Add Ollama Text Embedder

integrations/ollama/src/ollama_haystack/__init__.py

@@ -3,6 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 from ollama_haystack.chat.chat_generator import OllamaChatGenerator
+from ollama_haystack.embeddings.text_embedder import OllamaTextEmbedder
 from ollama_haystack.generator import OllamaGenerator
 
-__all__ = ["OllamaGenerator", "OllamaChatGenerator"]
+__all__ = ["OllamaGenerator", "OllamaChatGenerator", "OllamaTextEmbedder"]

integrations/ollama/src/ollama_haystack/embeddings/text_embedder.py

@@ -0,0 +1,58 @@
+from typing import Any, Dict, List, Optional
+
+import requests
+from haystack import component
+
+
+@component
+class OllamaTextEmbedder:
+    def __init__(
+        self,
+        model: str = "orca-mini",
+        url: str = "http://localhost:11434/api/embeddings",
+        generation_kwargs: Optional[Dict[str, Any]] = None,
+        timeout: int = 120,
+    ):
+        """
+        :param model: The name of the model to use. The model should be available in the running Ollama instance.
+            Default is "orca-mini".
+        :param url: The URL of the chat endpoint of a running Ollama instance.
+            Default is "http://localhost:11434/api/embeddings".
+        :param generation_kwargs: Optional arguments to pass to the Ollama generation endpoint, such as temperature,
+            top_p, and others. See the available arguments in
+            [Ollama docs](https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values).
+        :param timeout: The number of seconds before throwing a timeout error from the Ollama API.
+            Default is 120 seconds.
+        """
+        self.timeout = timeout
+        self.generation_kwargs = generation_kwargs or {}
+        self.url = url
+        self.model = model
+
+    def _create_json_payload(self, text: str, generation_kwargs: Optional[Dict[str, Any]]) -> Dict[str, Any]:
+        """
+        Returns A dictionary of JSON arguments for a POST request to an Ollama service
+          :param text: Text that is to be converted to an embedding
+          :param generation_kwargs:
+          :return: A dictionary of arguments for a POST request to an Ollama service
+        """
+        return {"model": self.model, "prompt": text, "options": {**self.generation_kwargs, **(generation_kwargs or {})}}
+
+    @component.output_types(embedding=List[float])
+    def run(self, text: str, generation_kwargs: Optional[Dict[str, Any]] = None):
+        """
+        Run an Ollama Model on a given chat history.
+        :param text: Text to be converted to an embedding.
+        :param generation_kwargs: Optional arguments to pass to the Ollama generation endpoint, such as temperature,
+            top_p, etc. See the
+            [Ollama docs](https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values).
+        :return: A dictionary with the key "embedding" and a list of floats as the value
+        """
+
+        payload = self._create_json_payload(text, generation_kwargs)
+
+        response = requests.post(url=self.url, json=payload, timeout=self.timeout)
+
+        response.raise_for_status()
+
+        return response.json()

integrations/ollama/tests/test_text_embedder.py

@@ -0,0 +1,32 @@
+from ollama_haystack import OllamaTextEmbedder
+
+
+class TestOllamaTextEmbedder:
+    def test_init_defaults(self):
+        embedder = OllamaTextEmbedder()
+
+        assert embedder.timeout == 120
+        assert embedder.generation_kwargs == {}
+        assert embedder.url == "http://localhost:11434/api/embeddings"
+        assert embedder.model == "orca-mini"
+
+    def test_init(self):
+        embedder = OllamaTextEmbedder(
+            model="llama2",
+            url="http://my-custom-endpoint:11434/api/embeddings",
+            generation_kwargs={"temperature": 0.5},
+            timeout=3000,
+        )
+
+        assert embedder.timeout == 3000
+        assert embedder.generation_kwargs == {"temperature": 0.5}
+        assert embedder.url == "http://my-custom-endpoint:11434/api/embeddings"
+        assert embedder.model == "llama2"
+
+    def test_run(self):
+        embedder = OllamaTextEmbedder()
+
+        reply = embedder.run("hello")
+
+        assert isinstance(reply, dict)
+        assert all(isinstance(element, float) for element in reply["embedding"])