add streamlit app update

app.py

@@ -21,26 +21,26 @@ import pandas as pd
 from llama_index.llms.azure_openai import AzureOpenAI
 from llama_index.embeddings.azure_openai import AzureOpenAIEmbedding
 
-api_key = "99ce0fb0520347829650be45470fa8d2"
-azure_endpoint = "https://datafigpt.openai.azure.com/"
-api_version = "2023-07-01-preview"
-
-llm = AzureOpenAI(
-    model="gpt-35-turbo",
-    deployment_name="gpt35turbo",
-    api_key=api_key,
-    azure_endpoint=azure_endpoint,
-    api_version=api_version,
-)
-
-# You need to deploy your own embedding model as well as your own chat completion model
-embed_model = AzureOpenAIEmbedding(
-    model="text-embedding-ada-002",
-    deployment_name="text-embedding-ada-002",
-    api_key=api_key,
-    azure_endpoint=azure_endpoint,
-    api_version=api_version,
-)
+# api_key = "99ce0fb0520347829650be45470fa8d2"
+# azure_endpoint = "https://datafigpt.openai.azure.com/"
+# api_version = "2023-07-01-preview"
+
+# llm = AzureOpenAI(
+#     model="gpt-35-turbo",
+#     deployment_name="gpt35turbo",
+#     api_key=api_key,
+#     azure_endpoint=azure_endpoint,
+#     api_version=api_version,
+# )
+
+# # You need to deploy your own embedding model as well as your own chat completion model
+# embed_model = AzureOpenAIEmbedding(
+#     model="text-embedding-ada-002",
+#     deployment_name="text-embedding-ada-002",
+#     api_key=api_key,
+#     azure_endpoint=azure_endpoint,
+#     api_version=api_version,
+# )
 
 os.environ[
     "PINECONE_API_KEY"
@@ -75,8 +75,8 @@ from llama_index.llms.openai import OpenAI
 
 # openai.api_key = os.getenv("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")
 # os.environ["OPENAI_API_KEY"] =  "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"
-# llm = OpenAI(temperature=0, model="gpt-4o")
-# embed_model = OpenAIEmbedding(model="text-embedding-ada-002")
+llm = OpenAI(temperature=0, model="gpt-4o")
+embed_model = OpenAIEmbedding(model="text-embedding-ada-002")
 
 from llama_index.core import Settings