Update app.py

app.py

@@ -20,7 +20,6 @@ from typing import List, Dict
 from ppt_chunker import ppt_chunk
 from outlines import models, generate
 from qdrant_client import QdrantClient
-from outlines.samplers import greedy
 from optimum_encoder import OptimumEncoder
 from unstructured.cleaners.core import clean
 from streamlit_navigation_bar import st_navbar
@@ -109,7 +108,6 @@ def query_hybrid_search(query: str, client: QdrantClient, collection_name: str,
 
 def build_prompt_conv():
     return f"""Generate a short, single-sentence summary of the user's intent or topic based on their question, capturing the main focus of what they want to discuss.
-    Do not write 'Summary :' before the single-sentence.
     
     Question : {st.session_state.user_input}
     """
@@ -200,7 +198,7 @@ def main(query: str, client: QdrantClient, collection_name: str, llm, dense_mode
     
     gen_text = outlines.generate.text(llm)
 
-    gen_choice = outlines.generate.choice(llm, choices=['Yes', 'No'], sampler=greedy())
+    gen_choice = outlines.generate.choice(llm, choices=['Yes', 'No'])
     prompt = route_llm(context, 'Is the context relevant to the question ?')
     action = gen_choice(prompt, max_tokens=2, sampling_params=SamplingParams(temperature=0))
     print(f'Choice: {action}')
@@ -221,7 +219,7 @@ def main(query: str, client: QdrantClient, collection_name: str, llm, dense_mode
         if not st.session_state.documents_only:
             answer = f'Documents Based :\n\n{answer}'
     else:
-        gen_choice = outlines.generate.choice(llm, choices=['Domain-Specific Question', 'General Question'], sampler=greedy())
+        gen_choice = outlines.generate.choice(llm, choices=['Domain-Specific Question', 'General Question'])
         prompt = build_initial_prompt(query)
         action = gen_choice(prompt, max_tokens=3, sampling_params=SamplingParams(temperature=0))
         print(f'Choice 2: {action}')