Merge pull request #899 from parea-ai/feat-anthropic-instructor

feat: anthropic instructor integration

parea/client.py

@@ -93,20 +93,23 @@ def wrap_openai_client(self, client: "OpenAI", integration: Optional[str] = None
         BetaWrappers(client).init()
 
         if integration:
-            self._client.add_integration(integration)
-
-        if integration == "instructor":
-            from parea.utils.trace_integrations.instructor import instrument_instructor_validation_errors
-
-            instrument_instructor_validation_errors()
+            self._add_integration(integration)
 
     def wrap_anthropic_client(self, client: "Anthropic", integration: Optional[str] = None) -> None:
         from parea.wrapper.anthropic.anthropic import AnthropicWrapper
 
         AnthropicWrapper().init(log=logger_all_possible, cache=self.cache, client=client)
 
         if integration:
-            self._client.add_integration(integration)
+            self._add_integration(integration)
+
+    def _add_integration(self, integration: str) -> None:
+        self._client.add_integration(integration)
+
+        if integration == "instructor":
+            from parea.utils.trace_integrations.instructor import instrument_instructor_validation_errors
+
+            instrument_instructor_validation_errors()
 
     def auto_trace_openai_clients(self, integration: Optional[str]) -> None:
         import openai

parea/wrapper/wrapper.py

@@ -87,7 +87,12 @@ def _init_trace(self, kwargs) -> Tuple[str, datetime, contextvars.Token]:
         if template_inputs := kwargs.pop("template_inputs", None):
             for m in kwargs.get("messages", []):
                 if isinstance(m, dict) and "content" in m:
-                    m["content"] = safe_format_template_to_prompt(m["content"], **template_inputs)
+                    if isinstance(m["content"], str):
+                        m["content"] = safe_format_template_to_prompt(m["content"], **template_inputs)
+                    elif isinstance(m["content"], list):
+                        for i, item in enumerate(m["content"]):
+                            if isinstance(item, dict) and "text" in item:
+                                m["content"][i]["text"] = safe_format_template_to_prompt(item["text"], **template_inputs)
 
         depth = len(new_trace_context) - 1
         root_trace_id = new_trace_context[0]

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "poetry.core.masonry.api"
 [tool.poetry]
 name = "parea-ai"
 packages = [{ include = "parea" }]
-version = "0.2.159"
+version = "0.2.160"
 description = "Parea python sdk"
 readme = "README.md"
 authors = ["joel-parea-ai <[email protected]>"]