Update app.py

app.py

@@ -1,10 +1,13 @@
-import os
 import subprocess
 import streamlit as st
 from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 import black
 from pylint import lint
 from io import StringIO
+import os
+import openai
+import json
+from streamlit_ace import st_ace
 
 # Set Hugging Face repository URL and project root path
 HUGGING_FACE_REPO_URL = "https://huggingface.co/spaces/acecalisto3/Mistri"
@@ -42,21 +45,18 @@ I am confident that I can leverage my expertise to assist you in developing and
         """
         return agent_prompt
 
-def autonomous_build(self, chat_history, workspace_projects):
-    """
-    Autonomous build logic based on chat history and workspace projects.
-    """
-    summary = "Chat History:\n" + '\n".join([f"User: {u}\nAgent: {a}" for u, a in chat_history])
-    summary += "\n\nWorkspace Projects:\n" + '\n'.join([f"{p}: {', '.join(ws_projects.keys())}" for p, ws_projects in workspace_projects.items()])
-
-    sentiment_analyzer = pipeline("sentiment-analysis")
-    sentiment_output = sentiment_analyzer(summary)[0]
-
-    # Use a Hugging Face model for more advanced logic
-    summarizer = pipeline("summarization")
-    next_step = summarizer(summary, max_length=50, min_length=25, do_sample=False)[0]['summary_text']
-
-    return summary, next_step
+    def autonomous_build(self, chat_history, workspace_projects):
+        """
+        Autonomous build logic based on chat history and workspace projects.
+        """
+        summary = "Chat History:\n" + '\n'.join([f"User: {u}\nAgent: {a}" for u, a in chat_history])
+        summary += "\n\nWorkspace Projects:\n" + '\n'.join([f"{p}: {', '.join(ws_projects.keys())}" for p, ws_projects in workspace_projects.items()])
+        sentiment_analyzer = pipeline("sentiment-analysis")
+        sentiment_output = sentiment_analyzer(summary)[0]
+        # Use a Hugging Face model for more advanced logic
+        summarizer = pipeline("summarization")
+        next_step = summarizer(summary, max_length=50, min_length=25, do_sample=False)[0]['summary_text']
+        return summary, next_step
 
 # Function to save an agent's prompt to a file and commit to the Hugging Face repository
 def save_agent_to_file(agent):
@@ -202,7 +202,11 @@ def sentiment_analysis(text):
 def translate_code(code, input_language, output_language):
     # Define a dictionary to map programming languages to their corresponding file extensions
     language_extensions = {
-        # Add language extensions here
+        "Python": ".py",
+        "JavaScript": ".js",
+        "C++": ".cpp",
+        "Java": ".java",
+        # Add more languages and extensions as needed
     }
 
     # Add code to handle edge cases such as invalid input and unsupported programming languages
@@ -329,16 +333,14 @@ elif app_mode == "Tool Box":
     source_language = st.text_input("Enter source language (e.g. 'Python'):")
     target_language = st.text_input("Enter target language (e.g. 'JavaScript'):")
     if st.button("Translate Code"):
-        translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-es")
-        translated_code = translator(code_to_translate, target_lang=target_language)[0]['translation_text']
+        translated_code = translate_code(code_to_translate, source_language, target_language)
         st.code(translated_code, language=target_language.lower())
 
     # Code Generation
     st.subheader("Code Generation")
     code_idea = st.text_input("Enter your code idea:")
     if st.button("Generate Code"):
-        generator = pipeline("text-generation", model="bigscience/T0_3B")
-        generated_code = generator(code_idea, max_length=100, num_return_sequences=1, do_sample=True)[0]['generated_text']
+        generated_code = generate_code(code_idea)
         st.code(generated_code, language="python")
 
     # Display Preset Commands
@@ -427,6 +429,28 @@ elif app_mode == "Workspace Chat App":
         st.write("Next Step:")
         st.write(next_step)
 
+    # Advanced Code Editor (Optional)
+    st.subheader("Advanced Code Editor")
+    selected_file = st.selectbox("Select a file from the workspace", st.session_state.workspace_projects[project_name]['files'])
+    file_path = os.path.join(PROJECT_ROOT, project_name, selected_file)
+    if os.path.exists(file_path):
+        with open(file_path, "r") as file:
+            file_content = file.read()
+        code_editor = st_ace(
+            file_content,
+            language="python",
+            theme="monokai",
+            height=300,
+            key="ace_editor",
+        )
+        if st.button("Save Changes"):
+            with open(file_path, "w") as file:
+                file.write(code_editor)
+            st.success(f"Changes saved to {selected_file}")
+            commit_and_push_changes(f"Update {selected_file}")
+    else:
+        st.warning(f"File {selected_file} not found in the workspace.")
+
 # Display current state for debugging
 st.sidebar.subheader("Current State")
 st.sidebar.json(st.session_state.current_state)