fix: adapt to Ollama client 0.4.0

integrations/ollama/pyproject.toml

@@ -19,15 +19,14 @@ classifiers = [
     "License :: OSI Approved :: Apache Software License",
     "Development Status :: 4 - Beta",
     "Programming Language :: Python",
-    "Programming Language :: Python :: 3.8",
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Programming Language :: Python :: Implementation :: CPython",
     "Programming Language :: Python :: Implementation :: PyPy",
 ]
-dependencies = ["haystack-ai", "ollama"]
+dependencies = ["haystack-ai", "ollama>=0.4.0"]
 
 [project.urls]
 Documentation = "https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/ollama#readme"
@@ -63,7 +62,7 @@ cov-retry = ["test-cov-retry", "cov-report"]
 docs = ["pydoc-markdown pydoc/config.yml"]
 
 [[tool.hatch.envs.all.matrix]]
-python = ["3.8", "3.9", "3.10", "3.11", "3.12"]
+python = ["3.9", "3.10", "3.11", "3.12"]
 
 
 [tool.hatch.envs.lint]

integrations/ollama/src/haystack_integrations/components/embedders/ollama/__init__.py

@@ -1,4 +1,4 @@
 from .document_embedder import OllamaDocumentEmbedder
 from .text_embedder import OllamaTextEmbedder
 
-__all__ = ["OllamaTextEmbedder", "OllamaDocumentEmbedder"]
+__all__ = ["OllamaDocumentEmbedder", "OllamaTextEmbedder"]

integrations/ollama/src/haystack_integrations/components/embedders/ollama/document_embedder.py

@@ -100,7 +100,7 @@ def _embed_batch(
             range(0, len(texts_to_embed), batch_size), disable=not self.progress_bar, desc="Calculating embeddings"
         ):
             batch = texts_to_embed[i]  # Single batch only
-            result = self._client.embeddings(model=self.model, prompt=batch, options=generation_kwargs)
+            result = self._client.embeddings(model=self.model, prompt=batch, options=generation_kwargs).model_dump()
             all_embeddings.append(result["embedding"])
 
         meta["model"] = self.model
@@ -122,7 +122,7 @@ def run(self, documents: List[Document], generation_kwargs: Optional[Dict[str, A
             - `documents`: Documents with embedding information attached
             - `meta`: The metadata collected during the embedding process
         """
-        if not isinstance(documents, list) or documents and not isinstance(documents[0], Document):
+        if not isinstance(documents, list) or (documents and not isinstance(documents[0], Document)):
             msg = (
                 "OllamaDocumentEmbedder expects a list of Documents as input."
                 "In case you want to embed a list of strings, please use the OllamaTextEmbedder."

integrations/ollama/src/haystack_integrations/components/embedders/ollama/text_embedder.py

@@ -62,7 +62,7 @@ def run(self, text: str, generation_kwargs: Optional[Dict[str, Any]] = None):
             - `embedding`: The computed embeddings
             - `meta`: The metadata collected during the embedding process
         """
-        result = self._client.embeddings(model=self.model, prompt=text, options=generation_kwargs)
+        result = self._client.embeddings(model=self.model, prompt=text, options=generation_kwargs).model_dump()
         result["meta"] = {"model": self.model}
 
         return result

integrations/ollama/src/haystack_integrations/components/generators/ollama/__init__.py

@@ -1,4 +1,4 @@
 from .chat.chat_generator import OllamaChatGenerator
 from .generator import OllamaGenerator
 
-__all__ = ["OllamaGenerator", "OllamaChatGenerator"]
+__all__ = ["OllamaChatGenerator", "OllamaGenerator"]

integrations/ollama/src/haystack_integrations/components/generators/ollama/chat/chat_generator.py

@@ -4,7 +4,7 @@
 from haystack.dataclasses import ChatMessage, StreamingChunk
 from haystack.utils.callable_serialization import deserialize_callable, serialize_callable
 
-from ollama import Client
+from ollama import ChatResponse, Client
 
 
 @component
@@ -111,12 +111,13 @@ def from_dict(cls, data: Dict[str, Any]) -> "OllamaChatGenerator":
     def _message_to_dict(self, message: ChatMessage) -> Dict[str, str]:
         return {"role": message.role.value, "content": message.content}
 
