Adds multiple choice message handling to MesopUI (#198)

* Multiple choice WIP(1)

* Multiple choice WIP(2)

* Multiple choice WIP(3)

* test fix

* tyest fixes

* added all caps instructions for message termination

* added all caps instructions for message termination

---------

Co-authored-by: Davorin Rusevljan <davorin.rusevljan@gmail.com>

docs/docs/SUMMARY.md

@@ -256,17 +256,19 @@ search:
                         - [header](api/fastagency/ui/mesop/components/ui_common/header.md)
                 - data_model
                     - [Conversation](api/fastagency/ui/mesop/data_model/Conversation.md)
+                    - [ConversationMessage](api/fastagency/ui/mesop/data_model/ConversationMessage.md)
                     - [State](api/fastagency/ui/mesop/data_model/State.md)
                 - main
                     - [conversation_box](api/fastagency/ui/mesop/main/conversation_box.md)
                     - [conversation_starter_box](api/fastagency/ui/mesop/main/conversation_starter_box.md)
                     - [get_ui](api/fastagency/ui/mesop/main/get_ui.md)
                     - [home_page](api/fastagency/ui/mesop/main/home_page.md)
-                    - [on_user_feedback](api/fastagency/ui/mesop/main/on_user_feedback.md)
                     - [past_conversations_box](api/fastagency/ui/mesop/main/past_conversations_box.md)
                     - [send_prompt](api/fastagency/ui/mesop/main/send_prompt.md)
                 - message
                     - [MesopGUIMessageVisitor](api/fastagency/ui/mesop/message/MesopGUIMessageVisitor.md)
+                    - [consume_responses](api/fastagency/ui/mesop/message/consume_responses.md)
+                    - [handle_message](api/fastagency/ui/mesop/message/handle_message.md)
                     - [message_box](api/fastagency/ui/mesop/message/message_box.md)
                 - send_prompt
                     - [send_prompt_to_autogen](api/fastagency/ui/mesop/send_prompt/send_prompt_to_autogen.md)

docs/docs/en/api/fastagency/ui/mesop/data_model/ConversationMessage.md

@@ -0,0 +1,11 @@
+---
+# 0.5 - API
+# 2 - Release
+# 3 - Contributing
+# 5 - Template Page
+# 10 - Default
+search:
+  boost: 0.5
+---
+
+::: fastagency.ui.mesop.data_model.ConversationMessage

docs/docs/en/api/fastagency/ui/mesop/message/consume_responses.md

@@ -0,0 +1,11 @@
+---
+# 0.5 - API
+# 2 - Release
+# 3 - Contributing
+# 5 - Template Page
+# 10 - Default
+search:
+  boost: 0.5
+---
+
+::: fastagency.ui.mesop.message.consume_responses

docs/docs/en/api/fastagency/ui/mesop/main/on_user_feedback.md → docs/docs/en/api/fastagency/ui/mesop/message/handle_message.md

@@ -8,4 +8,4 @@ search:
   boost: 0.5
 ---
 
-::: fastagency.ui.mesop.main.on_user_feedback
+::: fastagency.ui.mesop.message.handle_message

docs/docs_src/user_guide/custom_user_interactions/main.py

@@ -23,8 +23,8 @@
 wf = AutoGenWorkflows()
 
 
-@wf.register(name="exam_practice", description="Student and teacher chat")  # type: ignore[type-var]
-def exam_learning(ui: UI, initial_message: str, session_id: str) -> Optional[str]:
+@wf.register(name="exam_practice", description="Student and teacher chat")
+def exam_learning(ui: UI, initial_message: str, session_id: str) -> str:
 
     def is_termination_msg(msg: dict[str, Any]) -> bool:
         return msg["content"] is not None and "TERMINATE" in msg["content"]

