fix(bedrock): handle additional Nexus text tool call formats

litellm/llms/bedrock/chat/converse_transformation.py

@@ -5,6 +5,7 @@ Translating between OpenAI's `/chat/completion` format and Amazon's `/converse`
 import copy
 import json
 import re
+import ast
 import time
 import types
 from typing import Any, List, Literal, Optional, Tuple, Union, cast, overload
@@ -1863,6 +1864,78 @@ class AmazonConverseConfig(BaseConfig):
                 )
             )
 
+        tool_call_match = re.search(
+            r"<tool_call>\s*(.*?)\s*</tool_call>",
+            content,
+            flags=re.DOTALL | re.IGNORECASE,
+        )
+        if tool_call_match is not None:
+            parsed_tool_call = self._parse_json_string_if_possible(
+                tool_call_match.group(1)
+            )
+            if not isinstance(parsed_tool_call, dict):
+                return None
+
+            resolved_tool_name = self._resolve_nexus_tool_name(
+                cast(Optional[str], parsed_tool_call.get("name")), tool_call_names
+            )
+            if resolved_tool_name is None:
+                return None
+
+            parsed_tool_input: Any = parsed_tool_call.get(
+                "arguments", parsed_tool_call.get("input", {})
+            )
+            if isinstance(parsed_tool_input, str):
+                parsed_tool_input = self._parse_json_string_if_possible(
+                    parsed_tool_input
+                )
+            if not isinstance(parsed_tool_input, dict):
+                return None
+
+            return ChatCompletionMessageToolCall(
+                function=Function(
+                    name=resolved_tool_name,
+                    arguments=json.dumps(parsed_tool_input),
+                )
+            )
+
+        direct_function_call_match = re.match(
+            r"^\s*([A-Za-z0-9_.-]+)\s*\((.*)\)\s*$",
+            content,
+            flags=re.DOTALL,
+        )
+        if direct_function_call_match is not None:
+            resolved_tool_name = self._resolve_nexus_tool_name(
+                direct_function_call_match.group(1), tool_call_names
+            )
+            if resolved_tool_name is None:
+                return None
+
+            raw_tool_input = direct_function_call_match.group(2).strip()
+            parsed_tool_input: Any = {}
+            if raw_tool_input:
+                if raw_tool_input.startswith("{") and raw_tool_input.endswith("}"):
+                    parsed_tool_input = self._parse_json_string_if_possible(
+                        raw_tool_input
+                    )
+                else:
+                    parsed_tool_input = {}
+                    for key, value in re.findall(
+                        r"([A-Za-z_][A-Za-z0-9_]*)\s*=\s*(\"(?:[^\"\\]|\\.)*\"|'(?:[^'\\]|\\.)*')",
+                        raw_tool_input,
+                    ):
+                        parsed_tool_input[key] = ast.literal_eval(value)
+
+            if not isinstance(parsed_tool_input, dict):
+                return None
+
+            return ChatCompletionMessageToolCall(
+                function=Function(
+                    name=resolved_tool_name,
+                    arguments=json.dumps(parsed_tool_input),
+                )
+            )
+
         tool_use_match = re.search(
             r"<tool_use>\s*(.*?)\s*</tool_use>",
             content,

tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py

@@ -329,6 +329,88 @@ def test_apply_tool_call_transformation_if_needed_with_nexus_tool_use_xml_format
     )
 
 
+def test_apply_tool_call_transformation_if_needed_with_nexus_tool_call_json_format():
+    from litellm.types.utils import Message
+
+    config = AmazonConverseConfig()
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "read_file",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "path": {"type": "string"},
+                    },
+                    "required": ["path"],
+                },
+            },
+        }
+    ]
+    message = Message(
+        role="assistant",
+        content='<tool_call>{"name":"read_file","arguments":{"path":"README.md"}}</tool_call>',
+    )
+
+    transformed_message, transformed_finish_reason = (
+        config.apply_tool_call_transformation_if_needed(
+            message=message,
+            tools=tools,
+            initial_finish_reason="stop",
+        )
+    )
+
+    assert transformed_message.content is None
+    assert transformed_finish_reason == "tool_calls"
+    assert transformed_message.tool_calls is not None
+    assert transformed_message.tool_calls[0].function.name == "read_file"
+    assert transformed_message.tool_calls[0].function.arguments == json.dumps(
+        {"path": "README.md"}
+    )
+
+
+def test_apply_tool_call_transformation_if_needed_with_direct_function_call_format():
+    from litellm.types.utils import Message
+
+    config = AmazonConverseConfig()
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "read_file",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "path": {"type": "string"},
+                    },
+                    "required": ["path"],
+                },
+            },
+        }
+    ]
+    message = Message(
+        role="assistant",
+        content='read_file(path="README.md")',
+    )
+
+    transformed_message, transformed_finish_reason = (
+        config.apply_tool_call_transformation_if_needed(
+            message=message,
+            tools=tools,
+            initial_finish_reason="stop",
+        )
+    )
+
+    assert transformed_message.content is None
+    assert transformed_finish_reason == "tool_calls"
+    assert transformed_message.tool_calls is not None
+    assert transformed_message.tool_calls[0].function.name == "read_file"
+    assert transformed_message.tool_calls[0].function.arguments == json.dumps(
+        {"path": "README.md"}
+    )
+
+
 def test_apply_tool_call_transformation_if_needed_ignores_unknown_nexus_tool_name():
     from litellm.types.utils import Message