From 0d863f00ad57eef4928fa94614c416092182a0e3 Mon Sep 17 00:00:00 2001
From: Krrish Dholakia <krrishdholakia@gmail.com>
Date: Tue, 10 Oct 2023 07:34:55 -0700
Subject: [PATCH] refactor(bedrock.py): take model names from model cost dict

---
 docs/my-website/docs/providers/bedrock.md    |  21 +++++++++++--------
 litellm/__init__.py                          |   8 +++----
 litellm/__pycache__/__init__.cpython-311.pyc | Bin 13291 -> 13370 bytes
 litellm/__pycache__/utils.cpython-311.pyc    | Bin 159723 -> 159802 bytes
 litellm/tests/test_completion.py             |   2 +-
 litellm/utils.py                             |   5 +++++
 6 files changed, 21 insertions(+), 15 deletions(-)

diff --git a/docs/my-website/docs/providers/bedrock.md b/docs/my-website/docs/providers/bedrock.md
index ebf18f8fb9d..eed9627b317 100644
--- a/docs/my-website/docs/providers/bedrock.md
+++ b/docs/my-website/docs/providers/bedrock.md
@@ -29,7 +29,7 @@ os.environ["AWS_SECRET_ACCESS_KEY"] = ""
 os.environ["AWS_REGION_NAME"] = ""
 
