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matrix-pygmalion-bot
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memory

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Hendrik Langer 2 years ago
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ee1ffbac6b
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64bdbc9c0f
4 changed files with 81 additions and 58 deletions
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  1. 92
      matrix_pygmalion_bot/bot/ai/langchain.py
  2. 23
      matrix_pygmalion_bot/bot/ai/langchain_memory.py
  3. 12
      matrix_pygmalion_bot/bot/core.py
  4. 12
      matrix_pygmalion_bot/main.py

92
matrix_pygmalion_bot/bot/ai/langchain.py
View File

@ -102,24 +102,23 @@ class AI(object):
def get_memory(self, room_id, human_prefix="Human"): def get_memory(self, room_id, human_prefix="Human"):
if not room_id in self.rooms: if not room_id in self.rooms:
self.rooms[room_id] = {} self.rooms[room_id] = {}
memory = CustomMemory(memory_key="chat_history", input_key="input", human_prefix=human_prefix, ai_prefix=self.bot.name, llm=self.llm_summary, summary_prompt=prompt_progressive_summary, max_len=1200, min_len=200) if "moving_summary" in self.bot.rooms[room_id]:
moving_summary = self.bot.rooms[room_id]['moving_summary']
else:
moving_summary = "No previous events."
memory = CustomMemory(memory_key="chat_history", input_key="input", human_prefix=human_prefix, ai_prefix=self.bot.name, llm=self.llm_summary, summary_prompt=prompt_progressive_summary, moving_summary_buffer=moving_summary, max_len=1200, min_len=200)
self.rooms[room_id]["memory"] = memory self.rooms[room_id]["memory"] = memory
self.rooms[room_id]["summary"] = "No previous events." #memory.chat_memory.add_ai_message(self.bot.greeting)
memory.chat_memory.add_ai_message(self.bot.greeting)
#memory.save_context({"input": None, "output": self.bot.greeting})
memory.load_memory_variables({})
else: else:
memory = self.rooms[room_id]["memory"] memory = self.rooms[room_id]["memory"]
#print(f"memory: {memory.load_memory_variables({})}") if human_prefix != memory.human_prefix:
#print(f"memory has an estimated {self.llm_chat.get_num_tokens(memory.buffer)} number of tokens") memory.human_prefix = human_prefix
return memory return memory
async def add_chat_message(self, message): async def add_chat_message(self, message):
conversation_memory = self.get_memory(message.room_id) room_id = message.additional_kwargs['room_id']
langchain_message = message.to_langchain() conversation_memory = self.get_memory(room_id)
if message.user_id == self.bot.connection.user_id: conversation_memory.chat_memory.messages.append(message)
langchain_message.role = self.bot.name
conversation_memory.chat_memory.messages.append(langchain_message)
async def clear(self, room_id): async def clear(self, room_id):
conversation_memory = self.get_memory(room_id) conversation_memory = self.get_memory(room_id)
@ -176,7 +175,7 @@ class AI(object):
llm=self.llm_chat, llm=self.llm_chat,
prompt=PromptTemplate.from_template(prompt_template), prompt=PromptTemplate.from_template(prompt_template),
) )
output = await chain.arun(message.message) output = await chain.arun(message.content)
return output.strip() return output.strip()
@ -190,33 +189,11 @@ class AI(object):
chat_human_name = "### Human" chat_human_name = "### Human"
conversation_memory = self.get_memory(room_id, chat_human_name) conversation_memory = self.get_memory(room_id, chat_human_name)
conversation_memory.human_prefix = chat_human_name
readonlymemory = ReadOnlySharedMemory(memory=conversation_memory) readonlymemory = ReadOnlySharedMemory(memory=conversation_memory)
summary_memory = ConversationSummaryMemory(llm=self.llm_summary, memory_key="summary", input_key="input") #summary_memory = ConversationSummaryMemory(llm=self.llm_summary, memory_key="summary", input_key="input")
#combined_memory = CombinedMemory(memories=[conversation_memory, summary_memory]) #combined_memory = CombinedMemory(memories=[conversation_memory, summary_memory])
k = 1 # 5 #await self.bot.schedule(self.bot.queue, make_progressive_summary, self.rooms[room_id]["summary"], conversation_memory.buffer) #.add_done_callback(
max_k = 3 # 12
if len(conversation_memory.chat_memory.messages) > max_k*2:
async def make_progressive_summary(previous_summary, chat_history_text_string):
await asyncio.sleep(0) # yield for matrix-nio
#self.rooms[room_id]["summary"] = summary_memory.predict_new_summary(conversation_memory.chat_memory.messages, previous_summary).strip()
summary_chain = LLMChain(llm=self.llm_summary, prompt=prompt_progressive_summary, verbose=True)
self.rooms[room_id]["summary"] = await summary_chain.apredict(summary=previous_summary, chat_history=chat_history_text_string)
# ToDo: maybe add an add_task_done callback and don't access the variable directly from here?
logger.info(f"New summary is: \"{self.rooms[room_id]['summary']}\"")
conversation_memory.chat_memory.messages = conversation_memory.chat_memory.messages[-k * 2 :]
conversation_memory.load_memory_variables({})
#summary = summarize(conversation_memory.buffer)
#print(summary)
#return summary
logger.info("memory progressive summary scheduled...")
await self.bot.schedule(self.bot.queue, make_progressive_summary, self.rooms[room_id]["summary"], conversation_memory.buffer) #.add_done_callback(
