Merge pull request #24 from confident-ai/main

Merge from main.

deepeval/api.py

@@ -4,9 +4,13 @@
 import requests
 import warnings
 from requests.adapters import HTTPAdapter, Response, Retry
+import aiohttp
+from aiohttp import ClientSession
+from requests.adapters import HTTPAdapter
+from enum import Enum
+
 from deepeval.constants import API_KEY_ENV
 from deepeval.key_handler import KEY_FILE_HANDLER, KeyValues
-from enum import Enum
 
 API_BASE_URL = "https://app.confident-ai.com/api"
 
@@ -259,3 +263,77 @@ def quote_string(text: str) -> str:
             str: Quoted text in return
         """
         return urllib.parse.quote(text, safe="")
+
+    async def _api_request_async(
+        self,
+        method,
+        endpoint,
+        headers=None,
+        auth=None,
+        params=None,
+        body=None,
+        files=None,
+        data=None,
+    ):
+        """Generic asynchronous HTTP request method with error handling."""
+        url = f"{self.base_api_url}/{endpoint}"
+        async with ClientSession() as session:
+            try:
+                # Preparing the request body for file uploads if files are present
+                if files:
+                    data = aiohttp.FormData()
+                    for file_name, file_content in files.items():
+                        data.add_field(
+                            file_name, file_content, filename=file_name
+                        )
+
+                # Sending the request
+                res = await session.request(
+                    method=method,
+                    url=url,
+                    headers=headers,
+                    params=params,
+                    json=body,
+                )
+
+                # Check response status
+                if res.status == 200:
+                    try:
+                        json = await res.json()
+                        return json
+                    except ValueError:
+                        return await res.text()
+                else:
+                    # Determine how to process the response based on Content-Type
+                    content_type = res.headers.get("Content-Type", "")
+                    if "application/json" in content_type:
+                        error_response = await res.json()
+                    else:
+                        error_response = await res.text()
+
+                    # Specifically handle status code 400
+                    if res.status == 400:
+                        print(f"Error 400: Bad Request - {error_response}")
+
+                    print(f"Error {res.status}: {error_response}")
+                    return None
+
+            except Exception as err:
+                raise Exception(f"HTTP request failed: {err}") from err
+
+    async def post_request_async(
+        self, endpoint, body=None, files=None, data=None
+    ):
+        """Generic asynchronous POST Request Wrapper"""
+        print("hi")
+        return await self._api_request_async(
+            "POST",
+            endpoint,
+            headers=self._headers
+            if files is None
+            else self._headers_multipart_form_data,
+            auth=self._auth,
+            body=body,
+            files=files,
+            data=data,
+        )

deepeval/event.py

@@ -1,5 +1,7 @@
 from typing import Optional, List, Dict
 from deepeval.api import Api, Endpoints
+import threading
+import asyncio
 from pydantic import BaseModel, Field
 
 
@@ -32,7 +34,18 @@ def track(
     conversation_id: Optional[str] = None,
     additional_data: Optional[Dict] = None,
     fail_silently: Optional[bool] = True,
+    run_on_background_thread: Optional[bool] = True,
 ):
+    def track_event(event: APIEvent, api: Api, fail_silently: bool):
+        try:
+            _ = api.post_request(
+                endpoint=Endpoints.EVENT_ENDPOINT.value,
+                body=event.dict(by_alias=True, exclude_none=True),
+            )
+        except Exception as e:
+            if not fail_silently:
+                raise e
+
     event = APIEvent(
         name=event_name,
         model=model,
@@ -47,11 +60,10 @@ def track(
         additionalData=additional_data,
     )
     api = Api()
-    try:
-        _ = api.post_request(
-            endpoint=Endpoints.EVENT_ENDPOINT.value,
-            body=event.dict(by_alias=True, exclude_none=True),
+    if run_on_background_thread:
+        thread = threading.Thread(
+            target=track_event, args=(event, api, fail_silently), daemon=True
         )
-    except Exception as e:
-        if not fail_silently:
-            raise (e)
+        thread.start()
+    else:
+        track_event(event, api, fail_silently)

docs/docs/confident-ai-introduction.mdx

@@ -32,7 +32,7 @@ Continuous evaluation refers to the process of evaluating LLM applications in no
   />
 </div>
 
-Everything in `deepeval` is already automatically integrated with Confident AI, including `deepeval`'s [custom metrics](evaluation-metrics#custom-metrics). To start using Confident AI with `deepeval`, simply login in the CLI:
+Everything in `deepeval` is already automatically integrated with Confident AI, including `deepeval`'s [custom metrics](metrics-custom). To start using Confident AI with `deepeval`, simply login in the CLI:
 
 ```
 deepeval login

docs/docs/evaluation-test-cases.mdx

@@ -82,7 +82,7 @@ test_case = LLMTestCase(
 
 An expected output is literally what you would want the ideal output to be. Note that this parameter is **optional** depending on the metric you want to evaluate.
 
-The expected output doesn't have to exactly match the actual output in order for your test case to pass since `deepeval` uses a variety of methods to evaluate non-deterministic LLM outputs. We'll go into more details [in the metrics section.](evaluation-metrics)
+The expected output doesn't have to exactly match the actual output in order for your test case to pass since `deepeval` uses a variety of methods to evaluate non-deterministic LLM outputs. We'll go into more details [in the metrics section.](metrics-introduction)
 
 ```python
 # A hypothetical LLM application example

docs/docs/getting-started.mdx

@@ -34,7 +34,7 @@ In your newly created virtual environement, run:
 pip install -U deepeval
 ```
 
-You can also keep track of all evaluation results by logging into our [in all one evaluation platform](https://confident-ai.com), and use Confident AI's [proprietary LLM evaluation agent](evaluation-metrics#judgementalgpt) for evaluation:
+You can also keep track of all evaluation results by logging into our [in all one evaluation platform](https://confident-ai.com), and use Confident AI's [proprietary LLM evaluation agent](metrics-judgemental) for evaluation:
 
 ```console
 deepeval login