mirror of
https://github.com/lfnovo/open-notebook.git
synced 2026-04-29 03:50:04 +00:00
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
from langchain_core.language_models.chat_models import BaseChatModel
|
|
from langchain_core.messages import BaseMessage
|
|
from loguru import logger
|
|
|
|
from open_notebook.domain.models import model_manager
|
|
from open_notebook.models.llms import LanguageModel
|
|
from open_notebook.prompter import Prompter
|
|
from open_notebook.utils import token_count
|
|
|
|
|
|
def provision_langchain_model(content, config, default_type) -> BaseChatModel:
|
|
"""
|
|
Returns the best model to use based on the context size and on whether there is a specific model being requested in Config.
|
|
If context > 105_000, returns the large_context_model
|
|
If model_id is specified in Config, returns that model
|
|
Otherwise, returns the default model for the given type
|
|
"""
|
|
tokens = token_count(content)
|
|
|
|
if tokens > 105_000:
|
|
logger.debug(
|
|
f"Using large context model because the content has {tokens} tokens"
|
|
)
|
|
model = model_manager.get_default_model("large_context")
|
|
elif config.get("configurable", {}).get("model_id"):
|
|
model = model_manager.get_model(config.get("configurable", {}).get("model_id"))
|
|
else:
|
|
model = model_manager.get_default_model(default_type)
|
|
|
|
assert isinstance(model, LanguageModel), f"Model is not a LanguageModel: {model}"
|
|
return model.to_langchain()
|
|
|
|
|
|
# todo: turn into a graph
|
|
def run_pattern(
|
|
pattern_name: str,
|
|
config,
|
|
messages=[],
|
|
state: dict = {},
|
|
parser=None,
|
|
) -> BaseMessage:
|
|
system_prompt = Prompter(prompt_template=pattern_name, parser=parser).render(
|
|
data=state
|
|
)
|
|
payload = [system_prompt] + messages
|
|
chain = provision_langchain_model(str(payload), config, "transformation")
|
|
|
|
response = chain.invoke(payload)
|
|
|
|
return response
|