Fix agent knowledge (#2831)

* Added add_sources() * Fixed the agent knowledge querying * Added test cases * Fixed linting issue * Fixed logic * Seems like a falky test case * Minor changes * Added knowledge attriute to the crew documentation * Flaky test * fixed spaces * Flaky Test Case * Seems like a flaky test case --------- Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
2025-12-16 04:18:35 +00:00 · 2025-07-11 23:22:26 +05:30
parent c6caa763d7
commit eec1262d4f
6 changed files with 547 additions and 18 deletions
--- a/docs/en/concepts/crews.mdx
+++ b/docs/en/concepts/crews.mdx
@@ -32,6 +32,7 @@ A crew in crewAI represents a collaborative group of agents working together to
 | **Prompt File** _(optional)_          | `prompt_file`          | Path to the prompt JSON file to be used for the crew.                                                                                                                                                                                                     |
 | **Planning** *(optional)*             | `planning`             | Adds planning ability to the Crew. When activated before each Crew iteration, all Crew data is sent to an AgentPlanner that will plan the tasks and this plan will be added to each task description.                                                     |
 | **Planning LLM** *(optional)*         | `planning_llm`         | The language model used by the AgentPlanner in a planning process.                                                                                                                                                                                        |
+| **Knowledge Sources** _(optional)_    | `knowledge_sources`    | Knowledge sources available at the crew level, accessible to all the agents.                                                                                                                                                                                    |

 <Tip>
 **Crew Max RPM**: The `max_rpm` attribute sets the maximum number of requests per minute the crew can perform to avoid rate limits and will override individual agents' `max_rpm` settings if you set it.
--- a/src/crewai/agent.py
+++ b/src/crewai/agent.py
@@ -210,7 +210,6 @@ class Agent(BaseAgent):
                        sources=self.knowledge_sources,
                        embedder=self.embedder,
                        collection_name=self.role,
-                        storage=self.knowledge_storage or None,
                    )
                    self.knowledge.add_sources()
        except (TypeError, ValueError) as e:
@@ -341,7 +340,8 @@ class Agent(BaseAgent):
            self.knowledge_config.model_dump() if self.knowledge_config else {}
        )

-        if self.knowledge:
+
+        if self.knowledge or (self.crew and self.crew.knowledge):
            crewai_event_bus.emit(
                self,
                event=KnowledgeRetrievalStartedEvent(
@@ -353,25 +353,28 @@ class Agent(BaseAgent):
                    task_prompt
                )
                if self.knowledge_search_query:
-                    agent_knowledge_snippets = self.knowledge.query(
-                        [self.knowledge_search_query], **knowledge_config
-                    )
-                    if agent_knowledge_snippets:
-                        self.agent_knowledge_context = extract_knowledge_context(
-                            agent_knowledge_snippets
-                        )
-                        if self.agent_knowledge_context:
-                            task_prompt += self.agent_knowledge_context
-                    if self.crew:
-                        knowledge_snippets = self.crew.query_knowledge(
+                    # Quering agent specific knowledge
+                    if self.knowledge:
+                        agent_knowledge_snippets = self.knowledge.query(
                            [self.knowledge_search_query], **knowledge_config
                        )
-                        if knowledge_snippets:
-                            self.crew_knowledge_context = extract_knowledge_context(
-                                knowledge_snippets
+                        if agent_knowledge_snippets:
+                            self.agent_knowledge_context = extract_knowledge_context(
+                                agent_knowledge_snippets
                            )
-                            if self.crew_knowledge_context:
-                                task_prompt += self.crew_knowledge_context
+                            if self.agent_knowledge_context:
+                                task_prompt += self.agent_knowledge_context
+
+                    # Quering crew specific knowledge
+                    knowledge_snippets = self.crew.query_knowledge(
+                        [self.knowledge_search_query], **knowledge_config
+                    )
+                    if knowledge_snippets:
+                        self.crew_knowledge_context = extract_knowledge_context(
+                            knowledge_snippets
+                        )
+                        if self.crew_knowledge_context:
+                            task_prompt += self.crew_knowledge_context

                    crewai_event_bus.emit(
                        self,
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -1896,6 +1896,80 @@ def test_agent_with_knowledge_sources_generate_search_query():
        assert "red" in result.raw.lower()


