Improvements to AutoGen Assistant

samples/apps/autogen-assistant/README.md

@@ -19,64 +19,57 @@ Project Structure:
 - _autogenra/_ code for the backend classes and web api (FastAPI)
 - _frontend/_ code for the webui, built with Gatsby and Tailwind
 
-## Getting Started
-
-AutoGen requires access to an LLM. Please see the [AutoGen docs](https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints) on how to configure access to your LLM provider. In this sample, We recommend setting up your `OPENAI_API_KEY` or `AZURE_OPENAI_API_KEY` environment variable and then specifying the exact model parameters to be used in the `llm_config` that is passed to each agent specification. See the `get_default_agent_config()` method in `utils.py` to see an example of setting up `llm_config`. The example below shows how to configure access to an Azure OPENAI LLM.
-
-```python
-llm_config = LLMConfig(
-        config_list=[{
-                "model": "gpt-4",
-                "api_key": "<azure_api_key>",
-                "api_base": "<azure api base>",
-                "api_type": "azure",
-                "api_version": "2023-06-01-preview"
-        }],
-        temperature=0,
-    )
-```
+### Installation
 
-```bash
-export OPENAI_API_KEY=<your_api_key>
-```
+1.  **Install from PyPi**
 
-### Install and Run
+    We recommend using a virtual environment (e.g., conda) to avoid conflicts with existing Python packages. With Python 3.10 or newer active in your virtual environment, use pip to install AutoGen Assistant:
 
-To install a prebuilt version of the app from PyPi. We highly recommend using a virtual environment (e.g. miniconda) and **python 3.10+** to avoid dependency conflicts.
+    ```bash
+    pip install autogenra
+    ```
 
-```bash
-pip install autogenra
-autogenra ui --port 8081  # run the web ui on port 8081
-```
+2.  **Install from Source**
 
-### Install from Source
+    > Note: This approach requires some familiarity with building interfaces in React.
 
-To install the app from source, clone the repository and install the dependencies.
+    If you prefer to install from source, ensure you have Python 3.10+ and Node.js (version above 14.15.0) installed. Here's how you get started:
 
-```bash
-pip install -e .
-```
+    - Clone the AutoGen Assistant repository and install its Python dependencies:
 
-You will also need to build the app front end. Note that your Gatsby requires node > 14.15.0 . You may need to [upgrade your node](https://stackoverflow.com/questions/10075990/upgrading-node-js-to-latest-version) version as needed.
+      ```bash
+      pip install -e .
+      ```
 
-```bash
-npm install --global yarn
-cd frontend
-yarn install
-yarn build
-```
+    - Navigate to the `samples/apps/autogen-assistant/frontend` directory, install dependencies, and build the UI:
 
-The command above will build the frontend ui and copy the build artifacts to the `autogenra` web ui folder. Note that you may have to run `npm install  --force --legacy-peer-deps` to force resolve some peer dependencies.
+      ```bash
+      npm install -g gatsby-cli
+      npm install --global yarn
+      cd frontend
+      yarn install
+      yarn build
+      ```
 
-Run the web ui:
+    For Windows users, to build the frontend, you may need alternative commands to build the frontend.
+
+        ```bash
+
+        gatsby clean && rmdir /s /q ..\\autogenra\\web\\ui && (set \"PREFIX_PATH_VALUE=\" || ver>nul) && gatsby build --prefix-paths && xcopy /E /I /Y public ..\\autogenra\\web\\ui
+
+        ````
+
+### Running the Application
+
+Once installed, run the web UI by entering the following in your terminal:
 
 ```bash
-autogenra ui --port 8081 # run the web ui on port 8081
+autogenra ui --port 8081
 ```
 
-Navigate to <http://localhost:8081/> to view the web ui.
+This will start the application on the specified port. Open your web browser and go to `http://localhost:8081/` to begin using AutoGen Assistant.
 
