Update main.py

main.py

@@ -98,6 +98,10 @@ class imageInput(BaseModel):
 class ReportInput(BaseModel):
     topic: str = Query(default="market research",description="The main topic for the report")
     description: str = Query(default="",description="A brief description of the topic")
+    
+class RecommendationInput(BaseModel):
+    user_input: str = Query(default="", description="Input query to generate follow-up questions")
+    num_recommendations: int = Query(default=5, description="Number of recommendations to generate")
 
 @app.get("/", tags=["Home"])
 def api_home():
@@ -119,18 +123,20 @@ async def fetch_images(input: imageInput):
     return {"images": images}
 
 @app.post("/get_recommendations")
-async def generate_recommendations(input: imageInput):
+async def generate_recommendations(input: RecommendationInput):
     
     if input.user_input:
-        prompt = f"""create a list of {input.num_images} questions that a user might ask following the question: {input.user_input}:"""
+        prompt = f"""create a list of {input.num_recommendations} questions that a user might ask following the question: {input.user_input}:"""
     else:
-        prompt = f"""create a list of mixed {input.num_images} questions to create a report or plan or course on any of the topics product,market,research topic """
+        prompt = f"""create a list of mixed {input.num_recommendations} questions to create a report or plan or course on any of the topics product,market,research topic """
 
-    if st.session_state.user_query_full != st.session_state.recommendation_query:
-        response_topics = json_from_text(
+    response_topics = json_from_text(
             together_response(
                 prompt, model="meta-llama/Llama-3-8b-chat-hf", SysPrompt=SysPromptList,temperature=1
             )
         )
     return {"recommendations": response_topics}
+
+
+