Update app.py

app.py

@@ -86,6 +86,9 @@ class AIAgent:
             "READ_PROMPT": self.read_prompt,
             "TASK_PROMPT": self.task_prompt,
             "UNDERSTAND_TEST_RESULTS_PROMPT": self.understand_test_results_prompt,
+            "EXECUTE_COMMAND": self.execute_command,  # Add command execution
+            "PYTHON_INTERPRET": self.python_interpret,  # Add Python interpretation
+            "NLP": self.nlp,  # Add NLP capabilities
         }
         self.task_history: List[Dict[str, str]] = []
         self.current_task: Optional[str] = None
@@ -99,6 +102,7 @@ class AIAgent:
             "bigscience/T0_3B",
         ]  # Add more as needed
         self.selected_model = "gpt2"  # Default model
+        self.nlp_pipeline = None  # Initialize NLP pipeline later
 
     # --- Search Functionality ---
     def search(self, query: str) -> List[str]:
@@ -251,6 +255,12 @@ class AIAgent:
                 return "Enter the new task to start."
             elif action == "UNDERSTAND_TEST_RESULTS_PROMPT":
                 return "Enter your question about the test results."
+            elif action == "EXECUTE_COMMAND":
+                return "Enter the command to execute."
+            elif action == "PYTHON_INTERPRET":
+                return "Enter the Python code to interpret."
+            elif action == "NLP":
+                return "Enter the text for NLP analysis."
             else:
                 raise InvalidActionError("Please provide a valid action.")
         except InvalidActionError as e:
@@ -314,6 +324,39 @@ class AIAgent:
         """Provides a prompt to understand the test results."""
         return "What do you want to know about the test results?"
 
+    # --- Command Execution Functionality ---
+    def execute_command(self, command: str) -> str:
+        """Executes the provided command in the terminal."""
+        try:
+            process = subprocess.run(
+                command.split(), capture_output=True, text=True
+            )
+            return f"Command output:\n{process.stdout}"
+        except subprocess.CalledProcessError as e:
+            return f"Error executing command: {e}"
+
+    # --- Python Interpretation Functionality ---
+    def python_interpret(self, code: str) -> str:
+        """Interprets the provided Python code."""
+        try:
+            exec(code)
+            return "Python code executed successfully."
+        except Exception as e:
+            return f"Error interpreting Python code: {e}"
+
+    # --- NLP Functionality ---
+    def nlp(self, text: str) -> str:
+        """Performs NLP analysis on the provided text."""
+        try:
+            if not self.nlp_pipeline:
+                self.nlp_pipeline = pipeline(
+                    "sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-5-lit"
+                )  # Example NLP pipeline
+            analysis = self.nlp_pipeline(text)
+            return f"NLP Analysis: {analysis}"
+        except Exception as e:
+            return f"Error performing NLP analysis: {e}"
+
     # --- Input Handling Functionality ---
     def handle_input(self, input_str: str):
         """Handles user input and executes the corresponding action."""
@@ -401,64 +444,111 @@ if __name__ == "__main__":
         layout="wide",
         initial_sidebar_state="expanded",
     )
-    st.title("AI Agent")
-    st.sidebar.title("Agent Settings")
-
-    # --- Command Dropdown ---
-    command_options = [
-        "SEARCH",
-        "CODEGEN",
-        "REFINE-CODE",
-        "TEST-CODE",
-        "INTEGRATE-CODE",
-        "TEST-APP",
-        "GENERATE-REPORT",
-        "WORKSPACE-EXPLORER",
-        "ADD_PROMPT",
-        "ACTION_PROMPT",
-        "COMPRESS_HISTORY_PROMPT",
-        "LOG_PROMPT",
-        "LOG_RESPONSE",
-        "MODIFY_PROMPT",
-        "PREFIX",
-        "SEARCH_QUERY",
-        "READ_PROMPT",
-        "TASK_PROMPT",
-        "UNDERSTAND_TEST_RESULTS_PROMPT",
-    ]
-    selected_command = st.sidebar.selectbox("Command", command_options)
-
-    # --- Model Dropdown ---
-    selected_model = st.sidebar.selectbox(
-        "Model", agent.available_models, index=agent.available_models.index(agent.selected_model)
-    )
-    agent.selected_model = selected_model
-
-    # --- Input Field ---
-    input_str = st.text_input(f"Enter input for {selected_command}:")
-
-    # --- Execute Command ---
-    if st.button("Execute"):
-        if input_str:
-            agent.handle_input(f"{selected_command} {input_str}")
-            st.write(f"Output: {agent.task_history[-1]['output']}")
-
-    # --- Task History ---
-    st.subheader("Task History")
-    for task in agent.task_history:
-        st.write(f"**Action:** {task['action']}")
-        st.write(f"**Input:** {task['input']}")
-        st.write(f"**Output:** {task['output']}")
-
-    # --- Workspace Explorer ---
-    st.subheader("Workspace Explorer")
-    with st.expander("Explore Workspace"):
-        try:
-            workspace_output = agent.workspace_explorer()
-            st.write(workspace_output)
-        except WorkspaceExplorerError as e:
-            st.error(f"Error exploring workspace: {e}")
 
