Merge pull request #62 from daily-co/anthropic-support

Anthropic LLM service

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "dailyai"
-version = "0.0.3"
+version = "0.0.3.1"
 description = "An open source framework for real-time, multi-modal, conversational AI applications"
 license = { text = "BSD 2-Clause License" }
 readme = "README.md"
@@ -21,6 +21,7 @@ classifiers = [
 ]
 dependencies = [
     "aiohttp",
+    "anthropic",
     "azure-cognitiveservices-speech",
     "daily-python",
     "fal",

src/dailyai/services/anthropic_llm_service.py

@@ -0,0 +1,35 @@
+import asyncio
+import os
+from typing import AsyncGenerator
+from anthropic import AsyncAnthropic
+from dailyai.pipeline.frames import Frame, LLMMessagesQueueFrame, TextFrame
+
+from dailyai.services.ai_services import LLMService
+
+
+class AnthropicLLMService(LLMService):
+
+    def __init__(self, api_key, model="claude-3-opus-20240229", max_tokens=1024):
+        super().__init__()
+        self.client = AsyncAnthropic(api_key=api_key)
+        self.model = model
+        self.max_tokens = max_tokens
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if not isinstance(frame, LLMMessagesQueueFrame):
+            yield frame
+
+        stream = await self.client.messages.create(
+            max_tokens=self.max_tokens,
+            messages=[
+                {
+                    "role": "user",
+                    "content": "Hello, Claude",
+                }
+            ],
+            model=self.model,
+            stream=True,
+        )
+        async for event in stream:
+            if event.type == "content_block_delta":
+                yield TextFrame(event.delta.text)