Merge pull request #17193 from BerriAI/litellm_twelvelabs_int

Added support for twelvelabs pegasus

Author: Sameerlite

docs/my-website/docs/providers/bedrock.md

@@ -1683,6 +1683,131 @@ curl --location 'http://0.0.0.0:4000/chat/completions' \
 </TabItem>
 </Tabs>
 
+## TwelveLabs Pegasus - Video Understanding
+
+TwelveLabs Pegasus 1.2 is a video understanding model that can analyze and describe video content. LiteLLM supports this model through Bedrock's `/invoke` endpoint.
+
+| Property | Details |
+|----------|---------|
+| Provider Route | `bedrock/us.twelvelabs.pegasus-1-2-v1:0`, `bedrock/eu.twelvelabs.pegasus-1-2-v1:0` |
+| Provider Documentation | [TwelveLabs Pegasus Docs ↗](https://docs.twelvelabs.io/docs/models/pegasus) |
+| Supported Parameters | `max_tokens`, `temperature`, `response_format` |
+| Media Input | S3 URI or base64-encoded video |
+
+### Supported Features
+
+- **Video Analysis**: Analyze video content from S3 or base64 input
+- **Structured Output**: Support for JSON schema response format
+- **S3 Integration**: Support for S3 video URLs with bucket owner specification
+
+### Usage with S3 Video
+
+<Tabs>
+<TabItem value="sdk" label="SDK">
+
+```python title="TwelveLabs Pegasus SDK Usage" showLineNumbers
+from litellm import completion
+import os
+
+# Set AWS credentials
+os.environ["AWS_ACCESS_KEY_ID"] = "your-aws-access-key"
+os.environ["AWS_SECRET_ACCESS_KEY"] = "your-aws-secret-key"
+os.environ["AWS_REGION_NAME"] = "us-east-1"
+
+response = completion(
+    model="bedrock/us.twelvelabs.pegasus-1-2-v1:0",
+    messages=[{"role": "user", "content": "Describe what happens in this video."}],
+    mediaSource={
+        "s3Location": {
+            "uri": "s3://your-bucket/video.mp4",
+            "bucketOwner": "123456789012",  # 12-digit AWS account ID
+        }
+    },
+    temperature=0.2
+)
+
+print(response.choices[0].message.content)
+```
+
+</TabItem>
+
+<TabItem value="proxy" label="Proxy">
+
+**1. Add to config**
+
+```yaml title="config.yaml" showLineNumbers
+model_list:
+  - model_name: pegasus-video
+    litellm_params:
+      model: bedrock/us.twelvelabs.pegasus-1-2-v1:0
+      aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID
+      aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY
+      aws_region_name: os.environ/AWS_REGION_NAME
+```
+
+**2. Start proxy**
+
+```bash title="Start LiteLLM Proxy" showLineNumbers
+litellm --config /path/to/config.yaml
+
+# RUNNING at http://0.0.0.0:4000
+```
+
+**3. Test it!**
+
+```bash title="Test Pegasus via Proxy" showLineNumbers
+curl --location 'http://0.0.0.0:4000/chat/completions' \
+  --header 'Authorization: Bearer sk-1234' \
+  --header 'Content-Type: application/json' \
+  --data '{
+    "model": "pegasus-video",
+    "messages": [
+      {
+        "role": "user",
+        "content": "Describe what happens in this video."
+      }
+    ],
+    "mediaSource": {
+      "s3Location": {
+        "uri": "s3://your-bucket/video.mp4",
+        "bucketOwner": "123456789012"
+      }
+    },
+    "temperature": 0.2
+  }'
+```
+
+</TabItem>
+</Tabs>
+
+### Usage with Base64 Video
+
+You can also pass video content directly as base64:
+
+```python title="Base64 Video Input" showLineNumbers
+from litellm import completion
+import base64
+
+# Read video file and encode to base64
+with open("video.mp4", "rb") as video_file:
+    video_base64 = base64.b64encode(video_file.read()).decode("utf-8")
+
+response = completion(
+    model="bedrock/us.twelvelabs.pegasus-1-2-v1:0",
+    messages=[{"role": "user", "content": "What is happening in this video?"}],
+    mediaSource={
+        "base64String": video_base64
+    },
+    temperature=0.2,
+)
+
+print(response.choices[0].message.content)
+```
+
+### Important Notes
+
+- **Response Format**: The model supports structured output via `response_format` with JSON schema
+
 ## Provisioned throughput models
 To use provisioned throughput Bedrock models pass 
 - `model=bedrock/<base-model>`, example `model=bedrock/anthropic.claude-v2`. Set `model` to any of the [Supported AWS models](#supported-aws-bedrock-models)
@@ -1743,6 +1868,8 @@ Here's an example of using a bedrock model with LiteLLM. For a complete list, re
 | Meta Llama 2 Chat 70b      | `completion(model='bedrock/meta.llama2-70b-chat-v1', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
 | Mistral 7B Instruct        | `completion(model='bedrock/mistral.mistral-7b-instruct-v0:2', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
 | Mixtral 8x7B Instruct      | `completion(model='bedrock/mistral.mixtral-8x7b-instruct-v0:1', messages=messages)`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
+| TwelveLabs Pegasus 1.2 (US) | `completion(model='bedrock/us.twelvelabs.pegasus-1-2-v1:0', messages=messages, mediaSource={...})`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
+| TwelveLabs Pegasus 1.2 (EU) | `completion(model='bedrock/eu.twelvelabs.pegasus-1-2-v1:0', messages=messages, mediaSource={...})`   | `os.environ['AWS_ACCESS_KEY_ID']`, `os.environ['AWS_SECRET_ACCESS_KEY']`, `os.environ['AWS_REGION_NAME']` |
 
 
 ## Bedrock Embedding

litellm/__init__.py

@@ -1234,6 +1234,9 @@ def add_known_models():
 from .llms.bedrock.chat.invoke_transformations.amazon_titan_transformation import (
     AmazonTitanConfig,
 )
+from .llms.bedrock.chat.invoke_transformations.amazon_twelvelabs_pegasus_transformation import (
+    AmazonTwelveLabsPegasusConfig,
+)
 from .llms.bedrock.chat.invoke_transformations.base_invoke_transformation import (
     AmazonInvokeConfig,
 )

litellm/constants.py

@@ -856,6 +856,7 @@
     "nova",
     "deepseek_r1",
     "qwen3",
+    "twelvelabs",
 ]
 
 BEDROCK_EMBEDDING_PROVIDERS_LITERAL = Literal[