Update app.py

app.py

@@ -21,93 +21,87 @@ MODEL_OPTIONS = [
     "liquid/lfm-40b:free"
 ]
 
-# History storage
+# Initialize history
 history = []
 
-def generate_comparisons_with_history(input_text, selected_models, history_state):
+def generate_text(input_text, selected_model, history_state):
     global history
-    results = {}
-    for model in selected_models:
-        response = requests.post(
-            url="https://openrouter.ai/api/v1/chat/completions",
-            headers={
-                "Authorization": f"Bearer {API_KEY}",
-                "Content-Type": "application/json"
-            },
-            data=json.dumps({
-                "model": model,  # Use the current model
-                "messages": [{"role": "user", "content": input_text}],
-                "top_p": 1,
-                "temperature": 1,
-                "frequency_penalty": 0,
-                "presence_penalty": 0,
-                "repetition_penalty": 1,
-                "top_k": 0,
-            })
-        )
-        
-        # Parse the response
-        if response.status_code == 200:
-            try:
-                response_json = response.json()
-                results[model] = response_json.get("choices", [{}])[0].get("message", {}).get("content", "No content returned.")
-            except json.JSONDecodeError:
-                results[model] = "Error: Unable to parse response."
-        else:
-            results[model] = f"Error: {response.status_code}, {response.text}"
+    response = requests.post(
+        url="https://openrouter.ai/api/v1/chat/completions",
+        headers={
+            "Authorization": f"Bearer {API_KEY}",
+            "Content-Type": "application/json"
+        },
+        data=json.dumps({
+            "model": selected_model,  # Use selected model
+            "messages": [{"role": "user", "content": input_text}],
+            "top_p": 1,
+            "temperature": 1,
+            "frequency_penalty": 0,
+            "presence_penalty": 0,
+            "repetition_penalty": 1,
+            "top_k": 0,
+        })
+    )
     
-    # Add input and results to history
+    # Handle errors
+    if response.status_code != 200:
+        return f"Error: {response.status_code}, {response.text}", history_state
+    
+    # Parse and return the content of the response
+    try:
+        response_json = response.json()
+        result = response_json.get("choices", [{}])[0].get("message", {}).get("content", "No content returned.")
+    except json.JSONDecodeError:
+        result = "Error: Unable to parse response."
+    
+    # Add the current interaction to the history
     history_entry = {
         "input": input_text,
-        "selected_models": selected_models,
-        "outputs": results
+        "selected_model": selected_model,
+        "response": result
     }
     history.append(history_entry)
     
     # Update the history state
     history_state = history
     
-    return results, history_state
-
-def clear_history():
-    global history
-    history = []
-    return history
-
-# Create Gradio interface with multiple model selection and history
-with gr.Blocks() as demo:
-    input_text = gr.Textbox(lines=2, label="Input Text", placeholder="Enter your query here")
-    selected_models = gr.CheckboxGroup(choices=MODEL_OPTIONS, label="Select Models", value=[MODEL_OPTIONS[0]])
-    
-    # Define output components with scrollable containers
-    output_comparisons = gr.JSON(label="Model Comparisons", elem_id="output-comparisons")
-    output_history = gr.JSON(label="History", elem_id="output-history")
+    # Prepare the formatted history string
+    formatted_history = "\n".join([f"Input: {entry['input']}\nModel: {entry['selected_model']}\nResponse: {entry['response']}\n" for entry in history])
     
-    clear_history_button = gr.Button("Clear History")
+    return result, formatted_history
 
-    # Add a button to clear the history
-    clear_history_button.click(clear_history, outputs=output_history)
-    
-    # Define the button to trigger generating comparisons
-    generate_button = gr.Button("Generate Comparisons")
-    generate_button.click(generate_comparisons_with_history, inputs=[input_text, selected_models, gr.State()], outputs=[output_comparisons, output_history])
+# Create Gradio interface with a dropdown for model selection
+iface = gr.Interface(
+    fn=generate_text,
+    inputs=[
+        gr.Textbox(lines=2, label="Input Text", placeholder="Enter your query here"),
+        gr.Dropdown(choices=MODEL_OPTIONS, label="Select Model", value=MODEL_OPTIONS[0]),
+        gr.State()
+    ],
+    outputs=[
+        gr.Textbox(label="Response", placeholder="Response will be shown here"),
+        gr.Textbox(label="History", placeholder="Interaction history will be shown here", lines=10, interactive=False)
+    ],
+    title="Chat with OpenRouter Models"
+)
 
-    # Insert custom CSS using gr.HTML()
-    gr.HTML("""
-        <style>
-            #output-comparisons {
-                height: 300px;
-                overflow: auto;
-                border: 1px solid #ddd;
-                padding: 10px;
-            }
-            #output-history {
-                height: 300px;
-                overflow: auto;
-                border: 1px solid #ddd;
-                padding: 10px;
-            }
-        </style>
-    """)
+# Insert custom CSS for scrollable sections
+iface.add_component(gr.HTML("""
+    <style>
+        #output-comparisons {
+            height: 300px;
+            overflow: auto;
+            border: 1px solid #ddd;
+            padding: 10px;
+        }
+        #output-history {
+            height: 300px;
+            overflow: auto;
+            border: 1px solid #ddd;
+            padding: 10px;
+        }
+    </style>
+"""))
 
-demo.launch()
+iface.launch()