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Project description
hammad-python
Harmoniously Accelerated Micro-Modules (for) Application Development
hammad-python is an ecosystem of wrappers with the sole purpose of defining
opinionated resources that I myself use in my projects and day to day work when
building with Python.
The ecosystem is split into 4 main sub-packages:
hammad-python-core: Contains "stdlib" like resources such as converters, types, caching, etc. All of these resources can easily be implemented from scratch, and are built soley for convenience.hammad-python-data: Contains aCollectionclass / system that implements a simple vector / non vector database system.hammad-python-genai: Contains a collection of patterns for using Generative AI models as well as implementing concepts like Agentic Reasoning.hammad-python-http: HTTP / API related resources and utilities. Contains resources related to MCP, HTTP, OpenAPI & GraphQL Servers.
Installation
You can install any of the sub-packages, or the main package through pip or uv.
pip install hammad-python
Quickstart
Easily Use Language Models With Various Tools & Patterns
from ham.genai import Agent, LanguageModel
from ham.http import SearchClient
client = SearchClient()
def search_web(query: str) -> str:
return client.search(query)
# create your agent
# agents have rich functionality, and use `litellm` & `instructor` under the hood
agent = Agent(
instructions = "You are a helpful assistant who can search the web",
tools = [search_web]
)
print(agent.run("What is the weather in Tokyo?"))
>>> AgentResponse:
city='Tokyo' temperature=25.0 description='Clear sky'
>>> Model: openai/gpt-4o-mini
>>> Steps: 2
>>> Output Type: Response
>>> Total Tool Calls: 1
Vectorized & Searchable Collections
from ham.data import Collection
collection = Collection(vector=True)
collection.add("Rocks")
collection.add("Cucumber")
collection.add("Dragon")
collection.add("Apple")
# query the collection
for result in collection.query("Fruit"):
print(result.item)
>>> Apple
>>> Cucumber
>>> Dragon
>>> Rocks
HTTP & API Resources
from ham.http import function_server
# instantly launch a server by decorating a function
@function_server(path="/some-endpoint", auto_start=True)
def some_endpoint(name : str) -> str:
return f"Hello, {name}!"
Now in a separate file:
import requests
print(
requests.post(
"http://0.0.0.0:8000/some-endpoint",
json = {"name": "John"}
).json()
)
>>> {'result' : 'Hello, John!'}
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