+    # --- Tabbed Navigation ---
+    tabs = st.tabs(["Agent Generation", "Chat App"])
+
+    # --- Agent Generation Tab ---
+    with tabs[0]:
+        st.title("AI Agent Generation")
+        st.sidebar.title("Agent Settings")
+
+        # --- Command Dropdown ---
+        command_options = [
+            "SEARCH",
+            "CODEGEN",
+            "REFINE-CODE",
+            "TEST-CODE",
+            "INTEGRATE-CODE",
+            "TEST-APP",
+            "GENERATE-REPORT",
+            "WORKSPACE-EXPLORER",
+            "ADD_PROMPT",
+            "ACTION_PROMPT",
+            "COMPRESS_HISTORY_PROMPT",
+            "LOG_PROMPT",
+            "LOG_RESPONSE",
+            "MODIFY_PROMPT",
+            "PREFIX",
+            "SEARCH_QUERY",
+            "READ_PROMPT",
+            "TASK_PROMPT",
+            "UNDERSTAND_TEST_RESULTS_PROMPT",
+        ]
+        selected_command = st.sidebar.selectbox("Command", command_options)
+
+        # --- Model Dropdown ---
+        selected_model = st.sidebar.selectbox(
+            "Model",
+            agent.available_models,
+            index=agent.available_models.index(agent.selected_model),
+        )
+        agent.selected_model = selected_model
+
+        # --- Input Field ---
+        input_str = st.text_input(f"Enter input for {selected_command}:")
+
+        # --- Execute Command ---
+        if st.button("Execute"):
+            if input_str:
+                agent.handle_input(f"{selected_command} {input_str}")
+                st.write(f"Output: {agent.task_history[-1]['output']}")
+
+        # --- Task History ---
+        st.subheader("Task History")
+        for task in agent.task_history:
+            st.write(f"**Action:** {task['action']}")
+            st.write(f"**Input:** {task['input']}")
+            st.write(f"**Output:** {task['output']}")
+
+        # --- Workspace Explorer ---
+        st.subheader("Workspace Explorer")
+        with st.expander("Explore Workspace"):
+            try:
+                workspace_output = agent.workspace_explorer()
+                st.write(workspace_output)
+            except WorkspaceExplorerError as e:
+                st.error(f"Error exploring workspace: {e}")
+
+    # --- Chat App Tab ---
+    with tabs[1]:
+        st.title("Chat App")
+
+        # --- Chat History ---
+        chat_history = st.empty()
+        chat_history.text("Chat History:")
+
+        # --- Input Field ---
+        user_input = st.text_input("Enter your message:")
+
+        # --- Send Message ---
+        if st.button("Send"):
+            if user_input:
+                # --- Display User Message ---
+                chat_history.text(f"You: {user_input}")
+
+                # --- Process User Input ---
+                try:
+                    # --- Extract Command and Arguments ---
+                    action, *args = user_input.split()
+                    if action in agent.tools:
+                        if args:
+                            output = agent.tools[action](" ".join(args))
+                        else:
+                            output = agent.tools[action]()
+                        # --- Display Agent Response ---
+                        chat_history.text(f"Agent: {output}")
+                    else:
+                        # --- Treat as regular chat message ---
+                        output = agent.code_generation(user_input)
+                        # --- Display Agent Response ---
+                        chat_history.text(f"Agent: {output}")
+                except Exception as e:
+                    # --- Display Error Message ---
+                    chat_history.text(f"Agent: Error: {e}")
+
+                # --- Clear Input Field ---
+                user_input = ""
 
 # --- Gradio Integration ---
 def gradio_interface(input_text):