From ac5fcb673be73f087f1c84f19603245c9b6a4366 Mon Sep 17 00:00:00 2001
From: Krrish Dholakia <krrishdholakia@gmail.com>
Date: Wed, 20 Sep 2023 08:22:40 -0700
Subject: [PATCH] doc cleanup

---
 docs/my-website/docs/max_tokens_cost.md | 34 -------------------------
 docs/my-website/docs/token_usage.md     | 32 ++++++++++++++++++-----
 docs/my-website/sidebars.js             |  1 -
 3 files changed, 26 insertions(+), 41 deletions(-)
 delete mode 100644 docs/my-website/docs/max_tokens_cost.md

diff --git a/docs/my-website/docs/max_tokens_cost.md b/docs/my-website/docs/max_tokens_cost.md
deleted file mode 100644
index 5447f2e66a6..00000000000
--- a/docs/my-website/docs/max_tokens_cost.md
+++ /dev/null
@@ -1,34 +0,0 @@
-# get context window & cost per token 
-
-100+ LLMs supported: See full list [here](https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json)
-
-## using api.litellm.ai
-```shell
-curl 'https://api.litellm.ai/get_max_tokens?model=claude-2'
-```
-
-### output
-```json
-{
-    "input_cost_per_token": 1.102e-05,
-    "max_tokens": 100000,
-    "model": "claude-2",
-    "output_cost_per_token": 3.268e-05
-}
-```
-
-## using the litellm python package
-```python
-import litellm
-model_data = litellm.model_cost["gpt-4"]
-```
-
-### output
-```json
-{
-    "input_cost_per_token": 3e-06,
-    "max_tokens": 8192,
-    "model": "gpt-4",
-    "output_cost_per_token": 6e-05
-}
-```
\ No newline at end of file
diff --git a/docs/my-website/docs/token_usage.md b/docs/my-website/docs/token_usage.md
index 18758745d50..8a65a24fbc2 100644
--- a/docs/my-website/docs/token_usage.md
+++ b/docs/my-website/docs/token_usage.md
@@ -1,17 +1,21 @@
 # Completion Token Usage & Cost
 By default LiteLLM returns token usage in all completion requests ([See here](https://litellm.readthedocs.io/en/latest/output/))
 
-However, we also expose 5 public helper functions to calculate token usage across providers:
+However, we also expose 5 helper functions + **[NEW]** an API to calculate token usage across providers:
 
-- `token_counter`: This returns the number of tokens for a given input - it uses the tokenizer based on the model, and defaults to tiktoken if no model-specific tokenizer is available. 
+- `token_counter`: This returns the number of tokens for a given input - it uses the tokenizer based on the model, and defaults to tiktoken if no model-specific tokenizer is available. [**Jump to code**](#1-token_counter)
 
-- `cost_per_token`: This returns the cost (in USD) for prompt (input) and completion (output) tokens. It utilizes our model_cost map which can be found in `__init__.py` and also as a [community resource](https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json).
+- `cost_per_token`: This returns the cost (in USD) for prompt (input) and completion (output) tokens. Uses the live list from `api.litellm.ai`. [**Jump to code**](#2-cost_per_token)
 
-- `completion_cost`: This returns the overall cost (in USD) for a given LLM API Call. It combines `token_counter` and `cost_per_token` to return the cost for that query (counting both cost of input and output). 
+- `completion_cost`: This returns the overall cost (in USD) for a given LLM API Call. It combines `token_counter` and `cost_per_token` to return the cost for that query (counting both cost of input and output). [**Jump to code**](#3-completion_cost)
 
-- `get_max_tokens`: This returns a dictionary for a specific model, with it's max_tokens, input_cost_per_token and output_cost_per_token
+- `get_max_tokens`: This returns a dictionary for a specific model, with it's max_tokens, input_cost_per_token and output_cost_per_token. [**Jump to code**](#4-get_max_tokens)
 
-- `model_cost`: This returns a dictionary for all models, with their max_tokens, input_cost_per_token and output_cost_per_token [**List of all models**](https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json) (📣 This is a community maintained list. Contributions are welcome! ❤️)
+- `model_cost`: This returns a dictionary for all models, with their max_tokens, input_cost_per_token and output_cost_per_token. It uses the `api.litellm.ai` call shown below. [**Jump to code**](#5-model_cost)
+
+- `api.litellm.ai`: Live token + price count across [all supported models](https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json). [**Jump to code**](#6-apilitellmai)
+
+📣 This is a community maintained list. Contributions are welcome! ❤️
 
 ## Example Usage 
 
@@ -78,3 +82,19 @@ from litellm import model_cost
 print(model_cost) # {'gpt-3.5-turbo': {'max_tokens': 4000, 'input_cost_per_token': 1.5e-06, 'output_cost_per_token': 2e-06}, ...}
 ```
 
+### 6. `api.litellm.ai`
+
+**Example Curl Request**
+```shell
+curl 'https://api.litellm.ai/get_max_tokens?model=claude-2'
+```
+
+```json
+{
+    "input_cost_per_token": 1.102e-05,
+    "max_tokens": 100000,
+    "model": "claude-2",
+    "output_cost_per_token": 3.268e-05
+}
+```
+
diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js
index 3134f86220c..11062fc6709 100644
--- a/docs/my-website/sidebars.js
+++ b/docs/my-website/sidebars.js
@@ -80,7 +80,6 @@ const sidebars = {
     "token_usage",
     "exception_mapping",
     'debugging/local_debugging',
-    "max_tokens_cost",
     "budget_manager",
     "proxy_api",
     {