litellm-mirror/docs/my-website/docs/completion/document_understanding.md

import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

Using PDF Input

How to send / receieve pdf's (other document types) to a /chat/completions endpoint

Works for:

• Vertex AI models (Gemini + Anthropic)
• Bedrock Models
• Anthropic API Models

Quick Start

url

from litellm.utils import supports_pdf_input, completion

# set aws credentials
os.environ["AWS_ACCESS_KEY_ID"] = ""
os.environ["AWS_SECRET_ACCESS_KEY"] = ""
os.environ["AWS_REGION_NAME"] = ""


# pdf url
image_url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"

# model
model = "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0"

image_content = [
    {"type": "text", "text": "What's this file about?"},
    {
        "type": "image_url",
        "image_url": image_url, # OR {"url": image_url}
    },
]


if not supports_pdf_input(model, None):
    print("Model does not support image input")

response = completion(
    model=model,
    messages=[{"role": "user", "content": image_content}],
)
assert response is not None

1. Setup config.yaml

model_list:
  - model_name: bedrock-model
    litellm_params:
      model: bedrock/anthropic.claude-3-5-sonnet-20240620-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 the proxy

litellm --config /path/to/config.yaml

3. Test it!

curl -X POST 'http://0.0.0.0:4000/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-1234' \
-d '{
    "model": "bedrock-model",
    "messages": [
        {"role": "user", "content": {"type": "text", "text": "What's this file about?"}},
        {
            "type": "image_url",
            "image_url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf",
        }
    ]
}'

base64

from litellm.utils import supports_pdf_input, completion

# set aws credentials
os.environ["AWS_ACCESS_KEY_ID"] = ""
os.environ["AWS_SECRET_ACCESS_KEY"] = ""
os.environ["AWS_REGION_NAME"] = ""


# pdf url
image_url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
response = requests.get(url)
file_data = response.content

encoded_file = base64.b64encode(file_data).decode("utf-8")
base64_url = f"data:application/pdf;base64,{encoded_file}"

# model
model = "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0"

image_content = [
    {"type": "text", "text": "What's this file about?"},
    {
        "type": "image_url",
        "image_url": base64_url, # OR {"url": base64_url}
    },
]


if not supports_pdf_input(model, None):
    print("Model does not support image input")

response = completion(
    model=model,
    messages=[{"role": "user", "content": image_content}],
)
assert response is not None

Checking if a model supports pdf input

Use litellm.supports_pdf_input(model="bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0") -> returns True if model can accept pdf input

assert litellm.supports_pdf_input(model="bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0") == True

1. Define bedrock models on config.yaml

model_list:
  - model_name: bedrock-model # model group name
    litellm_params:
      model: bedrock/anthropic.claude-3-5-sonnet-20240620-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
    model_info: # OPTIONAL - set manually
      supports_pdf_input: True

2. Run proxy server

litellm --config config.yaml

3. Call /model_group/info to check if a model supports pdf input

curl -X 'GET' \
  'http://localhost:4000/model_group/info' \
  -H 'accept: application/json' \
  -H 'x-api-key: sk-1234'

Expected Response

{
  "data": [
    {
      "model_group": "bedrock-model",
      "providers": ["bedrock"],
      "max_input_tokens": 128000,
      "max_output_tokens": 16384,
      "mode": "chat",
      ...,
      "supports_pdf_input": true, # 👈 supports_pdf_input is true
    }
  ]
}

OpenAI 'file' message type

This is currently only supported for OpenAI models.

This will be supported for all providers soon.

import base64
from litellm import completion

with open("draconomicon.pdf", "rb") as f:
    data = f.read()

base64_string = base64.b64encode(data).decode("utf-8")

completion = completion(
    model="gpt-4o",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "file",
                    "file": {
                        "filename": "draconomicon.pdf",
                        "file_data": f"data:application/pdf;base64,{base64_string}",
                    }
                },
                {
                    "type": "text",
                    "text": "What is the first dragon in the book?",
                }
            ],
        },
    ],
)

print(completion.choices[0].message.content)

1. Setup config.yaml

model_list:
  - model_name: openai-model
    litellm_params:
      model: gpt-4o
      api_key: os.environ/OPENAI_API_KEY

2. Start the proxy

litellm --config config.yaml

3. Test it!

curl -X POST 'http://0.0.0.0:4000/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-1234' \
-d '{ 
    "model": "openai-model",
    "messages": [
        {"role": "user", "content": [
            {
                "type": "file",
                "file": {
                    "filename": "draconomicon.pdf",
                    "file_data": f"data:application/pdf;base64,{base64_string}",
                }
            }
        ]}
    ]
}'