+@pytest.mark.vcr(record_mode='none', filter_headers=["authorization"])
+def test_agent_with_knowledge_with_no_crewai_knowledge():
+    mock_knowledge = MagicMock(spec=Knowledge)
+
+    agent = Agent(
+        role="Information Agent",
+        goal="Provide information based on knowledge sources",
+        backstory="You have access to specific knowledge sources.",
+        llm=LLM(model="openrouter/openai/gpt-4o-mini",api_key=os.getenv('OPENROUTER_API_KEY')),
+        knowledge=mock_knowledge
+    )
+
+    # Create a task that requires the agent to use the knowledge
+    task = Task(
+        description="What is Vidit's favorite color?",
+        expected_output="Vidit's favorclearite color.",
+        agent=agent,
+    )
+
+    crew = Crew(agents=[agent], tasks=[task])
+    crew.kickoff()
+    mock_knowledge.query.assert_called_once()
+
+
+@pytest.mark.vcr(record_mode='none', filter_headers=["authorization"])
+def test_agent_with_only_crewai_knowledge():
+    mock_knowledge = MagicMock(spec=Knowledge)
+
+    agent = Agent(
+        role="Information Agent",
+        goal="Provide information based on knowledge sources",
+        backstory="You have access to specific knowledge sources.",
+        llm=LLM(model="openrouter/openai/gpt-4o-mini",api_key=os.getenv('OPENROUTER_API_KEY'))
+    )
+
+    # Create a task that requires the agent to use the knowledge
+    task = Task(
+        description="What is Vidit's favorite color?",
+        expected_output="Vidit's favorclearite color.",
+        agent=agent
+    )
+
+    crew = Crew(agents=[agent], tasks=[task],knowledge=mock_knowledge)
+    crew.kickoff()
+    mock_knowledge.query.assert_called_once()
+
+
+@pytest.mark.vcr(record_mode='none', filter_headers=["authorization"])
+def test_agent_knowledege_with_crewai_knowledge():
+    crew_knowledge = MagicMock(spec=Knowledge)
+    agent_knowledge = MagicMock(spec=Knowledge)
+
+
+    agent = Agent(
+        role="Information Agent",
+        goal="Provide information based on knowledge sources",
+        backstory="You have access to specific knowledge sources.",
+        llm=LLM(model="openrouter/openai/gpt-4o-mini",api_key=os.getenv('OPENROUTER_API_KEY')),
+        knowledge=agent_knowledge
+    )
+
+    # Create a task that requires the agent to use the knowledge
+    task = Task(
+        description="What is Vidit's favorite color?",
+        expected_output="Vidit's favorclearite color.",
+        agent=agent,
+    )
+
+    crew = Crew(agents=[agent],tasks=[task],knowledge=crew_knowledge)
+    crew.kickoff()
+    agent_knowledge.query.assert_called_once()
+    crew_knowledge.query.assert_called_once()
+
+
@pytest.mark.vcr(filter_headers=["authorization"])
 def test_litellm_auth_error_handling():
    """Test that LiteLLM authentication errors are handled correctly and not retried."""
--- a/tests/cassettes/test_agent_knowledege_with_crewai_knowledge.yaml
+++ b/tests/cassettes/test_agent_knowledege_with_crewai_knowledge.yaml
@@ -0,0 +1,150 @@
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--- a/tests/cassettes/test_agent_with_knowledge_with_no_crewai_knowledge.yaml
+++ b/tests/cassettes/test_agent_with_knowledge_with_no_crewai_knowledge.yaml
@@ -0,0 +1,151 @@
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--- a/tests/cassettes/test_agent_with_only_crewai_knowledge.yaml
+++ b/tests/cassettes/test_agent_with_only_crewai_knowledge.yaml
@@ -0,0 +1,150 @@
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