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fix: the validation Error with qwen-max-latest Model (#706)

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* fix: the validation Error with qwen-max-latest Model

    - Added comprehensive unit tests in tests/unit/graph/test_nodes.py for the new extract_plan_content function
    - Tests cover various input types: string, AIMessage, dictionary, other types
    - Includes a specific test case for issue #703 with the qwen-max-latest model
    - All tests pass successfully, confirming the function handles different input types correctly

* feat: address the code review concerns
This commit is contained in:
Willem Jiang
2025-11-24 21:13:15 +08:00
committed by GitHub
parent 478291df07
commit da514337da
2 changed files with 187 additions and 4 deletions
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44
src/graph/nodes.py
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@@ -5,7 +5,7 @@ import json
import logging
import os
from functools import partial
from typing import Annotated, Literal
from typing import Any, Annotated, Literal
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
from langchain_core.runnables import RunnableConfig
@@ -361,6 +361,34 @@ def planner_node(
)
def extract_plan_content(plan_data: str | dict | Any) -> str:
"""
Safely extract plan content from different types of plan data.
Args:
plan_data: The plan data which can be a string, AIMessage, or dict
Returns:
str: The plan content as a string (JSON string for dict inputs, or
extracted/original string for other types)
"""
if isinstance(plan_data, str):
# If it's already a string, return as is
return plan_data
elif hasattr(plan_data, 'content') and isinstance(plan_data.content, str):
# If it's an AIMessage or similar object with a content attribute
logger.debug(f"Extracting plan content from message object of type {type(plan_data).__name__}")
return plan_data.content
elif isinstance(plan_data, dict):
# If it's already a dictionary, convert to JSON string
logger.debug("Converting plan dictionary to JSON string")
return json.dumps(plan_data)
else:
# For any other type, try to convert to string
logger.warning(f"Unexpected plan data type {type(plan_data).__name__}, attempting to convert to string")
return str(plan_data)
def human_feedback_node(
state: State, config: RunnableConfig
) -> Command[Literal["planner", "research_team", "reporter", "__end__"]]:
@@ -406,7 +434,13 @@ def human_feedback_node(
plan_iterations = state["plan_iterations"] if state.get("plan_iterations", 0) else 0
goto = "research_team"
try:
current_plan = repair_json_output(current_plan)
# Safely extract plan content from different types (string, AIMessage, dict)
original_plan = current_plan
current_plan_content = extract_plan_content(current_plan)
logger.debug(f"Extracted plan content type: {type(current_plan_content).__name__}")
# Repair the JSON output
current_plan = repair_json_output(current_plan_content)
# increment the plan iterations
plan_iterations += 1
# parse the plan
@@ -414,8 +448,10 @@ def human_feedback_node(
# Validate and fix plan to ensure web search requirements are met
configurable = Configuration.from_runnable_config(config)
new_plan = validate_and_fix_plan(new_plan, configurable.enforce_web_search)
except json.JSONDecodeError:
logger.warning("Planner response is not a valid JSON")
except (json.JSONDecodeError, AttributeError) as e:
logger.warning(f"Failed to parse plan: {str(e)}. Plan data type: {type(current_plan).__name__}")
if isinstance(current_plan, dict) and "content" in original_plan:
logger.warning(f"Plan appears to be an AIMessage object with content field")
if plan_iterations > 1: # the plan_iterations is increased before this check
return Command(
update=preserve_state_meta_fields(state),