-To update the web ui, navigate to the frontend directory, make changes and rebuild the ui.
+Now that you have AutoGen Assistant installed and running, you are ready to explore its capabilities, including defining and modifying agent workflows, interacting with agents and sessions, and expanding agent skills.
 
 ## Capabilities
 
@@ -108,12 +101,18 @@ The agents responds by _writing and executing code_ to create a python program t
 
 ## FAQ
 
-- How do I add more skills to the research assistant? This can be done by adding a new file with documented functions to `autogenra/web/skills/global` directory.
-- How do I specify the agent configuration (e.g. temperature, model, agent system message, model etc). You can do either from the UI interface or by modifying the default agent configuration in `utils.py` (`get_default_agent_config()` method)
-- How do I reset the conversation? You can reset the conversation by deleting the `database.sqlite` file. You can also delete user files by deleting the `autogenra/web/files/user/<user_id_md5hash>` folder.
-- How do I view messages generated by agents? You can view the messages generated by the agents in the debug console. You can also view the messages in the `database.sqlite` file.
+**Q: How can I add more skills to the AutoGen Assistant?**
+A: You can extend the capabilities of your agents by adding new Python functions. The AutoGen Assistant interface also lets you directly paste functions that can be reused in the agent workflow.
+
+**Q: Where can I adjust the agent configurations and settings?**
+A: You can modify agent configurations directly from the UI or by editing the default configurations in the `utils.py` file under the `get_default_agent_config()` method (assuming you are building your own UI).
+
+**Q: If I want to reset the conversation with an agent, how do I go about it?**
+A: To reset your conversation history, you can delete the `database.sqlite` file. If you need to clear user-specific data, remove the relevant `autogenra/web/files/user/<user_id_md5hash>` folder.
+
+**Q: Is it possible to view the output and messages generated by the agents during interactions?**
+A: Yes, you can view the generated messages in the debug console of the web UI, providing insights into the agent interactions. Alternatively, you can inspect the `database.sqlite` file for a comprehensive record of messages.
 
 ## Acknowledgements
 
-Based on the [AutoGen](https://microsoft.github.io/autogen) project.
-Adapted in October 2023 from a research prototype (original credits: Gagan Bansal, Adam Fourney, Victor Dibia, Piali Choudhury, Saleema Amershi, Ahmed Awadallah, Chi Wang)
+AutoGen assistant is Based on the [AutoGen](https://microsoft.github.io/autogen) project. It is adapted in October 2023 from a research prototype (original credits: Gagan Bansal, Adam Fourney, Victor Dibia, Piali Choudhury, Saleema Amershi, Ahmed Awadallah, Chi Wang)

samples/apps/autogen-assistant/autogenra/__init__.py

@@ -0,0 +1,3 @@
+from .autogenflow import *
+from .autogenchat import *
+from .datamodel import *

samples/apps/autogen-assistant/autogenra/autogenchat.py

@@ -1,17 +1,17 @@
 import json
 import time
 from typing import List
-from .datamodel import FlowConfig, Message
+from .datamodel import AgentWorkFlowConfig, Message
 from .utils import extract_successful_code_blocks, get_default_agent_config, get_modified_files
-from .autogenflow import AutoGenFlow
+from .autogenflow import AutoGenWorkFlowManager
 import os
 
 
-class ChatManager:
+class AutoGenChatManager:
     def __init__(self) -> None:
         pass
 
-    def chat(self, message: Message, history: List, flow_config: FlowConfig = None, **kwargs) -> None:
+    def chat(self, message: Message, history: List, flow_config: AgentWorkFlowConfig = None, **kwargs) -> None:
         work_dir = kwargs.get("work_dir", None)
         scratch_dir = os.path.join(work_dir, "scratch")
         skills_suffix = kwargs.get("skills_prompt", "")
@@ -21,7 +21,9 @@ def chat(self, message: Message, history: List, flow_config: FlowConfig = None,
             flow_config = get_default_agent_config(scratch_dir, skills_suffix=skills_suffix)
 
