Add VESSL AI OpenAI API-compatible model provider and LLM model (#9474)

Co-authored-by: moon <moon@vessl.ai>

api/tests/integration_tests/.env.example

@@ -84,5 +84,10 @@ VOLC_EMBEDDING_ENDPOINT_ID=
 # 360 AI Credentials
 ZHINAO_API_KEY=
 
+# VESSL AI Credentials
+VESSL_AI_MODEL_NAME=
+VESSL_AI_API_KEY=
+VESSL_AI_ENDPOINT_URL=
+
 # Gitee AI Credentials
-GITEE_AI_API_KEY=
+GITEE_AI_API_KEY=

api/tests/integration_tests/model_runtime/vessl_ai/test_llm.py

@@ -0,0 +1,131 @@
+import os
+from collections.abc import Generator
+
+import pytest
+
+from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.message_entities import (
+    AssistantPromptMessage,
+    SystemPromptMessage,
+    UserPromptMessage,
+)
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.vessl_ai.llm.llm import VesslAILargeLanguageModel
+
+
+def test_validate_credentials():
+    model = VesslAILargeLanguageModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model=os.environ.get("VESSL_AI_MODEL_NAME"),
+            credentials={
+                "api_key": "invalid_key",
+                "endpoint_url": os.environ.get("VESSL_AI_ENDPOINT_URL"),
+                "mode": "chat",
+            },
+        )
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model=os.environ.get("VESSL_AI_MODEL_NAME"),
+            credentials={
+                "api_key": os.environ.get("VESSL_AI_API_KEY"),
+                "endpoint_url": "http://invalid_url",
+                "mode": "chat",
+            },
+        )
+
+    model.validate_credentials(
+        model=os.environ.get("VESSL_AI_MODEL_NAME"),
+        credentials={
+            "api_key": os.environ.get("VESSL_AI_API_KEY"),
+            "endpoint_url": os.environ.get("VESSL_AI_ENDPOINT_URL"),
+            "mode": "chat",
+        },
+    )
+
+
+def test_invoke_model():
+    model = VesslAILargeLanguageModel()
+
+    response = model.invoke(
+        model=os.environ.get("VESSL_AI_MODEL_NAME"),
+        credentials={
+            "api_key": os.environ.get("VESSL_AI_API_KEY"),
+            "endpoint_url": os.environ.get("VESSL_AI_ENDPOINT_URL"),
+            "mode": "chat",
+        },
+        prompt_messages=[
+            SystemPromptMessage(
+                content="You are a helpful AI assistant.",
+            ),
+            UserPromptMessage(content="Who are you?"),
+        ],
+        model_parameters={
+            "temperature": 1.0,
+            "top_k": 2,
+            "top_p": 0.5,
+        },
+        stop=["How"],
+        stream=False,
+        user="abc-123",
+    )
+
+    assert isinstance(response, LLMResult)
+    assert len(response.message.content) > 0
+
+
+def test_invoke_stream_model():
+    model = VesslAILargeLanguageModel()
+
+    response = model.invoke(
+        model=os.environ.get("VESSL_AI_MODEL_NAME"),
+        credentials={
+            "api_key": os.environ.get("VESSL_AI_API_KEY"),
+            "endpoint_url": os.environ.get("VESSL_AI_ENDPOINT_URL"),
+            "mode": "chat",
+        },
+        prompt_messages=[
+            SystemPromptMessage(
+                content="You are a helpful AI assistant.",
+            ),
+            UserPromptMessage(content="Who are you?"),
+        ],
+        model_parameters={
+            "temperature": 1.0,
+            "top_k": 2,
+            "top_p": 0.5,
+        },
+        stop=["How"],
+        stream=True,
+        user="abc-123",
+    )
+
+    assert isinstance(response, Generator)
+
+    for chunk in response:
+        assert isinstance(chunk, LLMResultChunk)
+        assert isinstance(chunk.delta, LLMResultChunkDelta)
+        assert isinstance(chunk.delta.message, AssistantPromptMessage)
+
+
+def test_get_num_tokens():
+    model = VesslAILargeLanguageModel()
+
+    num_tokens = model.get_num_tokens(
+        model=os.environ.get("VESSL_AI_MODEL_NAME"),
+        credentials={
+            "api_key": os.environ.get("VESSL_AI_API_KEY"),
+            "endpoint_url": os.environ.get("VESSL_AI_ENDPOINT_URL"),
+        },
+        prompt_messages=[
+            SystemPromptMessage(
+                content="You are a helpful AI assistant.",
+            ),
+            UserPromptMessage(content="Hello World!"),
+        ],
+    )
+
+    assert isinstance(num_tokens, int)
+    assert num_tokens == 21