updates

agent/_create.py

@@ -98,6 +98,9 @@ def agent(payload):
     print(response[-1].content)
     '''
     
-    print(response[-1].content)
-    return response[-1].content
+    response = response[-1].content[:-1] + ', "thread_id": "' + str(memory.thread_id) + '"}'
+    
+
+    print(response);
+    return response
     

agent/datastructures.py

@@ -26,7 +26,6 @@ class FrontEndActions(BaseModel):
 class ResponseSchema(BaseModel):
     """Always use this to format the final response to the user. This will be passed back to the frontend."""
     message: str = Field(description="final answer to respond to the user")
-    thread_id: int = Field(description="The ID of the checkpointer memory thread that this response is associated with. This is used to keep track of the conversation.")
     tools: List[str] = Field(description="A list of the tools used to generate the response.") 
     actions: List[FrontEndActions] = Field(description="List of suggested actions that should be passed back to the frontend to display. The use will click these to enact them. ")
 

agent/jsonencoder.py

@@ -1,16 +1,9 @@
 from langchain_openai import ChatOpenAI
-from agent.datastructures import parser
+from agent.datastructures import parser,ResponseSchema
 
 
 model = ChatOpenAI(model="gpt-3.5-turbo-0125", temperature=0)
-
-#from langchain_core.utils.function_calling import convert_pydantic_to_openai_function
-#from agent.datastructures import ResponseSchema
-
-#converted_tools = [convert_pydantic_to_openai_function(ResponseSchema)]
-
-#model.bind_functions(convert_pydantic_to_openai_function(ResponseSchema))
-
+model.with_structured_output(ResponseSchema)
 
 from langchain.prompts import ChatPromptTemplate,PromptTemplate, MessagesPlaceholder,SystemMessagePromptTemplate
 
@@ -30,9 +23,7 @@ prompt = PromptTemplate(
 
 prompt = ChatPromptTemplate.from_messages(
     [
-        ("system", "The thread_id of this conversation is {thread_id}."),     
         ("system", "You will be given the chat so far, you should render the final answer as a JSON object"),        
-        SystemMessagePromptTemplate.from_template("{format_instructions}").format(format_instructions=parser.get_format_instructions()),
         MessagesPlaceholder(variable_name="conversation"),
     ]
 )

agent/prompt.py

@@ -40,7 +40,7 @@ prompt = {
         
         1: ChatPromptTemplate.from_messages([
             ("system", "The thread_id of this conversation is {thread_id}."),  
-            ("system", "In your answer you should list the tools used to produce this answer"),     
+            ("system", "You should always "),     
             MessagesPlaceholder(variable_name="conversation")
          ])
           

agent/toolset.py

@@ -9,7 +9,9 @@ from langchain_core.pydantic_v1 import BaseModel, Field
 def frequently_asked_questions(input: str):
 
     """
-        Please always use this tool if the user has questions about our offer
+        You MUST use this tool to answer questions that users have.
+        Never try to answer a question without a tool.
+        If you cannot find the answer using this tool, you should pass the 'refer' action
     """
 
     # Load from local storage
@@ -21,7 +23,7 @@ def frequently_asked_questions(input: str):
         llm=ChatOpenAI(model="gpt-3.5-turbo-0125", temperature=0), 
         chain_type="stuff", 
         return_source_documents=False,
-        retriever=persisted_vectorstore.as_retriever(search_type="similarity_score_threshold",search_kwargs={"k":3, "score_threshold":0.5})) 
+        retriever=persisted_vectorstore.as_retriever(search_type="similarity_score_threshold",search_kwargs={"k":2, "score_threshold":0.75})) 
     result = qa.invoke(input)
     return result 
 
@@ -32,6 +34,8 @@ def check_eligibility(input: str):
     """
     from flask import request
     
+    print("https://rise.mmu.ac.uk/wp-content/themes/rise/helpers/user/student_eligibility/chatbotquery.php?query=eligibility&wpid="+request.values.get("user_id"))
+
     from langchain_community.document_loaders import WebBaseLoader
     document = WebBaseLoader("https://rise.mmu.ac.uk/wp-content/themes/rise/helpers/user/student_eligibility/chatbotquery.php?query=eligibility&wpid="+request.values.get("user_id")).load()
     return document[0].page_content