added simple password service that writes code for completion (still …

…working on)

saas_products/password/OAI_CONFIG_LIST

@@ -0,0 +1,6 @@
+[
+    {
+    "model": "gpt-3.5-turbo",
+    "api_key": "sk-1111"
+  }
+]

saas_products/password/password.py

@@ -0,0 +1,62 @@
+import autogen
+
+config_list = autogen.config_list_from_json(
+    "OAI_CONFIG_LIST",
+    filter_dict={
+        "model": ["gpt-3.5-turbo"],
+    },
+)
+
+llm_config = {
+    "config_list": config_list,
+    "seed": 42,
+    "temperature": 0.7,
+    "timeout": 300
+}
+
+user_proxy = autogen.UserProxyAgent(
+    name="Admin",
+    system_message="A human admin. Interact with the planner to discuss the plan. Plan execution needs to be approved "
+                   "by this admin.",
+    human_input_mode="TERMINATE",
+    code_execution_config={"last_n_messages": 3, "work_dir": "programming"},
+)
+
+engineer = autogen.AssistantAgent(
+    name="Engineer",
+    llm_config=llm_config,
+)
+
+planner = autogen.AssistantAgent(
+    name="Planner",
+    system_message='''Planner. Suggest a plan. Revise the plan based on feedback from admin and critic, until admin 
+    approval. The plan may involve an engineer who can write code and an executor and critic who doesn't write code. 
+    Explain the plan first. Be clear which step is performed by an engineer, executor, and critic.''',
+    llm_config=llm_config,
+)
+
+executor = autogen.AssistantAgent(
+    name="Executor",
+    system_message="Executor. Execute the code written by the engineer and report the result.  Once you execute the "
+                   "code, save it into a proper file under the correct directory.",
+    llm_config=llm_config
+)
+
+critic = autogen.AssistantAgent(
+    name="Critic",
+    system_message="Critic. Double check plan, claims, code from other agents and provide feedback.  You don't "
+                   "execute code, just provide feedback.",
+    llm_config=llm_config,
+)
+
+groupchat = autogen.GroupChat(agents=[user_proxy, engineer, planner, executor, critic], messages=[], max_round=20)
+manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
+
+user_proxy.initiate_chat(manager, message="I would like to build a simple application that allows me to call an api "
+                                          "to encrypt a message, which will be in the form of a string, and use the "
+                                          "RSA encryption algorithm.  Then this encrypted message should be stored in "
+                                          "a database table called Messages, which takes an id and then the column "
+                                          "for the message.  There should be another API that can be called to "
+                                          "retrieve the message based on an id, then grab the associated encrypted "
+                                          "message, decrypt it also using RSA and return the decrypted message.  Can "
+                                          "you create this as a flask application?")