curr working version with ReadME update

README.md

@@ -10,4 +10,22 @@ pinned: false
 license: mit
 ---
 
+## Files
+
+Everything running right now is simply Google Gemini in app.py
+
+model.py - some models we have tried but abandoned at last
+
+app.py - current working version supported by Hugging Face Space
+
+# Code
+
+Basically: 
+1. Call Gemini
+2. Add it into the interface
+3. Run the model 
+4. Clear the response 
+5. Output
+
+
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Tester.py

@@ -1,32 +0,0 @@
-import subprocess
-
-file_path = "model.py"
-
-# Self-defined inputs for each iteration, donno if it'll burn my computer 
-inputs = [
-    {"T_o": "What can I have for lunch today? I enjoys eating human beings and metals"},
-    {"T_o": "What can I drink after exercising?"},
-    {"T_o": "What can I do to improve my health?"},
-    {"T_o": "What should I do in Chinese New Year?"},
-]
-
-def run_with_inputs():
-    for i, config in enumerate(inputs):
-        print(f"Running test {i + 1} with input: {config['T_o']}")
-        
-        command = [
-            "python",
-            file_path,
-            f"--T_o", config["T_o"]
-        ]
-
-        try:
-            result = subprocess.run(command, capture_output=True, text=True, check=True)
-            print(f"Output for test {i + 1}:")
-            print(result.stdout)
-        except subprocess.CalledProcessError as e:
-            print(f"Error running test {i + 1}:")
-            print(e.stderr)
-
-if __name__ == "__main__":
-    run_with_inputs()

app.py

@@ -22,9 +22,9 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 print("Loading model...")
 #generator = LlamaModel() #can work, but super slow ~2min
 #generator = GPT2Model()  #can work, but not showing correct output
-#generator = GPTNeoXModel() 
-#generator = DistilGPT2Model() 
-#generator = LLaMA2Model()
+#generator = GPTNeoXModel() #storage requirements
+#generator = DistilGPT2Model() #Can work, but not showing correct output
+#generator = LLaMA2Model() #can work, too slow though
 
 genai.configure(api_key="AIzaSyAJF6isCNu6XfGA5TBFddXu9BTfAKaPF30")
 model = genai.GenerativeModel("gemini-1.5-flash")
@@ -41,6 +41,7 @@ def gradio_interface(question):
     try:
         # Access the first candidate's content using attributes
         content = answer.candidates[0].content.parts[0].text
+        
         # Remove newline characters
         cleaned_content = content.replace("\n", ", ").strip()
     except (AttributeError, IndexError) as e: