Now a function prototype with an LLM backend.

* Added langchain support (OpenAI's gpt-4o model)
* Created a system prompt that gives functional results
* Initial integration of logging for LLM responses (needs improvement)

requirements.txt

@@ -1,3 +1,3 @@
 langchain
 langchain_community
-
+langchain_openai

ssh_server.py

@@ -11,22 +11,52 @@ import logging
 import datetime
 import uuid
 
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import HumanMessage
+from langchain_core.chat_history import (
+    BaseChatMessageHistory,
+    InMemoryChatMessageHistory,
+)
+from langchain_core.runnables.history import RunnableWithMessageHistory
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+
+
 async def handle_client(process: asyncssh.SSHServerProcess) -> None:
 # This is the main loop for handling SSH client connections. 
 # Any user interaction should be done here.
 
     # Give each session a unique name
+    task_uuid = f"session-{uuid.uuid4()}"
     current_task = asyncio.current_task()
-    current_task.set_name(f"session-{uuid.uuid4()}")
+    current_task.set_name(task_uuid)
 
-    process.stdout.write('Welcome to my SSH server, %s!\n' %
+    llm_config = {"configurable": {"session_id": task_uuid}}
-                         process.get_extra_info('username'))
+
+    llm_response = await with_message_history.ainvoke(
+        {
+            "messages": [HumanMessage(content="")],
+            "username": process.get_extra_info('username')
+        },
+            config=llm_config
+    )
+
+    process.stdout.write(f"{llm_response.content}")
+    logger.info(f"OUTPUT: {llm_response.content}")
 
     try:
         async for line in process.stdin:
             line = line.rstrip('\n')
             logger.info(f"INPUT: {line}")
-            process.stdout.write('You entered: %s\n' % line)
+            llm_response = await with_message_history.ainvoke(
+                {
+                    "messages": [HumanMessage(content=line)],
+                    "username": process.get_extra_info('username')
+                },
+                    config=llm_config
+            )
+
+            process.stdout.write(f"{llm_response.content}")
+            logger.info(f"OUTPUT: {llm_response.content}")
     except asyncssh.BreakReceived:
         pass
 
@@ -42,7 +72,6 @@ class MySSHServer(asyncssh.SSHServer):
             logger.error('SSH connection error: ' + str(exc), file=sys.stderr)
 
         else:
-            print('SSH connection closed.')
             logger.info("SSH connection closed.")
 
     def begin_auth(self, username: str) -> bool:
@@ -87,6 +116,11 @@ def read_accounts() -> dict:
 
     return accounts
 
+def llm_get_session_history(session_id: str) -> BaseChatMessageHistory:
+    if session_id not in llm_sessions:
+        llm_sessions[session_id] = InMemoryChatMessageHistory()
+    return llm_sessions[session_id]
+
 #### MAIN ####
 
 # Always use UTC for logging
@@ -104,6 +138,47 @@ log_file_handler.setFormatter(logging.Formatter("%(asctime)s %(levelname)s:%(tas
 f = ContextFilter()
 logger.addFilter(f)
 
+# Now get access to the LLM
+llm_model = ChatOpenAI(model="gpt-4o")
+
+llm_sessions = dict()
+
+llm_prompt = ChatPromptTemplate.from_messages(
+    [
+        (
+            "system",
+            '''
+            You are a linux operating system accepting commands from a user via SSH. 
+            Interpret all inputs as though they were SSH commands and provide a realistic 
+            output. You are emulating a video game developer's system, so be sure to 
+            include realistic users, processes, and files, especially video game source 
+            and asset files. Do not include extraneous formatting in your responses. 
+            
+            On the first call, be sure to include a realistic MOTD. 
+            
+            End all responses with a realistic shell prompt to display to the user, 
+            including a space at the end. 
+            
+            Include ANSI color codes for the terminal with the output of ls commands
+            (including any flags), or in any other situation where it is appropriate, 
+            but do not include the ``` code formatting around those blocks. 
+            
+            Assume the username is {username}.
+            '''
+        ),
+        MessagesPlaceholder(variable_name="messages"),
+    ]
+)
+
+llm_chain = llm_prompt | llm_model
+
+with_message_history = RunnableWithMessageHistory(
+    llm_chain, 
+    llm_get_session_history,
+    input_messages_key="messages"
+)
+
+
 # Read the valid accounts
 accounts = read_accounts()