Merge pull request #363 from SylphAI-Inc/integrations

Multiple LLM provider integrations

adalflow/adalflow/components/model_client/__init__.py

@@ -46,7 +46,27 @@
 )
 
 DeepSeekClient = LazyImport(
-    "adalflow.components.model_client.deepseek_client.DeepSeekClient", None
+    "adalflow.components.model_client.deepseek_client.DeepSeekClient",
+    OptionalPackages.OPENAI,
+)
+
+MistralClient = LazyImport(
+    "adalflow.components.model_client.mistral_client.MistralClient",
+    OptionalPackages.MISTRAL,
+)
+
+XAIClient = LazyImport(
+    "adalflow.components.model_client.xai_client.XAIClient", OptionalPackages.OPENAI
+)
+
+FireworksClient = LazyImport(
+    "adalflow.components.model_client.fireworks_client.FireworksClient",
+    OptionalPackages.FIREWORKS,
+)
+
+SambaNovaClient = LazyImport(
+    "adalflow.components.model_client.sambanova_client.SambaNovaClient",
+    OptionalPackages.OPENAI,
 )
 
 GoogleGenAIClient = LazyImport(
@@ -87,6 +107,11 @@
     "GoogleGenAIClient",
     "OllamaClient",
     "TogetherClient",
+    "DeepSeekClient",
+    "MistralClient",
+    "XAIClient",
+    "FireworksClient",
+    "SambaNovaClient",
 ]
 
 for name in __all__:

adalflow/adalflow/components/model_client/fireworks_client.py

@@ -0,0 +1,53 @@
+from typing import Optional, Callable, Any, Literal
+from openai.types import Completion
+from adalflow.components.model_client.openai_client import OpenAIClient
+
+BASE_URL = "https://api.fireworks.ai/inference/v1/"
+
+
+class FireworksClient(OpenAIClient):
+    __doc__ = r"""A component wrapper for Fireworks AI's OpenAI-compatible API.
+
+    This class extends :class:`OpenAIClient` by customizing several key parameters:
+    - Sets the API base URL to ``"https://api.fireworks.ai/inference/v1/"``.
+    - Uses the environment variable ``"FIREWORKS_API_KEY"`` to obtain the API key.
+    - Defaults the input type to ``"messages"``, which is suitable for multi-turn chat interactions.
+
+    **Example usage with AdalFlow Generator:**
+
+    .. code-block:: python
+
+        from adalflow.core import Generator
+        from adalflow.components.model_client.fireworks_client import FireworksClient
+
+
+        generator = Generator(
+            model_client=FireworksClient(),
+            model_kwargs={
+                "model": "accounts/fireworks/models/llama-v3p1-8b-instruct",
+                "temperature": 0.7,
+            }
+        )
+
+        prompt_kwargs = {
+            "input_str": "Hello from Fireworks AI! Can you summarize the concept of quantum mechanics?"
+        }
+
+        response = generator(prompt_kwargs)
+    """
+
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        chat_completion_parser: Callable[[Completion], Any] = None,
+        input_type: Literal["text", "messages"] = "text",
+        base_url: str = BASE_URL,
+        env_api_key_name: str = "FIREWORKS_API_KEY",
+    ):
+        super().__init__(
+            api_key=api_key,
+            chat_completion_parser=chat_completion_parser,
+            input_type=input_type,
+            base_url=base_url,
+            env_api_key_name=env_api_key_name,
+        )

adalflow/adalflow/components/model_client/mistral_client.py

@@ -0,0 +1,101 @@
+from typing import Optional, Any, Callable, Literal
+from openai.types import Completion
+from adalflow.components.model_client.openai_client import OpenAIClient
+
+BASE_URL = "https://api.mistral.ai/v1"
+
+
+class MistralClient(OpenAIClient):
+    __doc__ = r"""A minimal Mistral client that inherits from :class:`OpenAIClient`.
+
+    This client is designed to work with Mistral’s API by setting:
+    - The API base URL to ``https://api.mistral.ai/v1``.
+    - The API key is fetched from the environment variable ``MISTRAL_API_KEY`` if not provided.
+    - The input format is supported as either ``"text"`` or ``"messages"``.
+    - The AdalFlow Generator is expected to supply additional model parameters (such as model name, temperature, and max_tokens)
+        in a single configuration point.
+
+    **Example usage with the AdalFlow Generator:**
+
+    .. code-block:: python
+
+        import os
+        from adalflow.core import Generator
+        from adalflow.components.model_client.mistral_client import MistralClient
+        from adalflow.utils import setup_env
+
+        setup_env()
+
+        generator = Generator(
+            model_client=MistralClient(),
+            model_kwargs={
+                "model": "mistral-large-latest",
+                "temperature": 0.7,
+                "max_tokens": 2000,
+            }
+        )
+
+        prompt_kwargs = {"input_str": "Explain the concept of machine learning."}
+
+        response = generator(prompt_kwargs)
+
+    """
+
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        base_url: str = BASE_URL,
+        input_type: Literal["text", "messages"] = "text",
+        env_api_key_name: str = "MISTRAL_API_KEY",
+        chat_completion_parser: Callable[[Completion], Any] = None,
+    ):
+        """
+        Initialize a MistralClient instance.
+
+        :param api_key: Mistral API key. If None, reads from the environment variable ``MISTRAL_API_KEY``.
+        :param base_url: URL for Mistral’s endpoint (default: ``https://api.mistral.ai/v1``).
+        :param input_type: Input format, either ``"text"`` or ``"messages"``.
+        :param env_api_key_name: Name of the environment variable to use for the Mistral API key (default: ``MISTRAL_API_KEY``).
+        :param chat_completion_parser: Optional function to parse responses from Mistral's API.
+        """
+        super().__init__(
+            api_key=api_key,
+            chat_completion_parser=chat_completion_parser,
+            input_type=input_type,
+            base_url=base_url,
+            env_api_key_name=env_api_key_name,
+        )
+
+
+if __name__ == "__main__":
+    import os
+    from adalflow.core import Generator
+    from adalflow.utils import setup_env, get_logger
+
+    # Set up logging and load environment variables.
+    get_logger(enable_file=False)
+    setup_env()
+
+    # Instantiate the MistralClient; the API key will be obtained from the environment if not explicitly provided.
+    client = MistralClient(api_key=os.getenv("MISTRAL_API_KEY"), input_type="messages")
+
+    # Create the Generator using the MistralClient and specify model parameters.
+    generator = Generator(
+        model_client=client,
+        model_kwargs={
+            "model": "mistral-large-latest",
+            "temperature": 0.7,
+            "max_tokens": 2000,
+        },
+    )
+
+    # Define the prompt to be processed.
+    prompt_kwargs = {"input_str": "Explain the concept of machine learning."}
+
+    # Generate and output the response.
+    response = generator(prompt_kwargs)
+
+    if response.error:
+        print(f"[Mistral] Generator Error: {response.error}")
+    else:
+        print(f"[Mistral] Response: {response.data}")

adalflow/adalflow/components/model_client/sambanova_client.py

@@ -0,0 +1,62 @@
+from typing import Optional, Any, Callable, Literal
+from openai.types import Completion
+from adalflow.components.model_client.openai_client import OpenAIClient
+
+BASE_URL = "https://api.sambanova.ai/v1/"
+__all__ = ["SambaNovaClient"]
+
+
+class SambaNovaClient(OpenAIClient):
+    __doc__ = r"""A component wrapper for SambaNova's OpenAI-compatible API.
+
+This client extends :class:`OpenAIClient` and customizes:
+  - The API key is read from the environment variable ``SAMBANOVA_API_KEY`` if not provided explicitly.
+
+**Example usage with the AdalFlow Generator:**
+
+.. code-block:: python
+
+    from adalflow.core import Generator
+    from adalflow.components.model_client.sambanova_client import SambaNovaClient
+
+    generator = Generator(
+        model_client=SambaNovaClient(),
+        model_kwargs={
+            "model": "Meta-Llama-3.1-8B-Instruct",
+            "temperature": 0.7,
+            "top_p": 0.9,
+        },
+    )
+
+    prompt_kwargs = {
+        "input_str": "Hello from SambaNova! Can you summarize the concept of quantum computing in simple terms?"
+    }
+
+    response = generator(prompt_kwargs)
+    """
+
+    def __init__(
+        self,
+        api_key: Optional[str] = None,
+        chat_completion_parser: Callable[[Completion], Any] = None,
+        input_type: Literal["text", "messages"] = "text",
+        base_url: str = BASE_URL,
+        env_api_key_name: str = "SAMBANOVA_API_KEY",
+    ):
+        """
+        Initialize a SambaNovaClient instance.
+
+        :param api_key: (Optional) SambaNova API key. If not provided, the client attempts to read from the
+                        environment variable ``SAMBANOVA_API_KEY``.
+        :param chat_completion_parser: (Optional) A custom function to parse SambaNova responses.
+        :param input_type: Specifies the input format, either ``"text"`` or ``"messages"``. Defaults to ``"messages"``.
+        :param base_url: SambaNova API endpoint. Defaults to ``"https://api.sambanova.ai/v1/"``.
+        :param env_api_key_name: The name of the environment variable holding the API key. Defaults to ``SAMBANOVA_API_KEY``.
+        """
+        super().__init__(
+            api_key=api_key,
+            chat_completion_parser=chat_completion_parser,
+            input_type=input_type,
+            base_url=base_url,
+            env_api_key_name=env_api_key_name,
+        )