Add application file

app.py

@@ -40,13 +40,13 @@ class REPOGPT:
 
 
 
-    def REPOGPT_Initialized(self,):
+    def REPOGPT_Initialized(self,image_included = False):
 
         
         os.environ["OPENAI_API_KEY"] = self.api_key
         if self.load_vectorstore == None:
          
-            loader = UnstructuredPDFLoader( self.create_repo_pdf(self.repo_link))
+            loader = UnstructuredPDFLoader( self.create_repo_pdf(self.repo_link,image_included = image_included))
             pages = loader.load_and_split()
             self.index = VectorstoreIndexCreator(vectorstore_cls = FAISS).from_loaders([loader])
             self.vectorstore = self.index.vectorstore
@@ -198,11 +198,19 @@ class REPOGPT:
 
    
 
-    def create_repo_pdf(self, repo_link, merged_pdf = "merged.pdf"):
+    def create_repo_pdf(self, repo_link, image_included = False,  merged_pdf = "merged.pdf"):
         self.merged_pdf_path = merged_pdf
         self.download_repo_zip(repo_link)
         folder_name = self.extract_zip('./main.zip', './')
         ingnore_list = ['__pycache__',]
+        if not image_included:
+            ingnore_list.append('.jpg')
+            ingnore_list.append('.png')
+            ingnore_list.append('.jpeg')
+            ingnore_list.append('.gif')
+            ingnore_list.append('.bmp')
+            ingnore_list.append('.tiff')
+
         pdf_files = []
         for root, dirs, files in os.walk(folder_name):
             for file in files:
@@ -290,14 +298,14 @@ with gr.Blocks() as demo:
     gr.Examples(
         examples=["Whats the name of this repo?",
                   "Whats this repo for?",
-                  "How can I use this. Example code ? Step by step",
+                  "How can I use this Example code ? Step by step",
                   "how can I use this Experiment trackers ? Step by step",
                   "how can I Performing gradient accumulation with Accelerate? Step by step?",
                   "Make it like water-color painting",
                   "What is the background color",
                   "Describe this image",
                   "please detect the depth of this image",
-                  "Can you use this depth image to generate a cute dog",
+                  "Whats the learning rate of this model?",
                   ],
         inputs=txt
     )