chore(langchain-ibm): Update chat_models to support granite with Langchain

libs/ibm/langchain_ibm/chat_models.py

@@ -1,5 +1,6 @@
 """IBM watsonx.ai chat wrapper."""
 
+import ast
 import hashlib
 import json
 import logging
@@ -90,6 +91,35 @@
 logger = logging.getLogger(__name__)
 
 
+def normalize_tool_arguments(args_str: str) -> str:
+    """Ensure arguments is always a proper JSON string.
+
+    Handles:
+    - JSON string
+    - Python dict string
+    - Extra wrapping quotes like '"{...}"'
+    Args:
+        args_str: tool call args_str.
+
+    Returns:
+        The LangChain tool call arguments args_str.
+    """
+    # Try to parse as JSON
+    try:
+        parsed = json.loads(args_str)
+    except json.JSONDecodeError:
+        pass
+    else:
+        if isinstance(parsed, str):
+            json.loads(parsed)
+            return parsed
+        return args_str
+
+    # Try Python literal (e.g., "{'a': 1}")
+    obj: Any = ast.literal_eval(args_str)
+    return json.dumps(obj, ensure_ascii=False)
+
+
 def _convert_dict_to_message(_dict: Mapping[str, Any], call_id: str) -> BaseMessage:
     """Convert a dictionary to a LangChain message.
 
@@ -117,6 +147,13 @@ def _convert_dict_to_message(_dict: Mapping[str, Any], call_id: str) -> BaseMess
         if raw_tool_calls := _dict.get("tool_calls"):
             additional_kwargs["tool_calls"] = raw_tool_calls
             for raw_tool_call in raw_tool_calls:
+                ## Code change to support langgraph with A2A and graph.astream.
+                if "function" in raw_tool_call:
+                    func = raw_tool_call.get("function", {})
+                    if "arguments" in func:
+                        raw_args = raw_tool_call["function"]["arguments"]
+                        json_args_str = normalize_tool_arguments(raw_args)
+                        raw_tool_call["function"]["arguments"] = json_args_str
                 try:
                     tool_calls.append(parse_tool_call(raw_tool_call, return_id=True))
                 except Exception as e:

libs/ibm/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "pdm.backend"
 
 [project]
 name = "langchain-ibm"
-version = "0.3.19.dev1"
+version = "0.3.20"
 description = "An integration package connecting IBM watsonx.ai and LangChain"
 authors = [{ name = "IBM" }]
 license = { text = "MIT" }

libs/ibm/tests/integration_tests/test_embeddings.py

@@ -15,7 +15,7 @@
 WX_PROJECT_ID = os.environ.get("WATSONX_PROJECT_ID", "")
 
 URL = "https://us-south.ml.cloud.ibm.com"
-MODEL_ID = "ibm/slate-125m-english-rtrvr"
+MODEL_ID = "ibm/slate-125m-english-rtrvr-v2"
 
 DOCUMENTS = ["What is a generative ai?", "What is a loan and how does it works?"]
 

libs/ibm/tests/integration_tests/test_embeddings_standard.py

@@ -9,7 +9,7 @@
 
 URL = "https://us-south.ml.cloud.ibm.com"
 
-MODEL_ID = "ibm/granite-embedding-107m-multilingual"
+MODEL_ID = "ibm/granite-embedding-278m-multilingual"
 
 
 class TestWatsonxEmbeddingsStandard(EmbeddingsIntegrationTests):

libs/ibm/tests/integration_tests/test_rerank.py

@@ -14,7 +14,7 @@
 
 URL = "https://us-south.ml.cloud.ibm.com"
 
-MODEL_ID = "ibm/slate-125m-english-rtrvr"
+MODEL_ID = "ibm/slate-125m-english-rtrvr-v2"
 
 
 def test_01_rerank_init() -> None:
@@ -47,7 +47,7 @@ def test_02_rerank_documents() -> None:
 
 
 def test_02_rerank_documents_with_params() -> None:
-    params = RerankParameters(truncate_input_tokens=1)
+    params = RerankParameters(truncate_input_tokens=2)
     test_documents = [
         Document(page_content="This is a test document."),
     ]