agent.py

# test.py

import os
from dotenv import load_dotenv
from github import Github, Auth

# LangChain imports
from langchain_groq import ChatGroq
from langchain_core.tools import tool
from langchain.agents import create_tool_calling_agent, AgentExecutor

# Load environment variables
load_dotenv()
GROQ_API_KEY = os.getenv("GROQ_API_KEY")
GITHUB_PAT = os.getenv("GITHUB_API_KEY")

if not (GROQ_API_KEY and GITHUB_PAT):
    raise ValueError("Please set GROQ_API_KEY and GITHUB_API_KEY in your .env")

# Initialize GitHub client
_auth = Auth.Token(GITHUB_PAT)
_gh = Github(auth=_auth)

# Define the GitHub tool
@tool
def get_repo_info(repo_name: str) -> str:
    """Fetch and summarize metadata about a GitHub repository."""
    try:
        repo = _gh.get_repo(repo_name)
    except Exception as e:
        return f" Error fetching '{repo_name}': {e}"

    name = repo.full_name
    desc = repo.description or "No description"
    url = repo.html_url
    owner = repo.owner.login
    stars = repo.stargazers_count
    forks = repo.forks_count
    issues = repo.open_issues_count
    created = repo.created_at.isoformat()
    updated = repo.updated_at.isoformat()
    watchers = repo.watchers_count
    default_br = repo.default_branch
    language = repo.language or "None"

    try:
        license_name = repo.get_license().license.name
    except:
        license_name = "None"

    topics = repo.get_topics()
    try:
        raw_md = repo.get_readme().decoded_content.decode("utf-8")
        snippet = raw_md[:300].replace("\n", " ") + "..."
    except:
        snippet = "No README found"

    contribs = repo.get_contributors()[:5]
    contrib_list = ", ".join(f"{c.login}({c.contributions})" for c in contribs)

    commits = repo.get_commits()[:3]
    commit_list = "; ".join(c.commit.message.split("\n")[0] for c in commits)

    return f"""
Repository: {name}
Description: {desc}
URL: {url}
Owner: {owner}
⭐ Stars: {stars}   🍴 Forks: {forks}   🐛 Open Issues: {issues}
👁️ Watchers: {watchers}   Default branch: {default_br}
⚙️ Language: {language}   License: {license_name}
🔍 Topics: {topics}

README Snippet: {snippet}

👥 Top Contributors: {contrib_list}
🧾 Latest Commits: {commit_list}
"""

# Instantiate the Groq LLM
llm = ChatGroq(
    model="llama-3.1-8b-instant",
    temperature=0.3,
    max_tokens=1024,
    api_key=GROQ_API_KEY,
)

# Define the tools to pass into the agent
tools = [get_repo_info]

# Pull default tool-calling agent prompt from LangChain hub
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder

prompt = ChatPromptTemplate.from_messages([
    ("system", 
     "You are GitHub Agent, an expert at analyzing repositories.\n"
     "When a user asks about a repo, call the tool and return a clear, concise summary of the repository based on the tool result.\n"
     "Avoid repeating raw tool output or adding unnecessary disclaimers.\n"
     "Respond in complete sentences, in natural language."
    ),
    MessagesPlaceholder(variable_name="chat_history", optional=True), 
    ("human", "{input}"),
    MessagesPlaceholder(variable_name="agent_scratchpad"),
])

# Create the agent using LangChain's legacy AgentExecutor approach
agent = create_tool_calling_agent(llm, tools, prompt)

# Run the agent
# At the bottom of test.py
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True, max_iterations=2)

# Export it
__all__ = ["agent_executor"]

# # Quick test
if __name__ == "__main__":
    import time
    user_input = "Give me details about the repo zamalali/deepgit"
    start_time = time.time()
    result = agent_executor.invoke({"input": user_input})
    end_time = time.time()
    print("\n Final Answer:\n", result["output"])
    print(f"\n Took {end_time - start_time:.2f} seconds")