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matrix-pygmalion-bot
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skip old messages, redo summary

master
Hendrik Langer 2 years ago
parent
30a12e6315
commit
06230a7e1e
3 changed files with 43 additions and 24 deletions
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  1. 61
      matrix_pygmalion_bot/bot/ai/langchain.py
  2. 5
      matrix_pygmalion_bot/bot/ai/langchain_memory.py
  3. 1
      matrix_pygmalion_bot/bot/memory/chatlog.py

61
matrix_pygmalion_bot/bot/ai/langchain.py
View File

@ -89,8 +89,8 @@ class AI(object):
self.rooms = {}
from ..wrappers.langchain_koboldcpp import KoboldCpp
self.llm_chat = KoboldCpp(temperature=self.bot.temperature, endpoint_url="http://172.16.85.10:5001/api/latest/generate", stop=['<|endoftext|>'])
self.llm_summary = KoboldCpp(temperature=0.2, endpoint_url="http://172.16.85.10:5002/api/latest/generate", stop=['<|endoftext|>'], max_tokens=512)
self.llm_chat = KoboldCpp(temperature=self.bot.temperature, endpoint_url="http://172.16.85.10:5001/api/latest/generate", stop=['<|endoftext|>'], verbose=True)
self.llm_summary = KoboldCpp(temperature=0.2, endpoint_url="http://172.16.85.10:5002/api/latest/generate", stop=['<|endoftext|>'], max_tokens=512, verbose=True)
self.llm_chat_model = "pygmalion-7b"
self.llm_summary_model = "vicuna-13b"
self.text_wrapper = text_wrapper
@ -108,9 +108,13 @@ class AI(object):
moving_summary = self.bot.rooms[room_id]['moving_summary']
else:
moving_summary = "No previous events."
if "last_message_ids_summarized" in self.bot.rooms[room_id]:
last_message_ids_summarized = self.bot.rooms[room_id]['last_message_ids_summarized']
else:
last_message_ids_summarized = []
if not human_prefix:
human_prefix = "Human"
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)
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, last_message_ids_summarized=last_message_ids_summarized)
self.rooms[room_id]["memory"] = memory
#memory.chat_memory.add_ai_message(self.bot.greeting)
else:
@ -122,6 +126,9 @@ class AI(object):
async def add_chat_message(self, message):
room_id = message.additional_kwargs['room_id']
conversation_memory = self.get_memory(room_id)
if 'event_id' in message.additional_kwargs and message.additional_kwargs['event_id'] in conversation_memory.last_message_ids_summarized:
#don't add already summarized messages
return
conversation_memory.chat_memory.messages.append(message)
conversation_memory.chat_memory_day.messages.append(message)
@ -218,28 +225,33 @@ class AI(object):
# the resulting template text to feed it into the instruct prompt's instruction
# or do this with the prompt.partial()
prompt = prompt_chat.partial(
ai_name=self.bot.name,
persona=self.bot.persona,
scenario=self.bot.scenario,
human_name=chat_human_name,
ai_name_chat=chat_ai_name,
)
if "summary" in prompt_chat.input_variables:
prompt = prompt.partial(summary=conversation_memory.moving_summary_buffer)
if "example_dialogue" in prompt_chat.input_variables:
prompt = prompt.partial(
example_dialogue=self.bot.example_dialogue.replace("{{user}}", chat_human_name)
for i in range(1):
prompt = prompt_chat.partial(
ai_name=self.bot.name,
persona=self.bot.persona,
scenario=self.bot.scenario,
human_name=chat_human_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")
await reply_fn(f"<WARNING> Prompt too large. Estimated {prompt_len} tokens")
await conversation_memory.prune_memory(conversation_memory.min_len)
if "summary" in prompt.input_variables:
prompt = prompt.partial(summary=conversation_memory.moving_summary_buffer)
if "example_dialogue" in prompt.input_variables:
prompt = prompt.partial(
example_dialogue=self.bot.example_dialogue.replace("{{user}}", chat_human_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")
await reply_fn(f"<WARNING> Prompt too large. Estimated {prompt_len} tokens")
if i == 0:
await conversation_memory.prune_memory(conversation_memory.min_len)
elif i == 1:
conversation_memory.moving_summary_buffer = await self.summarize(conversation_memory.moving_summary_buffer)
else:
break
#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)
@ -288,6 +300,7 @@ class AI(object):
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
self.bot.rooms[room_id]['last_message_ids_summarized'] = conversation_memory.last_message_ids_summarized
return output

5
matrix_pygmalion_bot/bot/ai/langchain_memory.py
View File

@ -52,6 +52,7 @@ class CustomMemory(BaseMemory):
#length_function: Callable[[str], int] = self.llm.get_num_tokens_from_messages,
moving_summary_buffer: str = ""
last_message_ids_summarized = []
llm: BaseLanguageModel
summary_prompt: BasePromptTemplate = SUMMARY_PROMPT
@ -102,6 +103,10 @@ class CustomMemory(BaseMemory):
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)
for m in pruned_memory:
if "event_id" in m.additional_kwargs:
self.last_message_ids_summarized.append(m.additional_kwargs['event_id'])
self.last_message_ids_summarized = self.last_message_ids_summarized[-100 :]
async def asave_context(self, input_msg: BaseMessage, output_msg: BaseMessage) -> None:
"""Save context from this conversation to buffer."""

1
matrix_pygmalion_bot/bot/memory/chatlog.py
View File

@ -15,6 +15,7 @@ class ChatLog(object):
if not message.room_id in self.chat_history:
self.chat_history[message.room_id] = {}
self.chat_history[message.room_id][message.event_id] = message
self.chat_history[message.room_id] = dict(list(self.chat_history[message.room_id].items())[-100 :])
if hasattr(self, 'directory') and is_new:
keepcharacters = (' ','.','_','-')

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