Move chromedriver to Git LFS

OpenAITools/ExpertTools.py

@@ -19,7 +19,8 @@ import numpy as np
 import time
 #from langchain.agents import create_pandas_dataframe_agent
 from langchain_experimental.agents import create_pandas_dataframe_agent
-from langchain.llms import OpenAI
+#from langchain.llms import OpenAI
+from langchain_community.llms import OpenAI
 
 # APIキーの設定
 openai.api_key = os.environ['OPENAI_API_KEY']
@@ -135,6 +136,7 @@ def print_agent_results(df, Ids,
 
 def search(query):
     Entrez.email = os.getenv('MAIL_ADRESS')
+    #Entrez.email='sing.monotonyflower@gmail.com'
     handle = Entrez.esearch(db='pubmed',
                            sort = 'relevance',
                            retmax = '20',
@@ -146,6 +148,7 @@ def search(query):
 def fetch_details(id_list):
     ids = ','.join(id_list)
     Entrez.email = os.getenv('MAIL_ADRESS')
+    #Entrez.email = 'sing.monotonyflower@gmail.com' 
     handle = Entrez.efetch(db = 'pubmed',
                           retmode = 'xml',
                           id = ids)

app.py

@@ -1,9 +1,11 @@
 from OpenAITools.ExpertTools import GetPubmedSummaryDf, generate, search
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, SummaryIndex
+from llama_index.core import  SummaryIndex
 from llama_index.core import Document
 from llama_index.llms.groq import Groq
 from llama_index.core import ServiceContext, set_global_service_context
 from llama_index.llms.llama_cpp.llama_utils import messages_to_prompt, completion_to_prompt
+#from llama_index.settings import Settings
+from llama_index.core import Settings
 import gradio as gr
 
 #models
@@ -31,8 +33,10 @@ def getMutationEffect(cancer_name, gene_name):
     completion_to_prompt=custom_completion_to_prompt,
     messages_to_prompt=messages_to_prompt,)
     #set global service context
-    ctx = ServiceContext.from_defaults(llm=llm)
-    set_global_service_context(ctx)
+    #ctx = ServiceContext.from_defaults(llm=llm)
+    #ctx = Settings(llm=llm)
+    Settings.llm = llm
+    #set_global_service_context(ctx)
     documents = [Document(text=t) for t in abstracts[:10]]
     index = SummaryIndex.from_documents(documents)
     query_engine = index.as_query_engine(response_mode="tree_summarize")

requirements.txt

@@ -14,7 +14,7 @@ greenlet==3.0.3
 hpack==4.0.0
 jsonpatch==1.33
 langchain==0.2.2
-langchain-community==0.2.2
+langchain-community==0.2.4
 langchain-core==0.2.4
 langchain-experimental==0.0.60
 langchain-openai==0.1.8