Improve welcome message

app.py

@@ -31,7 +31,7 @@ def initialize_agents(config_list, docs_path=None):
         human_input_mode="NEVER",
         max_consecutive_auto_reply=5,
         retrieve_config={
-            # "task": "qa",
+            "task": "code",
             "docs_path": docs_path,
             "chunk_token_size": 2000,
             "model": _config_list[0]["model"],
@@ -51,7 +51,7 @@ def initiate_chat(config_list, problem, queue, n_results=3):
     else:
         _config_list = config_list
     if len(_config_list[0].get("api_key", "")) < 2:
-        queue.put(["Please set the LLM config first"])
+        queue.put(["Hi, nice to meet you! Please enter your API keys in below text boxs."])
         return
     else:
         llm_config = (

test_group.py

@@ -0,0 +1,39 @@
+llm_config = {"config_list": config_list_gpt4, "seed": 42}
+
+ragproxyagent = RetrieveUserProxyAgent(
+    name="ragproxyagent",
+    human_input_mode="NEVER",
+    max_consecutive_auto_reply=10,
+    retrieve_config={
+        "task": "you need to fetch the answers related to company if needed",
+        "docs_path": "/content/Docs",
+        "chunk_token_size": 10,
+        "model": config_list_gpt4[0]["model"],
+        "client": chromadb.PersistentClient(path="/tmp/chromadb"),
+        "embedding_model": "all-mpnet-base-v2",
+    },
+)
+user_proxy = autogen.UserProxyAgent(
+   name="User_proxy",
+    human_input_mode="ALWAYS",
+    max_consecutive_auto_reply=5,
+    is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
+    code_execution_config={"work_dir": "web"},
+    llm_config=llm_config,
+    system_message="""You are a user of a mobile app. Reply to the agent with a suitable answer, otherwise reply I dont know or answer the agents questions with facts."""
+
+)
+support_agent = autogen.AssistantAgent(
+    name="support_agent",
+    llm_config=llm_config,
+    system_message="You are the founder of a mobile app. You are trying to find the reason for less usage and uninstalls from the customer by asking relevant questions. \
+    You try to answer the customer's query in the best possible way. If you do not know the answer ask for clarification or more data."
+)
+pm = autogen.AssistantAgent(
+    name="PM",
+    system_message="You are an expert in analysing if the objective of user research has been met from the conversation. Answer concisely.",
+    llm_config=llm_config,
+)
+groupchat = autogen.GroupChat(agents=[user_proxy, support_agent, pm, ragproxyagent], messages=[], max_round=8)
+manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
+but this seems not working the ragproxyagent is not participating in conversation