docs/docs_src/user_guide/custom_user_interactions/main_mesop.py

@@ -0,0 +1,136 @@
+import os
+from typing import Annotated, Any, Dict, Optional
+
+from autogen import register_function
+from autogen.agentchat import ConversableAgent
+
+from fastagency import FastAgency
+from fastagency import UI
+from fastagency.base import MultipleChoice, SystemMessage, TextInput
+from fastagency.ui.mesop import MesopUI
+from fastagency.runtime.autogen.base import AutoGenWorkflows
+
+llm_config = {
+    "config_list": [
+        {
+            "model": "gpt-4o-mini",
+            "api_key": os.getenv("OPENAI_API_KEY"),
+        }
+    ],
+    "temperature": 0.0,
+}
+
+wf = AutoGenWorkflows()
+
+
+@wf.register(name="exam_practice", description="Student and teacher chat")
+def exam_learning(ui: UI, initial_message: str, session_id: str) -> str:
+
+    def is_termination_msg(msg: dict[str, Any]) -> bool:
+        return msg["content"] is not None and "TERMINATE" in msg["content"]
+
+    student_agent = ConversableAgent(
+        name="Student_Agent",
+        system_message="You are a student writing a practice test. Your task is as follows:\n"
+        "  1) Retrieve exam questions by calling a function.\n"
+        "  2) Write a draft of proposed answers and engage in dialogue with your tutor.\n"
+        "  3) Once you are done with the dialogue, register the final answers by calling a function.\n"
+        "  4) Retrieve the final grade by calling a function.\n"
+        "Finally, terminate the chat by saying 'TERMINATE'.",
+        llm_config=llm_config,
+        human_input_mode="NEVER",
+        is_termination_msg=is_termination_msg,
+    )
+    teacher_agent = ConversableAgent(
+        name="Teacher_Agent",
+        system_message="You are a teacher.",
+        llm_config=llm_config,
+        human_input_mode="NEVER",
+        is_termination_msg=is_termination_msg,
+    )
+
+    def retrieve_exam_questions(
+        message: Annotated[str, "Message for examiner"]
+    ) -> Optional[str]:
+        try:
+            msg = MultipleChoice(
+                sender="student",
+                recipient="teacher",
+                prompt=message,
+                choices=[
+                    "1) Mona Lisa",
+                    "2) Innovations",
+                    "3) Florence at the time of Leonardo",
+                    "4) The Last Supper",
+                    "5) Vitruvian Man",
+                ],
+                default="1) Mona Lisa"
+            )
+            return ui.process_message(msg)
+        except Exception as e:
+            return f"retrieve_exam_questions() FAILED! {e}"
+
+    def write_final_answers(message: Annotated[str, "Message for examiner"]) -> str:
+        try:
+            msg = SystemMessage(
+                sender="function call logger",
+                recipient="system",
+                message={
+                    "operation": "storing final answers",
+                    "content": message,
+                },
+            )
+            ui.process_message(msg)
+            return "Final answers stored."
+        except Exception as e:
+            return f"write_final_answers() FAILED! {e}"
+
+    def get_final_grade(
+        message: Annotated[str, "Message for examiner"]
+    ) -> Optional[str]:
+        try:
+            msg = MultipleChoice(
+                sender="student",
+                recipient="teacher",
+                prompt=message,
+                choices=["A", "B", "C", "D", "F"],
+            )
+            return ui.process_message(msg)
+        except Exception as e:
+            return f"get_final_grade() FAILED! {e}"
+
+    register_function(
+        retrieve_exam_questions,
+        caller=student_agent,
+        executor=teacher_agent,
+        name="retrieve_exam_questions",
+        description="Get exam questions from examiner",
+    )
+
+    register_function(
+        write_final_answers,
+        caller=student_agent,
+        executor=teacher_agent,
+        name="write_final_answers",
+        description="Write a final answers to exam questions to examiner, but only after discussing with the tutor first.",
+    )
+
+    register_function(
+        get_final_grade,
+        caller=student_agent,
+        executor=teacher_agent,
+        name="get_final_grade",
+        description="Get the final grade after submitting the answers.",
+    )
+
+    chat_result = teacher_agent.initiate_chat(
+        student_agent,
+        message=initial_message,
+        summary_method="reflection_with_llm",
+        max_turns=10,
+    )
+
+    return chat_result.summary  # type: ignore[no-any-return]
+
+
+app = FastAgency(wf=wf, ui=MesopUI())

docs/docs_src/user_guide/external_rest_apis/main_mesop.py

@@ -0,0 +1,60 @@
+import os
+
+from autogen import UserProxyAgent
+from autogen.agentchat import ConversableAgent
+
+from fastagency import FastAgency
+from fastagency import UI
+from fastagency.ui.mesop import MesopUI
+from fastagency.runtime.autogen.base import AutoGenWorkflows
+
+from fastagency.api.openapi import OpenAPI
+
+
+llm_config = {
+    "config_list": [
+        {
+            "model": "gpt-4o-mini",
+            "api_key": os.getenv("OPENAI_API_KEY"),
+        }
+    ],
+    "temperature": 0.0,
+}
+
+WEATHER_OPENAPI_URL = "https://weather.tools.fastagency.ai/openapi.json"
+
+wf = AutoGenWorkflows()
+
+
+@wf.register(name="simple_weather", description="Weather chat")
+def weather_workflow(ui: UI, initial_message: str, session_id: str) -> str:
+
+    weather_api = OpenAPI.create(openapi_url=WEATHER_OPENAPI_URL)
+
+    user_agent = UserProxyAgent(
+        name="User_Agent",
+        system_message="You are a user agent",
+        llm_config=llm_config,
+        human_input_mode="NEVER",
+    )
+    weather_agent = ConversableAgent(
+        name="Weather_Agent",
+        system_message="You are a weather agent",
+        llm_config=llm_config,
+        human_input_mode="NEVER",
+    )
+
+    weather_api.register_for_llm(weather_agent)
+    weather_api.register_for_execution(user_agent)
+
+    chat_result = user_agent.initiate_chat(
+        weather_agent,
+        message=initial_message,
+        summary_method="reflection_with_llm",
+        max_turns=3,
+    )
+
+    return chat_result.summary  # type: ignore[no-any-return]
+
+
+app = FastAgency(wf=wf, ui=MesopUI())

