Merge pull request #175 from Riddhimaan-Senapati/main

Added support for deepseek LLMs

Author: ksolo

aisuite/providers/deepseek_provider.py

@@ -0,0 +1,34 @@
+import openai
+import os
+from aisuite.provider import Provider, LLMError
+
+
+class DeepseekProvider(Provider):
+    def __init__(self, **config):
+        """
+        Initialize the DeepSeek provider with the given configuration.
+        Pass the entire configuration dictionary to the OpenAI client constructor.
+        """
+        # Ensure API key is provided either in config or via environment variable
+        config.setdefault("api_key", os.getenv("DEEPSEEK_API_KEY"))
+        if not config["api_key"]:
+            raise ValueError(
+                "DeepSeek API key is missing. Please provide it in the config or set the OPENAI_API_KEY environment variable."
+            )
+        config["base_url"] = "https://api.deepseek.com"
+
+        # NOTE: We could choose to remove above lines for api_key since OpenAI will automatically
+        # infer certain values from the environment variables.
+        # Eg: OPENAI_API_KEY, OPENAI_ORG_ID, OPENAI_PROJECT_ID. Except for OPEN_AI_BASE_URL which has to be the deepseek url
+
+        # Pass the entire config to the OpenAI client constructor
+        self.client = openai.OpenAI(**config)
+
+    def chat_completions_create(self, model, messages, **kwargs):
+        # Any exception raised by OpenAI will be returned to the caller.
+        # Maybe we should catch them and raise a custom LLMError.
+        return self.client.chat.completions.create(
+            model=model,
+            messages=messages,
+            **kwargs  # Pass any additional arguments to the OpenAI API
+        )

guides/README.md

@@ -12,6 +12,7 @@ Here are the instructions for:
 - [OpenAI](openai.md)
 - [SambaNova](sambanova.md)
 - [xAI](xai.md)
+- [DeepSeek](deepseek.md)
 
 Unless otherwise stated, these guides have not been endorsed by the providers. 
 

guides/deepseek.md

@@ -0,0 +1,46 @@
+# DeepSeek
+
+To use DeepSeek with `aisuite`, you’ll need an [DeepSeek account](https://platform.deepseek.com). After logging in, go to the [API Keys](https://platform.deepseek.com/api_keys) section in your account settings and generate a new key. Once you have your key, add it to your environment as follows:
+
+```shell
+export DEEPSEEK_API_KEY="your-deepseek-api-key"
+```
+
+## Create a Chat Completion
+
+(Note: The DeepSeek uses an API format consistent with OpenAI, hence why we need to install OpenAI, there is no DeepSeek Library at least not for now)
+
+Install the `openai` Python client:
+
+Example with pip:
+```shell
+pip install openai
+```
+
+Example with poetry:
+```shell
+poetry add openai
+```
+
+In your code:
+```python
+import aisuite as ai
+client = ai.Client()
+
+provider = "deepseek"
+model_id = "deepseek-chat"
+
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": "What’s the weather like in San Francisco?"},
+]
+
+response = client.chat.completions.create(
+    model=f"{provider}:{model_id}",
+    messages=messages,
+)
+
+print(response.choices[0].message.content)
+```
+
+Happy coding! If you’d like to contribute, please read our [Contributing Guide](../CONTRIBUTING.md).

tests/providers/test_deepseek_provider.py

@@ -0,0 +1,46 @@
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from aisuite.providers.deepseek_provider import DeepseekProvider
+
+
+@pytest.fixture(autouse=True)
+def set_api_key_env_var(monkeypatch):
+    """Fixture to set environment variables for tests."""
+    monkeypatch.setenv("DEEPSEEK_API_KEY", "test-api-key")
+
+
+def test_groq_provider():
+    """High-level test that the provider is initialized and chat completions are requested successfully."""
+
+    user_greeting = "Hello!"
+    message_history = [{"role": "user", "content": user_greeting}]
+    selected_model = "our-favorite-model"
+    chosen_temperature = 0.75
+    response_text_content = "mocked-text-response-from-model"
+
+    provider = DeepseekProvider()
+    mock_response = MagicMock()
+    mock_response.choices = [MagicMock()]
+    mock_response.choices[0].message = MagicMock()
+    mock_response.choices[0].message.content = response_text_content
+
+    with patch.object(
+        provider.client.chat.completions,
+        "create",
+        return_value=mock_response,
+    ) as mock_create:
+        response = provider.chat_completions_create(
+            messages=message_history,
+            model=selected_model,
+            temperature=chosen_temperature,
+        )
+
+        mock_create.assert_called_with(
+            messages=message_history,
+            model=selected_model,
+            temperature=chosen_temperature,
+        )
+
+        assert response.choices[0].message.content == response_text_content