docs: add Elasticsearch logging tutorial and update sidebar

docs/my-website/docs/tutorials/elasticsearch_logging.md

@@ -0,0 +1,218 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# Elasticsearch Logging with LiteLLM
+
+Send your LLM requests, responses, costs, and performance data to Elasticsearch for analytics and monitoring.
+
+## Quick Start
+
+### 1. Start Elasticsearch
+
+```bash
+# Using Docker (simplest)
+docker run -d \
+  --name elasticsearch \
+  -p 9200:9200 \
+  -e "discovery.type=single-node" \
+  -e "xpack.security.enabled=false" \
+  docker.elastic.co/elasticsearch/elasticsearch:8.11.0
+```
+
+### 2. Configure LiteLLM
+
+<Tabs>
+<TabItem value="proxy" label="LiteLLM Proxy">
+
+Create a `config.yaml` file:
+
+```yaml
+model_list:
+  - model_name: gpt-4.1
+    litellm_params:
+      model: openai/gpt-4.1
+      api_key: os.environ/OPENAI_API_KEY
+
+litellm_settings:
+  success_callback: ["generic"]
+  failure_callback: ["generic"]
+
+general_settings:
+  generic_logger_endpoint: "http://localhost:9200/litellm-logs/_doc"
+  generic_logger_headers: 
+    "Content-Type": "application/json"
+```
+
+Start the proxy:
+```bash
+litellm --config config.yaml
+```
+
+</TabItem>
+<TabItem value="python-sdk" label="Python SDK">
+
+Configure the generic logger in your Python code:
+
+```python
+import litellm
+import os
+
+# Set up Elasticsearch endpoint
+os.environ["GENERIC_LOGGER_ENDPOINT"] = "http://localhost:9200/litellm-logs/_doc"
+os.environ["GENERIC_LOGGER_HEADERS"] = "Content-Type=application/json"
+
+# Enable logging
+litellm.success_callback = ["generic"]
+litellm.failure_callback = ["generic"]
+
+# Make your LLM calls
+response = litellm.completion(
+    model="gpt-4.1",
+    messages=[{"role": "user", "content": "Hello, world!"}]
+)
+```
+
+</TabItem>
+</Tabs>
+
+### 3. Test the Integration
+
+Make a test request to verify logging is working:
+
+<Tabs>
+<TabItem value="curl-proxy" label="Test Proxy">
+
+```bash
+curl -X POST "http://localhost:4000/v1/chat/completions" \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer sk-1234" \
+  -d '{
+    "model": "gpt-4.1",
+    "messages": [{"role": "user", "content": "Hello from LiteLLM!"}]
+  }'
+```
+
+</TabItem>
+<TabItem value="python-test" label="Test Python SDK">
+
+```python
+import litellm
+
+response = litellm.completion(
+    model="gpt-4.1",
+    messages=[{"role": "user", "content": "Hello from LiteLLM!"}],
+    user="test-user"
+)
+print("Response:", response.choices[0].message.content)
+```
+
+</TabItem>
+</Tabs>
+
+### 4. Verify It's Working
+
+```bash
+# Check if logs are being created
+curl "localhost:9200/litellm-logs/_search?pretty&size=1"
+```
+
+You should see your LLM requests with fields like `model`, `response_cost`, `total_tokens`, `messages`, etc.
+
+## Analytics Examples
+
+**Total costs by model:**
+```bash
+curl -X GET "localhost:9200/litellm-logs/_search" -H "Content-Type: application/json" -d '{
+  "size": 0,
+  "aggs": {
+    "models": {
+      "terms": {"field": "model"},
+      "aggs": {"total_cost": {"sum": {"field": "response_cost"}}}
+    }
+  }
+}'
+```
+
+**Average response time:**
+```bash
+curl -X GET "localhost:9200/litellm-logs/_search" -H "Content-Type: application/json" -d '{
+  "size": 0,
+  "aggs": {"avg_response_time": {"avg": {"field": "response_time"}}}
+}'
+```
+
+**Recent errors:**
+```bash
+curl -X GET "localhost:9200/litellm-logs/_search" -H "Content-Type: application/json" -d '{
+  "query": {"term": {"status": "failure"}},
+  "size": 10,
+  "sort": [{"endTime": {"order": "desc"}}]
+}'
+```
+
+## Production Setup
+
+**With Elasticsearch Cloud:**
+```yaml
+general_settings:
+  generic_logger_endpoint: "https://your-deployment.es.region.cloud.es.io/litellm-logs/_doc"
+  generic_logger_headers:
+    "Content-Type": "application/json"
+    "Authorization": "Bearer your-api-key"
+```
+
+**Docker Compose (Full Stack):**
+```yaml
+# docker-compose.yml
+version: '3.8'
+services:
+  elasticsearch:
+    image: docker.elastic.co/elasticsearch/elasticsearch:8.11.0
+    environment:
+      - discovery.type=single-node
+      - xpack.security.enabled=false
+    ports:
+      - "9200:9200"
+      
+  litellm:
+    image: ghcr.io/berriai/litellm:main-latest
+    ports:
+      - "4000:4000"
+    environment:
+      - OPENAI_API_KEY=${OPENAI_API_KEY}
+      - GENERIC_LOGGER_ENDPOINT=http://elasticsearch:9200/litellm-logs/_doc
+    command: ["--config", "/app/config.yaml"]
+    volumes:
+      - ./config.yaml:/app/config.yaml
+```
+
+**config.yaml:**
+```yaml
+model_list:
+  - model_name: gpt-4.1
+    litellm_params:
+      model: openai/gpt-4.1
+      api_key: os.environ/OPENAI_API_KEY
+
+litellm_settings:
+  success_callback: ["generic"]
+  failure_callback: ["generic"]
+
+general_settings:
+  master_key: sk-1234
+```
+
+## What's Logged
+
+LiteLLM sends a payload for every request including:
+
+- `model` - Model used (e.g., gpt-4.1)
+- `response_cost` - Cost in USD
+- `total_tokens`, `prompt_tokens`, `completion_tokens` - Token usage
+- `response_time` - How long the request took
+- `status` - "success" or "failure"
+- `messages` - Input messages
+- `response` - LLM response
+- `metadata` - User info, API keys, etc.
+
+See the full [StandardLoggingPayload specification](../proxy/logging_spec) for all available fields.

docs/my-website/sidebars.js

@@ -506,6 +506,7 @@ const sidebars = {
         "tutorials/prompt_caching",
         "tutorials/tag_management",
         'tutorials/litellm_proxy_aporia',
+        "tutorials/elasticsearch_logging",
         "tutorials/gemini_realtime_with_audio",
         "tutorials/claude_responses_api",
         {