 response = completion(
-            model="bedrock/anthropic.claude-instant-v1", 
+            model="anthropic.claude-instant-v1", 
             messages=[{ "content": "Hello, how are you?","role": "user"}]
 )
 ```
@@ -41,7 +41,7 @@ import os
 from litellm import completion
 
 response = completion(
-            model="bedrock/anthropic.claude-instant-v1", 
+            model="anthropic.claude-instant-v1", 
             messages=[{ "content": "Hello, how are you?","role": "user"}],
             aws_access_key_id="",
             aws_secret_access_key="",
@@ -66,7 +66,7 @@ bedrock = boto3.client(
 )
 
 response = completion(
-            model="bedrock/anthropic.claude-instant-v1",
+            model="anthropic.claude-instant-v1",
             messages=[{ "content": "Hello, how are you?","role": "user"}],
             aws_bedrock_client=bedrock,
 )
@@ -84,7 +84,7 @@ bedrock = dev_session.client(
 )
 
 response = completion(
-            model="bedrock/anthropic.claude-instant-v1",
+            model="anthropic.claude-instant-v1",
             messages=[{ "content": "Hello, how are you?","role": "user"}],
             aws_bedrock_client=bedrock,
 )
@@ -95,11 +95,14 @@ Here's an example of using a bedrock model with LiteLLM
 
 | Model Name               | Command                                                          | Environment Variables                                              |
 |--------------------------|------------------------------------------------------------------|---------------------------------------------------------------------|
-| Anthropic Claude-V2      | `completion(model='bedrock/anthropic.claude-v2', messages=messages)`   | `os.environ['ANTHROPIC_ACCESS_KEY_ID']`, `os.environ['ANTHROPIC_SECRET_ACCESS_KEY']`           |
-| Anthropic Claude-Instant V1 | `completion(model='bedrock/anthropic.claude-instant-v1', messages=messages)` | `os.environ['ANTHROPIC_ACCESS_KEY_ID']`, `os.environ['ANTHROPIC_SECRET_ACCESS_KEY']`           |
-| Anthropic Claude-V1      | `completion(model='bedrock/anthropic.claude-v1', messages=messages)`   | `os.environ['ANTHROPIC_ACCESS_KEY_ID']`, `os.environ['ANTHROPIC_SECRET_ACCESS_KEY']`           |
-| AI21 J2-Ultra            | `completion(model='bedrock/ai21.j2-ultra', messages=messages)` | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
-| AI21 J2-Mid              | `completion(model='bedrock/ai21.j2-mid', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
+| Anthropic Claude-V2      | `completion(model='anthropic.claude-v2', messages=messages)`   | `os.environ['ANTHROPIC_ACCESS_KEY_ID']`, `os.environ['ANTHROPIC_SECRET_ACCESS_KEY']`           |
+| Anthropic Claude-Instant V1 | `completion(model='anthropic.claude-instant-v1', messages=messages)` | `os.environ['ANTHROPIC_ACCESS_KEY_ID']`, `os.environ['ANTHROPIC_SECRET_ACCESS_KEY']`           |
+| Anthropic Claude-V1      | `completion(model='anthropic.claude-v1', messages=messages)`   | `os.environ['ANTHROPIC_ACCESS_KEY_ID']`, `os.environ['ANTHROPIC_SECRET_ACCESS_KEY']`           |
+| Amazon Titan Lite            | `completion(model='amazon.titan-text-lite-v1', messages=messages)` | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
+| Amazon Titan Express              | `completion(model='amazon.titan-text-express-v1', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
+| Cohere Command              | `completion(model='cohere.command-text-v14', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
+| AI21 J2-Mid             | `completion(model='ai21.j2-mid-v1', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
+| AI21 J2-Ultra              | `completion(model='ai21.j2-ultra-v1', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
 
 
 ## Streaming
diff --git a/litellm/__init__.py b/litellm/__init__.py
index dcdf2f96a4e..09ca2b2487b 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -94,6 +94,7 @@ vertex_code_text_models: List = []
 ai21_models: List = []
 nlp_cloud_models: List = []
 aleph_alpha_models: List = []
+bedrock_models: List = []
 for key, value in model_cost.items():
     if value.get('litellm_provider') == 'openai':
         open_ai_chat_completion_models.append(key)
@@ -120,6 +121,8 @@ for key, value in model_cost.items():
         nlp_cloud_models.append(key)
     elif value.get('litellm_provider') == 'aleph_alpha':
         aleph_alpha_models.append(key)
+    elif value.get('litellm_provider') == 'bedrock': 
+        bedrock_models.append(key)
 
 # well supported replicate llms
 replicate_models: List = [
@@ -196,11 +199,6 @@ petals_models = [
     "petals-team/StableBeluga2",
 ]
 
-bedrock_models: List = [
-    "amazon.titan-tg1-large",
-    "ai21.j2-grande-instruct"
-]
-
 ollama_models = [
     "llama2"
 ]
diff --git a/litellm/__pycache__/__init__.cpython-311.pyc b/litellm/__pycache__/__init__.cpython-311.pyc
index efd2f42d5a970354dce1a977d377eaff496dbdbe..c3290d45bfbee7f1b1978383bc749a79e982ed45 100644
GIT binary patch
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diff --git a/litellm/tests/test_completion.py b/litellm/tests/test_completion.py
index 639112f2df0..b2529f11b5b 100644
--- a/litellm/tests/test_completion.py
+++ b/litellm/tests/test_completion.py
@@ -806,7 +806,7 @@ def test_completion_bedrock_claude():
     print("calling claude")
     try:
         response = completion(
-            model="bedrock/anthropic.claude-instant-v1", 
+            model="anthropic.claude-instant-v1", 
             messages=messages,
             max_tokens=10,
             temperature=0.1,
diff --git a/litellm/utils.py b/litellm/utils.py
index a4ffa791807..55669b0e1fb 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -1409,8 +1409,13 @@ def get_llm_provider(model: str, custom_llm_provider: Optional[str] = None):
         ## petals
         elif model in litellm.petals_models:
             custom_llm_provider = "petals"
+        ## bedrock
+        elif model in litellm.bedrock_models:
+            custom_llm_provider = "bedrock"
+        # openai embeddings
         elif model in litellm.open_ai_embedding_models:
             custom_llm_provider = "openai"
+        # cohere embeddings
         elif model in litellm.cohere_embedding_models:
             custom_llm_provider = "cohere"