Litellm managed files docs (#9948)

* docs(files_endpoints.md): add doc on litellm managed files

* refactor: separate litellm managed file docs from `/files` docs

clearer

* docs(litellm_managed_files.md): add architecture diagram explaining managed files

docs/my-website/docs/files_endpoints.md

@@ -2,10 +2,12 @@
 import TabItem from '@theme/TabItem';
 import Tabs from '@theme/Tabs';
 
-# /files
+# Provider Files Endpoints
 
 Files are used to upload documents that can be used with features like Assistants, Fine-tuning, and Batch API.
 
+Use this to call the provider's `/files` endpoints directly, in the OpenAI format. 
+
 ## Quick Start
 
 - Upload a File
@@ -19,7 +21,7 @@ Files are used to upload documents that can be used with features like Assistant
 <Tabs>
 <TabItem value="proxy" label="LiteLLM PROXY Server">
 
-### 1. Setup config.yaml
+1. Setup config.yaml
 
 ```
 # for /files endpoints
@@ -32,7 +34,7 @@ files_settings:
     api_key: os.environ/OPENAI_API_KEY
 ```
 
-### 2. Start LiteLLM PROXY Server
+2. Start LiteLLM PROXY Server
 
 ```bash
 litellm --config /path/to/config.yaml
@@ -40,7 +42,7 @@ litellm --config /path/to/config.yaml
 ## RUNNING on http://0.0.0.0:4000
 ```
 
