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Pinecone memory and memory usage tracking

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douglas
2023-04-03 20:31:01 -04:00
parent 62dfd84599
commit 475671d1e8
9 changed files with 167 additions and 71 deletions
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37
scripts/chat.py
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@@ -23,6 +23,19 @@ def create_chat_message(role, content):
return {"role": role, "content": content}
def generate_context(prompt, relevant_memory, full_message_history, model):
current_context = [
create_chat_message(
"system", prompt), create_chat_message(
"system", f"Permanent memory: {relevant_memory}")]
# Add messages from the full message history until we reach the token limit
next_message_to_add_index = len(full_message_history) - 1
insertion_index = len(current_context)
# Count the currently used tokens
current_tokens_used = token_counter.count_message_tokens(current_context, model)
return next_message_to_add_index, current_tokens_used, insertion_index, current_context
# TODO: Change debug from hardcode to argument
def chat_with_ai(
@@ -41,7 +54,7 @@ def chat_with_ai(
prompt (str): The prompt explaining the rules to the AI.
user_input (str): The input from the user.
full_message_history (list): The list of all messages sent between the user and the AI.
permanent_memory (list): The list of items in the AI's permanent memory.
permanent_memory (Obj): The memory object containing the permanent memory.
token_limit (int): The maximum number of tokens allowed in the API call.
Returns:
@@ -53,18 +66,20 @@ def chat_with_ai(
print(f"Token limit: {token_limit}")
send_token_limit = token_limit - 1000
current_context = [
create_chat_message(
"system", prompt), create_chat_message(
"system", f"Permanent memory: {permanent_memory}")]
relevant_memory = permanent_memory.get_relevant(str(full_message_history[-5:]), 10)
# Add messages from the full message history until we reach the token limit
next_message_to_add_index = len(full_message_history) - 1
current_tokens_used = 0
insertion_index = len(current_context)
if debug:
print('Memory Stats: ', permanent_memory.get_stats())
next_message_to_add_index, current_tokens_used, insertion_index, current_context = generate_context(
prompt, relevant_memory, full_message_history, model)
while current_tokens_used > 2500:
# remove memories until we are under 2500 tokens
relevant_memory = relevant_memory[1:]
next_message_to_add_index, current_tokens_used, insertion_index, current_context = generate_context(
prompt, relevant_memory, full_message_history, model)
# Count the currently used tokens
current_tokens_used = token_counter.count_message_tokens(current_context, model)
current_tokens_used += token_counter.count_message_tokens([create_chat_message("user", user_input)], model) # Account for user input (appended later)
while next_message_to_add_index >= 0: