code exec

.vscode/launch.json

@@ -0,0 +1,16 @@
+{
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "debug streamlit",
+            "type": "debugpy",
+            "request": "launch",
+            "program": "./.venv/Lib/site-packages/streamlit",  // /home/xx/tmp/venv/bin/streamlit",
+            "args": [
+                "run",
+                "app.py"
+            ],
+            "justMyCode": false
+        }
+    ]
+}

README.md

@@ -13,3 +13,8 @@ license: apache-2.0
  Autogen Multiagent 
 
 
+## Code execution 
+
+ ![alt text](image.png)
+
+

app.py

@@ -3,6 +3,7 @@ import streamlit as st
 from configfile import Config
 from src.streamlitui.loadui import LoadStreamlitUI
 from src.usecases.multiagentschat import MultiAgentChat
+from src.usecases.multiagentcodeexecution import MultiAgentCodeExecution
 from src.usecases.withllamaIndex import WithLlamaIndexMultiAgentChat
 from src.usecases.agentchatsqlspider import AgentChatSqlSpider
 from src.LLMS.groqllm import GroqLLM
@@ -28,7 +29,12 @@ if __name__ == "__main__":
 
     if problem:
         # start multichat
-        if user_input['selected_usecase'] == "MultiAgent Chat":
+        if user_input['selected_usecase'] == "MultiAgent Code Execution":
+            obj_usecases_multichat = MultiAgentCodeExecution(assistant_name=['Assistant',"Product_Manager"], user_proxy_name='Userproxy', llm_config=llm_config,
+                                          problem=problem)
+            obj_usecases_multichat.run()
+            
+        elif user_input['selected_usecase'] == "MultiAgent Chat":
             obj_usecases_multichat = MultiAgentChat(assistant_name='Assistant', user_proxy_name='Userproxy', llm_config=llm_config,
                                           problem=problem)
             obj_usecases_multichat.run()

codegen/tmp_code_3e1806a0bf22b99c6c5d2b77650fe9a8.py

@@ -0,0 +1,36 @@
+import tkinter as tk
+
+class TodoApp:
+    def __init__(self, root):
+        self.root = root
+        self.tasks = []
+
+        # Create a text input field for task description
+        self.task_entry = tk.Entry(self.root, width=50)
+        self.task_entry.grid(row=0, column=0, padx=(20, 0), pady=(20, 0))
+
+        # Implement a button to add the task to the list
+        self.add_button = tk.Button(self.root, text="Add Task", command=self.add_task)
+        self.add_button.grid(row=0, column=1, padx=(10, 20), pady=(20, 0))
+
+        # Display the added task in a list
+        self.task_listbox = tk.Listbox(self.root, width=50, height=10)
+        self.task_listbox.grid(row=1, column=0, columnspan=2, padx=(20, 0), pady=(10, 20))
+
+    def add_task(self):
+        # Get the task description from the text input field
+        task = self.task_entry.get()
+
+        # Store the new task in a list
+        self.tasks.append(task)
+
+        # Clear the text input field
+        self.task_entry.delete(0, tk.END)
+
+        # Display the added task in the list
+        self.task_listbox.insert(tk.END, task)
+
+root = tk.Tk()
+app = TodoApp(root)
+root.mainloop()
+TERMINATE

configfile.ini

@@ -1,6 +1,6 @@
 [DEFAULT]
 PAGE_TITLE = AUTOGEN IN ACTION
 LLM_OPTIONS = Groq, Huggingface
-USECASE_OPTIONS = MultiAgent Chat, RAG Chat, With LLamaIndex Tool, AgentChat Sql Spider
+USECASE_OPTIONS = MultiAgent Code Execution, MultiAgent Chat, RAG Chat, With LLamaIndex Tool, AgentChat Sql Spider
 GROQ_MODEL_OPTIONS = mixtral-8x7b-32768, llama3-8b-8192, llama3-70b-8192, gemma-7b-i
 

src/usecases/multiagentcodeexecution.py

@@ -0,0 +1,41 @@
+import asyncio
+from src.agents.assistantagent import TrackableAssistantAgent
+from src.agents.userproxyagent import TrackableUserProxyAgent
+import streamlit as st
+import autogen
+
+
+class MultiAgentCodeExecution:
+    def __init__(self, assistant_name, user_proxy_name, llm_config, problem):
+        self.coder = TrackableAssistantAgent(name=assistant_name[0],
+                                                 system_message="""you are helpful assistant and efficient in writing code.""",
+                                                 human_input_mode="NEVER",
+                                                 llm_config=llm_config,
+                                                 )
+        
+        self.pm = TrackableAssistantAgent(name=assistant_name[1],
+                                                 system_message="""You are efficient in Creative in software product ideas. Reply "TERMINATE" in 
+                                                 the end when everything is done """,
+                                                 human_input_mode="NEVER",
+                                                 llm_config=llm_config,
+                                                 )
+         
+        self.user_proxy = TrackableUserProxyAgent(name=user_proxy_name,
+                                                  system_message="You are human Admin",
+                                                  human_input_mode="NEVER",
+                                                  llm_config=llm_config,
+                                                  code_execution_config={"last_n_messages":2,"work_dir" : "./codegen","use_docker":False},
+                                                  is_termination_msg=lambda x: x.get("content", "").strip().endswith(
+                                                      "TERMINATE"))
+        
+        self.groupchat = autogen.GroupChat(agents=[self.user_proxy,self.coder,self.pm],messages=[],max_round=12)
+        self.manager = autogen.GroupChatManager(groupchat=self.groupchat,llm_config=llm_config)
+        self.problem = problem
+        self.loop = asyncio.new_event_loop()
+        asyncio.set_event_loop(self.loop)
+
+    async def initiate_chat(self):
+        await self.user_proxy.a_initiate_chat(self.manager, message=self.problem, clear_history=st.session_state["chat_with_history"])
+
+    def run(self):
+        self.loop.run_until_complete(self.initiate_chat())