Naz786/Smart-AI-Code-Assistant
2
1import streamlit as st2import difflib3import re4import requests5import datetime6import streamlit.components.v1 as components7 8# --- CONFIG ---9# Place your API keys here10GROQ_API_KEY = st.secrets.get('GROQ_API_KEY', 'YOUR_GROQ_API_KEY')11BLACKBOX_API_KEY = st.secrets.get('BLACKBOX_API_KEY', 'YOUR_BLACKBOX_API_KEY')12 13PROGRAMMING_LANGUAGES = ["Python", "JavaScript", "TypeScript", "Java", "C++", "C#"]14SKILL_LEVELS = ["Beginner", "Intermediate", "Expert"]15USER_ROLES = ["Student", "Frontend Developer", "Backend Developer", "Data Scientist"]16EXPLANATION_LANGUAGES = ["English", "Spanish", "Chinese", "Urdu"]17EXAMPLE_QUESTIONS = [18 "What does this function do?",19 "How can I optimize this code?",20 "What are the potential bugs in this code?",21 "How does this algorithm work?",22 "What design patterns are used here?",23 "How can I make this code more readable?"24]25 26LANGUAGE_KEYWORDS = {27 "Python": ["def ", "import ", "self", "print(", "lambda", "None"],28 "JavaScript": ["function ", "console.log", "var ", "let ", "const ", "=>"],29 "TypeScript": ["interface ", "type ", ": string", ": number", "export ", "import "],30 "Java": ["public class", "System.out.println", "void main", "import java.", "new "],31 "C++": ["#include", "std::", "cout <<", "cin >>", "int main(", "using namespace"],32 "C#": ["using System;", "namespace ", "public class", "Console.WriteLine", "static void Main"]33}34 35# --- API STUBS ---36def call_groq_api(prompt, model="llama3-70b-8192"):37 # Replace with actual Groq API call38 headers = {"Authorization": f"Bearer {GROQ_API_KEY}", "Content-Type": "application/json"}39 data = {"model": model, "messages": [{"role": "user", "content": prompt}]}40 response = requests.post("https://api.groq.com/openai/v1/chat/completions", json=data, headers=headers)41 if response.status_code == 200:42 return response.json()['choices'][0]['message']['content']43 else:44 return f"[Groq API Error] {response.text}"45 46def call_blackbox_agent(messages):47 url = "https://api.blackbox.ai/v1/chat/completions"48 headers = {49 "Content-Type": "application/json",50 "Authorization": f"Bearer {BLACKBOX_API_KEY}"51 }52 data = {53 "model": "code-chat",54 "messages": messages55 }56 response = requests.post(url, headers=headers, json=data)57 if response.status_code == 200:58 return response.json()["choices"][0]["message"]["content"]59 else:60 return call_groq_api(messages[-1]["content"])61 62# --- UTILS ---63def code_matches_language(code, language):64 keywords = LANGUAGE_KEYWORDS.get(language, [])65 return any(kw in code for kw in keywords)66 67def calculate_code_complexity(code):68 # Dummy complexity metric69 lines = code.count('\n') + 170 return f"{lines} lines"71 72def get_inline_diff(original, modified):73 diff = difflib.unified_diff(74 original.splitlines(),75 modified.splitlines(),76 lineterm='',77 fromfile='Original',78 tofile='Refactored'79 )80 return '\n'.join(diff)81 82def is_coding_question(question):83 """84 Uses Blackbox AI agent to check if the question is about programming/code.85 Returns True if yes, False otherwise.86 """87 messages = [88 {"role": "system", "content": "You are a helpful coding assistant."},89 {"role": "user", "content": f"Is the following question about programming or code? Answer only 'yes' or 'no'. Question: {question}"}90 ]91 try:92 response = call_blackbox_agent(messages)93 return 'yes' in response.lower()94 except Exception:95 return False96 97def get_explanation_prompt(code, programming_language, skill_level, user_role, explanation_language, question=None):98 lang_instruction = f" Respond in {explanation_language}." if explanation_language != "English" else ""99 if question:100 return f"{question}\n\nCode:\n{code}\n{lang_instruction}"101 return (102 f"Explain this {programming_language} code for a {skill_level} {user_role}.{lang_instruction}\n{code}"103 )104 105# --- SESSION STATE FOR CHAT HISTORY ---106if "workflow_history" not in st.session_state:107 st.session_state.workflow_history = []108if "semantic_history" not in st.session_state:109 st.session_state.semantic_history = []110if "comment_history" not in st.session_state:111 st.session_state.comment_history = []112 113# --- STREAMLIT APP ---114st.set_page_config(page_title="Code Workflows", layout="wide")115st.title("Code Genie")116 117# Navigation118page = st.sidebar.radio("Navigate", ["Home", "Code Workflows", "Semantic Search", "Code Comment Generator"])119 120if page == "Home":121 st.header("Welcome to the Code Genie!")122 st.markdown("""123 - **Full Code Workflow:** Complete code analysis pipeline with explanation, refactoring, review, and testing (powered by Groq/Blackbox)124 - **Semantic Search:** Ask natural language questions about your code and get intelligent answers125 - **Code Comment Generator:** Helps