#t = datetime.fromtimestamp(message.additional_kwargs['timestamp']) #t = datetime.fromtimestamp(message.additional_kwargs['timestamp'])
#when = humanize.naturaltime(t) #when = humanize.naturaltime(t)
@ -231,11 +208,20 @@ class AI(object):
ai_name=self.bot.name, ai_name=self.bot.name,
persona=self.bot.persona, persona=self.bot.persona,
scenario=self.bot.scenario, scenario=self.bot.scenario,
summary=self.rooms[room_id]["summary"], summary=conversation_memory.moving_summary_buffer,
human_name=chat_human_name, human_name=chat_human_name,
#example_dialogue=replace_all(self.bot.example_dialogue, {"{{user}}": chat_human_name, "{{char}}": chat_ai_name}) #example_dialogue=replace_all(self.bot.example_dialogue, {"{{user}}": chat_human_name, "{{char}}": chat_ai_name})
ai_name_chat=chat_ai_name, ai_name_chat=chat_ai_name,
) )
tmp_prompt_text = prompt.format(chat_history=conversation_memory.buffer, input=message.content)
prompt_len = self.llm_chat.get_num_tokens(tmp_prompt_text)
if prompt_len+256 > 2000:
logger.warning(f"Prompt too large. Estimated {prompt_len} tokens")
#roleplay_chain = RoleplayChain(llm_chain=chain, character_name=self.bot.name, persona=self.bot.persona, scenario=self.bot.scenario, ai_name_chat=chat_ai_name, human_name_chat=chat_human_name)
chain = ConversationChain( chain = ConversationChain(
llm=self.llm_chat, llm=self.llm_chat,
@ -247,8 +233,6 @@ class AI(object):
# output = llm_chain(inputs={"ai_name": self.bot.name, "persona": self.bot.persona, "scenario": self.bot.scenario, "human_name": chat_human_name, "ai_name_chat": self.bot.name, "chat_history": "", "input": message.content})['results'][0]['text'] # output = llm_chain(inputs={"ai_name": self.bot.name, "persona": self.bot.persona, "scenario": self.bot.scenario, "human_name": chat_human_name, "ai_name_chat": self.bot.name, "chat_history": "", "input": message.content})['results'][0]['text']
#roleplay_chain = RoleplayChain(llm_chain=chain, character_name=self.bot.name, persona=self.bot.persona, scenario=self.bot.scenario, ai_name_chat=chat_ai_name, human_name_chat=chat_human_name)
stop = ['<|endoftext|>', f"\n{chat_human_name}"] stop = ['<|endoftext|>', f"\n{chat_human_name}"]
#print(f"Message is: \"{message.content}\"") #print(f"Message is: \"{message.content}\"")
await asyncio.sleep(0) await asyncio.sleep(0)
@ -264,20 +248,26 @@ class AI(object):
own_message_resp = await reply_fn(output) own_message_resp = await reply_fn(output)
langchain_ai_message = AIMessage( output_message = AIMessage(
content=output, content=output,
additional_kwargs={ additional_kwargs={
"timestamp": datetime.now().timestamp(), "timestamp": datetime.now().timestamp(),
"user_name": self.bot.name, "user_name": self.bot.name,
"event_id": own_message_resp.event_id, "event_id": own_message_resp.event_id,
"user_id": None, "user_id": self.bot.connection.user_id,
"room_name": message.additional_kwargs['room_name'], "room_name": message.additional_kwargs['room_name'],
"room_id": own_message_resp.room_id, "room_id": own_message_resp.room_id,
} }
) )
conversation_memory.save_context({"input": message.content}, {"ouput": output}) await conversation_memory.asave_context(message, output_message)
conversation_memory.load_memory_variables({}) summary_len = self.llm_chat.get_num_tokens(conversation_memory.moving_summary_buffer)
if summary_len > 400:
logger.warning("Summary is getting too long. Refining...")
conversation_memory.moving_summary_buffer = await self.summarize(conversation_memory.moving_summary_buffer)
new_summary_len = self.llm_chat.get_num_tokens(conversation_memory.moving_summary_buffer)
logger.info(f"Refined summary from {summary_len} tokens to {new_summary_len} tokens ({new_summary_len-summary_len} tokens)")
self.bot.rooms[room_id]['moving_summary'] = conversation_memory.moving_summary_buffer
return output return output
@ -293,11 +283,13 @@ class AI(object):
await asyncio.sleep(0) # yield for matrix-nio await asyncio.sleep(0) # yield for matrix-nio
diary_chain = LLMChain(llm=self.llm_summary, prompt=prompt_outline, verbose=True) diary_chain = LLMChain(llm=self.llm_summary, prompt=prompt_outline, verbose=True)
conversation_memory = self.get_memory(room_id) conversation_memory = self.get_memory(room_id)
#self.rooms[message.room_id]["summary"]
string_messages = [] if self.llm_summary.get_num_tokens(conversation_memory.buffer_day) < 1600:
for m in conversation_memory.chat_memory_day.messages: input_text = conversation_memory.buffer_day
string_messages.append(f"{message.role}: {message.content}") else:
return await diary_chain.apredict(text="\n".join(string_messages)) input_text = conversation_memory.moving_summary_buffer
return await diary_chain.apredict(text=input_text)
async def agent(self): async def agent(self):
@ -371,7 +363,7 @@ class AI(object):
content=f"~~~~ {datetime.now().strftime('%A, %B %d, %Y')} ~~~~", content=f"~~~~ {datetime.now().strftime('%A, %B %d, %Y')} ~~~~",
additional_kwargs={ additional_kwargs={
"timestamp": datetime.now().timestamp(), "timestamp": datetime.now().timestamp(),
"user_name": self.bot.name, "user_name": None,
"event_id": None, "event_id": None,
"user_id": None, "user_id": None,
"room_name": None, "room_name": None,

