Default to gpt-4-turbo-preview for chat model, extract questions actor

GPT-4 is more expensive and generally less capable than gpt-4-turbo-preview

documentation/docs/get-started/setup.mdx

@@ -175,7 +175,7 @@ To use the desktop client, you need to go to your Khoj server's settings page (h
 1. Go to http://localhost:42110/server/admin and login with your admin credentials.
     1. Go to [OpenAI settings](http://localhost:42110/server/admin/database/openaiprocessorconversationconfig/) in the server admin settings to add an OpenAI processor conversation config. This is where you set your API key. Alternatively, you can go to the [offline chat settings](http://localhost:42110/server/admin/database/offlinechatprocessorconversationconfig/) and simply create a new setting with `Enabled` set to `True`.
     2. Go to the ChatModelOptions if you want to add additional models for chat.
-       - Set the `chat-model` field to a supported chat model[^1] of your choice. For example, you can specify `gpt-4` if you're using OpenAI or `mistral-7b-instruct-v0.1.Q4_0.gguf` if you're using offline chat.
+       - Set the `chat-model` field to a supported chat model[^1] of your choice. For example, you can specify `gpt-4-turbo-preview` if you're using OpenAI or `mistral-7b-instruct-v0.1.Q4_0.gguf` if you're using offline chat.
        - Make sure to set the `model-type` field to `OpenAI` or `Offline` respectively.
        - The `tokenizer` and `max-prompt-size` fields are optional. Set them only when using a non-standard model (i.e not mistral, gpt or llama2 model).
 1. Select files and folders to index [using the desktop client](/get-started/setup#2-download-the-desktop-client). When you click 'Save', the files will be sent to your server for indexing.

documentation/docs/miscellaneous/advanced.md

@@ -35,7 +35,7 @@ Use structured query syntax to filter entries from your knowledge based used by
 Use this if you want to use non-standard, open or commercial, local or hosted LLM models for Khoj chat
 1. Setup your desired chat LLM by installing an OpenAI compatible LLM API Server like [LiteLLM](https://docs.litellm.ai/docs/proxy/quick_start), [llama-cpp-python](https://github.com/abetlen/llama-cpp-python?tab=readme-ov-file#openai-compatible-web-server)
 2. Set environment variable `OPENAI_API_BASE="<url-of-your-llm-server>"` before starting Khoj
-3. Add ChatModelOptions with `model-type` `OpenAI`, and `chat-model` to anything (e.g `gpt-4`) during [Config](/get-started/setup#3-configure)
+3. Add ChatModelOptions with `model-type` `OpenAI`, and `chat-model` to anything (e.g `gpt-3.5-turbo`) during [Config](/get-started/setup#3-configure)
    - *(Optional)* Set the `tokenizer` and `max-prompt-size` relevant to the actual chat model you're using
 
 #### Sample Setup using LiteLLM and Mistral API

src/khoj/processor/conversation/openai/gpt.py

@@ -19,7 +19,7 @@ logger = logging.getLogger(__name__)
 
 def extract_questions(
     text,
-    model: Optional[str] = "gpt-4",
+    model: Optional[str] = "gpt-4-turbo-preview",
     conversation_log={},
     api_key=None,
     temperature=0,

src/khoj/utils/constants.py

@@ -7,7 +7,7 @@ app_env_filepath = "~/.khoj/env"
 telemetry_server = "https://khoj.beta.haletic.com/v1/telemetry"
 content_directory = "~/.khoj/content/"
 default_offline_chat_model = "mistral-7b-instruct-v0.1.Q4_0.gguf"
-default_online_chat_model = "gpt-4"
+default_online_chat_model = "gpt-4-turbo-preview"
 
 empty_config = {
     "search-type": {