you add helpful comments to your code for better readability126 """)127 st.info("Select a feature from the sidebar to get started.")128 129elif page == "Code Workflows":130 st.header("Full Code Workflows")131 code_input = st.text_area("Paste your code here", height=200)132 uploaded_file = st.file_uploader("Or upload a code file", type=["py", "js", "ts", "java", "cpp", "cs"])133 if uploaded_file:134 code_input = uploaded_file.read().decode("utf-8")135 st.text_area("File content", code_input, height=200, key="file_content")136 col1, col2, col3, col4 = st.columns(4)137 with col1:138 programming_language = st.selectbox("Programming Language", PROGRAMMING_LANGUAGES)139 with col2:140 skill_level = st.selectbox("Skill Level", SKILL_LEVELS)141 with col3:142 user_role = st.selectbox("Your Role", USER_ROLES)143 with col4:144 explanation_language = st.selectbox("Explanation Language", EXPLANATION_LANGUAGES)145 if code_input:146 st.caption(f"Complexity: {calculate_code_complexity(code_input)}")147 if st.button("Run Workflow", type="primary"):148 if not code_input.strip():149 st.error("Please paste or upload your code.")150 elif not code_matches_language(code_input, programming_language):151 st.error(f"Language mismatch. Please check your code and language selection.")152 else:153 with st.spinner("Running AI Workflow..."):154 lang_instruction = f" Respond in {explanation_language}." if explanation_language != "English" else ""155 role_level_instruction = f" The user is a {skill_level} {user_role}."156 steps = [157 ("Explain", call_groq_api(get_explanation_prompt(code_input, programming_language, skill_level, user_role, explanation_language))),158 ("Refactor", call_blackbox_agent([159 {"role": "system", "content": "You are a helpful coding assistant."},160 {"role": "user", "content": f"Refactor this {programming_language} code for a {skill_level} {user_role}: {code_input}{lang_instruction}"}161 ])),162 ("Review", call_groq_api(f"Review this {programming_language} code for errors and improvements for a {skill_level} {user_role}: {code_input}{lang_instruction}")),163 ("ErrorDetection", call_groq_api(f"Find bugs in this {programming_language} code for a {skill_level} {user_role}: {code_input}{lang_instruction}")),164 ("TestGeneration", call_groq_api(f"Generate tests for this {programming_language} code for a {skill_level} {user_role}: {code_input}{lang_instruction}")),165 ]166 timeline = []167 for step, output in steps:168 timeline.append({"step": step, "output": output})169 st.success("Workflow complete!")170 for t in timeline:171 st.subheader(t["step"])172 st.write(t["output"])173 # Show code diff (dummy for now)174 st.subheader("Code Diff (Original vs Refactored)")175 refactored_code = steps[1][1] # Blackbox agent output176 st.code(get_inline_diff(code_input, refactored_code), language=programming_language.lower())177 # Download report178 report = f"AI Workflow Report\nGenerated on: {datetime.datetime.now()}\nLanguage: {programming_language}\nSkill Level: {skill_level}\nRole: {user_role}\n\n"179 for t in timeline:180 report += f"## {t['step']}\n{t['output']}\n\n---\n\n"181 st.download_button("Download Report", report, file_name="ai_workflow_report.txt")182 # Save to chat history183 st.session_state.workflow_history.append({184 "timestamp": str(datetime.datetime.now()),185 "user_code": code_input,186 "params": {187 "language": programming_language,188 "skill": skill_level,189 "role": user_role,190 "explanation_language": explanation_language191 },192 "timeline": timeline,193 "refactored_code": refactored_code194 })195 # Show chat history for workflows196 st.markdown("### Workflow Chat History")197 if st.button("Clear Workflow History"):198 st.session_state.workflow_history = []199 for entry in reversed(st.session_state.workflow_history):200 st.markdown(f"**[{entry['timestamp']}]**")201 st.code(entry["user_code"], language=entry["params"]["language"].lower())202 for t in entry["timeline"]:203 st.subheader(t["step"])204 st.write(t["output"])205 st.subheader("Code Diff (Original vs Refactored)")206 st.code(get_inline_diff(entry["user_code"], entry["refactored_code"]), language=entry["params"]["language"].lower())207 st.markdown("---")208 209elif page == "Semantic Search":210 st.header("Semantic Search")211 code_input = st.text_area("Paste your code here", height=200, key="sem_code")212 uploaded_file = st.file_uploader("Or upload a code file", type=["py", "js", "ts", "java", "cpp", "cs"], key="sem_file")213 if uploaded_file:214 code_input = uploaded_file.read().decode("utf-8")215 st.text_area("File content", code_input, height=200, key="sem_file_content")216 col1, col2, col3, col4 = st.columns(4)217 with col1:218 programming_language = st.selectbox("Programming Language", PROGRAMMING_LANGUAGES, key="sem_lang")219 with col2:220 