docs logging to GCS

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

@@ -0,0 +1,129 @@
+
+# 🪣 Logging GCS, s3 Buckets
+
+LiteLLM Supports Logging to the following Cloud Buckets
+- (Enterprise) ✨ [Google Cloud Storage Buckets](#logging-proxy-inputoutput-to-google-cloud-storage-buckets)
+- (Free OSS) [Amazon s3 Buckets](#logging-proxy-inputoutput---s3-buckets) 
+
+## Logging Proxy Input/Output to Google Cloud Storage Buckets
+
+Log LLM Logs to [Google Cloud Storage Buckets](https://cloud.google.com/storage?hl=en)
+
+:::info
+
+✨ This is an Enterprise only feature [Get Started with Enterprise here](https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat)
+
+:::
+
+
+### Usage
+
+1. Add `gcs_bucket` to LiteLLM Config.yaml
+```yaml
+model_list:
+- litellm_params:
+    api_base: https://openai-function-calling-workers.tasslexyz.workers.dev/
+    api_key: my-fake-key
+    model: openai/my-fake-model
+  model_name: fake-openai-endpoint
+
+litellm_settings:
+  callbacks: ["gcs_bucket"] # 👈 KEY CHANGE # 👈 KEY CHANGE
+```
+
+2. Set required env variables
+
+```shell
+GCS_BUCKET_NAME="<your-gcs-bucket-name>"
+GCS_PATH_SERVICE_ACCOUNT="/Users/ishaanjaffer/Downloads/adroit-crow-413218-a956eef1a2a8.json" # Add path to service account.json
+```
+
+3. Start Proxy
+
+```
+litellm --config /path/to/config.yaml
+```
+
+4. Test it! 
+
+```bash
+curl --location 'http://0.0.0.0:4000/chat/completions' \
+--header 'Content-Type: application/json' \
+--data ' {
+      "model": "fake-openai-endpoint",
+      "messages": [
+        {
+          "role": "user",
+          "content": "what llm are you"
+        }
+      ],
+    }
+'
+```
+
+
+### Expected Logs on GCS Buckets
+
+<Image img={require('../../img/gcs_bucket.png')} />
+
+
+
+## Logging Proxy Input/Output - s3 Buckets
+
+We will use the `--config` to set 
+
+- `litellm.success_callback = ["s3"]` 
+
+This will log all successfull LLM calls to s3 Bucket
+
+**Step 1** Set AWS Credentials in .env
+
+```shell
+AWS_ACCESS_KEY_ID = ""
+AWS_SECRET_ACCESS_KEY = ""
+AWS_REGION_NAME = ""
+```
+
+**Step 2**: Create a `config.yaml` file and set `litellm_settings`: `success_callback`
+
+```yaml
+model_list:
+ - model_name: gpt-3.5-turbo
+    litellm_params:
+      model: gpt-3.5-turbo
+litellm_settings:
+  success_callback: ["s3"]
+  s3_callback_params:
+    s3_bucket_name: logs-bucket-litellm   # AWS Bucket Name for S3
+    s3_region_name: us-west-2              # AWS Region Name for S3
+    s3_aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID  # us os.environ/<variable name> to pass environment variables. This is AWS Access Key ID for S3
+    s3_aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY  # AWS Secret Access Key for S3
+    s3_path: my-test-path # [OPTIONAL] set path in bucket you want to write logs to
+    s3_endpoint_url: https://s3.amazonaws.com  # [OPTIONAL] S3 endpoint URL, if you want to use Backblaze/cloudflare s3 buckets
+```
+
+**Step 3**: Start the proxy, make a test request
+
+Start proxy
+
+```shell
+litellm --config config.yaml --debug
+```
+
+Test Request
+
+```shell
+curl --location 'http://0.0.0.0:4000/chat/completions' \
+    --header 'Content-Type: application/json' \
+    --data ' {
+    "model": "Azure OpenAI GPT-4 East",
+    "messages": [
+        {
+        "role": "user",
+        "content": "what llm are you"
+        }
+    ]
+    }'
+```
+
+Your logs should be available on the specified s3 Bucket

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

@@ -8,7 +8,6 @@ Log Proxy input, output, and exceptions using:
 - Langsmith
 - DataDog
 - DynamoDB
-- s3 Bucket
 - etc.
 
 import Image from '@theme/IdealImage';
@@ -1379,66 +1378,6 @@ Expected output on Datadog
 
 <Image img={require('../../img/dd_small1.png')} />
 
-## Logging Proxy Input/Output - s3 Buckets
-
-We will use the `--config` to set 
-
-- `litellm.success_callback = ["s3"]` 
-
-This will log all successfull LLM calls to s3 Bucket
-
-**Step 1** Set AWS Credentials in .env
-
-```shell
-AWS_ACCESS_KEY_ID = ""
-AWS_SECRET_ACCESS_KEY = ""
-AWS_REGION_NAME = ""
-```
-
-**Step 2**: Create a `config.yaml` file and set `litellm_settings`: `success_callback`
-
-```yaml
-model_list:
- - model_name: gpt-3.5-turbo
-    litellm_params:
-      model: gpt-3.5-turbo
-litellm_settings:
-  success_callback: ["s3"]
-  s3_callback_params:
-    s3_bucket_name: logs-bucket-litellm   # AWS Bucket Name for S3
-    s3_region_name: us-west-2              # AWS Region Name for S3
-    s3_aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID  # us os.environ/<variable name> to pass environment variables. This is AWS Access Key ID for S3
-    s3_aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY  # AWS Secret Access Key for S3
-    s3_path: my-test-path # [OPTIONAL] set path in bucket you want to write logs to
-    s3_endpoint_url: https://s3.amazonaws.com  # [OPTIONAL] S3 endpoint URL, if you want to use Backblaze/cloudflare s3 buckets
-```
-
-**Step 3**: Start the proxy, make a test request
-
-Start proxy
-
-```shell
-litellm --config config.yaml --debug
-```
-
-Test Request
-
-```shell
-curl --location 'http://0.0.0.0:4000/chat/completions' \
-    --header 'Content-Type: application/json' \
-    --data ' {
-    "model": "Azure OpenAI GPT-4 East",
-    "messages": [
-        {
-        "role": "user",
-        "content": "what llm are you"
-        }
-    ]
-    }'
-```
-
-Your logs should be available on the specified s3 Bucket
-
 ## Logging Proxy Input/Output - DynamoDB
 
 We will use the `--config` to set 

docs/my-website/sidebars.js

@@ -47,7 +47,7 @@ const sidebars = {
         {
           type: "category",
           label: "🪢 Logging",
-          items: ["proxy/logging", "proxy/streaming_logging"],
+          items: ["proxy/logging", "proxy/bucket", "proxy/streaming_logging"],
         },
         "proxy/team_logging",
         "proxy/guardrails",