23
matrix_pygmalion_bot/bot/ai/langchain_memory.py
View File

@ -88,9 +88,25 @@ class CustomMemory(BaseMemory):
curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer) curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
loop = asyncio.get_event_loop() loop = asyncio.get_event_loop()
self.moving_summary_buffer = loop.run_until_complete( self.moving_summary_buffer = loop.run_until_complete(
self.apredict_new_summary(pruned_memory, self.moving_summary_buffer) self.predict_new_summary(pruned_memory, self.moving_summary_buffer)
) )
async def asave_context(self, input_msg: BaseMessage, output_msg: BaseMessage) -> None:
"""Save context from this conversation to buffer."""
self.chat_memory.messages.append(input_msg)
self.chat_memory.messages.append(output_msg)
self.chat_memory_day.messages.append(input_msg)
self.chat_memory_day.messages.append(output_msg)
# Prune buffer if it exceeds max token limit
buffer = self.chat_memory.messages
curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
if curr_buffer_length > self.max_len:
pruned_memory = []
while curr_buffer_length > self.min_len:
pruned_memory.append(buffer.pop(0))
curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
self.moving_summary_buffer = await self.apredict_new_summary(pruned_memory, self.moving_summary_buffer)
def clear(self) -> None: def clear(self) -> None:
"""Clear memory contents.""" """Clear memory contents."""
@ -157,9 +173,10 @@ class CustomMemory(BaseMemory):
ai_prefix=self.ai_prefix, ai_prefix=self.ai_prefix,
) )
chain = LLMChain(llm=self.llm, prompt=self.summary_prompt) chain = LLMChain(llm=self.llm, prompt=self.summary_prompt, verbose = True)
await asyncio.sleep(0) await asyncio.sleep(0)
return await chain.apredict(summary=existing_summary, new_lines=new_lines) output = await chain.apredict(summary=existing_summary, chat_history=new_lines)
return output.strip()
class ChatMessageHistoryMessage(BaseModel): class ChatMessageHistoryMessage(BaseModel):

