Merge pull request #168 from Chainlit/willy/lc-reasoning

feat: add reasoning token support to lc

Author: willydouhard

literalai/callback/langchain_callback.py

@@ -92,7 +92,33 @@ def _convert_message_dict(
             if function_call:
                 msg["function_call"] = function_call
             else:
-                msg["content"] = kwargs.get("content", "")
+                content = kwargs.get("content")
+                if isinstance(content, list):
+                    tool_calls = []
+                    content_parts = []
+                    for item in content:
+                        if item.get("type") == "tool_use":
+                            tool_calls.append(
+                                {
+                                    "id": item.get("id"),
+                                    "type": "function",
+                                    "function": {
+                                        "name": item.get("name"),
+                                        "arguments": item.get("input"),
+                                    },
+                                }
+                            )
+                        elif item.get("type") == "text":
+                            content_parts.append(
+                                {"type": "text", "text": item.get("text")}
+                            )
+
+                    if tool_calls:
+                        msg["tool_calls"] = tool_calls
+                    if content_parts:
+                        msg["content"] = content_parts  # type: ignore
+                else:
+                    msg["content"] = content  # type: ignore
 
             if tool_calls:
                 msg["tool_calls"] = tool_calls
@@ -123,7 +149,34 @@ def _convert_message(
             if function_call:
                 msg["function_call"] = function_call
             else:
-                msg["content"] = message.content  # type: ignore
+                if isinstance(message.content, list):
+                    tool_calls = []
+                    content_parts = []
+                    for item in message.content:
+                        if isinstance(item, str):
+                            continue
+                        if item.get("type") == "tool_use":
+                            tool_calls.append(
+                                {
+                                    "id": item.get("id"),
+                                    "type": "function",
+                                    "function": {
+                                        "name": item.get("name"),
+                                        "arguments": item.get("input"),
+                                    },
+                                }
+                            )
+                        elif item.get("type") == "text":
+                            content_parts.append(
+                                {"type": "text", "text": item.get("text")}
+                            )
+
+                    if tool_calls:
+                        msg["tool_calls"] = tool_calls
+                    if content_parts:
+                        msg["content"] = content_parts  # type: ignore
+                else:
+                    msg["content"] = message.content  # type: ignore
 
             if tool_calls:
                 msg["tool_calls"] = tool_calls
@@ -201,7 +254,12 @@ def _build_llm_settings(
                     {"type": "function", "function": f} for f in settings["functions"]
                 ]
             if "tools" in settings:
-                tools = settings["tools"]
+                tools = [
+                    {"type": "function", "function": t}
+                    if t.get("type") != "function"
+                    else t
+                    for t in settings["tools"]
+                ]
             return provider, model, tools, settings
 
     DEFAULT_TO_IGNORE = [
@@ -411,7 +469,9 @@ def _start_trace(self, run: Run) -> None:
             )
             step.tags = run.tags
             step.metadata = run.metadata
-            step.input = self.process_content(run.inputs)
+
+            if step.type != "llm":
+                step.input = self.process_content(run.inputs)
 
             self.steps[str(run.id)] = step
 
@@ -484,7 +544,6 @@ def _on_run_update(self, run: Run) -> None:
                             if v is not None
                         }
 
-                    current_step.output = message_completion
                 else:
                     completion_start = self.completion_generations[str(run.id)]
                     duration = time.time() - completion_start["start"]
@@ -509,7 +568,6 @@ def _on_run_update(self, run: Run) -> None:
                         output_token_count=usage_metadata.get("output_tokens"),
                         token_count=usage_metadata.get("total_tokens"),
                     )
-                    current_step.output = {"content": completion}
 
                 if current_step:
                     if current_step.metadata is None:
@@ -521,7 +579,8 @@ def _on_run_update(self, run: Run) -> None:
             outputs = run.outputs or {}
 
             if current_step:
-                current_step.output = self.process_content(outputs)
+                if current_step.type != "llm":
+                    current_step.output = self.process_content(outputs)
                 current_step.end()
 
         def _on_error(self, error: BaseException, *, run_id: "UUID", **kwargs: Any):