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fix(ollama): robustly parse single-quoted JSON in tool calls (#32109)
**Description:** This PR makes argument parsing for Ollama tool calls more robust. Some LLMs—including Ollama—may return arguments as Python-style dictionaries with single quotes (e.g., `{'a': 1}`), which are not valid JSON and previously caused parsing to fail. The updated `_parse_json_string` method in `langchain_ollama.chat_models` now attempts standard JSON parsing and, if that fails, falls back to `ast.literal_eval` for safe evaluation of Python-style dictionaries. This improves interoperability with LLMs and fixes a common usability issue for tool-based agents. **Issue:** Closes #30910 **Dependencies:** None **Tests:** - Added new unit tests for double-quoted JSON, single-quoted dicts, mixed quoting, and malformed/failure cases. - All tests pass locally, including new coverage for single-quoted inputs. **Notes:** - No breaking changes. - No new dependencies introduced. - Code is formatted and linted (`ruff format`, `ruff check`). - If maintainers have suggestions for further improvements, I’m happy to revise! Thank you for maintaining LangChain! Looking forward to your feedback.
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@ -5,7 +5,7 @@ build-backend = "pdm.backend"
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[project]
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authors = []
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license = { text = "MIT" }
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requires-python = ">=3.9"
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requires-python = ">=3.9, <4.0"
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dependencies = [
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"langchain-core<1.0.0,>=0.3.66",
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"langchain-text-splitters<1.0.0,>=0.3.8",
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@ -2,6 +2,7 @@
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from __future__ import annotations
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import ast
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import json
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from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
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from operator import itemgetter
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@ -77,31 +78,43 @@ def _get_usage_metadata_from_generation_info(
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def _parse_json_string(
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json_string: str,
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*,
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raw_tool_call: dict[str, Any],
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skip: bool, # noqa: FBT001
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skip: bool,
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) -> Any:
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"""Attempt to parse a JSON string for tool calling.
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It first tries to use the standard json.loads. If that fails, it falls
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back to ast.literal_eval to safely parse Python literals, which is more
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robust against models using single quotes or containing apostrophes.
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Args:
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json_string: JSON string to parse.
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skip: Whether to ignore parsing errors and return the value anyways.
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raw_tool_call: Raw tool call to include in error message.
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skip: Whether to ignore parsing errors and return the value anyways.
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Returns:
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The parsed JSON string.
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The parsed JSON string or Python literal.
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Raises:
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OutputParserException: If the JSON string wrong invalid and skip=False.
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OutputParserException: If the string is invalid and skip=False.
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"""
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try:
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return json.loads(json_string)
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except json.JSONDecodeError as e:
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except json.JSONDecodeError:
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try:
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# Use ast.literal_eval to safely parse Python-style dicts
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# (e.g. with single quotes)
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return ast.literal_eval(json_string)
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except (SyntaxError, ValueError) as e:
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# If both fail, and we're not skipping, raise an informative error.
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if skip:
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return json_string
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msg = (
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f"Function {raw_tool_call['function']['name']} arguments:\n\n"
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f"{raw_tool_call['function']['arguments']}\n\nare not valid JSON. "
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f"Received JSONDecodeError {e}"
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f"{raw_tool_call['function']['arguments']}"
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"\n\nare not valid JSON or a Python literal. "
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f"Received error: {e}"
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)
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raise OutputParserException(msg) from e
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except TypeError as e:
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@ -8,10 +8,15 @@ from unittest.mock import patch
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import pytest
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from httpx import Client, Request, Response
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from langchain_core.exceptions import OutputParserException
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from langchain_core.messages import ChatMessage
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from langchain_tests.unit_tests import ChatModelUnitTests
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from langchain_ollama.chat_models import ChatOllama, _parse_arguments_from_tool_call
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from langchain_ollama.chat_models import (
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ChatOllama,
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_parse_arguments_from_tool_call,
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_parse_json_string,
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)
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MODEL_NAME = "llama3.1"
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@ -49,13 +54,11 @@ def test_arbitrary_roles_accepted_in_chatmessages(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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monkeypatch.setattr(Client, "stream", _mock_httpx_client_stream)
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llm = ChatOllama(
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model=MODEL_NAME,
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verbose=True,
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format=None,
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)
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messages = [
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ChatMessage(
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role="somerandomrole",
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@ -64,7 +67,6 @@ def test_arbitrary_roles_accepted_in_chatmessages(
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ChatMessage(role="control", content="thinking"),
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ChatMessage(role="user", content="What is the meaning of life?"),
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]
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llm.invoke(messages)
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@ -83,3 +85,58 @@ def test_validate_model_on_init(mock_validate_model: Any) -> None:
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# Test that validate_model is NOT called by default
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ChatOllama(model=MODEL_NAME)
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mock_validate_model.assert_not_called()
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# Define a dummy raw_tool_call for the function signature
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dummy_raw_tool_call = {
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"function": {"name": "test_func", "arguments": ""},
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}
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# --- Regression tests for tool-call argument parsing (see #30910) ---
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@pytest.mark.parametrize(
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"input_string, expected_output",
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[
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# Case 1: Standard double-quoted JSON
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('{"key": "value", "number": 123}', {"key": "value", "number": 123}),
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# Case 2: Single-quoted string (the original bug)
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("{'key': 'value', 'number': 123}", {"key": "value", "number": 123}),
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# Case 3: String with an internal apostrophe
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('{"text": "It\'s a great test!"}', {"text": "It's a great test!"}),
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# Case 4: Mixed quotes that ast can handle
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("{'text': \"It's a great test!\"}", {"text": "It's a great test!"}),
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],
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)
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def test_parse_json_string_success_cases(
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input_string: str, expected_output: Any
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) -> None:
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"""Tests that _parse_json_string correctly parses valid and fixable strings."""
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raw_tool_call = {"function": {"name": "test_func", "arguments": input_string}}
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result = _parse_json_string(input_string, raw_tool_call=raw_tool_call, skip=False)
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assert result == expected_output
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def test_parse_json_string_failure_case_raises_exception() -> None:
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"""Tests that _parse_json_string raises an exception for truly malformed strings."""
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malformed_string = "{'key': 'value',,}"
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raw_tool_call = {"function": {"name": "test_func", "arguments": malformed_string}}
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with pytest.raises(OutputParserException):
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_parse_json_string(
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malformed_string,
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raw_tool_call=raw_tool_call,
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skip=False,
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)
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def test_parse_json_string_skip_returns_input_on_failure() -> None:
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"""Tests that skip=True returns the original string on parse failure."""
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malformed_string = "{'not': valid,,,}"
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raw_tool_call = {"function": {"name": "test_func", "arguments": malformed_string}}
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result = _parse_json_string(
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malformed_string,
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raw_tool_call=raw_tool_call,
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skip=True,
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)
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assert result == malformed_string
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