🔧 chore(utils.py): add setup_llm_caching function to set up LLM caching
✨ feat(main.py): call setup_llm_caching function on app startup
The `setup_llm_caching` function is added to `utils.py` to set up LLM caching. The function is then called on app startup in `main.py` using the `app.on_event("startup")` method. This improves the performance of the application by caching LLM objects.
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@ -7,6 +7,7 @@ import re
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import yaml
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from langchain.base_language import BaseLanguageModel
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from PIL.Image import Image
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from langflow.utils.logger import logger
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def load_file_into_dict(file_path: str) -> dict:
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@ -58,3 +59,12 @@ def try_setting_streaming_options(langchain_object, websocket):
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def extract_input_variables_from_prompt(prompt: str) -> list[str]:
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"""Extract input variables from prompt."""
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return re.findall(r"{(.*?)}", prompt)
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def setup_llm_caching():
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"""Setup LLM caching."""
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import langchain
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from langchain.cache import SQLiteCache
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logger.debug("Setting up LLM caching")
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langchain.llm_cache = SQLiteCache()
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@ -3,6 +3,7 @@ from fastapi.middleware.cors import CORSMiddleware
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from langflow.api import router
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from langflow.database.base import create_db_and_tables
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from langflow.interface.utils import setup_llm_caching
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def create_app():
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@ -28,6 +29,7 @@ def create_app():
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app.include_router(router)
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app.on_event("startup")(create_db_and_tables)
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app.on_event("startup")(setup_llm_caching)
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return app
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