issue #962

docs/pages/Guides/How-to-use-different-LLM.md

@@ -1,48 +1,17 @@
 # Setting Up Local Language Models for Your App
 
-Your app relies on two essential models: Embeddings and Text Generation. While OpenAI's default models work seamlessly, you have the flexibility to switch providers or even run the models locally.
+Setting up local language models for your app can significantly enhance its capabilities, enabling it to understand and generate text in multiple languages without relying on external APIs. By integrating local language models, you can improve privacy, reduce latency, and ensure continuous functionality even in offline environments. Here's a comprehensive guide on how to set up local language models for your application:
 
-## Step 1: Configure Environment Variables
-
-Navigate to the `.env` file or set the following environment variables:
-
-```env
-LLM_NAME=<your Text Generation model>
-API_KEY=<API key for Text Generation>
-EMBEDDINGS_NAME=<LLM for Embeddings>
-EMBEDDINGS_KEY=<API key for Embeddings>
-VITE_API_STREAMING=<true or false>
-```
-
-You can omit the keys if users provide their own. Ensure you set `LLM_NAME` and `EMBEDDINGS_NAME`.
-
-## Step 2: Choose Your Models
-
-**Options for `LLM_NAME`:**
-- openai ([More details](https://platform.openai.com/docs/models))
-- anthropic ([More details](https://docs.anthropic.com/claude/reference/selecting-a-model))
-- manifest ([More details](https://python.langchain.com/docs/integrations/llms/manifest))
-- cohere ([More details](https://docs.cohere.com/docs/llmu))
-- llama.cpp ([More details](https://python.langchain.com/docs/integrations/llms/llamacpp))
-- huggingface (Arc53/DocsGPT-7B by default)
-- sagemaker ([Mode details](https://aws.amazon.com/sagemaker/))
+## Steps:
+ 1.Visit the chat screen and you will be to see the default LLM selected
 
 
-Note: for huggingface you can choose any model inside application/llm/huggingface.py or pass llm_name on init, loads   
+ 2.Click on it and you will get a drop down of various LLM's available to choose 
 
-**Options for `EMBEDDINGS_NAME`:**
-- openai_text-embedding-ada-002
-- huggingface_sentence-transformers/all-mpnet-base-v2
-- huggingface_hkunlp/instructor-large
-- cohere_medium
+ 
+ 3.Choose the LLM of your choice 
 
-If you want to be completely local, set `EMBEDDINGS_NAME` to `huggingface_sentence-transformers/all-mpnet-base-v2`. 
+### Video Demo
+<Image src="/llms.gif" alt="llms" />
 
-For llama.cpp Download the required model and place it in the `models/` folder.
 
-Alternatively, for local Llama setup, run `setup.sh` and choose option 1. The script handles the DocsGPT model addition.
-
-## Step 3: Local Hosting for Privacy
-
-If working with sensitive data, host everything locally by setting `LLM_NAME`, llama.cpp or huggingface, use any model available on Hugging Face, for llama.cpp you need to convert it into gguf format.
-That's it! Your app is now configured for local and private hosting, ensuring optimal security for critical data.