(docs) using gemini vision with base64

This commit is contained in:
ishaan-jaff 2024-02-29 15:55:56 -08:00
parent 8d76df6a5e
commit 02c3955c51
2 changed files with 46 additions and 3 deletions

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@ -152,8 +152,14 @@ LiteLLM Supports the following image types passed in `url`
- Images with Cloud Storage URIs - gs://cloud-samples-data/generative-ai/image/boats.jpeg
- Images with direct links - https://storage.googleapis.com/github-repo/img/gemini/intro/landmark3.jpg
- Videos with Cloud Storage URIs - https://storage.googleapis.com/github-repo/img/gemini/multimodality_usecases_overview/pixel8.mp4
- Base64 Encoded Local Images
**Example Request - image url**
<Tabs>
<TabItem value="direct" label="Images with direct links">
**Example Request**
```python
import litellm
@ -179,6 +185,43 @@ response = litellm.completion(
)
print(response)
```
</TabItem>
<TabItem value="base" label="Local Base64 Images">
```python
import litellm
def encode_image(image_path):
import base64
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode("utf-8")
image_path = "cached_logo.jpg"
# Getting the base64 string
base64_image = encode_image(image_path)
response = litellm.completion(
model="vertex_ai/gemini-pro-vision",
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "Whats in this image?"},
{
"type": "image_url",
"image_url": {
"url": "data:image/jpeg;base64," + base64_image
},
},
],
}
],
)
print(response)
```
</TabItem>
</Tabs>
## Chat Models

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@ -122,8 +122,6 @@ const sidebars = {
"providers/openai_compatible",
"providers/azure",
"providers/azure_ai",
"providers/huggingface",
"providers/ollama",
"providers/vertex",
"providers/palm",
"providers/gemini",
@ -132,6 +130,8 @@ const sidebars = {
"providers/aws_sagemaker",
"providers/bedrock",
"providers/anyscale",
"providers/huggingface",
"providers/ollama",
"providers/perplexity",
"providers/groq",
"providers/vllm",