chore: bump pipecat version and fix tests (#263)

* chore: bump pipecat version and fix tests

* chore: add github workflow to run tests

* fix: install reqirements.dev.txt in test script

* fix: fix api-test action

* feat: add integration test

* test: add integration tests

* test: add test for function call mute strategy

api/tests/test_pipecat_engine_context_update.py

@@ -14,18 +14,10 @@ result in the context when generating the next response.
 """
 
 import asyncio
-from typing import Any, Dict, List
+from typing import List
 from unittest.mock import AsyncMock, patch
 
 import pytest
-
-from api.services.workflow.pipecat_engine import PipecatEngine
-from api.services.workflow.workflow import WorkflowGraph
-from api.tests.conftest import (
-    AGENT_SYSTEM_PROMPT,
-    END_CALL_SYSTEM_PROMPT,
-    START_CALL_SYSTEM_PROMPT,
-)
 from pipecat.frames.frames import LLMContextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -35,75 +27,21 @@ from pipecat.processors.aggregators.llm_response_universal import (
     LLMAssistantAggregatorParams,
     LLMContextAggregatorPair,
 )
-from pipecat.tests import MockLLMService, MockTTSService
 from pipecat.tests.mock_transport import MockTransport
 from pipecat.transports.base_transport import TransportParams
 
-
-class ContextCapturingMockLLM(MockLLMService):
-    """A MockLLMService that captures the context state at each generation.
-
-    This allows us to verify that tool call results are present in the context
-    when the next LLM generation is triggered.
-    """
-
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self.captured_contexts: List[Dict[str, Any]] = []
-
-    async def _stream_chat_completions_universal_context(self, context):
-        """Override to capture context state before streaming chunks."""
-        # Deep copy the messages to avoid mutation issues
-        messages_snapshot = []
-        for msg in context.messages:
-            msg_copy = dict(msg)
-            # Copy content to avoid reference issues
-            if "content" in msg_copy:
-                msg_copy["content"] = (
-                    str(msg_copy["content"]) if msg_copy["content"] else None
-                )
-            messages_snapshot.append(msg_copy)
-
-        self.captured_contexts.append(
-            {
-                "step": self._current_step,
-                "messages": messages_snapshot,
-                "system_prompt": self._settings.system_instruction,
-            }
-        )
-
-        # Call parent implementation to stream the mock chunks
-        return await super()._stream_chat_completions_universal_context(context)
-
-    def get_context_at_step(self, step: int) -> Dict[str, Any]:
-        """Get the captured context at a specific step (0-indexed)."""
-        for ctx in self.captured_contexts:
-            if ctx["step"] == step:
-                return ctx
-        return None
-
-    def has_tool_call_result_at_step(self, step: int, function_name: str) -> bool:
-        """Check if a tool call result for the given function exists in context at step."""
-        ctx = self.get_context_at_step(step)
-        if not ctx:
-            return False
-
-        for msg in ctx["messages"]:
-            # Check for tool/function role messages
-            if msg.get("role") == "tool" and msg.get("name") == function_name:
-                return True
-            # Also check for tool_call_id which indicates a tool response
-            if msg.get("tool_call_id") and function_name in str(msg.get("name", "")):
-                return True
-
-        return False
-
-    def get_system_prompt_at_step(self, step: int) -> str:
-        """Get the system prompt from settings at a specific step."""
-        ctx = self.get_context_at_step(step)
-        if ctx:
-            return ctx.get("system_prompt") or ""
-        return ""
+from api.services.workflow.pipecat_engine import PipecatEngine
+from api.services.workflow.workflow import WorkflowGraph
+from api.tests.conftest import (
+    AGENT_SYSTEM_PROMPT,
+    END_CALL_SYSTEM_PROMPT,
+    START_CALL_SYSTEM_PROMPT,
+)
+from pipecat.tests import (
+    ContextCapturingMockLLM,
+    MockLLMService,
+    MockTTSService,
+)
 
 
 async def run_pipeline_and_capture_context(
@@ -142,7 +80,7 @@ async def run_pipeline_and_capture_context(
     context = LLMContext()
 
     # Add assistant context aggregator
-    assistant_params = LLMAssistantAggregatorParams(expect_stripped_words=True)
+    assistant_params = LLMAssistantAggregatorParams()
     context_aggregator = LLMContextAggregatorPair(
         context, assistant_params=assistant_params
     )
@@ -184,7 +122,7 @@ async def run_pipeline_and_capture_context(
 
     # Patch DB calls
     with patch(
-        "api.services.workflow.pipecat_engine.get_organization_id_from_workflow_run",
+        "api.db:db_client.get_organization_id_by_workflow_run_id",
         new_callable=AsyncMock,
         return_value=1,
     ):