fastagency/studio/models/agents/assistant.py

@@ -16,7 +16,7 @@ class AssistantAgent(AgentBaseModel):
         Field(
             description="The system message of the agent. This message is used to inform the agent about his role in the conversation"
         ),
-    ] = "You are a helpful assistant. After you successfully answer all questions and there are no new questions asked after your response (e.g. there is no specific direction or question asked after you give a response), terminate the chat by outputting 'TERMINATE'"
+    ] = "You are a helpful assistant. After you successfully answer all questions and there are no new questions asked after your response (e.g. there is no specific direction or question asked after you give a response), terminate the chat by outputting 'TERMINATE' (IMPORTANT: use all caps)"
 
     @classmethod
     async def create_autogen(

fastagency/ui/mesop/base.py

@@ -221,13 +221,27 @@ def conversation_worker(ui: MesopUI, subconversation: MesopUI) -> None:
                 },
             )
         )
+
+        # io.process_message(
+        #    IOMessage.create(
+        #        sender="tester",
+        #        recipient="workflow",
+        #        type="multiple_choice",
+        #        prompt="Concentrate and choose correct answer. When are you going to write unit tests?",
+        #        choices=["Today", "Tomorrow", "Never", "I already have unit tests"],
+        #        default="Tomorrow",
+        #        single=True,
+        #    )
+        # )
+
         try:
             result = wf.run(
                 name=name,
                 session_id="session_id",
                 ui=subconversation,  # type: ignore[arg-type]
                 initial_message=initial_message,
             )
+
         except Exception as ex:
             ui.process_message(
                 IOMessage.create(

fastagency/ui/mesop/components/inputs.py

@@ -12,8 +12,12 @@ def _on_blur(e: me.InputBlurEvent) -> None:
 
 
 def input_user_feedback(
-    send_feedback: Callable[[me.ClickEvent], Iterator[None]],
+    send_feedback: Callable[[me.ClickEvent], Iterator[None]], disabled: bool = False
 ) -> None:
+    def _on_feedback_blur(e: me.InputBlurEvent) -> None:
+        state = me.state(State)
+        state.conversation.feedback = e.value
+
     with me.box(
         style=me.Style(
             border_radius=16,
@@ -26,16 +30,20 @@ def input_user_feedback(
         with me.box(style=me.Style(flex_grow=1)):
             me.native_textarea(
                 placeholder="Provide a feedback to the team",
-                on_blur=_on_blur,
-                key="feedback",
+                on_blur=_on_feedback_blur,
+                disabled=disabled,
                 style=me.Style(
                     padding=me.Padding(top=16, left=16),
                     outline="none",
                     width="100%",
                     border=me.Border.all(me.BorderSide(style="none")),
                 ),
             )
-        with me.content_button(type="icon", on_click=send_feedback):
+        with me.content_button(
+            type="icon",
+            on_click=send_feedback,
+            disabled=disabled,
+        ):
             me.icon("send")
 
 

fastagency/ui/mesop/data_model.py

@@ -4,6 +4,14 @@
 import mesop as me
 
 
+@dataclass
+class ConversationMessage:
+    io_message_json: str = ""
+    level: int = 0
+    conversation_id: str = ""
+    feedback: list[str] = field(default_factory=list)
+
+
 @dataclass
 class Conversation:
     id: str = ""
@@ -12,8 +20,7 @@ class Conversation:
     waiting_for_feedback: bool = False
     feedback: str = ""
     is_from_the_past: bool = False
-    # messages: list[ConversationMessage] = field(default_factory=list)
-    messages: list[str] = field(default_factory=list)
+    messages: list[ConversationMessage] = field(default_factory=list)
     fastagency: Optional[str] = None
 
 
@@ -24,4 +31,3 @@ class State:
     conversation: Conversation
     past_conversations: list[Conversation] = field(default_factory=list)
     hide_past: bool = True
-    fastagency: Optional[str] = None