diff --git a/integrations/llms/vertex-ai/files.mdx b/integrations/llms/vertex-ai/files.mdx
index cf7ebf7a..a0e14c7c 100644
--- a/integrations/llms/vertex-ai/files.mdx
+++ b/integrations/llms/vertex-ai/files.mdx
@@ -304,4 +304,132 @@ print(file_content)
 </Tabs>
 
 
-Note: The `ListFiles` endpoint is not supported for Vertex AI. 
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+Note: The `ListFiles` endpoint is not supported for Vertex AI. 
+
+
+### Uploading Files for Inference
+
+Vertex AI supports inference with files that are uploaded to GCS, to upload files for inference i.e not for `batch` and `fine-tune`, please check below code snippet.
+
+<Tabs>
+ <Tab title="Python">
+```python
+from portkey_ai import Portkey
+
+# Initialize the Portkey client
+portkey = Portkey(
+    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
+    provider="@VERTEX_PROVIDER",   
+    vertex_storage_bucket_name="your_bucket_name", # Specify the GCS bucket name
+    provider_file_name="your_file_name.png", # Specify the file name in GCS
+    provider_model="gemini-1.5-flash-001" # Specify the model to use
+)
+
+upload_file_response = portkey.files.create(
+  purpose="upload",
+  file=open("your_file_name.png", "rb"),
+  extra_headers={"x-portkey-file-purpose": "upload"}
+)
+
+print(upload_file_response)
+```
+  </Tab>
+    <Tab title="NodeJS">
+```js
+import { Portkey } from 'portkey-ai';
+import * as fs from 'fs';
+
+// Initialize the Portkey client
+const portkey = Portkey({
+    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
+    provider:"@VERTEX_PROVIDER",   
+    vertexStorageBucketName: "your_bucket_name", // Specify the GCS bucket name
+    providerFileName: "your_file_name.png", // Specify the file name in GCS
+    providerModel: "gemini-1.5-flash-001" // Specify the model to use
+});
+
+const uploadFile = async () => {
+  const file = await portkey.files.create({
+    purpose: "upload",
+    file: fs.createReadStream("your_file_name.png"),
+    extra_headers: {"x-portkey-file-purpose": "upload"}
+  });
+
+  console.log(file);
+}
+
+uploadFile();
+```
+  </Tab>
+<Tab title="REST">
+```sh
+curl -X POST --header 'x-portkey-api-key: <portkey_api_key>' \
+ --header 'x-portkey-provider: <vertex_virtual_key>' \
+ --header 'x-portkey-vertex-storage-bucket-name: <bucket_name>' \
+ --header 'x-portkey-provider-file-name: <file_name>.png' \
+ --header 'x-portkey-provider-model: <model_name>' \
+ --header 'x-portkey-file-purpose: "upload"' \
+ --form 'purpose="upload"' \
+ --form 'file=@your_file_name.png' \
+ 'https://api.portkey.ai/v1/files'
+```
+</Tab>
+  <Tab title="OpenAI NodeJS">
+```js
+import OpenAI from 'openai';
+import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai';
+import * as fs from 'fs';
+
+const openai = new OpenAI({
+  apiKey: 'OPENAI_API_KEY',
+  baseURL: PORTKEY_GATEWAY_URL,
+  defaultHeaders: createHeaders({
+    provider:"@VERTEX_PROVIDER",
+    apiKey: "PORTKEY_API_KEY",
+    vertexStorageBucketName: "your_bucket_name",
+    providerFileName: "your_file_name.png",
+    providerModel: "gemini-1.5-flash-001"
+  })
+});
+
+const uploadFile = async () => {
+  const file = await openai.files.create({
+    purpose: "upload",
+    file: fs.createReadStream("your_file_name.png"),
+    extraHeaders: {"x-portkey-file-purpose": "upload"}
+  });
+
+  console.log(file);
+}
+
+uploadFile();
+```
+  </Tab>
+    <Tab title="OpenAI Python">
+```python
+from openai import OpenAI
+from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders
+
+openai = OpenAI(
+    api_key='OPENAI_API_KEY',
+    base_url=PORTKEY_GATEWAY_URL,
+    default_headers=createHeaders(
+        provider="@VERTEX_PROVIDER",
+        api_key="PORTKEY_API_KEY",
+        vertex_storage_bucket_name="your_bucket_name",
+        provider_file_name="your_file_name.png",
+        provider_model="gemini-1.5-flash-001"
+    )
+)
+
+upload_file_response = openai.files.create(
+  purpose="upload",
+  file=open("your_file_name.png", "rb"),
+  extra_headers={"x-portkey-file-purpose": "upload"}
+)
+
+print(upload_file_response)
+```
+  </Tab>
+ 
+</Tabs>
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