🚀 DevOS AI V2: CLI AI Codebase Analyzer

agents/debug_agent.py

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+from llm.provider import ask_llm
+
+
+def debug_error(file_path, model):
+    try:
+        with open(file_path, "r") as f:
+            error = f.read().strip()
+    except FileNotFoundError:
+        return f"❌ File not found: {file_path}"
+
+    if not error:
+        return "❌ Error file is empty"
+
+    prompt = f"""
+You are a senior software engineer.
+
+Debug this error:
+
+{error}
+
+Explain clearly:
+
+1. Root cause
+2. Why it happens
+3. Step-by-step fix
+4. Example fix
+"""
+
+    result = ask_llm(prompt, model)
+
+    if not result:
+        return "❌ No response from LLM"
+
+    return result

agents/search_agent.py

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+from core.parser import get_code_files
+from llm.provider import ask_llm
+
+
+def search_code(repo_path, query, model):
+    files = get_code_files(repo_path)
+
+    matches = []
+
+    for file in files:
+        try:
+            with open(file, "r", encoding="utf-8") as f:
+                lines = f.readlines()
+
+                for i, line in enumerate(lines):
+                    if query.lower() in line.lower():
+                        snippet = "".join(lines[max(0, i-2):i+3])
+
+                        matches.append(f"""
+FILE: {file}
+LINE: {i+1}
+CODE:
+{snippet}
+""")
+
+                        if len(matches) >= 5:
+                            break
+
+        except:
+            continue
+
+    if not matches:
+        return "❌ No matches found"
+
+    context = "\n\n".join(matches)
+
+    prompt = f"""
+You are a senior software engineer analyzing search results from a codebase.
+
+User query: "{query}"
+
+Code snippets:
+{context}
+
+IMPORTANT:
+- Do NOT describe prompts or text
+- Focus on actual code logic
+- Ignore placeholder strings
+
+Give a professional answer:
+
+1. Relevant functionality found
+- What real functionality matches the query
+
+2. Where it exists
+- File names and modules
+
+3. How it works
+- Explain logic of code (not text)
+
+4. Summary
+- What developer should understand from this
+
+Be precise, technical, and useful.
+"""
+
+    result = ask_llm(prompt, model)
+
+    if not result or "❌" in result:
+        return "❌ No meaningful response from LLM for search"
+
+    return result

cli/main.py

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+import sys
+from core.engine import build_context, build_prompt
+from llm.provider import ask_llm
+from agents.debug_agent import debug_error
+from agents.search_agent import search_code
+
+
+def explain(path, model):
+    context = build_context(path)
+    prompt = build_prompt(context, "Explain this codebase")
+    return ask_llm(prompt, model)
+
+
+def main():
+    if len(sys.argv) < 3:
+        print("""
+Usage:
+  explain <path> [--model openrouter|google|auto]
+  search <path> "<query>" [--model openrouter|google|auto]
+  debug <file> [--model openrouter|google|auto]
+""")
+        return
+
+    command = sys.argv[1]
+    model = "auto"
+
+    if "--model" in sys.argv:
+        idx = sys.argv.index("--model")
+        if idx + 1 < len(sys.argv):
+            model = sys.argv[idx + 1]
+
+    print("🔍 Processing...\n")
+
+    if command == "explain":
+        result = explain(sys.argv[2], model)
+
+    elif command == "search":
+        result = search_code(sys.argv[2], sys.argv[3], model)
+
+    elif command == "debug":
+        result = debug_error(sys.argv[2], model)
+
+    else:
+        result = "❌ Unknown command"
+
+    print("💡 Result:\n")
+    print(result)
+
+
+if __name__ == "__main__":
+    main()