12
matrix_pygmalion_bot/bot/core.py
View File

@ -81,6 +81,7 @@ class ChatBot(object):
task.cancel() task.cancel()
# Wait until all worker tasks are cancelled. # Wait until all worker tasks are cancelled.
await asyncio.gather(*self.background_tasks, return_exceptions=True) await asyncio.gather(*self.background_tasks, return_exceptions=True)
await self.write_conf2(self.rooms)
await self.connection.logout() await self.connection.logout()
async def load_ai(self, available_text_endpoints, available_image_endpoints): async def load_ai(self, available_text_endpoints, available_image_endpoints):
@ -137,6 +138,10 @@ class ChatBot(object):
if self.name.casefold() == message.user_name.casefold(): if self.name.casefold() == message.user_name.casefold():
"""Bot and user have the same name""" """Bot and user have the same name"""
message.user_name += " 2" # or simply "You" message.user_name += " 2" # or simply "You"
if message.is_from(self.connection.user_id):
message.role = "ai"
else:
message.role = "human"
if not room.room_id in self.rooms: if not room.room_id in self.rooms:
self.rooms[room.room_id] = {} self.rooms[room.room_id] = {}
@ -148,18 +153,15 @@ class ChatBot(object):
if not self.connection.synced: if not self.connection.synced:
if not message.is_command() and not message.is_error(): if not message.is_command() and not message.is_error():
await self.ai.add_chat_message(message) await self.ai.add_chat_message(message.to_langchain())
self.chatlog.save(message, False) self.chatlog.save(message, False)
return return
if message.is_from(self.connection.user_id): if message.is_from(self.connection.user_id):
"""Skip messages from ouselves""" """Skip messages from ouselves"""
message.role = "ai"
self.chatlog.save(message) self.chatlog.save(message)
await self.connection.room_read_markers(room.room_id, event.event_id, event.event_id) await self.connection.room_read_markers(room.room_id, event.event_id, event.event_id)
return return
else:
message.role = "human"
# if event.decrypted: # if event.decrypted:
# encrypted_symbol = "🛡 " # encrypted_symbol = "🛡 "
@ -201,7 +203,7 @@ class ChatBot(object):
self.rooms[room.room_id]['num_messages'] += 1 self.rooms[room.room_id]['num_messages'] += 1
self.last_conversation = datetime.now() self.last_conversation = datetime.now()
self.chatlog.save(message) self.chatlog.save(message)
print("done")
async def redaction_cb(self, room, event) -> None: async def redaction_cb(self, room, event) -> None:
self.chatlog.remove_message_by_id(event.event_id) self.chatlog.remove_message_by_id(event.event_id)

12
matrix_pygmalion_bot/main.py
View File

@ -61,6 +61,13 @@ async def main() -> None:
try: try:
# loop = asyncio.get_running_loop()
#
# for signame in {'SIGINT', 'SIGTERM'}:
# loop.add_signal_handler(
# getattr(signal, signame),
# functools.partial(ask_exit, signame, loop))
if sys.version_info[0] == 3 and sys.version_info[1] < 11: if sys.version_info[0] == 3 and sys.version_info[1] < 11:
tasks = [] tasks = []
for bot in bots: for bot in bots:
@ -81,6 +88,11 @@ async def main() -> None:
await bot.disconnect() await bot.disconnect()
sys.exit(0) sys.exit(0)
#def ask_exit(signame, loop):
# print("got signal %s: exit" % signame)
# loop.stop()
if __name__ == "__main__": if __name__ == "__main__":
asyncio.run(main()) asyncio.run(main())

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