switch to text-davinci-003

app.py

@@ -35,7 +35,7 @@ def init_pinecone(index_name):
     count = stats['namespaces']['']['vector_count']
     return index, dims, count
 
-def create_context(question, index, lib_meta, max_len=3750, size="curie", top_k=5):
+def create_context(question, index, lib_meta, max_len=3750, top_k=5):
     """
     Find most relevant context for a question via Pinecone search
     """
@@ -69,7 +69,7 @@ def create_context(question, index, lib_meta, max_len=3750, size="curie", top_k=
 
 def answer_question(
     index,
-    fine_tuned_qa_model="text-davinci-002",
+    fine_tuned_qa_model="text-davinci-003",
     question="Am I allowed to publish model outputs to Twitter, without a human review?",
     instruction="Answer the question based on the context below, and if the question can't be answered based on the context, say \"I don't know\"\n\nContext:\n{0}\n\n---\n\nQuestion: {1}\nAnswer:",
     max_len=3550,
@@ -88,7 +88,6 @@ def answer_question(
         index,
         lib_meta=domains,
         max_len=max_len,
-        size=size,
         top_k=top_k
     )
     if debug:
@@ -200,11 +199,11 @@ st.sidebar.write(f"""
 
 **Pinecone index size**: {count}
 
-**OpenAI embedding model**: *text-search-curie-query-001*
+**OpenAI embedding model**: *text-embedding-ada-002*
 
 **Vector dimensionality**: {dims}
 
-**OpenAI generation model**: *text-davinci-002*
+**OpenAI generation model**: *text-davinci-003*
 
 ---