assistant/ConfigureAssistant.py

@@ -69,7 +69,7 @@ class ConfigureAssistant:
             instructions=AI_ASSISTANT_INSTRUCTIONS,
             model="gpt-4o",
             temperature=0.1,
-            tools=[{"type": "file_search"}, {"type": "code_interpreter"}],
+            tools=[{"type": "file_search"}, ], # {"type": "code_interpreter"}], # Code interpreter doesn't seem to return a delta properly
         )
 
     def get_file_paths(self, excluded_folders=None):
@@ -101,10 +101,16 @@ class ConfigureAssistant:
         # TO DO: Preprocess Outjob and PcbDoc files into something OpenAI (or future vector DB) can understand
         excluded_extensions = ["schdoc", "exe", "so", "dll", "outjob", "pcbdoc", "png"]
 
-        if extension in self.SUPPORTED_FORMATS and extension not in excluded_extensions:
-            return os.path.basename(file_path), True
+        # If the extension is not in supported formats and not in excluded extensions, rename the file
+        if extension not in self.SUPPORTED_FORMATS and extension not in excluded_extensions:
+            new_file_path = f"{file_path}.txt"
+            os.rename(file_path, new_file_path)
+            print(f"Renamed unsupported file: {file_path} to {new_file_path}")
+            return new_file_path, True
+        elif extension in self.SUPPORTED_FORMATS:
+            return file_path, True
         else:
-            print(f"Skipping unsupported file: {file_path}")
+            print(f"Skipping excluded file: {file_path}")
             return file_path, False
 
     def create_vector_store(self):
@@ -127,10 +133,10 @@ class ConfigureAssistant:
             if not should_upload:
                 continue
             try:
-                with open(path, "rb") as file_stream:
+                with open(new_filename, "rb") as file_stream:
                     file_content = file_stream.read()
                     spoofed_file = io.BytesIO(file_content)
-                    spoofed_file.name = new_filename  # Spoof the filename
+                    spoofed_file.name = os.path.basename(new_filename)  # Spoof the filename
                     # Upload the file to the vector store
                     file_batch = (
                         self.client.beta.vector_stores.file_batches.upload_and_poll(

assistant/OpenAIResourceManager.py

@@ -1,7 +1,8 @@
-import os
-import logging
-import pandas as pd
 from openai import OpenAI
+import argparse
+import logging
+import os
+import pandas as pd
 import textwrap
 
 class OpenAIResourceManager:
@@ -167,12 +168,30 @@ class OpenAIResourceManager:
         print("")
         self.show_all_files()
 
-if __name__ == "__main__":
+
+
+def main():
+    """
+    Main function that either shows or deletes resources based on the command line arguments.
+    """
+    parser = argparse.ArgumentParser(
+        description="Displays or deletes all resources associated with the OpenAI account."
+    )
+    parser.add_argument(
+        "--delete", action="store_true", help="Flag to delete resources instead of showing them."
+    )
+    args = parser.parse_args()
+
     # Get the OpenAI API key from the environment variables
     api_key = os.getenv("OPENAI_API_KEY")
     # Create an instance of the OpenAIResourceManager
     manager = OpenAIResourceManager(api_key=api_key)
 
-    # Show or delete all resources in tables
+    # Delete resources conditionally
+    if args.delete:
+        manager.delete_all_resources()
+
     manager.show_all_resources()
-    # manager.delete_all_resources()
+
+if __name__ == "__main__":
+    main()

assistant/QueryAssistant.py

@@ -189,7 +189,7 @@ if __name__ == "__main__":
     parser.add_argument(
         "--assistant_id",
         type=str,
-        default="asst_JUXTF2T6n3RFDjkolNqdtPxj",
+        default="asst_W20wgEl0ZModBiMWzcgC0E3E",
         help="The assistant ID to use.",
     )
     parser.add_argument(