feat: add content filter for thinking agent

Author: SchrodingersCattt

agents/matmaster_agent/flow_agents/agent.py

@@ -94,6 +94,9 @@
     StepValidationSchema,
 )
 from agents.matmaster_agent.flow_agents.thinking_agent.agent import ThinkingAgent
+from agents.matmaster_agent.flow_agents.thinking_agent.callback import (
+    filter_thinking_llm_contents,
+)
 from agents.matmaster_agent.flow_agents.thinking_agent.constant import THINKING_AGENT
 from agents.matmaster_agent.flow_agents.utils import (
     check_plan,
@@ -216,6 +219,7 @@ def after_init(self):
             model=MatMasterLlmConfig.default_litellm_model,
             description='在制定计划前对工具选择与顺序进行推理',
             instruction='',
+            before_model_callback=filter_thinking_llm_contents,
         )
 
         self._execution_agent = None

agents/matmaster_agent/flow_agents/constant.py

@@ -1,9 +1,12 @@
 from agents.matmaster_agent.flow_agents.expand_agent.constant import EXPAND_AGENT
 from agents.matmaster_agent.flow_agents.intent_agent.constant import INTENT_AGENT
+from agents.matmaster_agent.flow_agents.plan_make_agent.constant import PLAN_MAKE_AGENT
 from agents.matmaster_agent.flow_agents.scene_agent.constant import SCENE_AGENT
 
 # Agent Constants
 MATMASTER_SUPERVISOR_AGENT = 'matmaster_supervisor_agent'
+EXECUTION_SUMMARY_AGENT = 'execution_summary_agent'
+REPORT_AGENT = 'report_agent'
 
 # Function-Call Constants
 MATMASTER_FLOW = 'matmaster_flow'
@@ -21,3 +24,12 @@
     EXPAND_AGENT.replace('_agent', '_schema'),
     SCENE_AGENT,
 ]
+
+THINKING_CONTEXT_FILTER_KEYWORDS = UNIVERSAL_CONTEXT_FILTER_KEYWORDS + [
+    PLAN_MAKE_AGENT,
+    MATMASTER_FLOW,
+    MATMASTER_FLOW_PLANS,
+    MATMASTER_GENERATE_NPS,
+    EXECUTION_SUMMARY_AGENT,
+    REPORT_AGENT,
+]

agents/matmaster_agent/flow_agents/thinking_agent/callback.py

@@ -0,0 +1,44 @@
+import logging
+from typing import Optional
+
+from google.adk.agents.callback_context import CallbackContext
+from google.adk.models import LlmRequest, LlmResponse
+from google.genai.types import Content, Part
+
+from agents.matmaster_agent.constant import MATMASTER_AGENT_NAME, ModelRole
+from agents.matmaster_agent.flow_agents.constant import (
+    THINKING_CONTEXT_FILTER_KEYWORDS,
+)
+from agents.matmaster_agent.logger import PrefixFilter
+from agents.matmaster_agent.utils.context_utils import is_content_has_keywords
+
+logger = logging.getLogger(__name__)
+logger.addFilter(PrefixFilter(MATMASTER_AGENT_NAME))
+logger.setLevel(logging.INFO)
+
+
+async def filter_thinking_llm_contents(
+    callback_context: CallbackContext, llm_request: LlmRequest
+) -> Optional[LlmResponse]:
+    contents = []
+    for content in llm_request.contents[::-1]:
+        if is_content_has_keywords(
+            content,
+            THINKING_CONTEXT_FILTER_KEYWORDS,
+        ):
+            continue
+        contents.insert(0, content)
+
+    logger.info(
+        f'{callback_context.session.id} {callback_context.agent_name} contents = {len(contents)}'
+    )
+
+    if not contents:
+        contents = [
+            Content(
+                role=ModelRole,
+                parts=[Part(text='Default Text')],
+            )
+        ]
+
+    llm_request.contents = contents