update api details

pages/1_paper_search.py

@@ -13,7 +13,6 @@ import numpy as np
 
 # openai.organization = st.secrets.openai.org
 # openai.api_key = st.secrets.openai.api_key
-st.write(st.secrets['openai'])
 openai.organization = st.secrets["org"]
 openai.api_key = st.secrets["api_key"]
 os.environ["OPENAI_API_KEY"] = openai.api_key

pages/3_qa_sources.py

@@ -18,8 +18,10 @@ from langchain.document_loaders import TextLoader
 from langchain.indexes import VectorstoreIndexCreator
 API_ENDPOINT = "https://api.openai.com/v1/chat/completions"
 
-openai.organization = st.secrets.openai.org
-openai.api_key = st.secrets.openai.api_key
+# openai.organization = st.secrets.openai.org
+# openai.api_key = st.secrets.openai.api_key
+openai.organization = st.secrets["org"]
+openai.api_key = st.secrets["api_key"]
 os.environ["OPENAI_API_KEY"] = openai.api_key
 
 @st.cache_data
@@ -190,20 +192,20 @@ def generate_chat_completion(messages, model="gpt-4", temperature=1, max_tokens=
         return response.json()["choices"][0]["message"]["content"]
     else:
         raise Exception(f"Error {response.status_code}: {response.text}")
-        
-        
+
+
 model_data = [arxiv_ada_embeddings, embeddings, all_titles, all_text, all_authors]
 
 def run_query(query, return_n = 3, show_pure_answer = False, show_all_sources = True):
-    
+
     show_authors = True
     show_summary = True
-    sims, absts, fhdrs, simids = list_similar_papers_v2(model_data, 
-                                  doc_id = query, 
-                                  input_type='keywords', 
-                                  show_authors = show_authors, show_summary = show_summary, 
+    sims, absts, fhdrs, simids = list_similar_papers_v2(model_data,
+                                  doc_id = query,
+                                  input_type='keywords',
+                                  show_authors = show_authors, show_summary = show_summary,
                                   return_n = return_n)
-    
+
     temp_abst = ''
     loaders = []
     for i in range(len(absts)):
@@ -239,7 +241,7 @@ def run_query(query, return_n = 3, show_pure_answer = False, show_all_sources =
     textstr = ''
     ng = len(output['sources'].split())
     abs_indices = []
-    
+
     for i in range(ng):
         if i == (ng-1):
             tempid = output['sources'].split()[i].split('_')[1][0:-4]
@@ -271,13 +273,13 @@ def run_query(query, return_n = 3, show_pure_answer = False, show_all_sources =
         textstr = textstr + ' '
         textstr = textstr + '  \n'
     st.markdown(textstr)
-    
+
     fig = plt.figure(figsize=(9,9))
     plt.scatter(e2d[0:,0], e2d[0:,1],s=2)
     plt.scatter(e2d[simids,0], e2d[simids,1],s=30)
     plt.scatter(e2d[abs_indices,0], e2d[abs_indices,1],s=100,color='k',marker='d')
     st.pyplot(fig)
-    
+
     if show_all_sources == True:
         st.markdown('\n #### Other interesting papers:')
         st.markdown(sims)
@@ -289,4 +291,4 @@ st.markdown('Concise answers for questions using arxiv abstracts + GPT-4. Please
 query = st.text_input('Your question here:', value="What sersic index does a disk galaxy have?")
 return_n = st.slider('How many papers should I show?', 1, 20, 10)
 
-sims = run_query(query, return_n = return_n)
+sims = run_query(query, return_n = return_n)