Update app.py

app.py

@@ -32,6 +32,8 @@ history = []
 def gen_from_infer(purpose,history,image,model_drop,chat_drop,choice):
     #out_img = infer(out_prompt)
     history.clear()
+    if seed == 0:
+        seed = random.randint(1,1111111111111111)
     out_prompt=generate(purpose,history,chat_drop)
     history.append((purpose,out_prompt))
     yield (history,None)        
@@ -60,11 +62,12 @@ def format_prompt(message, history):
   prompt += f"[INST] {message} [/INST]"
   return prompt
 
-def run_gpt(in_prompt,history,model_drop):
+def run_gpt(in_prompt,history,model_drop,seed=0):
     client = InferenceClient(c_models[int(model_drop)])
     print(f'history :: {history}')
     prompt=format_prompt(in_prompt,history)
-    seed = random.randint(1,1111111111111111)
+    if seed == 0:
+        seed = random.randint(1,1111111111111111)
     print (seed)
     generate_kwargs = dict(
         temperature=1.0,
@@ -82,7 +85,7 @@ def run_gpt(in_prompt,history,model_drop):
         resp += response.token.text
     return resp
     
-def run_idefics(in_prompt,history,model_drop):
+def run_idefics(in_prompt,history,model_drop,seed):
     client = InferenceClient("HuggingFaceM4/idefics-9b-instruct")
     print(f'history :: {history}')
     prompt=format_prompt(in_prompt,history)
@@ -106,21 +109,21 @@ def run_idefics(in_prompt,history,model_drop):
     return resp
 
 
-def generate(purpose,history,chat_drop):
+def generate(purpose,history,chat_drop,seed):
     print (history)
-    out_prompt = run_gpt(purpose,history,chat_drop)
+    out_prompt = run_gpt(purpose,history,chat_drop,seed)
     return out_prompt
 
-def describe(purpose,history,image,chat_drop):
+def describe(purpose,history,image,chat_drop,seed):
     print (history)
     purpose=f"{purpose},![]({image})"
     out_prompt = run_idefics(purpose,history,chat_drop)
     return out_prompt
    
-def run(purpose,history,image,model_drop,chat_drop,choice):
+def run(purpose,history,image,model_drop,chat_drop,choice,seed):
     if choice == "Generate":
         #out_img = infer(out_prompt)
-        out_prompt=generate(purpose,history,chat_drop)
+        out_prompt=generate(purpose,history,chat_drop,seed)
         history.append((purpose,out_prompt))
         yield (history,None)        
         model=loaded_model[int(model_drop)]
@@ -142,7 +145,7 @@ def run(purpose,history,image,model_drop,chat_drop,choice):
             yield ([(purpose,"an Error occured")],None)
     if choice == "Describe":
         #out_img = infer(out_prompt)
-        out_prompt=describe(purpose,history,image,model_drop,chat_drop)
+        out_prompt=describe(purpose,history,image,model_drop,chat_drop,seed)
         history.append((purpose,out_prompt))
         yield (history,None)        
         
@@ -173,6 +176,11 @@ with gr.Blocks(css=style) as iface:
             msg = gr.Textbox()
             model_drop=gr.Dropdown(label="Diffusion Models", type="index", choices=[m for m in models], value=models[0])
             chat_model_drop=gr.Dropdown(label="Chatbot Models", type="index", choices=[m for m in c_models], value=c_models[0])
+            chat_seed=gr.Slider(label="Seed (0 for random)", minimum=0,maximum=1000000000000,
+                                value=random.randint(1,1000000000000),step=1,
+                                interactive=True,
+                               info="Set Seed to 0 to randomize the session")
+
             with gr.Group():
                 with gr.Row():
                     submit_b = gr.Button()
@@ -184,7 +192,7 @@ with gr.Blocks(css=style) as iface:
 
     run_test = test_btn.click(gen_from_infer, [msg,chatbot,sumbox,model_drop,chat_model_drop,agent_choice],[chatbot,sumbox],concurrency_limit=20)
     
-    sub_b = submit_b.click(run, [msg,chatbot,sumbox,model_drop,chat_model_drop,agent_choice],[chatbot,sumbox],concurrency_limit=20)
-    sub_e = msg.submit(run, [msg, chatbot,sumbox,model_drop,chat_model_drop,agent_choice], [chatbot,sumbox],concurrency_limit=20)
+    sub_b = submit_b.click(run, [msg,chatbot,sumbox,model_drop,chat_model_drop,agent_choice,seed],[chatbot,sumbox],concurrency_limit=20)
+    sub_e = msg.submit(run, [msg, chatbot,sumbox,model_drop,chat_model_drop,agent_choice,seed], [chatbot,sumbox],concurrency_limit=20)
     stop_b.click(None,None,None, cancels=[sub_b,sub_e])
 iface.queue(default_concurrency_limit=None).launch()