VERSION 1.0.0b1 (#147)

## LLMstudio Version 1.0.0b1

### What was done in this PR:

- new libraries: llmstudio-core, llmstudio-tracker, llmstudio-proxy,
llmstudio (former monolith)
- **Modularization and Refactoring**: Shifted the structure towards
modularization to enhance maintainability and scalability. Significant
changes were made in the core components to make them more modular,
including separating server components and organizing imports.
- **LLM Provider Updates**: Implemented changes in the LLM provider
instantiation. The provider now requires additional parameters such as
`api_key` and accepts a structured `chat_request`. This restructuring
also includes making the proxy and tracking optional for more flexible
usage.
- **Feature Enhancements**:
- Added asynchronous chat support, both with and without streaming, and
implemented synchronous methods.
- Introduced `session_id` tracking for chat sessions and logging support
for better traceability.
- Incorporated dynamic API versioning and the ability to handle multiple
API providers, including OpenAI, Azure, and VertexAI.
- Added support for LangChain agents and tool calling with parallel
execution.
- Adapted VertexAI integration for both regular and tool-calling
functions.
- Provided support for legacy UTC compatibility to address compatibility
with older Python versions.
- **Automated Testing and Documentation**:
- Enhanced test automation for development processes, including adding
tests for modularized components.
- Updated the documentation, added docstrings to LLM classes, and
provided a tutorial on using `langgraph`.
- **Formatting and Configuration**:
- Applied consistent formatting, added `isort` and `flake8`
configurations, and updated pre-commit hooks.
- Updated `config.yaml` for easier configuration management and enhanced
initialization for Azure-based clients.

### How it was tested:

- Conducted automated tests across development environments to verify
the correctness of modularized components and new functionality.
- Validated the functionality of asynchronous and synchronous chat
capabilities with various LLM providers, including OpenAI, Azure, and
VertexAI.
- Tested new `session_id` integration for accuracy in tracking sessions
and seamless functionality with logging tools.
- Verified compatibility across Python versions, particularly with UTC
handling in legacy versions.
- Reviewed server component separation and ensured compatibility with
modular server deployments.

### Additional notes:

- **Any breaking changes?**  
Yes, breaking changes were introduced in the LLM provider instantiation.
The new instantiation now requires specifying parameters in the
following format:
  ```python
  llm = LLM(provider=provider, api_key=api_key, **kwargs)
  chat_request = {
      "chat_input": "Hello, my name is Json",
      "model": model,
      "is_stream": False,
      "retries": 0,
      "parameters": {
          "temperature": 0,
          "max_tokens": 100,
          "response_format": {"type": "json_object"},
          "functions": None,
      }
  }
  llm.achat(**chat_request)
  ```

- **Any new dependencies added?**  
New dependencies are introduced to support modularization, API
versioning, and enhanced testing, though specific package details should
be checked in `pyproject.toml`.

- **Any performance improvements?**  
Optimized API calls with parallel execution for tool calls, streamlined
server components, and minimized function calls within the LLM provider,
which should contribute to overall performance improvements.

.gitignore

@@ -53,11 +53,11 @@ node_modules
 # Environments
 env
 env3
-.env
+.env*
 .env*.local
-.venv
-env/
-venv/
+.venv*
+env*/
+venv*/
 ENV/
 env.bak/
 venv.bak/

.pre-commit-config.yaml

@@ -3,43 +3,37 @@ repos:
     rev: v4.4.0
     hooks:
       - id: trailing-whitespace
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
       - id: end-of-file-fixer
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
       - id: check-yaml
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
       - id: check-added-large-files
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
 
   - repo: https://github.com/psf/black
     rev: 22.12.0
     hooks:
       - id: black
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
 
   - repo: https://github.com/pycqa/isort
     rev: 5.12.0
     hooks:
       - id: isort
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
         args:
           - "--profile=black"
 
-  - repo: https://github.com/myint/autoflake
-    rev: v1.4
+  - repo: https://github.com/PyCQA/autoflake
+    rev: v2.3.1
     hooks:
       - id: autoflake
-        files: llmstudio/
-        exclude: ^llmstudio/ui/
+        files: libs/
+        exclude: 'libs/core/llmstudio_core/providers/__init__.py|libs/llmstudio/llmstudio/providers/__init__.py'
         args:
-          # - --remove-all-unused-imports
-          - --recursive
-          - --remove-unused-variables
-          - --in-place
-        additional_dependencies: [flake8]
+        - --remove-all-unused-imports
+        - --recursive
+        - --remove-unused-variables
+        - --in-place
+        additional_dependencies: [flake8]

Makefile

@@ -1,2 +1,2 @@
-start-db:
-	docker compose up --build
+format:
+	pre-commit run --all-files

docs/quickstart.mdx

@@ -45,7 +45,7 @@ description: "Let's have you setup LLMstudio"
 Using it in a Python notebook is also fairly simple! Just run the following cell:
 
 ```python
-from llmstudio import LLM
+from llmstudio.providers import LLM
 model = LLM("anthropic/claude-2.1")
 model.chat("What are Large Language Models?")
 ```