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Add required env parameters for azure usage

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This commit is contained in:
Kari Ahdan
2023-04-10 16:43:06 +03:00
parent 4d42e14d3d
commit a504f0bdd3
5 changed files with 12 additions and 4 deletions
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2
.env.template
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@@ -10,5 +10,7 @@ USE_AZURE=False
OPENAI_API_BASE=your-base-url-for-azure OPENAI_API_BASE=your-base-url-for-azure
OPENAI_API_VERSION=api-version-for-azure OPENAI_API_VERSION=api-version-for-azure
OPENAI_DEPLOYMENT_ID=deployment-id-for-azure OPENAI_DEPLOYMENT_ID=deployment-id-for-azure
AZURE_CHAT_DEPLOYMENT_ID=deployment-id-for-azure-chat-ai
AZURE_EMBEDDINGS_DEPLOYMENT_ID=deployment-id-for-azure-embeddigs-ai
IMAGE_PROVIDER=dalle IMAGE_PROVIDER=dalle
HUGGINGFACE_API_TOKEN= HUGGINGFACE_API_TOKEN=

2
README.md
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@@ -93,7 +93,7 @@ pip install -r requirements.txt
4. Rename `.env.template` to `.env` and fill in your `OPENAI_API_KEY`. If you plan to use Speech Mode, fill in your `ELEVEN_LABS_API_KEY` as well. 4. Rename `.env.template` to `.env` and fill in your `OPENAI_API_KEY`. If you plan to use Speech Mode, fill in your `ELEVEN_LABS_API_KEY` as well.
- Obtain your OpenAI API key from: https://platform.openai.com/account/api-keys. - Obtain your OpenAI API key from: https://platform.openai.com/account/api-keys.
- Obtain your ElevenLabs API key from: https://beta.elevenlabs.io. You can view your xi-api-key using the "Profile" tab on the website. - Obtain your ElevenLabs API key from: https://beta.elevenlabs.io. You can view your xi-api-key using the "Profile" tab on the website.
- If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and provide the `OPENAI_API_BASE`, `OPENAI_API_VERSION` and `OPENAI_DEPLOYMENT_ID` values as explained here: https://pypi.org/project/openai/ in the `Microsoft Azure Endpoints` section - If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and provide the `OPENAI_API_BASE`, `OPENAI_API_VERSION` and `OPENAI_DEPLOYMENT_ID` values as explained here: https://pypi.org/project/openai/ in the `Microsoft Azure Endpoints` section. Additionally you need separate deployments for both embeddings and chat. Add their ID values to `AZURE_CHAT_DEPLOYMENT_ID` and `AZURE_EMBEDDINGS_DEPLOYMENT_ID` respectively
## 🔧 Usage ## 🔧 Usage

2
scripts/config.py
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@@ -49,6 +49,8 @@ class Config(metaclass=Singleton):
self.openai_api_base = os.getenv("OPENAI_API_BASE") self.openai_api_base = os.getenv("OPENAI_API_BASE")
self.openai_api_version = os.getenv("OPENAI_API_VERSION") self.openai_api_version = os.getenv("OPENAI_API_VERSION")
self.openai_deployment_id = os.getenv("OPENAI_DEPLOYMENT_ID") self.openai_deployment_id = os.getenv("OPENAI_DEPLOYMENT_ID")
self.azure_chat_deployment_id = os.getenv("AZURE_CHAT_DEPLOYMENT_ID")
self.azure_embeddigs_deployment_id = os.getenv("AZURE_EMBEDDINGS_DEPLOYMENT_ID")
openai.api_type = "azure" openai.api_type = "azure"
openai.api_base = self.openai_api_base openai.api_base = self.openai_api_base
openai.api_version = self.openai_api_version openai.api_version = self.openai_api_version

2
scripts/llm_utils.py
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@@ -9,7 +9,7 @@ def create_chat_completion(messages, model=None, temperature=None, max_tokens=No
"""Create a chat completion using the OpenAI API""" """Create a chat completion using the OpenAI API"""
if cfg.use_azure: if cfg.use_azure:
response = openai.ChatCompletion.create( response = openai.ChatCompletion.create(
deployment_id=cfg.openai_deployment_id, deployment_id=cfg.azure_chat_deployment_id,
model=model, model=model,
messages=messages, messages=messages,
temperature=temperature, temperature=temperature,

6
scripts/memory/base.py
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@@ -1,11 +1,15 @@
"""Base class for memory providers.""" """Base class for memory providers."""
import abc import abc
from config import AbstractSingleton from config import AbstractSingleton, Config
import openai import openai
cfg = Config()
def get_ada_embedding(text): def get_ada_embedding(text):
text = text.replace("\n", " ") text = text.replace("\n", " ")
if cfg.use_azure:
return openai.Embedding.create(input=[text], engine=cfg.azure_embeddigs_deployment_id, model="text-embedding-ada-002")["data"][0]["embedding"]
else:
return openai.Embedding.create(input=[text], model="text-embedding-ada-002")["data"][0]["embedding"] return openai.Embedding.create(input=[text], model="text-embedding-ada-002")["data"][0]["embedding"]