langchain/templates/rag-redis/rag_redis/config.py
Tyler Hutcherson 4209457bdc
Redis langserve template (#12443)
Add Redis langserve template! Eventually will add semantic caching to
this too. But I was struggling to get that to work for some reason with
the LCEL implementation here.

- **Description:** Introduces the Redis LangServe template. A simple RAG
based app built on top of Redis that allows you to chat with company's
public financial data (Edgar 10k filings)
  - **Issue:** None
- **Dependencies:** The template contains the poetry project
requirements to run this template
  - **Tag maintainer:** @baskaryan @Spartee 
  - **Twitter handle:** @tchutch94

**Note**: this requires the commit here that deletes the
`_aget_relevant_documents()` method from the Redis retriever class that
wasn't implemented. That was breaking the langserve app.

---------

Co-authored-by: Sam Partee <sam.partee@redis.com>
2023-10-28 08:31:12 -07:00

77 lines
2.2 KiB
Python

import os
def get_boolean_env_var(var_name, default_value=False):
"""Retrieve the boolean value of an environment variable.
Args:
var_name (str): The name of the environment variable to retrieve.
default_value (bool): The default value to return if the variable
is not found.
Returns:
bool: The value of the environment variable, interpreted as a boolean.
"""
true_values = {'true', '1', 't', 'y', 'yes'}
false_values = {'false', '0', 'f', 'n', 'no'}
# Retrieve the environment variable's value
value = os.getenv(var_name, '').lower()
# Decide the boolean value based on the content of the string
if value in true_values:
return True
elif value in false_values:
return False
else:
return default_value
# Check for openai API key
if "OPENAI_API_KEY" not in os.environ:
raise Exception("Must provide an OPENAI_API_KEY as an env var.")
# Whether or not to enable langchain debugging
DEBUG = get_boolean_env_var("DEBUG", False)
# Set DEBUG env var to "true" if you wish to enable LC debugging module
if DEBUG:
import langchain
langchain.debug=True
# Embedding model
EMBED_MODEL = os.getenv("EMBED_MODEL",
"sentence-transformers/all-MiniLM-L6-v2")
# Redis Connection Information
REDIS_HOST = os.getenv("REDIS_HOST", "localhost")
REDIS_PORT = int(os.getenv("REDIS_PORT", 6379))
def format_redis_conn_from_env():
redis_url = os.getenv("REDIS_URL", None)
if redis_url:
return redis_url
else:
using_ssl = get_boolean_env_var("REDIS_SSL", False)
start = "rediss://" if using_ssl else "redis://"
# if using RBAC
password = os.getenv("REDIS_PASSWORD", None)
username = os.getenv("REDIS_USERNAME", "default")
if password is not None:
start += f"{username}:{password}@"
return start + f"{REDIS_HOST}:{REDIS_PORT}"
REDIS_URL = format_redis_conn_from_env()
# Vector Index Configuration
INDEX_NAME = os.getenv("INDEX_NAME", "rag-redis")
current_file_path = os.path.abspath(__file__)
parent_dir = os.path.dirname(current_file_path)
schema_path = os.path.join(parent_dir, 'schema.yml')
INDEX_SCHEMA = schema_path