skill_level = st.selectbox("Skill Level", SKILL_LEVELS, key="sem_skill")221 with col3:222 user_role = st.selectbox("Your Role", USER_ROLES, key="sem_role")223 with col4:224 explanation_language = st.selectbox("Explanation Language", EXPLANATION_LANGUAGES, key="sem_expl")225 226 st.caption("Example questions:")227 st.write(", ".join(EXAMPLE_QUESTIONS))228 229 # Only text input for question230 question = st.text_input("Ask a question about your code", key="sem_question")231 232 # Run Semantic Search button233 if st.button("Run Semantic Search"):234 if not code_input.strip() or not question.strip():235 st.error("Both code and question are required.")236 elif not code_matches_language(code_input, programming_language):237 st.error(f"Language mismatch. Please check your code and language selection.")238 else:239 with st.spinner("Running Semantic Search..."):240 prompt = get_explanation_prompt(code_input, programming_language, skill_level, user_role, explanation_language, question=question)241 answer = call_groq_api(prompt)242 st.success("Answer:")243 st.write(answer)244 # Save to chat history245 st.session_state.semantic_history.append({246 "timestamp": str(datetime.datetime.now()),247 "user_code": code_input,248 "question": question,249 "params": {250 "language": programming_language,251 "skill": skill_level,252 "role": user_role,253 "explanation_language": explanation_language254 },255 "answer": answer256 })257 # Show chat history for semantic search258 st.markdown("### Semantic Search Chat History")259 if st.button("Clear Semantic History"):260 st.session_state.semantic_history = []261 for entry in reversed(st.session_state.semantic_history):262 st.markdown(f"**[{entry['timestamp']}]**")263 st.code(entry["user_code"], language=entry["params"]["language"].lower())264 st.markdown(f"**Q:** {entry['question']}")265 st.markdown(f"**A:** {entry['answer']}")266 st.markdown("---")267 268elif page == "Code Comment Generator":269 st.header("Code Comment Generator")270 code_input = st.text_area("Paste your code here", height=200, key="comment_code")271 uploaded_file = st.file_uploader("Or upload a code file", type=["py", "js", "ts", "java", "cpp", "cs"], key="comment_file")272 if uploaded_file:273 code_input = uploaded_file.read().decode("utf-8")274 st.text_area("File content", code_input, height=200, key="comment_file_content")275 programming_language = st.selectbox("Programming Language", PROGRAMMING_LANGUAGES, key="comment_lang")276 if st.button("Generate Comments"):277 if not code_input.strip():278 st.error("Please paste or upload your code.")279 elif not code_matches_language(code_input, programming_language):280 st.error(f"Language mismatch. Please check your code and language selection.")281 else:282 with st.spinner("Generating commented code..."):283 lang_instruction = f" Respond in {explanation_language}." if explanation_language != "English" else ""284 role_level_instruction = f" The user is a {skill_level} {user_role}."285 prompt = (286 f"Add clear, helpful comments to this {programming_language} code for a {skill_level} {user_role}.{lang_instruction}\n\n"287 f"{code_input}"288 )289 commented_code = call_blackbox_agent([290 {"role": "system", "content": "You are a helpful coding assistant."},291 {"role": "user", "content": prompt}292 ])293 st.success("Commented code generated!")294 st.code(commented_code, language=programming_language.lower())295 st.download_button("Download Commented Code", commented_code, file_name="commented_code.txt")296 # Save to chat history297 st.session_state.comment_history.append({298 "timestamp": str(datetime.datetime.now()),299 "user_code": code_input,300 "params": {301 "language": programming_language,302 "skill": skill_level,303 "role": user_role,304 "explanation_language": explanation_language305 },306 "commented_code": commented_code307 })308 # Show chat history for code comments309 st.markdown("### Code Comment Chat History")310 if st.button("Clear Comment History"):311 st.session_state.comment_history = []312 for entry in reversed(st.session_state.comment_history):313 st.markdown(f"**[{entry['timestamp']}]**")314 st.code(entry["user_code"], language=entry["params"]["language"].lower())315 st.markdown("**Commented Code:**")316 st.code(entry["commented_code"], language=entry["params"]["language"].lower())317 st.markdown("---")318 319st.markdown("---")320 321 322def split_code_into_chunks(code, lang):323 if lang.lower() == "python":324 # Corrected regex pattern for Python code splitting325 pattern = r'(def\s+\w+\(.*?\):|class\s+\w+\(.*?\)?:)'326 splits = re.split(pattern, code)327 chunks = []328 for i in range(1, len(splits), 2):329 header = splits[i]330 body = splits[i+1] if (i+1) < len(splits) else ""331 chunks.append(header + body)332 return chunks if chunks else [code]333 else:334 return [code]