mirror of
https://github.com/aljazceru/Auto-GPT.git
synced 2026-01-19 22:14:28 +01:00
added support of API key based auth
This commit is contained in:
@@ -24,5 +24,6 @@ USE_WEAVIATE_EMBEDDED=False
|
||||
WEAVIATE_EMBEDDED_PATH="/home/me/.local/share/weaviate"
|
||||
WEAVIATE_USERNAME=
|
||||
WEAVIATE_PASSWORD=
|
||||
WEAVIATE_API_KEY=
|
||||
MEMORY_INDEX="auto-gpt"
|
||||
MEMORY_BACKEND="local"
|
||||
|
||||
@@ -226,7 +226,7 @@ export PINECONE_ENV="Your pinecone region" # something like: us-east4-gcp
|
||||
## Weaviate Setup
|
||||
|
||||
[Weaviate](https://weaviate.io/) is an open-source vector database. It allows to store data objects and vector embeddings from ML-models and scales seamlessly to billion of data objects. [An instance of Weaviate can be created locally (using Docker), on Kubernetes or using Weaviate Cloud Services](https://weaviate.io/developers/weaviate/quickstart).
|
||||
Although still experimental, [Embedded Weaviate](https://weaviate.io/developers/weaviate/installation/embedded) is supported which allows the Auto-GPT process itself to start a Weaviate instance. To enable it, set `USE_WEAVIATE_EMBEDDED` to `True` and make sure you `pip install "weaviate-client>=3.15.4"`.
|
||||
Although still experimental, [Embedded Weaviate](https://weaviate.io/developers/weaviate/installation/embedded) is supported which allows the Auto-GPT process itself to start a Weaviate instance. To enable it, set `USE_WEAVIATE_EMBEDDED` to `True` and make sure you `pip install "weaviate-client>=3.15.4"`.
|
||||
|
||||
#### Setting up environment variables
|
||||
|
||||
@@ -239,6 +239,7 @@ WEAVIATE_PORT="8080"
|
||||
WEAVIATE_PROTOCOL="http"
|
||||
WEAVIATE_USERNAME="your username"
|
||||
WEAVIATE_PASSWORD="your password"
|
||||
WEAVIATE_API_KEY="your weaviate API key if you have one"
|
||||
WEAVIATE_EMBEDDED_PATH="/home/me/.local/share/weaviate" # this is optional and indicates where the data should be persisted when running an embedded instance
|
||||
USE_WEAVIATE_EMBEDDED=False # set to True to run Embedded Weaviate
|
||||
MEMORY_INDEX="Autogpt" # name of the index to create for the application
|
||||
|
||||
@@ -74,7 +74,8 @@ class Config(metaclass=Singleton):
|
||||
self.weaviate_username = os.getenv("WEAVIATE_USERNAME", None)
|
||||
self.weaviate_password = os.getenv("WEAVIATE_PASSWORD", None)
|
||||
self.weaviate_scopes = os.getenv("WEAVIATE_SCOPES", None)
|
||||
self.weaviate_embedded_path = os.getenv('WEAVIATE_EMBEDDED_PATH', '~/.local/share/weaviate')
|
||||
self.weaviate_embedded_path = os.getenv("WEAVIATE_EMBEDDED_PATH", "~/.local/share/weaviate")
|
||||
self.weaviate_api_key = os.getenv("WEAVIATE_API_KEY", None)
|
||||
self.use_weaviate_embedded = os.getenv("USE_WEAVIATE_EMBEDDED", "False") == "True"
|
||||
|
||||
self.image_provider = os.getenv("IMAGE_PROVIDER")
|
||||
|
||||
@@ -46,6 +46,8 @@ class WeaviateMemory(MemoryProviderSingleton):
|
||||
def _build_auth_credentials(self, cfg):
|
||||
if cfg.weaviate_username and cfg.weaviate_password:
|
||||
return weaviate_auth.AuthClientPassword(cfg.weaviate_username, cfg.weaviate_password)
|
||||
if cfg.weaviate_api_key:
|
||||
return weaviate.auth.AuthApiKey(api_key=cfg.weaviate_api_key)
|
||||
else:
|
||||
return None
|
||||
|
||||
|
||||
Reference in New Issue
Block a user