[ENH] Add support for Ollama assistants

docs/examples/gallery_streaming.py

@@ -31,6 +31,14 @@
 #       - [ragna.assistants.Gpt4][]
 #     - [llamafile](https://github.com/Mozilla-Ocho/llamafile)
 #       - [ragna.assistants.LlamafileAssistant][]
+#     - [Ollama](https://ollama.com/)
+#       - [ragna.assistants.OllamaGemma2B][]
+#       - [ragna.assistants.OllamaLlama2][]
+#       - [ragna.assistants.OllamaLlava][]
+#       - [ragna.assistants.OllamaMistral][]
+#       - [ragna.assistants.OllamaMixtral][]
+#       - [ragna.assistants.OllamaOrcaMini][]
+#       - [ragna.assistants.OllamaPhi2][]
 
 from ragna import assistants
 

docs/tutorials/gallery_python_api.py

@@ -87,6 +87,14 @@
 #       - [ragna.assistants.Jurassic2Ultra][]
 #     - [llamafile](https://github.com/Mozilla-Ocho/llamafile)
 #       - [ragna.assistants.LlamafileAssistant][]
+#     - [Ollama](https://ollama.com/)
+#       - [ragna.assistants.OllamaGemma2B][]
+#       - [ragna.assistants.OllamaLlama2][]
+#       - [ragna.assistants.OllamaLlava][]
+#       - [ragna.assistants.OllamaMistral][]
+#       - [ragna.assistants.OllamaMixtral][]
+#       - [ragna.assistants.OllamaOrcaMini][]
+#       - [ragna.assistants.OllamaPhi2][]
 #
 #     !!! note
 #

ragna/assistants/__init__.py

@@ -6,6 +6,13 @@
     "CommandLight",
     "GeminiPro",
     "GeminiUltra",
+    "OllamaGemma2B",
+    "OllamaPhi2",
+    "OllamaLlama2",
+    "OllamaLlava",
+    "OllamaMistral",
+    "OllamaMixtral",
+    "OllamaOrcaMini",
     "Gpt35Turbo16k",
     "Gpt4",
     "Jurassic2Ultra",
@@ -19,6 +26,15 @@
 from ._demo import RagnaDemoAssistant
 from ._google import GeminiPro, GeminiUltra
 from ._llamafile import LlamafileAssistant
+from ._ollama import (
+    OllamaGemma2B,
+    OllamaLlama2,
+    OllamaLlava,
+    OllamaMistral,
+    OllamaMixtral,
+    OllamaOrcaMini,
+    OllamaPhi2,
+)
 from ._openai import Gpt4, Gpt35Turbo16k
 
 # isort: split

ragna/assistants/_ai21labs.py

@@ -7,6 +7,7 @@
 
 class Ai21LabsAssistant(HttpApiAssistant):
     _API_KEY_ENV_VAR = "AI21_API_KEY"
+    _STREAMING_PROTOCOL = None
     _MODEL_TYPE: str
 
     @classmethod
@@ -27,7 +28,8 @@ async def answer(
         # See https://docs.ai21.com/reference/j2-chat-api#chat-api-parameters
         # See https://docs.ai21.com/reference/j2-complete-api-ref#api-parameters
         # See https://docs.ai21.com/reference/j2-chat-api#understanding-the-response
-        response = await self._client.post(
+        async for data in self._call_api(
+            "POST",
             f"https://api.ai21.com/studio/v1/j2-{self._MODEL_TYPE}/chat",
             headers={
                 "accept": "application/json",
@@ -46,10 +48,8 @@ async def answer(
                 ],
                 "system": self._make_system_content(sources),
             },
-        )
-        await self._assert_api_call_is_success(response)
-
-        yield cast(str, response.json()["outputs"][0]["text"])
+        ):
+            yield cast(str, data["outputs"][0]["text"])
 
 
 # The Jurassic2Mid assistant receives a 500 internal service error from the remote

ragna/assistants/_anthropic.py

@@ -2,11 +2,12 @@
 
 from ragna.core import PackageRequirement, RagnaException, Requirement, Source
 
-from ._http_api import HttpApiAssistant
+from ._http_api import HttpApiAssistant, HttpStreamingProtocol
 
 
 class AnthropicAssistant(HttpApiAssistant):
     _API_KEY_ENV_VAR = "ANTHROPIC_API_KEY"
+    _STREAMING_PROTOCOL = HttpStreamingProtocol.SSE
     _MODEL: str
 
