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Merge branch 'master' into patch-1

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Ishwor Panta
2023-04-13 19:10:06 +05:45
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@@ -96,10 +96,15 @@ pip install -r requirements.txt
```
5. 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 ElevenLabs API key from: https://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_AZURE_API_BASE`, `OPENAI_AZURE_API_VERSION` and `OPENAI_AZURE_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 `OPENAI_AZURE_CHAT_DEPLOYMENT_ID` and `OPENAI_AZURE_EMBEDDINGS_DEPLOYMENT_ID` respectively
- Obtain your OpenAI API key from: https://platform.openai.com/account/api-keys.
- Obtain your ElevenLabs API key from: https://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 then:
- Rename `azure.yaml.template` to `azure.yaml` and provide the relevant `azure_api_base`, `azure_api_version` and all of the deployment ids for the relevant models in the `azure_model_map` section:
- `fast_llm_model_deployment_id` - your gpt-3.5-turbo or gpt-4 deployment id
- `smart_llm_model_deployment_id` - your gpt-4 deployment id
- `embedding_model_deployment_id` - your text-embedding-ada-002 v2 deployment id
- Please specify all of these values as double quoted strings
- details can be found here: https://pypi.org/project/openai/ in the `Microsoft Azure Endpoints` section and here: https://learn.microsoft.com/en-us/azure/cognitive-services/openai/tutorials/embeddings?tabs=command-line for the embedding model.
## 🔧 Usage
@@ -207,7 +212,7 @@ MEMORY_INDEX=whatever
Pinecone enables the storage of vast amounts of vector-based memory, allowing for only relevant memories to be loaded for the agent at any given time.
1. Go to app.pinecone.io and make an account if you don't already have one.
1. Go to [pinecone](https://app.pinecone.io/) and make an account if you don't already have one.
2. Choose the `Starter` plan to avoid being charged.
3. Find your API key and region under the default project in the left sidebar.