference.Tests.csproj", "{5970868F-831E-418F-89A9-4EC599563E16}"
+EndProject
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "AutoGen.Tests.Share", "test\AutoGen.Test.Share\AutoGen.Tests.Share.csproj", "{143725E2-206C-4D37-93E4-9EDF699826B2}"
+EndProject
 Global
 	GlobalSection(SolutionConfigurationPlatforms) = preSolution
 		Debug|Any CPU = Debug|Any CPU
@@ -194,6 +200,18 @@ Global
 		{12079C18-A519-403F-BBFD-200A36A0C083}.Debug|Any CPU.Build.0 = Debug|Any CPU
 		{12079C18-A519-403F-BBFD-200A36A0C083}.Release|Any CPU.ActiveCfg = Release|Any CPU
 		{12079C18-A519-403F-BBFD-200A36A0C083}.Release|Any CPU.Build.0 = Release|Any CPU
+		{5C45981D-1319-4C25-935C-83D411CB28DF}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{5C45981D-1319-4C25-935C-83D411CB28DF}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{5C45981D-1319-4C25-935C-83D411CB28DF}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{5C45981D-1319-4C25-935C-83D411CB28DF}.Release|Any CPU.Build.0 = Release|Any CPU
+		{5970868F-831E-418F-89A9-4EC599563E16}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{5970868F-831E-418F-89A9-4EC599563E16}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{5970868F-831E-418F-89A9-4EC599563E16}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{5970868F-831E-418F-89A9-4EC599563E16}.Release|Any CPU.Build.0 = Release|Any CPU
+		{143725E2-206C-4D37-93E4-9EDF699826B2}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{143725E2-206C-4D37-93E4-9EDF699826B2}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{143725E2-206C-4D37-93E4-9EDF699826B2}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{143725E2-206C-4D37-93E4-9EDF699826B2}.Release|Any CPU.Build.0 = Release|Any CPU
 	EndGlobalSection
 	GlobalSection(SolutionProperties) = preSolution
 		HideSolutionNode = FALSE
@@ -229,6 +247,9 @@ Global
 		{6B82F26D-5040-4453-B21B-C8D1F913CE4C} = {F823671B-3ECA-4AE6-86DA-25E920D3FE64}
 		{0E635268-351C-4A6B-A28D-593D868C2CA4} = {FBFEAD1F-29EB-4D99-A672-0CD8473E10B9}
 		{12079C18-A519-403F-BBFD-200A36A0C083} = {FBFEAD1F-29EB-4D99-A672-0CD8473E10B9}
+		{5C45981D-1319-4C25-935C-83D411CB28DF} = {18BF8DD7-0585-48BF-8F97-AD333080CE06}
+		{5970868F-831E-418F-89A9-4EC599563E16} = {F823671B-3ECA-4AE6-86DA-25E920D3FE64}
+		{143725E2-206C-4D37-93E4-9EDF699826B2} = {F823671B-3ECA-4AE6-86DA-25E920D3FE64}
 	EndGlobalSection
 	GlobalSection(ExtensibilityGlobals) = postSolution
 		SolutionGuid = {93384647-528D-46C8-922C-8DB36A382F0B}

dotnet/eng/Version.props

@@ -15,6 +15,7 @@
         <MicrosoftASPNETCoreVersion>8.0.4</MicrosoftASPNETCoreVersion>
         <GoogleCloudAPIPlatformVersion>3.0.0</GoogleCloudAPIPlatformVersion>
         <JsonSchemaVersion>4.3.0.2</JsonSchemaVersion>
+        <AzureAIInferenceVersion>1.0.0-beta.1</AzureAIInferenceVersion>
         <PowershellSDKVersion>7.4.4</PowershellSDKVersion>
     </PropertyGroup>
 </Project>

dotnet/sample/AutoGen.BasicSamples/CodeSnippet/RunCodeSnippetCodeSnippet.cs

@@ -16,7 +16,7 @@ public async Task CodeSnippet1()
 
         #region code_snippet_1_1
         var kernel = DotnetInteractiveKernelBuilder
-            .CreateDefaultBuilder() // add C# and F# kernels
+            .CreateDefaultInProcessKernelBuilder() // add C# and F# kernels
             .Build();
         #endregion code_snippet_1_1
 
@@ -67,7 +67,7 @@ public async Task CodeSnippet1()
 
         #region code_snippet_1_4
         var pythonKernel = DotnetInteractiveKernelBuilder
-            .CreateDefaultBuilder()
+            .CreateDefaultInProcessKernelBuilder()
             .AddPythonKernel(venv: "python3")
             .Build();
 

dotnet/sample/AutoGen.BasicSamples/Example04_Dynamic_GroupChat_Coding_Task.cs

@@ -16,7 +16,7 @@ public static async Task RunAsync()
         var instance = new Example04_Dynamic_GroupChat_Coding_Task();
 
         var kernel = DotnetInteractiveKernelBuilder
-            .CreateDefaultBuilder()
+            .CreateDefaultInProcessKernelBuilder()
             .AddPythonKernel("python3")
             .Build();
 

dotnet/sample/AutoGen.BasicSamples/Example07_Dynamic_GroupChat_Calculate_Fibonacci.cs

@@ -233,7 +233,9 @@ public static async Task<IAgent> CreateReviewerAgentAsync(OpenAIClient openAICli
     public static async Task RunWorkflowAsync()
     {
         long the39thFibonacciNumber = 63245986;
-        var kernel = DotnetInteractiveKernelBuilder.CreateDefaultBuilder().Build();
+        var kernel = DotnetInteractiveKernelBuilder
+            .CreateDefaultInProcessKernelBuilder()
+            .Build();
 
         var config = LLMConfiguration.GetAzureOpenAIGPT3_5_Turbo();
         var openaiClient = new OpenAIClient(new Uri(config.Endpoint), new Azure.AzureKeyCredential(config.ApiKey));
@@ -344,7 +346,9 @@ public static async Task RunAsync()
         var config = LLMConfiguration.GetAzureOpenAIGPT3_5_Turbo();
         var openaiClient = new OpenAIClient(new Uri(config.Endpoint), new Azure.AzureKeyCredential(config.ApiKey));
 
-        var kernel = DotnetInteractiveKernelBuilder.CreateDefaultBuilder().Build();
+        var kernel = DotnetInteractiveKernelBuilder
+            .CreateDefaultInProcessKernelBuilder()
+            .Build();
         #region create_group_chat
         var reviewer = await CreateReviewerAgentAsync(openaiClient, config.DeploymentName);
         var coder = await CreateCoderAgentAsync(openaiClient, config.DeploymentName);