     @classmethod
@@ -40,7 +41,7 @@ async def answer(
     ) -> AsyncIterator[str]:
         # See https://docs.anthropic.com/claude/reference/messages_post
         # See https://docs.anthropic.com/claude/reference/streaming
-        async for data in self._stream_sse(
+        async for data in self._call_api(
             "POST",
             "https://api.anthropic.com/v1/messages",
             headers={

ragna/assistants/_cohere.py

@@ -2,11 +2,12 @@
 
 from ragna.core import RagnaException, Source
 
-from ._http_api import HttpApiAssistant
+from ._http_api import HttpApiAssistant, HttpStreamingProtocol
 
 
 class CohereAssistant(HttpApiAssistant):
     _API_KEY_ENV_VAR = "COHERE_API_KEY"
+    _STREAMING_PROTOCOL = HttpStreamingProtocol.JSONL
     _MODEL: str
 
     @classmethod
@@ -29,7 +30,7 @@ async def answer(
         # See https://docs.cohere.com/docs/cochat-beta
         # See https://docs.cohere.com/reference/chat
         # See https://docs.cohere.com/docs/retrieval-augmented-generation-rag
-        async for event in self._stream_jsonl(
+        async for event in self._call_api(
             "POST",
             "https://api.cohere.ai/v1/chat",
             headers={

ragna/assistants/_google.py

@@ -1,38 +1,15 @@
 from typing import AsyncIterator
 
-from ragna._compat import anext
-from ragna.core import PackageRequirement, Requirement, Source
+from ragna.core import Source
 
-from ._http_api import HttpApiAssistant
-
-
-# ijson does not support reading from an (async) iterator, but only from file-like
-# objects, i.e. https://docs.python.org/3/tutorial/inputoutput.html#methods-of-file-objects.
-# See https://github.com/ICRAR/ijson/issues/44 for details.
-# ijson actually doesn't care about most of the file interface and only requires the
-# read() method to be present.
-class AsyncIteratorReader:
-    def __init__(self, ait: AsyncIterator[bytes]) -> None:
-        self._ait = ait
-
-    async def read(self, n: int) -> bytes:
-        # n is usually used to indicate how many bytes to read, but since we want to
-        # return a chunk as soon as it is available, we ignore the value of n. The only
-        # exception is n == 0, which is used by ijson to probe the return type and
-        # set up decoding.
-        if n == 0:
-            return b""
-        return await anext(self._ait, b"")  # type: ignore[call-arg]
+from ._http_api import HttpApiAssistant, HttpStreamingProtocol
 
 
 class GoogleAssistant(HttpApiAssistant):
     _API_KEY_ENV_VAR = "GOOGLE_API_KEY"
+    _STREAMING_PROTOCOL = HttpStreamingProtocol.JSON
     _MODEL: str
 
-    @classmethod
-    def _extra_requirements(cls) -> list[Requirement]:
-        return [PackageRequirement("ijson")]
-
     @classmethod
     def display_name(cls) -> str:
         return f"Google/{cls._MODEL}"
@@ -51,9 +28,7 @@ def _instructize_prompt(self, prompt: str, sources: list[Source]) -> str:
     async def answer(
         self, prompt: str, sources: list[Source], *, max_new_tokens: int = 256
     ) -> AsyncIterator[str]:
-        import ijson
-
-        async with self._client.stream(
+        async for chunk in self._call_api(
             "POST",
             f"https://generativelanguage.googleapis.com/v1beta/models/{self._MODEL}:streamGenerateContent",
             params={"key": self._api_key},
@@ -64,7 +39,10 @@ async def answer(
                 ],
                 # https://ai.google.dev/docs/safety_setting_gemini
                 "safetySettings": [
-                    {"category": f"HARM_CATEGORY_{category}", "threshold": "BLOCK_NONE"}
+                    {
+                        "category": f"HARM_CATEGORY_{category}",
+                        "threshold": "BLOCK_NONE",
+                    }
                     for category in [
                         "HARASSMENT",
                         "HATE_SPEECH",
@@ -78,14 +56,9 @@ async def answer(
                     "maxOutputTokens": max_new_tokens,
                 },
             },
-        ) as response:
-            await self._assert_api_call_is_success(response)
-
-            async for chunk in ijson.items(
-                AsyncIteratorReader(response.aiter_bytes(1024)),
-                "item.candidates.item.content.parts.item.text",
-            ):
-                yield chunk
+            parse_kwargs=dict(item="item.candidates.item.content.parts.item.text"),
+        ):
+            yield chunk
 
 
 class GeminiPro(GoogleAssistant):