Update app.py

app.py

@@ -21,7 +21,7 @@ from langchain.llms.base import LLM
 from typing import Optional, List, Mapping, Any
 
 import ast
-from utils import ClaudeLLM, extract_website_name, remove_numbers
+from utils import ClaudeLLM, ClaudeLLM2, extract_website_name, remove_numbers
 
 embeddings = HuggingFaceEmbeddings()
 db = FAISS.load_local('db_full', embeddings)
@@ -70,7 +70,7 @@ def retrieve_thoughts(query, ):
     tier_1_adjusted.sort_values("score", inplace = True)
     tier_1_adjusted['ref'] = range(1, len(tier_1_adjusted) + 1 )
 
-    return {'tier 1':tier_1_adjusted[:12], 'tier 2': tier_2_adjusted.loc[:5]}
+    return {'tier 1':tier_1_adjusted[:min(len(tier_1_adjusted), 100)], 'tier 2': tier_2_adjusted.loc[:5]}
 
 def get_references(query):
   # TO-DO FINSIH UPP.
@@ -207,8 +207,8 @@ def qa_retrieve(query,):
         )
 
 
-    # llm = BardLLM()
-    chain = LLMChain(llm=llm_4, prompt = prompt)
+    llm = ClaudeLLM2()
+    chain = LLMChain(llm=llm, prompt = prompt)
 
     consensus = chain.run(query=query, articles="\n".join(tier_1), session_prompt = session_prompt,).strip()
 
@@ -259,7 +259,7 @@ def qa_intro(query, cynthesis, tier_1,):
   # llm = BardLLM()
   chain = LLMChain(llm=llm_4, prompt = prompt)
 
-  intro = chain.run(query=query, articles="\n".join(tier_1))
+  intro = chain.run(query=query, articles="\n".join(tier_1[:15]))
   return intro.strip()
 
 def qa_conclusion(query, cynthesis, tier_1,):
@@ -294,7 +294,7 @@ def qa_conclusion(query, cynthesis, tier_1,):
   # llm = BardLLM()
   chain = LLMChain(llm=llm_4, prompt = prompt)
 
-  conclusion = chain.run(query=query, articles="\n".join(tier_1), cynthesis = cynthesis)
+  conclusion = chain.run(query=query, articles="\n".join(tier_1[:15]), cynthesis = cynthesis)
   return conclusion.strip()
     
 def qa_faqs(query):