Fix/gemma2 chat template (#1657)

* chore/embeddings-docs

* chore: add embedding capabilities

* chore: remove un developed file

* fix: gemma2 chat template renderer

* format code

Author: nguyenhoangthuan99

docs/docs/capabilities/embeddings.md

@@ -1,7 +1,103 @@
 ---
 title: Embeddings
 ---
-
 :::info
-🚧 Cortex is currently under development, and this page is a stub for future development. 
-:::
+🚧 Cortex is currently under development, and this page is a stub for future development.
+:::
+
+cortex.cpp now support embeddings endpoint with fully OpenAI compatible.
+
+For embeddings API usage please refer to [API references](/api-reference#tag/chat/POST/v1/embeddings). This tutorial show you how to use embeddings in cortex with openai python SDK.
+
+## Embedding with openai compatible
+
+### 1. Start server and run model
+
+```
+cortex run llama3.1:8b-gguf-q4-km
+```
+
+### 2. Create script `embeddings.py` with this content
+
+```
+from datetime import datetime
+from openai import OpenAI
+from pydantic import BaseModel
+ENDPOINT = "http://localhost:39281/v1"
+MODEL = "llama3.1:8bb-gguf-q4-km"
+client = OpenAI(
+    base_url=ENDPOINT,
+    api_key="not-needed"
+)
+```
+
+### 3. Create embeddings
+
+```
+response = client.embeddings.create(input = "embedding", model=MODEL, encoding_format="base64")
+print(response)
+```
+
+The reponse will be like this
+
+```
+CreateEmbeddingResponse(
+    data=[
+        Embedding(
+            embedding='hjuAPOD8TryuPU8...',
+            index=0,
+            object='embedding'
+        )
+    ],
+    model='meta-llama3.1-8b-instruct',
+    object='list',
+    usage=Usage(
+        prompt_tokens=2,
+        total_tokens=2
+    )
+)
+```
+
+
+The output embeddings is encoded as base64 string. Default the model will output the embeddings in float mode.
+
+```
+response = client.embeddings.create(input = "embedding", model=MODEL)
+print(response)
+```
+
+Result will be
+
+```
+CreateEmbeddingResponse(
+    data=[
+        Embedding(
+            embedding=[0.1, 0.3, 0.4 ....],
+            index=0,
+            object='embedding'
+        )
+    ],
+    model='meta-llama3.1-8b-instruct',
+    object='list',
+    usage=Usage(
+        prompt_tokens=2,
+        total_tokens=2
+    )
+)
+```
+
+Cortex also supports all input types as [OpenAI](https://platform.openai.com/docs/api-reference/embeddings/create#embeddings-create-input).
+
+```sh
+# input as string
+response = client.embeddings.create(input = "embedding", model=MODEL)
+
+# input as array of string
+response = client.embeddings.create(input = ["embedding"], model=MODEL)
+
+# input as array of tokens
+response = client.embeddings.create(input = [12,44,123], model=MODEL)
+
+# input as array of arrays contain tokens
+response = client.embeddings.create(input = [[912,312,54],[12,433,1241]], model=MODEL)
+```