Added prem sdk documentation under deep dive

docs/docs/deep-dive/language_model_clients/remote_models/PremAI.mdx

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+## PremAI
+
+[PremAI](https://app.premai.io) is a unified platform that lets you build powerful production-ready GenAI-powered applications with the least effort so that you can focus more on user experience and overall growth. With dspy, you can connect with several [best-in-class LLMs](https://models.premai.io/) of your choice with a single interface.
+
+### Prerequisites
+
+Refer to the [quick start](https://docs.premai.io/introduction) guide to getting started with the PremAI platform, create your first project and grab your API key.
+
+### Setting up the PremAI Client
+
+The constructor initializes the base class `LM` to support prompting requests to supported PremAI hosted models. This requires the following parameters:
+
+- `model` (_str_): Models supported by PremAI. Example: `mistral-tiny`. We recommend using the model selected in [project launchpad](https://docs.premai.io/get-started/launchpad).
+- `project_id` (_int_): The [project id](https://docs.premai.io/get-started/projects) which contains the model of choice.
+- `api_key` (_Optional[str]_, _optional_): API provider from PremAI. Defaults to None.
+- `session_id` (_Optional[int]_, _optional_): The ID of the session to use. It helps to track the chat history.
+- `**kwargs`: Additional language model arguments will be passed to the API provider.
+
+Example of PremAI constructor:
+
+```python
+class PremAI(LM):
+    def __init__(
+        self,
+        model: str,
+        project_id: int,
+        api_key: str,
+        base_url: Optional[str] = None,
+        session_id: Optional[int] = None,
+        **kwargs,
+    ) -> None:
+```
+
+### Under the Hood
+
+#### `__call__(self, prompt: str, **kwargs) -> str`
+
+**Parameters:**
+- `prompt` (_str_): Prompt to send to PremAI.
+- `**kwargs`: Additional keyword arguments for completion request.
+
+**Returns:**
+- `str`: Completions string from the chosen LLM provider 
+
+Internally, the method handles the specifics of preparing the request prompt and corresponding payload to obtain the response.
+
+### Using the PremAI client
+
+```python
+premai_client = dspy.PremAI(project_id=1111)
+```
+
+Please note that, this is a dummy `project_id`. You need to change this to the project_id you are interested to use with dspy. 
+
+```python
+dspy.configure(lm=premai_client)
+
+#Example DSPy CoT QA program
+qa = dspy.ChainOfThought('question -> answer')
+
+response = qa(question="What is the capital of Paris?") 
+print(response.answer)
+```
+
+2) Generate responses using the client directly.
+
+```python
+response = premai_client(prompt='What is the capital of Paris?')
+print(response)
+```