-### 3. Use OpenAI's /files endpoints
+3. Use OpenAI's /files endpoints
 
 Upload a File
 

docs/my-website/docs/proxy/litellm_managed_files.md

@@ -0,0 +1,279 @@
+import TabItem from '@theme/TabItem';
+import Tabs from '@theme/Tabs';
+import Image from '@theme/IdealImage';
+
+# [BETA] LiteLLM Managed Files
+
+Use this to reuse the same 'file id' across different providers.
+
+| Feature | Description | Comments |
+| --- | --- | --- |
+| Proxy | ✅ |  |
+| SDK | ❌ | Requires postgres DB for storing file ids |
+| Available across all providers | ✅ |  |
+
+
+
+Limitations of LiteLLM Managed Files:
+- Only works for `/chat/completions` requests. 
+- Assumes just 1 model configured per model_name.
+
+Follow [here](https://github.com/BerriAI/litellm/discussions/9632) for multiple models, batches support.
+
+### 1. Setup config.yaml
+
+```
+model_list:
+    - model_name: "gemini-2.0-flash"
+      litellm_params:
+        model: vertex_ai/gemini-2.0-flash
+        vertex_project: my-project-id
+        vertex_location: us-central1
+    - model_name: "gpt-4o-mini-openai"
+      litellm_params:
+        model: gpt-4o-mini
+        api_key: os.environ/OPENAI_API_KEY
+```
+
+### 2. Start proxy
+
+```bash
+litellm --config /path/to/config.yaml
+```
+
+### 3. Test it!
+
+Specify `target_model_names` to use the same file id across different providers. This is the list of model_names set via config.yaml (or 'public_model_names' on UI). 
+
+```python
+target_model_names="gpt-4o-mini-openai, gemini-2.0-flash" # 👈 Specify model_names
+```
+
+Check `/v1/models` to see the list of available model names for a key.
+
+#### **Store a PDF file**
+
+```python
+from openai import OpenAI
+
+client = OpenAI(base_url="http://0.0.0.0:4000", api_key="sk-1234", max_retries=0)
+
+
+# Download and save the PDF locally 
+url = (
+    "https://storage.googleapis.com/cloud-samples-data/generative-ai/pdf/2403.05530.pdf"
+)
+response = requests.get(url)
+response.raise_for_status()
+
+# Save the PDF locally
+with open("2403.05530.pdf", "wb") as f:
+    f.write(response.content)
+
+file = client.files.create(
+    file=open("2403.05530.pdf", "rb"),
+    purpose="user_data", # can be any openai 'purpose' value
+    extra_body={"target_model_names": "gpt-4o-mini-openai, gemini-2.0-flash"}, # 👈 Specify model_names
+)
+
+print(f"file id={file.id}")
+```
+
+#### **Use the same file id across different providers**
+
+<Tabs>
+<TabItem value="openai" label="OpenAI">
+
+```python
+completion = client.chat.completions.create(
+    model="gpt-4o-mini-openai",
+    messages=[
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this recording?"},
+                {
+                    "type": "file",
+                    "file": {
+                        "file_id": file.id,
+                    },
+                },
+            ],
+        },
+    ]
+)
+
+print(completion.choices[0].message)
+```
+
+
+</TabItem>
+<TabItem value="vertex" label="Vertex AI">
+
+```python
+completion = client.chat.completions.create(
+    model="gemini-2.0-flash",
+    messages=[
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this recording?"},
+                {
+                    "type": "file",
+                    "file": {
+                        "file_id": file.id,
+                    },
+                },
+            ],
+        },
+    ]
+)
+
+print(completion.choices[0].message)
+
+```
+
+</TabItem>
+</Tabs>
+
+### Complete Example
+
+```python   
+import base64
+import requests
+from openai import OpenAI
+
+client = OpenAI(base_url="http://0.0.0.0:4000", api_key="sk-1234", max_retries=0)
+
+
+# Download and save the PDF locally
+url = (
+    "https://storage.googleapis.com/cloud-samples-data/generative-ai/pdf/2403.05530.pdf"
+)
+response = requests.get(url)
+response.raise_for_status()
+
+# Save the PDF locally
+with open("2403.05530.pdf", "wb") as f:
+    f.write(response.content)
+
+# Read the local PDF file
+file = client.files.create(
+    file=open("2403.05530.pdf", "rb"),
+    purpose="user_data", # can be any openai 'purpose' value
+    extra_body={"target_model_names": "gpt-4o-mini-openai, vertex_ai/gemini-2.0-flash"},
+)
+
+print(f"file.id: {file.id}") # 👈 Unified file id
+
+## GEMINI CALL ### 
+completion = client.chat.completions.create(
+    model="gemini-2.0-flash",
+    messages=[
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this recording?"},
+                {
+                    "type": "file",
+                    "file": {
+                        "file_id": file.id,
+                    },
+                },
+            ],
+        },
+    ]
+)
+
+print(completion.choices[0].message)
+
+
+### OPENAI CALL ### 
+completion = client.chat.completions.create(
+    model="gpt-4o-mini-openai",
+    messages=[
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this recording?"},
+                {
+                    "type": "file",
+                    "file": {
+                        "file_id": file.id,
+                    },
+                },
+            ],
+        },
+    ],
+)
+
+print(completion.choices[0].message)
+
+```
+
+
+### Supported Endpoints
+
+#### Create a file - `/files`
+
+```python
+from openai import OpenAI
+
+client = OpenAI(base_url="http://0.0.0.0:4000", api_key="sk-1234", max_retries=0)
+
+# Download and save the PDF locally
+url = (
+    "https://storage.googleapis.com/cloud-samples-data/generative-ai/pdf/2403.05530.pdf"
+)
+response = requests.get(url)
+response.raise_for_status()
+
+# Save the PDF locally
+with open("2403.05530.pdf", "wb") as f:
+    f.write(response.content)
+
+# Read the local PDF file
+file = client.files.create(
+    file=open("2403.05530.pdf", "rb"),
+    purpose="user_data", # can be any openai 'purpose' value
+    extra_body={"target_model_names": "gpt-4o-mini-openai, vertex_ai/gemini-2.0-flash"},
+)
+```
+
+#### Retrieve a file - `/files/{file_id}`
+
+```python
+client = OpenAI(base_url="http://0.0.0.0:4000", api_key="sk-1234", max_retries=0)
+
+file = client.files.retrieve(file_id=file.id)
+```
+
+#### Delete a file - `/files/{file_id}/delete`
+
+```python
+client = OpenAI(base_url="http://0.0.0.0:4000", api_key="sk-1234", max_retries=0)
+
+file = client.files.delete(file_id=file.id)
+```
+
+### FAQ
+
+**1. Does LiteLLM store the file?**
+
+No, LiteLLM does not store the file. It only stores the file id's in the postgres DB.
+
+**2. How does LiteLLM know which file to use for a given file id?**
+
+LiteLLM stores a mapping of the litellm file id to the model-specific file id in the postgres DB. When a request comes in, LiteLLM looks up the model-specific file id and uses it in the request to the provider.
+
+**3. How do file deletions work?**
+
+When a file is deleted, LiteLLM deletes the mapping from the postgres DB, and the files on each provider.
+
+### Architecture
+
+
+
+
+
+<Image img={require('../../img/managed_files_arch.png')}  style={{ width: '800px', height: 'auto' }} />

docs/my-website/sidebars.js

@@ -340,7 +340,15 @@ const sidebars = {
         },
         "rerank",
         "assistants",
+        
+        {
+          type: "category",
+          label: "/files",
+          items: [
             "files_endpoints",
+            "proxy/litellm_managed_files",
+          ],
+        },
         "batches",
         "realtime",
         "fine_tuning",