Adjusted anthropic import

paperqa/__init__.py

@@ -7,6 +7,7 @@
     OpenAIEmbeddingModel,
     LangchainLLMModel,
     OpenAILLMModel,
+    AnthropicLLMModel,
     LlamaEmbeddingModel,
     NumpyVectorStore,
     LangchainVectorStore,
@@ -26,6 +27,7 @@
     "EmbeddingModel",
     "OpenAIEmbeddingModel",
     "OpenAILLMModel",
+    "AnthropicLLMModel",
     "LangchainLLMModel",
     "LlamaEmbeddingModel",
     "SentenceTransformerEmbeddingModel",

paperqa/llms.py

@@ -373,18 +373,43 @@ def set_model_name(cls, data: Any) -> Any:
 
         async def achat(self, client: Any, messages: list[dict[str, str]]) -> str:
             aclient = self._check_client(client)
-            completion = await aclient.messages.create(
-                messages=messages, **process_llm_config(self.config, "max_tokens")
+            # filter out system
+            sys_message = next(
+                (m["content"] for m in messages if m["role"] == "system"), None
             )
+            # BECAUISE THEY DO NOT USE NONE TO INDICATE SENTINEL
+            # LIKE ANY SANE PERSON
+            if sys_message:
+                completion = await aclient.messages.create(
+                    system=sys_message,
+                    messages=[m for m in messages if m["role"] != "system"],
+                    **process_llm_config(self.config, "max_tokens"),
+                )
+            else:
+                completion = await aclient.messages.create(
+                    messages=[m for m in messages if m["role"] != "system"],
+                    **process_llm_config(self.config, "max_tokens"),
+                )
             return completion.content or ""
 
         async def achat_iter(self, client: Any, messages: list[dict[str, str]]) -> Any:
             aclient = self._check_client(client)
-            completion = await aclient.messages.create(
-                messages=messages,
-                **process_llm_config(self.config, "max_tokens"),
-                stream=True,
+            sys_message = next(
+                (m["content"] for m in messages if m["role"] == "system"), None
             )
+            if sys_message:
+                completion = await aclient.messages.create(
+                    stream=True,
+                    system=sys_message,
+                    messages=[m for m in messages if m["role"] != "system"],
+                    **process_llm_config(self.config, "max_tokens"),
+                )
+            else:
+                completion = await aclient.messages.create(
+                    stream=True,
+                    messages=[m for m in messages if m["role"] != "system"],
+                    **process_llm_config(self.config, "max_tokens"),
+                )
             async for event in completion:
                 if isinstance(event, ContentBlockDeltaEvent):
                     yield event.delta.text

paperqa/version.py

@@ -1 +1 @@
-__version__ = "4.0.0-pre.10"
+__version__ = "4.0.0-pre.11"