diff --git a/deepeval/api.py b/deepeval/api.py
index 719516786..734a5ee5f 100644
--- a/deepeval/api.py
+++ b/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,
+        )
diff --git a/deepeval/event.py b/deepeval/event.py
index 709f03c09..73b6d6b1e 100644
--- a/deepeval/event.py
+++ b/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)
diff --git a/docs/docs/confident-ai-introduction.mdx b/docs/docs/confident-ai-introduction.mdx
index 7cc3a0bcb..bd6f69221 100644
--- a/docs/docs/confident-ai-introduction.mdx
+++ b/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
diff --git a/docs/docs/evaluation-test-cases.mdx b/docs/docs/evaluation-test-cases.mdx
index be1ff5c98..e21f8e3c8 100644
--- a/docs/docs/evaluation-test-cases.mdx
+++ b/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
diff --git a/docs/docs/getting-started.mdx b/docs/docs/getting-started.mdx
index 811802a6a..a34f15793 100644
--- a/docs/docs/getting-started.mdx
+++ b/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
diff --git a/poetry.lock b/poetry.lock
index badd5ac49..161ba87c4 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -450,63 +450,63 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
 
 [[package]]
 name = "coverage"
-version = "7.3.4"
+version = "7.4.0"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "coverage-7.4.0.tar.gz", hash = "sha256:707c0f58cb1712b8809ece32b68996ee1e609f71bd14615bd8f87a1293cb610e"},
 ]
 
 [package.extras]
@@ -544,25 +544,27 @@ typing-inspect = ">=0.4.0,<1"
 
 [[package]]
 name = "datasets"
-version = "2.14.4"
+version = "2.16.0"
 description = "HuggingFace community-driven open-source library of datasets"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "datasets-2.14.4-py3-none-any.whl", hash = "sha256:29336bd316a7d827ccd4da2236596279b20ca2ac78f64c04c9483da7cbc2459b"},
-    {file = "datasets-2.14.4.tar.gz", hash = "sha256:ef29c2b5841de488cd343cfc26ab979bff77efa4d2285af51f1ad7db5c46a83b"},
+    {file = "datasets-2.16.0-py3-none-any.whl", hash = "sha256:301cc39b3d81cd751100b79c85f8ae8626c17b0b113819ba2831c204d90b43f2"},
+    {file = "datasets-2.16.0.tar.gz", hash = "sha256:91b06f7a8f0329179e7d603004102a6cc7a424a2f599315297a061caa1f8fa64"},
 ]
 
 [package.dependencies]
 aiohttp = "*"
 dill = ">=0.3.0,<0.3.8"
-fsspec = {version = ">=2021.11.1", extras = ["http"]}
-huggingface-hub = ">=0.14.0,<1.0.0"
+filelock = "*"
+fsspec = {version = ">=2023.1.0,<=2023.10.0", extras = ["http"]}
+huggingface-hub = ">=0.19.4"
 multiprocess = "*"
 numpy = ">=1.17"
 packaging = "*"
 pandas = "*"
 pyarrow = ">=8.0.0"
+pyarrow-hotfix = "*"
 pyyaml = ">=5.1"
 requests = ">=2.19.0"
 tqdm = ">=4.62.1"
@@ -572,15 +574,15 @@ xxhash = "*"
 apache-beam = ["apache-beam (>=2.26.0,<2.44.0)"]
 audio = ["librosa", "soundfile (>=0.12.1)"]
 benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
-dev = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "black (>=23.1,<24.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "pyyaml (>=5.3.1)", "rarfile (>=4.0)", "ruff (>=0.0.241)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
+dev = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.1.5)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
 docs = ["s3fs", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos", "torch", "transformers"]
-jax = ["jax (>=0.2.8,!=0.3.2,<=0.3.25)", "jaxlib (>=0.1.65,<=0.3.25)"]
+jax = ["jax (>=0.3.14)", "jaxlib (>=0.3.14)"]
 metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk", "requests-file (>=1.5.1)", "rouge-score", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "spacy (>=3.0.0)", "texttable (>=1.6.3)", "tldextract", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "typer (<0.5.0)"]
-quality = ["black (>=23.1,<24.0)", "pyyaml (>=5.3.1)", "ruff (>=0.0.241)"]
+quality = ["ruff (>=0.1.5)"]
 s3 = ["s3fs"]
 tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos"]
 tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
-tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
+tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "jax (>=0.3.14)", "jaxlib (>=0.3.14)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch (>=2.0.0)", "transformers", "typing-extensions (>=4.6.1)", "zstandard"]
 torch = ["torch"]
 vision = ["Pillow (>=6.2.1)"]
 
@@ -806,13 +808,13 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2023.12.2"
+version = "2023.10.0"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fsspec-2023.12.2-py3-none-any.whl", hash = "sha256:d800d87f72189a745fa3d6b033b9dc4a34ad069f60ca60b943a63599f5501960"},
-    {file = "fsspec-2023.12.2.tar.gz", hash = "sha256:8548d39e8810b59c38014934f6b31e57f40c1b20f911f4cc2b85389c7e9bf0cb"},
+    {file = "fsspec-2023.10.0-py3-none-any.whl", hash = "sha256:346a8f024efeb749d2a5fca7ba8854474b1ff9af7c3faaf636a4548781136529"},
+    {file = "fsspec-2023.10.0.tar.gz", hash = "sha256:330c66757591df346ad3091a53bd907e15348c2ba17d63fd54f5c39c4457d2a5"},
 ]
 
 [package.dependencies]
@@ -2142,6 +2144,17 @@ files = [
 [package.dependencies]
 numpy = ">=1.16.6"
 
+[[package]]
+name = "pyarrow-hotfix"
+version = "0.6"
+description = ""
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "pyarrow_hotfix-0.6-py3-none-any.whl", hash = "sha256:dcc9ae2d220dff0083be6a9aa8e0cdee5182ad358d4931fce825c545e5c89178"},
+    {file = "pyarrow_hotfix-0.6.tar.gz", hash = "sha256:79d3e030f7ff890d408a100ac16d6f00b14d44a502d7897cd9fc3e3a534e9945"},
+]
+
 [[package]]
 name = "pydantic"
 version = "2.5.3"
@@ -3879,4 +3892,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.12"
-content-hash = "999515af5757ca9c0f111d90fe0bcb416dd62e1f9fc04bfa6183a5a87c49b10e"
+content-hash = "8b882533d1c305fc650e8609cb93c420c3becbff3abb398cb247f5bbd42a73ec"
diff --git a/pyproject.toml b/pyproject.toml
index 3888e2aab..c12a227af 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -41,6 +41,8 @@ protobuf = "*"
 typer = "*"
 setuptools = "*"
 wheel = "*"
+aiohttp = "*"
+
 
 [tool.black]
 line-length = 80