Update app.py

app.py

@@ -1,25 +1,60 @@
 import gradio as gr
 import subprocess
 from gradio.mix import Parallel
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import os
+import openai
+import json
 
-def qa_prompting(model):
-    # Call your `run_llm.py` script for QA-Based Prompting with the selected model
-    output = subprocess.check_output([sys.executable, "run_llm.py", "--model", model, ...], text=True)
-    return output
+# Set your OpenAI API key
+openai.api_key = "your_openai_api_key"
 
-def strategy_1_interface():
-    model_names = ["ChatGPT", "LLaMA", "Vicuna", "Alpaca", "Flan-T5"]
-    interfaces = []
-    for model_name in model_names:
-        interfaces.append(gr.Interface(
-            fn=qa_prompting,
-            inputs=gr.inputs.Textbox(label=f"{model_name} Input"),
-            outputs=gr.outputs.Textbox(label=f"{model_name} Output"),
-            title=f"Strategy 1 - QA-Based Prompting: {model_name}",
-        ))
+# Define a list of models you want to use
+models = {
+    "ChatGPT": "gpt3.5-turbo-0613",
+    "LLaMA": "lmsys/llama-13b",
+    "Vicuna": "lmsys/vicuna-13b-v1.3",
+    "Alpaca": "lmsys/alpaca-7B",
+    "Flan-T5": "lmsys/fastchat-t5-3b-v1.0",
+}
 
-    return Parallel(*interfaces)
+# Define a function to run your `run_llm.py` script with the selected model
+def run_llm(model, text, prompt_type):
+    if "ChatGPT" in model:
+        # Use your `run_llm.py` script for ChatGPT
+        script = "python run_llm.py ... --model {} --text '{}' --prompt_type {}".format(
+            model, text, prompt_type
+        )
+    else:
+        # Use your `run_llm.py` script for other models
+        script = "python run_llm.py ... --model {} --text '{}' --prompt_type {}".format(
+            models[model], text, prompt_type
+        )
+
+    result = subprocess.check_output(script, shell=True, text=True)
+    return result
+
+# Create a Gradio interface for each model and each strategy
+interfaces = {}
+for model in models:
+    for strategy in range(1, 4):
+        name = f"{model} - Strategy {strategy}"
+        interface = gr.Interface(
+            fn=Parallel(
+                run_llm, model=model, prompt_type=strategy
+            ),
+            inputs="textbox",
+            outputs="text",
+            title=name,
+            live=True,
+        )
+        interfaces[name] = interface
 
 if __name__ == "__main__":
-    iface = strategy_1_interface()
-    iface.launch()
+    gr.Interface(
+        [interfaces[name] for name in interfaces],
+        title="LLM Strategies",
+        live=True,
+        share=True,
+        server_port=7860,
+    ).launch()