Now checks for classificatory credits

agent/_create.py

@@ -83,7 +83,7 @@ def agent(payload):
     
     from langchain_core.messages import HumanMessage
 
-    input = payload.get("input") or "What is Rise for?"
+    input = payload.get("input") or "Can I earn credit?"
     inputs = [HumanMessage(content=input)]
 
     response = app.invoke(inputs, {"configurable": {"thread_id": memory.thread_id} } )

agent/toolset.py

@@ -25,6 +25,17 @@ def frequently_asked_questions(input: str):
     result = qa.invoke(input)
     return result 
 
+@tool
+def check_eligibility(input: str):
+    """
+        Use this to check whether a student is eligible to earn classificatory credits
+    """
+    from flask import request
+    
+    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
+
 class RecommendActivityInput(BaseModel):
     profile: str = Field(description="should be a penportrait of the user describing their interests and objectives. If they have a specific thing they are interested in, it should state that")
 
@@ -49,7 +60,7 @@ def recommend_activity(profile: str) -> str:
     result = qa.invoke("recommend an activity relevant to the following profile: "+profile)
     return result 
 
-tools = [frequently_asked_questions]
+tools = [frequently_asked_questions, check_eligibility]
 
 from langgraph.prebuilt import ToolExecutor