         # print("Flow config: ", flow_config)
-        flow = AutoGenFlow(config=flow_config, history=history, work_dir=scratch_dir, asst_prompt=skills_suffix)
+        flow = AutoGenWorkFlowManager(
+            config=flow_config, history=history, work_dir=scratch_dir, assistant_prompt=skills_suffix
+        )
         message_text = message.content.strip()
 
         output = ""
@@ -36,11 +38,7 @@ def chat(self, message: Message, history: List, flow_config: FlowConfig = None,
         successful_code_blocks = extract_successful_code_blocks(agent_chat_messages)
         successful_code_blocks = "\n\n".join(successful_code_blocks)
         output = (
-            (
-                flow.sender.last_message()["content"]
-                + "\n The following code snippets were used: \n"
-                + successful_code_blocks
-            )
+            (flow.sender.last_message()["content"] + "\n" + successful_code_blocks)
             if successful_code_blocks
             else flow.sender.last_message()["content"]
         )
@@ -51,14 +49,15 @@ def chat(self, message: Message, history: List, flow_config: FlowConfig = None,
         modified_files = get_modified_files(start_time, end_time, scratch_dir, dest_dir=work_dir)
         metadata["files"] = modified_files
 
-        print("Modified files: ", modified_files)
+        print("Modified files: ", len(modified_files))
 
         output_message = Message(
             user_id=message.user_id,
             root_msg_id=message.root_msg_id,
             role="assistant",
             content=output,
             metadata=json.dumps(metadata),
+            session_id=message.session_id,
         )
 
         return output_message

samples/apps/autogen-assistant/autogenra/autogenflow.py

@@ -1,16 +1,20 @@
 from typing import List, Optional
 from dataclasses import asdict
 import autogen
-from .datamodel import AgentFlowSpec, FlowConfig, Message
+from .datamodel import AgentFlowSpec, AgentWorkFlowConfig, Message
 
 
-class AutoGenFlow:
+class AutoGenWorkFlowManager:
     """
-    AutoGenFlow class to load agents from a provided configuration and run a chat between them
+    AutoGenWorkFlowManager class to load agents from a provided configuration and run a chat between them
     """
 
     def __init__(
-        self, config: FlowConfig, history: Optional[List[Message]] = None, work_dir: str = None, asst_prompt: str = None
+        self,
+        config: AgentWorkFlowConfig,
+        history: Optional[List[Message]] = None,
+        work_dir: str = None,
+        assistant_prompt: str = None,
     ) -> None:
         """
         Initializes the AutoGenFlow with agents specified in the config and optional
@@ -21,8 +25,8 @@ def __init__(
             history: An optional list of previous messages to populate the agents' history.
 
         """
-        self.work_dir = work_dir
-        self.asst_prompt = asst_prompt
+        self.work_dir = work_dir or "work_dir"
+        self.assistant_prompt = assistant_prompt or ""
         self.sender = self.load(config.sender)
         self.receiver = self.load(config.receiver)
 
@@ -87,13 +91,14 @@ def sanitize_agent_spec(self, agent_spec: AgentFlowSpec) -> AgentFlowSpec:
             code_execution_config = agent_spec.config.code_execution_config or {}
             code_execution_config["work_dir"] = self.work_dir
             agent_spec.config.code_execution_config = code_execution_config
+
         if agent_spec.type == "assistant":
             agent_spec.config.system_message = (
                 autogen.AssistantAgent.DEFAULT_SYSTEM_MESSAGE
                 + "\n\n"
                 + agent_spec.config.system_message
                 + "\n\n"
-                + self.asst_prompt
+                + self.assistant_prompt
             )
 
         return agent_spec

samples/apps/autogen-assistant/autogenra/datamodel.py

@@ -2,7 +2,7 @@
 from datetime import datetime
 from typing import Any, Callable, Dict, List, Literal, Optional, Union
 from pydantic.dataclasses import dataclass
-from dataclasses import field
+from dataclasses import asdict, field
 
