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Create agent.py
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agent.py
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import os
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from typing import Optional
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from crewai import Agent, Task, Crew, Process
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from crewai_tools import GithubSearchTool
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from google import genai # Google's Gemini client
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# ---------------------------
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# CONFIG
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# ---------------------------
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# Required environment variables
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GITHUB_TOKEN = os.getenv("GITHUB_TOKEN")
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GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") # from AI Studio
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DEFAULT_CONTENT_TYPES = ["code", "pr", "issue", "repo"]
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# Gemini client setup
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if not GOOGLE_API_KEY:
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raise ValueError("❌ Missing GOOGLE_API_KEY (get one from https://aistudio.google.com)")
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client = genai.Client(api_key=GOOGLE_API_KEY)
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MODEL_NAME = os.getenv("GEMINI_MODEL", "gemini-1.5-flash") # fast & cheap
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# ---------------------------
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# Custom Gemini-backed LLM wrapper
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# ---------------------------
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class GeminiLLM:
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def __init__(self, model: str):
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self.model = model
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def generate(self, prompt: str) -> str:
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"""CrewAI-compatible .generate() interface."""
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try:
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response = client.models.generate_content(
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model=self.model,
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contents=prompt,
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generation_config={"temperature": 0.7}
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)
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return response.text
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except Exception as e:
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return f"⚠️ Gemini API error: {e}"
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# Instantiate a Gemini LLM
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gemini_llm = GeminiLLM(MODEL_NAME)
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# ---------------------------
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# GithubSearchTool
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# ---------------------------
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def github_tool(repo_url: Optional[str] = None) -> GithubSearchTool:
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if not GITHUB_TOKEN:
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raise RuntimeError("Missing GITHUB_TOKEN in environment.")
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if repo_url:
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return GithubSearchTool(
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github_repo=repo_url,
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gh_token=GITHUB_TOKEN,
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content_types=DEFAULT_CONTENT_TYPES,
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)
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return GithubSearchTool(
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gh_token=GITHUB_TOKEN,
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content_types=DEFAULT_CONTENT_TYPES,
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)
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# ---------------------------
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# Agents
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# ---------------------------
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def make_agents(repo_url: str):
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repo_search = github_tool(repo_url)
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repo_mapper = Agent(
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role="Repository Mapper",
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goal="Map repository structure, dependencies, and build tools.",
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backstory="Understands folder trees and project metadata deeply.",
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tools=[repo_search],
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llm=gemini_llm,
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verbose=True,
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)
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code_reviewer = Agent(
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role="Code Reviewer",
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goal="Perform detailed code reviews for quality, readability, and maintainability.",
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backstory="An experienced engineer identifying refactors and anti-patterns.",
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tools=[repo_search],
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llm=gemini_llm,
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verbose=True,
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)
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security_auditor = Agent(
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role="Security Auditor",
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goal="Detect security vulnerabilities, secrets, and risky dependencies.",
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backstory="Thinks like a red team but reports like a white hat.",
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tools=[repo_search],
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llm=gemini_llm,
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verbose=True,
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)
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doc_explainer = Agent(
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role="Documentation Explainer",
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goal="Explain project architecture, flow, and quickstart guide.",
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backstory="A great teacher simplifying complex systems.",
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tools=[repo_search],
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llm=gemini_llm,
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verbose=True,
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)
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manager = Agent(
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role="Engineering Manager",
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goal="Coordinate all other agents and compile a cohesive final report.",
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backstory="A senior manager ensuring thoroughness and clarity.",
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allow_delegation=True,
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llm=gemini_llm,
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verbose=True,
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)
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return repo_mapper, code_reviewer, security_auditor, doc_explainer, manager
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# ---------------------------
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# Tasks
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# ---------------------------
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def make_tasks(repo_url: str, brief: str = ""):
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preface = f"Target repository: {repo_url}\n{brief}\nPrefer file references and clear sections."
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t_map = Task(
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description=f"{preface}\nMap repo structure and dependencies.",
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expected_output="Markdown summary of repo structure.",
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agent_role="Repository Mapper",
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)
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t_review = Task(
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description=f"{preface}\nCode review with key issues, refactors, and suggestions.",
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expected_output="Concise bullet-based code review with examples.",
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agent_role="Code Reviewer",
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)
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t_sec = Task(
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description=f"{preface}\nSecurity audit (secrets, unsafe libs, injections, etc.).",
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expected_output="Security findings in table format.",
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agent_role="Security Auditor",
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)
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t_doc = Task(
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description=f"{preface}\nExplain architecture, modules, and how to run the project.",
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expected_output="Readable architecture explanation and quickstart.",
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agent_role="Documentation Explainer",
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)
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t_merge = Task(
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description="Merge all findings into one cohesive Markdown report with clear sections.",
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expected_output="Final Markdown report.",
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agent_role="Engineering Manager",
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)
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return t_map, t_review, t_sec, t_doc, t_merge
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# ---------------------------
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# Runner
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# ---------------------------
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def run_repo_review(repo_url: str, brief: str = "") -> str:
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repo_mapper, reviewer, auditor, explainer, manager = make_agents(repo_url)
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| 158 |
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t_map, t_review, t_sec, t_doc, t_merge = make_tasks(repo_url, brief)
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| 159 |
+
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crew = Crew(
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| 161 |
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agents=[repo_mapper, reviewer, auditor, explainer, manager],
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tasks=[t_map, t_review, t_sec, t_doc, t_merge],
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| 163 |
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process=Process.hierarchical,
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| 164 |
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manager_agent=manager,
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| 165 |
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verbose=True,
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)
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| 167 |
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result = crew.kickoff()
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| 168 |
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return str(result)
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