Update app.py

app.py

@@ -9,22 +9,19 @@ from langchain.agents import AgentExecutor, create_openai_functions_agent
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.messages import AIMessage, HumanMessage
 from langchain.tools import StructuredTool
+# cache
 from gptcache import cache
-from gptcache.adapter.langchain_models import LangChainLLMs
-from gptcache.embedding import Onnx
-from gptcache.manager import CacheBase, VectorBase, get_data_manager
-from gptcache.similarity_evaluation.distance import SearchDistanceEvaluation
+from gptcache.adapter.langchain_models import LangChainChat
+
+def get_msg(data, **_):
+    return data.get("messages")[-1].content
 
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
-onnx = Onnx()
-data_manager = get_data_manager(CacheBase("sqlite"), VectorBase("faiss", dimension=onnx.dimension))
 cache.init(
-    embedding_func=onnx.to_embeddings,
-    data_manager=data_manager,
-    similarity_evaluation=SearchDistanceEvaluation(),
-    )
-cache.set_openai_key()
+    pre_embedding_func=get_msg,
+)
+
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
 def repo_get_all_employees_from_database():
     url = "https://api.airtable.com/v0/appopGmlHujYnd6Vw/Interviewers?maxRecords=100&view=Grid%20view"
@@ -85,7 +82,7 @@ class GetEmployees(BaseModel):
     duration_hours: int = Field(..., description="Required duration of the availability in hours")
 
 # llm = ChatOpenAI(temperature=1.0, model_name="gpt-3.5-turbo", openai_api_key=OPENAI_API_KEY)
-llm = LangChainLLMs(llm=ChatOpenAI(temperature=1.0, model_name="gpt-3.5-turbo", openai_api_key=OPENAI_API_KEY))
+llm = LangChainChat(llm=ChatOpenAI(temperature=1.0, model_name="gpt-3.5-turbo", openai_api_key=OPENAI_API_KEY))
 
 tools = [
     StructuredTool.from_function(