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Sumeet Dugg
Sumeet Dugg

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Context-Aware Code Summarizer

#hermesagentchallenge #devchallenge #agents

Hermes Agent Challenge Submission: Build With Hermes Agent

This is a submission for the Hermes Agent Challenge: Build With Hermes Agent

What I Built

A static analysis and documentation tool that scans Python project directories, tracks file-level changes using MD5 hashing, extracts structural metadata via AST parsing, and maintains a persistent skeleton cache of your codebase.

Overview

This tool monitors a target project directory for modifications across watched file extensions. When changes are detected, it re-parses affected Python files to extract class definitions, method signatures, and docstrings, then writes the updated structural index back to a persistent JSON cache. A secondary file crawler leverages the Hermes Agent shell environment for direct file read operations within active terminal sessions.

Features

  • Directory scanning with configurable exclusion lists and file extension filters
  • MD5-based change detection to avoid redundant re-parsing
  • AST-based extraction of classes, methods, functions, and module docstrings
  • Persistent skeleton cache stored as a JSON index file
  • Automatic purging of deleted file entries from the cache
  • Shell-integrated file reading via the Hermes Agent terminal and file operations tools
  • Configurable local LLM backend via llama-server (supports GGUF models)

Project Structure 

project-root/
|-- components/
|   |-- crawler.py            # Core directory scanner and change tracker
|   |-- fileReadCrawler.py    # Shell-integrated file reader using Hermes Agent
|   |-- parser.py             # AST-based Python code parser
|-- main.py                   # Entry point and user input handler
|-- server.bat                # llama-server startup script (Windows)
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Configuration

The tool expects a config.json file in your designated config directory. Supported keys:

Key Type Default Description
exclude_dirs list of strings [".git", "__pycache__", "venv"] Directories to skip during scanning
watch_extensions list of strings [".py", ".json", ".md"] File extensions to monitor
output_dir string "docs" Directory where generated documentation is saved
project_name string "System" Project name used in generated output headers
target_file string "ARCHITECTURE.md" Output documentation file name

Example config.json:

{
  "exclude_dirs": [".git", "__pycache__", "venv", "node_modules"],
  "watch_extensions": [".py", ".json", ".md"],
  "output_dir": "docs",
  "project_name": "MyProject",
  "target_file": "ARCHITECTURE.md"
}
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Usage

Run the tool from the project root:

python main.py
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You will be prompted for three paths:

  1. Target project path - the root directory of the project you want to scan
  2. Config directory path - the directory containing your config.json
  3. Skeleton cache path - the directory where project_skeleton.json will be stored

Paths can be pasted directly (including drag-and-drop paths with surrounding quotes; these are stripped automatically).

Code

Github : https://github.com/sumeetpypi/Hermes-Agent-Context-Aware-Code-Summarizer.git

My Tech Stack

Requirements

  • Python 3.9 or higher
  • Hermes Agent package (hermes_agent) with terminal_tool and file_operations modules
  • llama.cpp server binary (for local LLM backend, optional)
  • A GGUF-format model file if using the local inference server

How I Used Hermes Agent

Hermes Agent Integration

The ProjectFileCrawler class reads files via ShellFileOperations, which requires an active Hermes Agent terminal session. A terminal session must be initialized before constructing a ProjectFileCrawler instance, as the crawler extracts the active environment from the _active_environments global registry.

If no active environment is found, a RuntimeError is raised with the message:

AIAgent to create markdown files

No active environment sessions found. Run a terminal_tool command first.
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Local LLM Server (Windows)

The included server.bat launches a llama-server instance for local inference. Edit the MODEL_PATH variable to point to your GGUF model file before running.

Default settings:

Parameter Value
Context size 8192
Port 8080
Threads 12

To start the server:

server.bat
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Hermes Agent: Editing MINIMUM_CONTEXT_LENGTH

To modify the MINIMUM_CONTEXT_LENGTH variable used by the Hermes Agent for metadata file processing, locate the configuration or constants file within the hermes_agent package (typically hermes_agent/config.py or hermes_agent/constants.py) and update the variable directly:

# hermes_agent/config.py (or constants.py)
MINIMUM_CONTEXT_LENGTH = 512  # Set to your required minimum token count
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To allow the agent to locate and edit this value dynamically at runtime, pass an updated max_tokens value when constructing the agent or calling the relevant tool. The agent reads MINIMUM_CONTEXT_LENGTH to decide whether the current context window is large enough to process a metadata file. If the context is below this threshold, the agent will skip or defer the operation.

If you are extending the Hermes Agent to support editing this variable programmatically, add a configuration setter in the agent initialization path and expose it as a parameter in the tool interface.

Known Limitations

  • Non-Python files (.json, .md) are logged as changed but do not undergo structural parsing. Full parsing support for these types is noted as not yet implemented.
  • The DocumentationGenerator.generate_architecture_markdown method is currently commented out in main.py and is not active.
  • The file crawler requires an active Hermes Agent terminal session and will fail if invoked without one.

License

This project does not currently include a license file. All rights reserved until a license is specified.

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