[Feat] Observability integration - Opik by Comet (#6062)

* Added Opik logging and evaluation

* Updated doc examples

* Default tags should be [] in case appending

* WIP

* Work in progress

* Opik integration

* Opik integration

* Revert changes on litellm_logging.py

* Updated Opik integration for synchronous API calls

* Updated Opik documentation

---------

Co-authored-by: Douglas Blank <doug@comet.com>
Co-authored-by: Doug Blank <doug.blank@gmail.com>

tests/local_testing/test_opik.py

@@ -0,0 +1,175 @@
+import io
+import os
+import sys
+
+sys.path.insert(0, os.path.abspath("../.."))
+
+import asyncio
+import logging
+
+import pytest
+
+import litellm
+from litellm._logging import verbose_logger
+from unittest.mock import AsyncMock, Mock
+
+verbose_logger.setLevel(logging.DEBUG)
+
+litellm.set_verbose = True
+import time
+
+@pytest.mark.asyncio
+async def test_opik_logging_http_request():
+    """
+    - Test that HTTP requests are made to Opik
+    - Traces and spans are batched correctly
+    """
+    try:
+        from litellm.integrations.opik.opik import OpikLogger
+
+        os.environ["OPIK_URL_OVERRIDE"] = "https://fake.comet.com/opik/api"
+        os.environ["OPIK_API_KEY"] = "anything"
+        os.environ["OPIK_WORKSPACE"] = "anything"
+
+        # Initialize OpikLogger
+        test_opik_logger = OpikLogger()
+
+        litellm.callbacks = [test_opik_logger]
+        test_opik_logger.batch_size = 12
+        litellm.set_verbose = True
+
+        # Create a mock for the async_client's post method
+        mock_post = AsyncMock()
+        mock_post.return_value.status_code = 202
+        mock_post.return_value.text = "Accepted"
+        test_opik_logger.async_httpx_client.post = mock_post
+
+        # Make multiple calls to ensure we don't hit the batch size
+        for _ in range(5):
+            response = await litellm.acompletion(
+                model="gpt-3.5-turbo",
+                messages=[{"role": "user", "content": "Test message"}],
+                max_tokens=10,
+                temperature=0.2,
+                mock_response="This is a mock response",
+            )
+        await asyncio.sleep(1)
+
+        # Check batching of events and that the queue contains 5 trace events and 5 span events
+        assert mock_post.called == False, "HTTP request was made but events should have been batched"
+        assert len(test_opik_logger.log_queue) == 10
+
+        # Now make calls to exceed the batch size
+        for _ in range(3):
+            response = await litellm.acompletion(
+                model="gpt-3.5-turbo",
+                messages=[{"role": "user", "content": "Test message"}],
+                max_tokens=10,
+                temperature=0.2,
+                mock_response="This is a mock response",
+            )
+        
+        # Wait a short time for any asynchronous operations to complete
+        await asyncio.sleep(1)
+
+        # Check that the queue was flushed after exceeding batch size
+        assert len(test_opik_logger.log_queue) < test_opik_logger.batch_size
+
+        # Check that the data has been sent when it goes above the flush interval
+        await asyncio.sleep(test_opik_logger.flush_interval)
+        assert len(test_opik_logger.log_queue) == 0
+
+        # Clean up
+        for cb in litellm.callbacks:
+            if isinstance(cb, OpikLogger):
+                await cb.async_httpx_client.client.aclose()
+
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+def test_sync_opik_logging_http_request():
+    """
+    - Test that HTTP requests are made to Opik
+    - Traces and spans are batched correctly
+    """
+    try:
+        from litellm.integrations.opik.opik import OpikLogger
+
+        os.environ["OPIK_URL_OVERRIDE"] = "https://fake.comet.com/opik/api"
+        os.environ["OPIK_API_KEY"] = "anything"
+        os.environ["OPIK_WORKSPACE"] = "anything"
+
+        # Initialize OpikLogger
+        test_opik_logger = OpikLogger()
+
+        litellm.callbacks = [test_opik_logger]
+        litellm.set_verbose = True
+
+        # Create a mock for the clients's post method
+        mock_post = Mock()
+        mock_post.return_value.status_code = 204
+        mock_post.return_value.text = "Accepted"
+        test_opik_logger.sync_httpx_client.post = mock_post
+
+        # Make multiple calls to ensure we don't hit the batch size
+        for _ in range(5):
+            response = litellm.completion(
+                model="gpt-3.5-turbo",
+                messages=[{"role": "user", "content": "Test message"}],
+                max_tokens=10,
+                temperature=0.2,
+                mock_response="This is a mock response",
+            )
+        
+        # Need to wait for a short amount of time as the log_success callback is called in a different thread
+        time.sleep(1)
+
+        # Check that 5 spans and 5 traces were sent
+        assert mock_post.call_count == 10, f"Expected 10 HTTP requests, but got {mock_post.call_count}"
+        
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+@pytest.mark.asyncio
+@pytest.mark.skip(reason="local-only test, to test if everything works fine.")
+async def test_opik_logging():
+    try:
+        from litellm.integrations.opik.opik import OpikLogger
+        
+        # Initialize OpikLogger
+        test_opik_logger = OpikLogger()
+        litellm.callbacks = [test_opik_logger]
+        litellm.set_verbose = True
+
+        # Log a chat completion call
+        response = await litellm.acompletion(
+            model="gpt-3.5-turbo",
+            messages=[{"role": "user", "content": "What LLM are you ?"}],
+            max_tokens=10,
+            temperature=0.2,
+            metadata={"opik": {"custom_field": "custom_value"}}
+        )
+        print("Non-streaming response:", response)
+        
+        # Log a streaming completion call
+        stream_response = await litellm.acompletion(
+            model="gpt-3.5-turbo",
+            messages=[{"role": "user", "content": "Stream = True - What llm are you ?"}],
+            max_tokens=10,
+            temperature=0.2,
+            stream=True,
+            metadata={"opik": {"custom_field": "custom_value"}}
+        )
+        print("Streaming response:")
+        async for chunk in stream_response:
+            print(chunk.choices[0].delta.content, end='', flush=True)
+        print()  # New line after streaming response
+
+        await asyncio.sleep(2)
+
+        assert len(test_opik_logger.log_queue) == 4
+        
+        await asyncio.sleep(test_opik_logger.flush_interval + 1)
+        assert len(test_opik_logger.log_queue) == 0
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")