-    def _build_message_from_ollama_response(self, ollama_response: Dict[str, Any]) -> ChatMessage:
+    def _build_message_from_ollama_response(self, ollama_response: ChatResponse) -> ChatMessage:
         """
         Converts the non-streaming response from the Ollama API to a ChatMessage.
         """
-        message = ChatMessage.from_assistant(content=ollama_response["message"]["content"])
-        message.meta.update({key: value for key, value in ollama_response.items() if key != "message"})
+        response_dict = ollama_response.model_dump()
+        message = ChatMessage.from_assistant(content=response_dict["message"]["content"])
+        message.meta.update({key: value for key, value in response_dict.items() if key != "message"})
         return message
 
     def _convert_to_streaming_response(self, chunks: List[StreamingChunk]) -> Dict[str, List[Any]]:
@@ -133,9 +134,11 @@ def _build_chunk(self, chunk_response: Any) -> StreamingChunk:
         """
         Converts the response from the Ollama API to a StreamingChunk.
         """
-        content = chunk_response["message"]["content"]
-        meta = {key: value for key, value in chunk_response.items() if key != "message"}
-        meta["role"] = chunk_response["message"]["role"]
+        chunk_response_dict = chunk_response.model_dump()
+
+        content = chunk_response_dict["message"]["content"]
+        meta = {key: value for key, value in chunk_response_dict.items() if key != "message"}
+        meta["role"] = chunk_response_dict["message"]["role"]
 
         chunk_message = StreamingChunk(content, meta)
         return chunk_message

integrations/ollama/src/haystack_integrations/components/generators/ollama/generator.py

@@ -4,7 +4,7 @@
 from haystack.dataclasses import StreamingChunk
 from haystack.utils.callable_serialization import deserialize_callable, serialize_callable
 
-from ollama import Client
+from ollama import Client, GenerateResponse
 
 
 @component
@@ -118,15 +118,14 @@ def from_dict(cls, data: Dict[str, Any]) -> "OllamaGenerator":
             data["init_parameters"]["streaming_callback"] = deserialize_callable(serialized_callback_handler)
         return default_from_dict(cls, data)
 
-    def _convert_to_response(self, ollama_response: Dict[str, Any]) -> Dict[str, List[Any]]:
+    def _convert_to_response(self, ollama_response: GenerateResponse) -> Dict[str, List[Any]]:
         """
         Converts a response from the Ollama API to the required Haystack format.
         """
+        reply = ollama_response.response
+        meta = {key: value for key, value in ollama_response.model_dump().items() if key != "response"}
 
-        replies = [ollama_response["response"]]
-        meta = {key: value for key, value in ollama_response.items() if key != "response"}
-
-        return {"replies": replies, "meta": [meta]}
+        return {"replies": [reply], "meta": [meta]}
 
     def _convert_to_streaming_response(self, chunks: List[StreamingChunk]) -> Dict[str, List[Any]]:
         """
@@ -154,8 +153,9 @@ def _build_chunk(self, chunk_response: Any) -> StreamingChunk:
         """
         Converts the response from the Ollama API to a StreamingChunk.
         """
-        content = chunk_response["response"]
-        meta = {key: value for key, value in chunk_response.items() if key != "response"}
+        chunk_response_dict = chunk_response.model_dump()
+        content = chunk_response_dict["response"]
+        meta = {key: value for key, value in chunk_response_dict.items() if key != "response"}
 
         chunk_message = StreamingChunk(content, meta)
         return chunk_message

integrations/ollama/tests/test_chat_generator.py

@@ -4,7 +4,7 @@
 import pytest
 from haystack.components.generators.utils import print_streaming_chunk
 from haystack.dataclasses import ChatMessage, ChatRole
-from ollama._types import ResponseError
+from ollama._types import ChatResponse, ResponseError
 
 from haystack_integrations.components.generators.ollama import OllamaChatGenerator
 
@@ -86,18 +86,18 @@ def test_from_dict(self):
     def test_build_message_from_ollama_response(self):
         model = "some_model"
 
-        ollama_response = {
-            "model": model,
-            "created_at": "2023-12-12T14:13:43.416799Z",
-            "message": {"role": "assistant", "content": "Hello! How are you today?"},
-            "done": True,
-            "total_duration": 5191566416,
-            "load_duration": 2154458,
-            "prompt_eval_count": 26,
-            "prompt_eval_duration": 383809000,
-            "eval_count": 298,
-            "eval_duration": 4799921000,
-        }
+        ollama_response = ChatResponse(
+            model=model,
+            created_at="2023-12-12T14:13:43.416799Z",
+            message={"role": "assistant", "content": "Hello! How are you today?"},
+            done=True,
+            total_duration=5191566416,
+            load_duration=2154458,
+            prompt_eval_count=26,
+            prompt_eval_duration=383809000,
+            eval_count=298,
+            eval_duration=4799921000,
+        )
 
         observed = OllamaChatGenerator(model=model)._build_message_from_ollama_response(ollama_response)