diff --git a/python/chat/clients.mdx b/python/chat/clients.mdx
index ecfd403aa..97234ec38 100644
--- a/python/chat/clients.mdx
+++ b/python/chat/clients.mdx
@@ -69,9 +69,117 @@ Initialize the Unify client.
 - `messages` - A list of messages comprising the conversation so far.
   If provided, user_message must be None.
   
-- `api_key` - API key for accessing the Unify API.
-  If None, it attempts to retrieve the API key from the environment variable
-  UNIFY_KEY. Defaults to None.
+- `frequency_penalty` - Number between -2.0 and 2.0. Positive values penalize new
+  tokens based on their existing frequency in the text so far, decreasing the
+  model's likelihood to repeat the same line verbatim.
+  
+- `logit_bias` - Modify the likelihood of specified tokens appearing in the
+  completion. Accepts a JSON object that maps tokens (specified by their token
+  ID in the tokenizer) to an associated bias value from -100 to 100.
+  Mathematically, the bias is added to the logits generated by the model prior
+  to sampling. The exact effect will vary per model, but values between -1 and
+  1 should decrease or increase likelihood of selection; values like -100 or
+  100 should result in a ban or exclusive selection of the relevant token.
+  
+- `logprobs` - Whether to return log probabilities of the output tokens or not.
+  If true, returns the log probabilities of each output token returned in the
+  content of message.
+  
+- `top_logprobs` - An integer between 0 and 20 specifying the number of most
+  likely tokens to return at each token position, each with an associated log
+  probability. logprobs must be set to true if this parameter is used.
+  
+- `max_tokens` - The maximum number of tokens that can be generated in the chat
+  completion. The total length of input tokens and generated tokens is limited
+  by the model's context length. Defaults to the provider's default max_tokens
+  when the value is None.
+  
+- `n` - How many chat completion choices to generate for each input message. Note
+  that you will be charged based on the number of generated tokens across all
+  of the choices. Keep n as 1 to minimize costs.
+  
+- `presence_penalty` - Number between -2.0 and 2.0. Positive values penalize new
+  tokens based on whether they appear in the text so far, increasing the
+  model's likelihood to talk about new topics.
+  
+- `response_format` - An object specifying the format that the model must output.
+  Setting to `{ "type": "json_schema", "json_schema": {...} }` enables
+  Structured Outputs which ensures the model will match your supplied JSON
+  schema. Learn more in the Structured Outputs guide. Setting to
+  `{ "type": "json_object" }` enables JSON mode, which ensures the message the
+  model generates is valid JSON.
+  
+- `seed` - If specified, a best effort attempt is made to sample
+  deterministically, such that repeated requests with the same seed and
+  parameters should return the same result. Determinism is not guaranteed, and
+  you should refer to the system_fingerprint response parameter to monitor
+  changes in the backend.
+  
+- `stop` - Up to 4 sequences where the API will stop generating further tokens.
+  
+- `stream` - If True, generates content as a stream. If False, generates content
+  as a single response. Defaults to False.
+  
+- `stream_options` - Options for streaming response. Only set this when you set
+- `stream` - true.
+  
+- `temperature` - What sampling temperature to use, between 0 and 2.
+  Higher values like 0.8 will make the output more random,
+  while lower values like 0.2 will make it more focused and deterministic.
+  It is generally recommended to alter this or top_p, but not both.
+  Defaults to the provider's default max_tokens when the value is None.
+  
+- `top_p` - An alternative to sampling with temperature, called nucleus sampling,
+  where the model considers the results of the tokens with top_p probability
+  mass. So 0.1 means only the tokens comprising the top 10% probability mass
+  are considered. Generally recommended to alter this or temperature, but not
+  both.
+  
+- `tools` - A list of tools the model may call. Currently, only functions are
+  supported as a tool. Use this to provide a list of functions the model may
+  generate JSON inputs for. A max of 128 functions are supported.
+  
+- `tool_choice` - Controls which (if any) tool is called by the
+  model. none means the model will not call any tool and instead generates a
+  message. auto means the model can pick between generating a message or
+  calling one or more tools. required means the model must call one or more
+  tools. Specifying a particular tool via
+  `{ "type": "function", "function": {"name": "my_function"} }`
+  forces the model to call that tool.
+  none is the default when no tools are present. auto is the default if tools
+  are present.
+  
+- `parallel_tool_calls` - Whether to enable parallel function calling during tool
+  use.
+  
+- `use_custom_keys` - Whether to use custom API keys or our unified API keys
+  with the backend provider.
+  
+- `tags` - Arbitrary number of tags to classify this API query as needed. Helpful
+  for generally grouping queries across tasks and users, for logging purposes.
+  
+- `message_content_only` - If True, only return the message content
+  chat_completion.choices[0].message.content.strip(" ") from the OpenAI
+  return. Otherwise, the full response chat_completion is returned.
+  Defaults to True.
+  
+- `cache` - If True, then the arguments will be stored in a local cache file, and
+  any future calls with identical arguments will read from the cache instead
+  of running the LLM query. This can help to save costs and also debug
+  multi-step LLM applications, while keeping early steps fixed.
+  This argument only has any effect when stream=False.
+  
+- `extra_headers` - Additional "passthrough" headers for the request which are
+  provider-specific, and are not part of the OpenAI standard. They are handled
+  by the provider-specific API.
+  
+- `extra_query` - Additional "passthrough" query parameters for the request which
+  are provider-specific, and are not part of the OpenAI standard. They are
+  handled by the provider-specific API.
+  
+- `kwargs` - Additional "passthrough" JSON properties for the body of the
+  request, which are provider-specific, and are not part of the OpenAI
+  standard. They will be handled by the provider-specific API.
   
 
 **Raises**: