feat(genie): add TogetherGenie for TogetherAI integration

pyproject.toml

@@ -114,6 +114,7 @@ milvus = ["pymilvus>=2.1.0"]
 
 # Optional dependencies for the genie
 genie = ["pydantic>=2.0.0", "google-genai>=1.0.0"]
+togetherai = ["pydantic>=2.0.0", "together>=0.3.0"]
 
 # All dependencies
 all = [
@@ -155,6 +156,7 @@ all = [
     "catsu>=0.0.1",
     "litellm>=1.0.0",
     "datasets>=1.14.0",
+    "together>=0.3.0",
 ]
 dev = [
     "datasets>=1.14.0",

src/chonkie/genie/__init__.py

@@ -6,6 +6,7 @@
 from .gemini import GeminiGenie
 from .groq import GroqGenie
 from .openai import OpenAIGenie
+from .together import TogetherGenie
 
 # Add all genie classes to __all__
 __all__ = [
@@ -15,4 +16,5 @@
     "GeminiGenie",
     "GroqGenie",
     "OpenAIGenie",
+    "TogetherGenie",
 ]

src/chonkie/genie/together.py

@@ -0,0 +1,101 @@
+"""TogetherGenie for TogetherAI's models."""
+import importlib.util as importutil
+import os
+from typing import TYPE_CHECKING, Any, Dict, Optional
+
+from .base import BaseGenie
+
+class TogetherGenie(BaseGenie):
+    """Genie using TogetherAI's hosted models (OpenAI-compatible style)."""
+
+    SUPPORTED_JSON_MODELS = {
+        "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
+        "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
+        "meta-llama/Llama-3.2-3B-Instruct-Turbo",
+        "meta-llama/Llama-3.3-70B-Instruct-Turbo",
+        "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
+        "meta-llama/Llama-4-Scout-17B-16E-Instruct",
+        "deepseek-ai/DeepSeek-V3",
+        "Qwen/Qwen3-235B-A22B-fp8-tput",
+        "Qwen/Qwen2.5-VL-72B-Instruct",
+    }
+
+    def __init__(
+        self,
+        model: str = "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
+        api_key: Optional[str] = None,
+    ):
+        """Initialize the TogetherGenie class.
+
+        Args:
+            model (str): The TogetherAI model to use.
+            api_key (Optional[str]): The API key to use. Defaults to the environment variable TOGETHER_API_KEY.
+        """
+        super().__init__()
+        try:
+            from pydantic import BaseModel
+            from together import Together
+        except ImportError as e:
+            raise ImportError(
+                "TogetherGenie requires `together` and `pydantic`. Install with `pip install chonkie[togetherai]`"
+            ) from e
+
+        self.api_key = api_key or os.environ.get("TOGETHER_API_KEY")
+        if not self.api_key:
+            raise ValueError(
+                "TogetherGenie requires an API key. Pass `api_key` or set TOGETHER_API_KEY env var."
+            )
+
+        self.model = model
+        self.client = Together(api_key=self.api_key)
+
+    def generate(self, prompt: str) -> str:
+        """Generate a basic chat completion."""
+        response = self.client.chat.completions.create(
+            model=self.model,
+            messages=[{"role": "user", "content": prompt}],
+        )
+        content = response.choices[0].message.content
+        if content is None:
+            raise ValueError("TogetherAI returned empty response content.")
+        return content
+
+    def generate_json(self, prompt: str, schema: "BaseModel") -> Dict[str, Any]:
+        """Generate a JSON-formatted response using Together's structured output feature.
+
+        Note:
+            This only works with Together models that support JSON mode.
+            See: https://docs.together.ai/docs/json-mode
+
+        """     
+        if self.model not in self.SUPPORTED_JSON_MODELS:
+            raise ValueError(f"Model `{self.model}` does not support JSON mode.")
+
+        response = self.client.chat.completions.create(
+            model=self.model,
+            messages=[
+                {
+                    "role": "user",
+                    "content": prompt,
+                },
+            ],
+            response_format={
+                "type": "json_object",
+                "schema": schema.model_json_schema(),
+            },
+        )
+
+        content = response.choices[0].message.content
+        if content is None:
+            raise ValueError("TogetherAI returned no content in the JSON response.")
+
+        return schema.model_validate_json(content).model_dump()
+
+    def _is_available(self) -> bool:
+        return (
+            importutil.find_spec("together") is not None
+            and importutil.find_spec("pydantic") is not None
+        )
+
+    def __repr__(self) -> str:
+        return f"TogetherGenie(model={self.model})"