Refactor package structure: rename to "llm_client", update imports, and enhance setup configuration

README.md

@@ -1,4 +1,4 @@
-# _llm
+# llm_client
 
 A Python package for interacting with LLM models through Ollama, supporting both remote API and local Ollama instances.
 
@@ -47,7 +47,7 @@ These can be set in a `.env` file in your project directory or in the ArangoDB e
 ## Basic Usage
 
 ```python
-from _llm import LLM
+from llm_client import LLM
 
 # Initialize the LLM
 llm = LLM()
@@ -64,7 +64,7 @@ print(result.content)
 ### Working with Images
 
 ```python
-from _llm import LLM
+from llm_client import LLM
 
 llm = LLM()
 response = llm.generate(
@@ -77,7 +77,7 @@ response = llm.generate(
 ### Streaming Responses
 
 ```python
-from _llm import LLM
+from llm_client import LLM
 
 llm = LLM()
 for chunk_type, chunk in llm.generate(
@@ -91,7 +91,7 @@ for chunk_type, chunk in llm.generate(
 
 ```python
 import asyncio
-from _llm import LLM
+from llm_client import LLM
 
 async def main():
     llm = LLM()

__init__.py

@@ -0,0 +1,7 @@
+"""
+llm_client: A Python package for interacting with LLM models through Ollama.
+"""
+
+from _llm.llm import LLM
+
+__all__ = ["LLM"]

_llm/__init__.py

@@ -1,4 +1,7 @@
-from .llm import LLM, remove_thinking
+"""
+llm_client: A Python package for interacting with LLM models through Ollama.
+"""
 
-__version__ = "0.1.0"
+from _llm.llm import LLM
-__all__ = ["LLM", "remove_thinking"]
+
+__all__ = ["LLM"]

_llm/llm.py

@@ -19,7 +19,6 @@ from colorprinter.print_color import *
 
 env_manager.set_env()
 
-print(os.environ)
 tokenizer = tiktoken.get_encoding("cl100k_base")
 
 
@@ -306,7 +305,6 @@ class LLM:
         Generate a response based on the provided query and context.
         """
         model = self._prepare_messages_and_model(query, user_input, context, messages, images, model)
-        print(f"[generate] model after _prepare_messages_and_model: {model}")
         temperature = temperature if temperature else self.options["temperature"]
         if not force_local:
             try:
@@ -393,7 +391,6 @@ class LLM:
                 keep_alive=3600 * 24 * 7,
             )
             summary = response.message.content.strip()
-            print_blue("Summary:", summary)
             return summary
         except ResponseError as e:
             print_red("Error generating summary:", e)

llm_client.py

@@ -0,0 +1,7 @@
+"""
+llm_client package entry point to simplify imports
+"""
+
+from _llm import LLM
+
+__all__ = ["LLM"]

setup.py

@@ -1,9 +1,14 @@
+"""
+llm_client package setuptools configuration.
+"""
+
 from setuptools import setup, find_packages
 
 setup(
-    name="llm_client",  # Changed from "_llm" to "llm_client"
+    name="llm_client",
     version="0.1.0",
-    packages=find_packages(),
+    packages=["_llm"],
+    py_modules=["llm_client"],
     install_requires=[
         "requests",
         "tiktoken",