core/engine.py

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+from core.parser import get_code_files, read_files
+
+PRIORITY = ["main", "app", "engine", "cli", "api"]
+
+
+def rank_files(files):
+    scored = []
+
+    for f in files:
+        score = 0
+        name = f.lower()
+
+        for p in PRIORITY:
+            if p in name:
+                score += 5
+
+        if "core" in name or "llm" in name:
+            score += 3
+
+        scored.append((score, f))
+
+    scored.sort(reverse=True)
+    return [f for _, f in scored]
+
+
+def build_context(repo_path):
+    files = get_code_files(repo_path)
+    ranked = rank_files(files)
+
+    top_files = ranked[:5]
+    return read_files(top_files)
+
+
+def build_prompt(context, question):
+    return f"""
+You are a senior software engineer analyzing a real codebase.
+
+STRICT RULES:
+- Use ONLY the given code context
+- Do NOT assume missing features
+- Do NOT mention technologies not present in context
+
+CONTEXT:
+{context}
+
+TASK:
+{question}
+
+Respond in this format:
+
+1. Purpose
+- What this system actually does (based only on code)
+
+2. Architecture
+- Real structure (modules, flow)
+
+3. Key Components
+- Explain actual files/modules found
+
+4. Execution Flow
+- Step-by-step how system works
+
+Keep answer precise, technical, and grounded in code.
+"""

core/parser.py

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+import os
+
+IGNORE_DIRS = {
+    ".venv", "__pycache__", ".git", "node_modules",
+    "dist", "build",
+    "apps",        
+    "frontend",    
+    "infrastructure"
+}
+
+EXTENSIONS = (".py", ".js", ".ts", ".tsx")
+
+
+def get_code_files(repo_path):
+    code_files = []
+
+    for root, dirs, files in os.walk(repo_path):
+        dirs[:] = [d for d in dirs if d not in IGNORE_DIRS]
+
+        for file in files:
+            if file.endswith(EXTENSIONS):
+                code_files.append(os.path.join(root, file))
+
+    return code_files
+
+
+def read_files(files, max_chars=800):
+    contents = []
+
+    for file in files:
+        try:
+            with open(file, "r", encoding="utf-8") as f:
+                text = f.read()[:max_chars]
+                contents.append(f"\n# FILE: {file}\n{text}")
+        except:
+            continue
+
+    return "\n\n".join(contents)

llm/provider.py

@@ -0,0 +1,95 @@
+import os
+import requests
+from dotenv import load_dotenv
+
+load_dotenv()
+
+OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+
+
+def ask_openrouter(prompt):
+    if not OPENROUTER_API_KEY:
+        return None
+
+    try:
+        res = requests.post(
+            "https://openrouter.ai/api/v1/chat/completions",
+            headers={
+                "Authorization": f"Bearer {OPENROUTER_API_KEY}",
+                "Content-Type": "application/json"
+            },
+            json={
+                "model": "openai/gpt-3.5-turbo",
+                "messages": [{"role": "user", "content": prompt}]
+            },
+            timeout=20
+        )
+
+        data = res.json()
+
+        if "choices" in data:
+            return data["choices"][0]["message"]["content"]
+
+        return None
+
+    except:
+        return None
+
+
+def ask_google(prompt):
+    if not GOOGLE_API_KEY:
+        return None
+
+    try:
+        res = requests.post(
+            f"https://generativelanguage.googleapis.com/v1/models/gemini-2.5-flash:generateContent?key={GOOGLE_API_KEY}",
+            headers={"Content-Type": "application/json"},
+            json={
+                "contents": [{"parts": [{"text": prompt}]}]
+            },
+            timeout=30
+        )
+
+        data = res.json()
+
+        if "candidates" in data:
+            return data["candidates"][0]["content"]["parts"][0]["text"]
+
+        return None
+
+    except:
+        return None
+
+
+def ask_llm(prompt, model="auto"):
+
+    def clean(res):
+        if not res:
+            return None
+        res = str(res).strip()
+        return res if len(res) > 10 else None   # IMPORTANT
+
+    # -------- OPENROUTER --------
+    if model == "openrouter":
+        res = clean(ask_openrouter(prompt))
+        return res if res else "❌ OpenRouter returned empty response"
+
+    # -------- GOOGLE --------
+    if model == "google":
+        res = clean(ask_google(prompt))
+        return res if res else "❌ Google returned empty response"
+
+    # -------- AUTO MODE --------
+    if model == "auto":
+        res = clean(ask_openrouter(prompt))
+        if res:
+            return res
+
+        res = clean(ask_google(prompt))
+        if res:
+            return res
+
+        return "❌ All LLM providers failed or returned empty"
+
+    return "❌ Invalid model"