Autogen 1st usecases

app.py

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+import streamlit as st
+
+from configfile import Config
+from src.streamlitui.loadui import LoadStreamlitUI
+from src.usecases.multiagentschat import MultiAgentChat
+from src.LLMS.groqllm import GroqLLM
+
+
+# MAIN Function START
+
+
+if __name__ == "__main__":
+    # config
+    obj_config = Config()
+    # load ui
+    ui = LoadStreamlitUI()
+    user_input = ui.load_streamlit_ui()
+
+    # Configure LLM
+    obj_llm_config = GroqLLM(user_controls_input=user_input)
+    obj_llm_config.groq_llm_config()
+    llm_config = st.session_state['llm_config']
+
+    # userInput
+    problem = st.chat_input("Start Chat ")
+
+    if problem:
+        # start multichat
+        obj_usecases = MultiAgentChat(assistant_name='Assistant', user_proxy_name='Userproxy', llm_config=llm_config,
+                                      problem=problem)
+        obj_usecases.run()

configfile.ini

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+[DEFAULT]
+PAGE_TITLE = AUTOGEN IN ACTION
+LLM_OPTIONS = Groq, Huggingface
+USECASE_OPTIONS = MultiAgent Chat, RAG Chat, With LLamaIndex Tool, Teachable Agent, With Langchain
+GROQ_MODEL_OPTIONS = Mixtral 8x7b, llama3-8b-8192, llama3-70b-8192, gemma-7b-i
+

configfile.py

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+from configparser import ConfigParser
+
+
+class Config:
+  def __init__(self, config_file="configfile.ini"):
+    self.config = ConfigParser()
+    self.config.read(config_file)
+
+  def get_llm_options(self):
+    return self.config["DEFAULT"].get("LLM_OPTIONS").split(", ")
+
+  def get_usecase_options(self):
+    return self.config["DEFAULT"].get("USECASE_OPTIONS").split(", ")
+
+  def get_groq_model_options(self):
+    return self.config["DEFAULT"].get("GROQ_MODEL_OPTIONS").split(", ")
+
+  def get_page_title(self):
+    return self.config["DEFAULT"].get("PAGE_TITLE")
+

requirements.txt

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+streamlit
+pyautogen
+groq

src/agents/assistantagent.py

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+from autogen import AssistantAgent
+import streamlit as st
+
+
+class TrackableAssistantAgent(AssistantAgent):
+    def _process_received_message(self, message, sender, silent):
+        with st.chat_message(sender.name):
+            st.write(message)
+        return super()._process_received_message(message, sender, silent)

src/agents/userproxyagent.py

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+from autogen import UserProxyAgent
+import streamlit as st
+
+
+class TrackableUserProxyAgent(UserProxyAgent):
+    def _process_received_message(self, message, sender, silent):
+        with st.chat_message("user"):
+            st.write(message)
+        return super()._process_received_message(message, sender, silent)

src/streamlitui/loadui.py

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+import streamlit as st
+from configfile import Config  # Import the Config class
+
+
+class LoadStreamlitUI:
+    def __init__(self):
+        self.config = Config()  # Create a Config instance
+        self.user_controls = {}
+
+    def load_streamlit_ui(self):
+        st.set_page_config(page_title= "🤖 " + self.config.get_page_title(), layout="wide")
+        st.header("🤖 " + self.config.get_page_title())
+
+        with st.sidebar:
+            # Get options from config
+            llm_options = self.config.get_llm_options()
+            usecase_options = self.config.get_usecase_options()
+
+            # LLM selection
+            self.user_controls["selected_llm"] = st.selectbox("Select LLM", llm_options)
+
+            if self.user_controls["selected_llm"] == 'Groq':
+                # Model selection
+                model_options = self.config.get_groq_model_options()
+                self.user_controls["selected_groq_model"] = st.selectbox("Select Model", model_options)
+                # API key input
+                self.user_controls["GROQ_API_KEY"] = st.session_state["GROQ_API_KEY"] = st.text_input("API Key",
+                                                                                                      type="password")
+            # Use case selection
+            self.user_controls["selected_usecase"] = st.selectbox("Select Usecases", usecase_options)
+            st.session_state["chat_with_history"] = st.sidebar.toggle("Chat With History")
+
+        return self.user_controls

src/usecases/multiagentschat.py

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+import asyncio
+from src.agents.assistantagent import TrackableAssistantAgent
+from src.agents.userproxyagent import TrackableUserProxyAgent
+import streamlit as st
+
+
+class MultiAgentChat:
+    def __init__(self, assistant_name, user_proxy_name, llm_config, problem):
+        self.assistant = TrackableAssistantAgent(name=assistant_name,
+                                                 system_message="""you are helpful assistant. 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 Admin",
+                                                  human_input_mode="NEVER",
+                                                  llm_config=llm_config,
+                                                  code_execution_config=False,
+                                                  is_termination_msg=lambda x: x.get("content", "").strip().endswith(
+                                                      "TERMINATE"))
+        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.assistant, message=self.problem, clear_history=st.session_state["chat_with_history"])
+
+    def run(self):
+        self.loop.run_until_complete(self.initiate_chat())