From 16f13dd55c2dd741c4fca2c35c9c3fd94441e1ca Mon Sep 17 00:00:00 2001
From: Krrish Dholakia <krrishdholakia@gmail.com>
Date: Mon, 6 Jan 2025 21:09:09 -0800
Subject: [PATCH] docs(prompt_management.md): update docs to show how to point
 to load balanced model name

---
 .../docs/proxy/prompt_management.md           | 10 ++-
 ...odel_prices_and_context_window_backup.json | 76 +++++++++++++++++--
 2 files changed, 76 insertions(+), 10 deletions(-)

diff --git a/docs/my-website/docs/proxy/prompt_management.md b/docs/my-website/docs/proxy/prompt_management.md
index 34902f3d0b..693477ed74 100644
--- a/docs/my-website/docs/proxy/prompt_management.md
+++ b/docs/my-website/docs/proxy/prompt_management.md
@@ -43,11 +43,15 @@ resp = litellm.completion(
 
 ```yaml
 model_list:
-  - model_name: gpt-3.5-turbo
+  - model_name: my-langfuse-model
     litellm_params:
-      model: langfuse/gpt-3.5-turbo
+      model: langfuse/openai-model
       prompt_id: "<langfuse_prompt_id>"
       api_key: os.environ/OPENAI_API_KEY
+  - model_name: openai-model
+    litellm_params:
+      model: openai/gpt-3.5-turbo
+      api_key: os.environ/OPENAI_API_KEY
 ```
 
 2. Start the proxy
@@ -66,7 +70,7 @@ curl -L -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
 -H 'Content-Type: application/json' \
 -H 'Authorization: Bearer sk-1234' \
 -d '{
-    "model": "gpt-3.5-turbo",
+    "model": "my-langfuse-model",
     "messages": [
         {
             "role": "user",
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 2ef931458c..b3c9904c9f 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -7695,6 +7695,22 @@
         "litellm_provider": "voyage",
         "mode": "embedding"
     },
+    "voyage/voyage-finance-2": {
+        "max_tokens": 32000,
+        "max_input_tokens": 32000,
+        "input_cost_per_token": 0.00000012,
+        "output_cost_per_token": 0.000000,
+        "litellm_provider": "voyage",
+        "mode": "embedding"
+    },
+    "voyage/voyage-lite-02-instruct": {
+        "max_tokens": 4000,
+        "max_input_tokens": 4000,
+        "input_cost_per_token": 0.0000001,
+        "output_cost_per_token": 0.000000,
+        "litellm_provider": "voyage",
+        "mode": "embedding"
+    },
     "voyage/voyage-law-2": {
         "max_tokens": 16000,
         "max_input_tokens": 16000,
@@ -7719,22 +7735,68 @@
         "litellm_provider": "voyage",
         "mode": "embedding"
     },
-    "voyage/voyage-lite-02-instruct": {
-        "max_tokens": 4000,
-        "max_input_tokens": 4000,
-        "input_cost_per_token": 0.0000001,
+    "voyage/voyage-3-large": {
+        "max_tokens": 32000,
+        "max_input_tokens": 32000,
+        "input_cost_per_token": 0.00000018,
         "output_cost_per_token": 0.000000,
         "litellm_provider": "voyage",
         "mode": "embedding"
     },
-    "voyage/voyage-finance-2": {
-        "max_tokens": 4000,
-        "max_input_tokens": 4000,
+    "voyage/voyage-3": {
+        "max_tokens": 32000,
+        "max_input_tokens": 32000,
+        "input_cost_per_token": 0.00000006,
+        "output_cost_per_token": 0.000000,
+        "litellm_provider": "voyage",
+        "mode": "embedding"
+    },
+    "voyage/voyage-3-lite": {
+        "max_tokens": 32000,
+        "max_input_tokens": 32000,
+        "input_cost_per_token": 0.00000002,
+        "output_cost_per_token": 0.000000,
+        "litellm_provider": "voyage",
+        "mode": "embedding"
+    },
+    "voyage/voyage-code-3": {
+        "max_tokens": 32000,
+        "max_input_tokens": 32000,
+        "input_cost_per_token": 0.00000018,
+        "output_cost_per_token": 0.000000,
+        "litellm_provider": "voyage",
+        "mode": "embedding"
+    },
+    "voyage/voyage-multimodal-3": {
+        "max_tokens": 32000,
+        "max_input_tokens": 32000,
         "input_cost_per_token": 0.00000012,
         "output_cost_per_token": 0.000000,
         "litellm_provider": "voyage",
         "mode": "embedding"
     },
+    "voyage/rerank-2": {
+        "max_tokens": 16000,
+        "max_input_tokens": 16000,
+        "max_output_tokens": 16000,
+        "max_query_tokens": 16000,
+        "input_cost_per_token": 0.00000005,
+        "input_cost_per_query": 0.00000005,
+        "output_cost_per_token": 0.0,
+        "litellm_provider": "voyage",
+        "mode": "rerank"
+    },
+    "voyage/rerank-2-lite": {
+        "max_tokens": 8000,
+        "max_input_tokens": 8000,
+        "max_output_tokens": 8000,
+        "max_query_tokens": 8000,
+        "input_cost_per_token": 0.00000002,
+        "input_cost_per_query": 0.00000002,
+        "output_cost_per_token": 0.0,
+        "litellm_provider": "voyage",
+        "mode": "rerank"
+    },
     "databricks/databricks-meta-llama-3-1-405b-instruct": {
         "max_tokens": 128000,
         "max_input_tokens": 128000,