 
 @dataclass
@@ -17,6 +17,7 @@ class Message(object):
     ra: Optional[str] = None
     code: Optional[str] = None
     metadata: Optional[Any] = None
+    session_id: Optional[str] = None
 
     def __post_init__(self):
         if self.msg_id is None:
@@ -25,18 +26,9 @@ def __post_init__(self):
             self.timestamp = datetime.now()
 
     def dict(self):
-        return {
-            "user_id": self.user_id,
-            "role": self.role,
-            "content": self.content,
-            "root_msg_id": self.root_msg_id,
-            "msg_id": self.msg_id,
-            "timestamp": self.timestamp,
-            "personalize": self.personalize,
-            "ra": self.ra,
-            "code": self.code,
-            "metadata": self.metadata,
-        }
+        result = asdict(self)
+        result["timestamp"] = result["timestamp"].isoformat()
+        return result
 
 
 # web api data models
@@ -69,7 +61,7 @@ class AgentConfig:
     """Data model for Agent Config for Autogen"""
 
     name: str
-    llm_config: Optional[LLMConfig] = None
+    llm_config: Optional[Union[LLMConfig, bool]] = False
     human_input_mode: str = "NEVER"
     max_consecutive_auto_reply: int = 10
     system_message: Optional[str] = None
@@ -86,35 +78,86 @@ class AgentFlowSpec:
 
 
 @dataclass
-class FlowConfig:
+class AgentWorkFlowConfig:
     """Data model for Flow Config for Autogen"""
 
     name: str
     sender: AgentFlowSpec
     receiver: Union[AgentFlowSpec, List[AgentFlowSpec]]
     type: Literal["default", "groupchat"] = "default"
 
+    def dict(self):
+        return asdict(self)
+
+
+@dataclass
+class Session(object):
+    """Data model for AutoGen Chat Session"""
+
+    user_id: str
+    session_id: Optional[str] = None
+    timestamp: Optional[datetime] = None
+    flow_config: AgentWorkFlowConfig = None
+
+    def __post_init__(self):
+        if self.timestamp is None:
+            self.timestamp = datetime.now()
+        if self.session_id is None:
+            self.session_id = str(uuid.uuid4())
+
+    def dict(self):
+        result = asdict(self)
+        result["timestamp"] = self.timestamp.isoformat()
+        return result
+
+
+@dataclass
+class Gallery(object):
+    """Data model for Gallery Item"""
+
+    session: Session
+    messages: List[Message]
+    tags: List[str]
+    id: Optional[str] = None
+    timestamp: Optional[datetime] = None
+
+    def __post_init__(self):
+        if self.timestamp is None:
+            self.timestamp = datetime.now()
+        if self.id is None:
+            self.id = str(uuid.uuid4())
+
+    def dict(self):
+        result = asdict(self)
+        result["timestamp"] = self.timestamp.isoformat()
+        return result
+
 
 @dataclass
 class ChatWebRequestModel(object):
     """Data model for Chat Web Request for Web End"""
 
     message: Message
-    flow_config: FlowConfig
+    flow_config: AgentWorkFlowConfig
 
 
 @dataclass
 class DeleteMessageWebRequestModel(object):
     user_id: str
     msg_id: str
+    session_id: Optional[str] = None
 
 
 @dataclass
-class ClearDBWebRequestModel(object):
+class CreateSkillWebRequestModel(object):
     user_id: str
+    skills: Union[str, List[str]]
 
 
 @dataclass
-class CreateSkillWebRequestModel(object):
+class DBWebRequestModel(object):
     user_id: str
-    skills: Union[str, List[str]]
+    msg_id: Optional[str] = None
+    session: Optional[Session] = None
+    skills: Optional[Union[str, List[str]]] = None
+    tags: Optional[List[str]] = None