backend/app/core/ai_provider.py

@@ -7,6 +7,7 @@ backends for JSON generation used by the AI Flow Builder.
 
 import logging
 from abc import ABC, abstractmethod
+from collections.abc import AsyncIterator
 
 from app.core.config import settings
 
@@ -54,6 +55,26 @@ class AIProvider(ABC):
         """
         ...
 
+    async def generate_text_stream(
+        self,
+        system_prompt: str,
+        messages: list[dict[str, str]],
+        max_tokens: int = 4096,
+    ) -> "AsyncIterator[str]":
+        """Stream a text response token by token.
+
+        Args:
+            system_prompt: System-level instruction for the model.
+            messages: List of message dicts with "role" and "content" keys.
+            max_tokens: Maximum output tokens.
+
+        Yields:
+            Text chunks as they are generated.
+        """
+        raise NotImplementedError("Streaming not supported for this provider")
+        # Make this an async generator to satisfy type checker
+        yield ""  # pragma: no cover
+
 
 class GeminiProvider(AIProvider):
     """Google Gemini provider using the google-genai SDK."""
@@ -221,6 +242,23 @@ class AnthropicProvider(AIProvider):
         # Anthropic doesn't differentiate between JSON and text mode
         return await self.generate_json(system_prompt, messages, max_tokens)
 
+    async def generate_text_stream(
+        self,
+        system_prompt: str,
+        messages: list[dict[str, str]],
+        max_tokens: int = 4096,
+    ) -> AsyncIterator[str]:
+        client = _get_anthropic_client(self._api_key, self._timeout)
+
+        async with client.messages.stream(
+            model=self._model,
+            max_tokens=max_tokens,
+            system=system_prompt,
+            messages=messages,
+        ) as stream:
+            async for text in stream.text_stream:
+                yield text
+
 
 def get_ai_provider(model: str | None = None) -> AIProvider:
     """Factory that returns the configured AI provider.