Add large file via LFS

.gitattributes

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+*.gguf filter=lfs diff=lfs merge=lfs -text

.gitignore

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-# ---> Python
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$py.class
-
-# C extensions
-*.so
-
-# Distribution / packaging
-.Python
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-share/python-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
-
-# PyInstaller
-#  Usually these files are written by a python script from a template
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
-
-# Installer logs
-pip-log.txt
-pip-delete-this-directory.txt
-
-# Unit test / coverage reports
-htmlcov/
-.tox/
-.nox/
-.coverage
-.coverage.*
-.cache
-nosetests.xml
-coverage.xml
-*.cover
-*.py,cover
-.hypothesis/
-.pytest_cache/
-cover/
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-db.sqlite3
-db.sqlite3-journal
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-
-# PyBuilder
-.pybuilder/
-target/
-
-# Jupyter Notebook
-.ipynb_checkpoints
-
-# IPython
-profile_default/
-ipython_config.py
-
-# pyenv
-#   For a library or package, you might want to ignore these files since the code is
-#   intended to run in multiple environments; otherwise, check them in:
-# .python-version
-
-# pipenv
-#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-#   However, in case of collaboration, if having platform-specific dependencies or dependencies
-#   having no cross-platform support, pipenv may install dependencies that don't work, or not
-#   install all needed dependencies.
-#Pipfile.lock
-
-# UV
-#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
-#   This is especially recommended for binary packages to ensure reproducibility, and is more
-#   commonly ignored for libraries.
-#uv.lock
-
-# poetry
-#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
-#   This is especially recommended for binary packages to ensure reproducibility, and is more
-#   commonly ignored for libraries.
-#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
-#poetry.lock
-
-# pdm
-#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
-#pdm.lock
-#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
-#   in version control.
-#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
-.pdm.toml
-.pdm-python
-.pdm-build/
-
-# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
-__pypackages__/
-
-# Celery stuff
-celerybeat-schedule
-celerybeat.pid
-
-# SageMath parsed files
-*.sage.py
-
-# Environments
-.env
-.venv
-env/
 venv/
-ENV/
-env.bak/
-venv.bak/
-
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
-# mkdocs documentation
-/site
-
-# mypy
-.mypy_cache/
-.dmypy.json
-dmypy.json
-
-# Pyre type checker
-.pyre/
-
-# pytype static type analyzer
-.pytype/
-
-# Cython debug symbols
-cython_debug/
-
-# PyCharm
-#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
-#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
-#  and can be added to the global gitignore or merged into this file.  For a more nuclear
-#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
-

README.md

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-# MUDProject
-

test-folders/main.py

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+from llama_cpp import Llama
+from langchain_core.language_models import LLM
+from langchain.prompts import PromptTemplate
+from langchain.agents import AgentExecutor, create_react_agent
+from langchain.tools import Tool
+from typing import Optional, List
+from googlesearch import search
+from bs4 import BeautifulSoup
+import requests
+# --- LLaMA-CPP model setup ---
+llm_model = Llama(
+    model_path="ReAction-1.5B.Q5_K_M.gguf",
+    n_ctx=2**21,
+    n_threads=8,
+    use_mlock=True,
+    verbose=False
+)
+
+# --- LangChain wrapper ---
+class LlamaCppLLM(LLM):
+    @property
+    def _llm_type(self) -> str:
+        return "llama-cpp"
+
+    def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
+        result = llm_model(
+            prompt,
+            stop=stop,
+            max_tokens=1024,
+            echo=False,
+            
+        )
+        output = result["choices"][0]["text"].strip()
+        return output
+
+custom_llm = LlamaCppLLM()
+
+# --- Tool definition ---
+def extract_text(html):
+    soup = BeautifulSoup(html, "html.parser")
+    # Remove scripts and styles
+    for tag in soup(["script", "style"]):
+        tag.decompose()
+    text = soup.get_text(separator=" ", strip=True)
+    return text
+def weather(city: str) -> str:
+    return f"The weather in {city} is Sunny."
+def search_google(query:str):
+    print(f"serach tool called {query}")
+    return [url for url in search(query,stop=5)]
+def get_webhtml(url):
+    print(url)
+    url = url.replace("'","")
+    if url:
+        r = requests.get(url)
+    else:
+        return None
+    return extract_text(r.text) if r.status_code == 200 else None
+weather_tool = Tool(
+    name="weather",
+    func=weather,
+    description="Use this tool to get the weather of a given city. Input should be the city name."
+)
+search_tool = Tool(
+        name = "search_tool",
+        func=search_google,
+        description="Returns the first 5 results from google with a specific query"
+        )
+html_tool = Tool(
+        name="get_webhtml",
+        func=get_webhtml,
+        description="Given a url, it provides the HTML for it. If it returns None, the website isn't available."
+        )
+
+# --- Custom ReAct prompt ---
+prompt_template = PromptTemplate.from_template("""
+You are a helpful assistant that can use tools to answer questions.
+
+TOOLS:
+{tools}
+
+FORMAT:
+Question: the input question
+Thought: think about what to do
+Action: pick one of [{tool_names}]
+Action Input: "<the input to the action>"
+
+Observation: result of the action
+... (you can repeat Thought/Action/Observation until you reach a Final Answer) ...
+... (Also, only use Action Input AFTER you use Action, so before you use Action input again, you have to call a tool again. Reach a final Answer before 3 iterations) ...
+Thought: I now know the final answer
+Final Answer: <the final answer>
+        
+
+NEW QUESTION:
+
+Question: {input}
+{agent_scratchpad}
+""")
+
+# --- Create ReAct agent ---
+react_agent = create_react_agent(
+    llm=custom_llm,
+    tools=[search_tool,html_tool],
+    prompt=prompt_template
+)
+
+agent = AgentExecutor(
+    agent=react_agent,
+    tools=[search_tool,html_tool],
+    verbose=True,
+    handle_parsing_errors=True,
+    max_iterations=5
+)
+
+# --- Run it ---
+response = agent.invoke({"input": "What is the weather in San Francisco"})
+print("\nFinal Output:\n", response)
+

utils.py

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+class Item():
+    def __init__(self,material_name,item_owner=None,**kwargs):
+        self.material_name = material_name
+        self.item_owner = item_owner if item_owner else "Wild"
+        self.__dict__.update(kwargs)
+class Entity():
+    def __init__(self,name:str,health:int,isInvincible,statusEffects,**kwargs):
+        pass
+class Player(Entity):
+    pass
+class StatusEffects():
+    pass
+class EntityAttributes():
+    pass
+class Skill():
+    pass
+class Inventory():
+    def __init__(self,max_space,items=None):
+        pass
+
+