Update to v0.0.4

Author: SyntaxError4Life

README.md

@@ -35,12 +35,14 @@ for token, tool, tool_bool in T.handle_streaming(stream) :
 
 ```bash
 .
-├── __version__ = "0.0.3_genesis"
+├── __version__ = "0.0.4_genesis"
 │
 ├── clients
 │   ├── veniceai(api_key:str) -> openai.OpenAI
 │   ├── deepseek(api_key:str) -> openai.OpenAI
 │   ├── openrouter(api_key:str) -> openai.OpenAI
+│   ├── xai(api_key:str) -> openai.OpenAI
+│   ├── groq(api_key:str) -> openai.OpenAI
 │   │
 │   ├── veniceai_request(client:openai.OpenAI, messages:list[dict], model:str, temperature:float, max_tokens:int, tools: list[dict], include_venice_system_prompt:bool=False, **kwargs) -> openai.Stream
 │   ├── generic_request(client:openai.OpenAI, messages:list[dict], model:str, temperature:float, max_tokens:int, tools:list[dict], **kwargs) -> openai.Stream
@@ -69,6 +71,11 @@ for token, tool, tool_bool in T.handle_streaming(stream) :
 - [ ]   v1.x.x: Reduce dependencies to Python for Rust backend
 - [ ]   v2.0.0: Backend totally in Rust
 
+## Changelog
+
+#### **v0.0.4** :
+- Add **xai** and **groq** provider
+
 ## Advanced Examples
 
 - [tools call in a JSON database with Qwen3 4b](https://github.com/SyntaxError4Life/open-taranis/blob/main/examples/test_json_database.py)

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "open-taranis"
-version = "0.0.3" 
+version = "0.0.4" 
 description = "Minimalist Python framework for AI agents logic-only coding with streaming, tool calls, and multi-LLM provider support"
 authors = [{name = "SyntaxError4Life", email = "lilian@zanomega.com"}]
 dependencies = ["openai"]

src/open_taranis/__init__.py

@@ -2,21 +2,56 @@
 import json
 import re
 
-__version__ = "0.0.3_genesis"
+__version__ = "0.0.4_genesis"
 
 class clients:
+
+# ==============================
+# The clients with their URL
+# ==============================
+
     @staticmethod
     def veniceai(api_key: str) -> openai.OpenAI:
+        """
+        Use `clients.veniceai_request` for call
+        """
         return openai.OpenAI(api_key=api_key, base_url="https://api.venice.ai/api/v1")
 
     @staticmethod
     def deepseek(api_key: str) -> openai.OpenAI:
+        """
+        Use `clients.generic_request` for call
+        """
         return openai.OpenAI(api_key=api_key, base_url="https://api.deepseek.com")
 
     @staticmethod
     def openrouter(api_key: str) -> openai.OpenAI:
+        """
+        Use `clients.openrouter_request` for call
+        """
         return openai.OpenAI(api_key=api_key, base_url="https://openrouter.ai/api/v1")
 
+    @staticmethod
+    def xai(api_key: str) -> openai.OpenAI:
+        """
+        Use `clients.generic_request` for call
+        """
+        return openai.OpenAI(api_key=api_key, base_url="https://api.x.ai/v1")
+
+    @staticmethod
+    def groq(api_key: str) -> openai.OpenAI:
+        """
+        Use `clients.generic_request` for call
+        """
+        return openai.OpenAI(api_key=api_key, base_url="https://api.groq.com/openai/v1")
+
+
+# ==============================
+# Customers for calls with their specifications
+#
+# Like "include_venice_system_prompt" for venice.ai or custom app for openrouter
+# ==============================
+
     @staticmethod
     def veniceai_request(client: openai.OpenAI, messages: list[dict], model:str="defaut", temperature:float=0.7, max_tokens:int=4096, tools:list[dict]=None, include_venice_system_prompt:bool=False, **kwargs) -> openai.Stream:
         base_params = {
@@ -48,9 +83,9 @@ def veniceai_request(client: openai.OpenAI, messages: list[dict], model:str="def
         params = {**base_params, **tool_params, **venice_params}
 
         return client.chat.completions.create(**params)
-    
+
     @staticmethod
-    def generic_request(client: openai.OpenAI, messages: list[dict], model:str="defaut", temperature:float=0.7, max_tokens:int=4096, tools:list[dict]=None, **kwargs) -> openai.Stream:
+    def openrouter_request(client: openai.OpenAI, messages: list[dict], model:str="defaut", temperature:float=0.7, max_tokens:int=4096, tools:list[dict]=None, **kwargs) -> openai.Stream:
         base_params = {
             "model": model,
             "messages": messages,
@@ -69,10 +104,16 @@ def generic_request(client: openai.OpenAI, messages: list[dict], model:str="defa
 
         params = {**base_params, **tool_params}
 
-        return client.chat.completions.create(**params)
+        return client.chat.completions.create(
+            **params,
+            extra_headers={
+                "HTTP-Referer": "https://zanomega.com/",
+                "X-Title": "Zanomega/open-taranis"
+            }
+        )
 
     @staticmethod
-    def openrouter_request(client: openai.OpenAI, messages: list[dict], model:str="defaut", temperature:float=0.7, max_tokens:int=4096, tools:list[dict]=None, **kwargs) -> openai.Stream:
+    def generic_request(client: openai.OpenAI, messages: list[dict], model:str="defaut", temperature:float=0.7, max_tokens:int=4096, tools:list[dict]=None, **kwargs) -> openai.Stream:
         base_params = {
             "model": model,
             "messages": messages,
@@ -91,13 +132,11 @@ def openrouter_request(client: openai.OpenAI, messages: list[dict], model:str="d
 
         params = {**base_params, **tool_params}
 
-        return client.chat.completions.create(
-            **params,
-            extra_headers={
-                "HTTP-Referer": "https://zanomega.com/",
-                "X-Title": "Zanomega/open-taranis"
-            }
-        )
+        return client.chat.completions.create(**params)
+
+# ==============================
+# Functions for the streaming
+# ==============================
 
 def handle_streaming(stream: openai.Stream):
     """
@@ -199,7 +238,11 @@ def handle_tool_call(tool_call:dict) -> tuple[str, str, dict, str] :
 
     return fid, fname, args, ""
 
-def create_assistant_response(content:str, tool_calls:list[dict]=None) -> dict:
+# ==============================
+# Functions to simplify the messages roles
+# ==============================
+
+def create_assistant_response(content:str, tool_calls:list[dict]=None) -> dict[str, str]:
     """
     Creates an assistant message, optionally with tool calls.