Improve user prompt and make resource_type a list in the search tool schema

Author: mbertrand

ai_chat/agents.py

@@ -157,7 +157,10 @@ class SearchAgentService(BaseChatAgentService):
 dictionary: {OfferedBy.as_dict()}  DO NOT USE THE offered_by FILTER OTHERWISE.
 
 If the user mentions courses, programs, videos, or podcasts in particular, filter
-the search by resource_category.  DO NOT USE THE resource_type FILTER OTHERWISE.
+the search by resource_type.  DO NOT USE THE resource_type FILTER OTHERWISE.
+You MUST combine multiple resource types in one request like this:
+"resource_type=course&resource_type=program". Do not attempt more than one query per
+user message.
 
 If the user asks what other courses are taught by a particular instructor,
 search the catalog for courses taught by that instructor.
@@ -175,7 +178,9 @@ class SearchToolSchema(pydantic.BaseModel):
         """Schema for the search_courses function tool"""
 
         q: str
-        resource_type: Optional[enum_zip("resource_type", LearningResourceType.names())]
+        resource_type: Optional[
+            list[enum_zip("resource_type", LearningResourceType.names())]
+        ]
         level: Optional[enum_zip("level", LevelType.names())]
         free: Optional[bool]
         certificate: Optional[bool]
@@ -205,6 +210,7 @@ def __init__(  # noqa: PLR0913
         )
         self.temperature = temperature
         self.search_parameters = []
+        self.search_results = []
         self.agent = self.create_agent()
         self.create_agent()
 
@@ -247,6 +253,7 @@ def search_courses(self, q: str, **kwargs) -> str:
                 {k: result.get(k) for k in main_properties}
                 for result in response.json().get("results", [])
             ]
+            self.search_results.append(results)
             return json.dumps(results)
         except requests.exceptions.RequestException as e:
             log.exception("Error querying MIT API")
@@ -289,6 +296,7 @@ def get_comment_metadata(self):
         metadata = {
             "metadata": {
                 "search_parameters": self.search_parameters,
+                "search_results": self.search_results,
                 "system_prompt": self.instructions,
             }
         }

frontends/ol-components/src/components/Nlux-AiChat/AiChat.tsx

@@ -11,6 +11,7 @@ import { personas } from "./personas"
 
 import "@nlux/themes/unstyled.css"
 import "./nlux-theme.css"
+import { styled } from "ol-components"
 
 type NluxAiChatProps = Pick<
   AiChatProps,
@@ -19,6 +20,11 @@ type NluxAiChatProps = Pick<
   send: StreamSend
 }
 
+const StyledDebugPre = styled.pre({
+  width: "80%",
+  "white-space": "pre-wrap",
+})
+
 const NluxAiChat: React.FC<NluxAiChatProps> = (props) => {
   const adapter = useAsStreamAdapter(props.send, [])
   const [lastMessageReceived, setLastMessageReceived] = useState("")
@@ -42,9 +48,9 @@ const NluxAiChat: React.FC<NluxAiChatProps> = (props) => {
         {...props}
       />
       {lastMessageReceived ? (
-        <>
+        <div>
           <p>Debug Info:</p>
-          <pre>
+          <StyledDebugPre>
             {lastMessageReceived
               ? lastMessageReceived.toString()?.includes('{"error":')
                 ? JSON.stringify(
@@ -64,8 +70,8 @@ const NluxAiChat: React.FC<NluxAiChatProps> = (props) => {
                     )
                   : ""
               : ""}
-          </pre>
-        </>
+          </StyledDebugPre>
+        </div>
       ) : null}
     </>
   )