Update to v0.2.0

Author: SyntaxError4Life

README.md

@@ -2,18 +2,30 @@
 
 Python framework for AI agents logic-only coding with streaming, tool calls, and multi-LLM provider support.
 
+Only the **"fairly stable"** versions are published on PyPi, but to get the latest experimental versions, clone this repository and install it !
+
 ## Installation
 
 ```bash
 pip install open-taranis --upgrade
 ```
+For package on **PyPi**
+
+
+**or**
+```bash
+git clone https://github.com/SyntaxError4Life/open-taranis && cd open-taranis/ && pip install .
+```
+For last version
 
 ## Quick Start
 
+<details><summary><b>Simplest</b></summary>
+
 ```python
 import open_taranis as T
 
-client = T.clients.openrouter("api_key")
+client = T.clients.openrouter() # API_KEY in env_var
 
 messages = [
     T.create_user_prompt("Tell me about yourself")
@@ -22,31 +34,75 @@ messages = [
 stream = T.clients.openrouter_request(
     client=client,
     messages=messages,
-    model="mistralai/mistral-7b-instruct:free", 
+    model="nvidia/nemotron-3-nano-30b-a3b:free", 
 )
 
 print("assistant : ",end="")
 for token, tool, tool_bool in T.handle_streaming(stream) : 
     if token :
         print(token, end="")
 ```
+</details> 
+
+<details><summary><b>To create a simple display using gradio as backend</b></summary>
 
-To create a simple display using gradio as backend :
 ```python
 import open_taranis as T
 import open_taranis.web_front as W
 import gradio as gr
 
 gr.ChatInterface(
     fn=W.chat_fn_gradio(
-    client=T.clients.openrouter(API_KEY),
+    client=T.clients.openrouter(), # API_KEY in env_var
     request=T.clients.openrouter_request,
-    model="mistralai/mistral-7b-instruct:free",
+    model="nvidia/nemotron-3-nano-30b-a3b:free",
     _system_prompt="You are an agent named **Taranis**"
 ).create_fn(),
     title="web front"
 ).launch()
+``` 
+</details>  
+
+
+
+<details><summary><b>Make a simple agent with a context windows on the 6 last turns</b></summary>
+
+```python
+import open_taranis as T
+
+class Agent(T.agent_base):
+    def __init__(self):
+        super().__init__()
+
+        self.client = T.clients.openrouter()
+        self._system_prompt = [T.create_system_prompt(
+            "You're an agent nammed **Taranis** !"
+        )]
+
+
+    def create_stream(self):
+        return T.clients.openrouter_request(
+            client=self.client,
+            messages=self._system_prompt+self.messages,
+            model="nvidia/nemotron-3-nano-30b-a3b:free"
+        )
+
+    def manage_messages(self):
+        self.messages = self.messages[-12:] # Each turn have 1 user and 1 assistant
+
+My_agent = Agent()
+
+while True :
+    prompt = input("user : ")
+
+    print("\n\nagent : ", end="")
+
+    for t in My_agent(prompt):
+        print(t, end="", flush=True)
+    
+    print("\n\n","="*60,"\n")
 ```
+</details>  
 
 ---
 
@@ -70,19 +126,33 @@ gr.ChatInterface(
 - [X]   v0.0.1: start
 - [X]   v0.0.x: Add and confirm other API providers (in the cloud, not locally)
 - [X]   v0.1.x: Functionality verifications in [examples](https://github.com/SyntaxError4Life/open-taranis/blob/main/examples/)
-- [ ] > v0.2.0: Add features for **logic-only coding** approach
+- [ ] > v0.2.0: Add features for **logic-only coding** approach, start with `agent_base`
+- [ ]   v0.3.x: Add a full agent in **TUI** and upgrade web client **deployments**
 - The rest will follow soon.
 
 ## Changelog
 
+<details><summary> <b>v0.0.x : The start</b> </summary>
+
 - **v0.0.4** : Add **xai** and **groq** provider
 - **v0.0.6** : Add **huggingface** provider and args for **clients.veniceai_request**
+</details>   
+
+<details><summary><b>v0.1.x : Gradio, commands and TUI</b></summary>
+  
 - **v0.1.0** : Start the **docs**, add **update-checker** and preparing for the continuation of the project...
 - **v0.1.1** : Code to deploy a **frontend with gradio** added (no complex logic at the moment, ex: tool_calls)
 - **v0.1.2** : Fixed a display bug in the **web_front** and experimentally added **ollama as a backend**
 - **v0.1.3** : Fixed the memory reset in the **web_front** and remove **ollama module** for **openai front** (work 100 times better)
 - **v0.1.4** : Fixed `web_front` for native use on huggingface, as well as `handle_streaming` which had tool retrieval issues
 - **v0.1.7** : Added a **TUI** and **commands**, detection of **env variables** (API keys) and tools in the framework
+</details>   
+
+<details><summary><b>v0.2.x : Agents</b></summary>
+
+- **v0.2.0** : Adding `agent_base`
+</details>   
+
 
 ## Advanced Examples
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "open-taranis"
-version = "0.1.7"
+version = "0.2.0"
 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", "bs4"]

src/open_taranis/__init__.py

@@ -7,7 +7,7 @@
 import inspect
 from typing import Any, Callable, Literal, Union, get_args, get_origin
 
-__version__ = "0.1.7"
+__version__ = "0.2.0"
 
 import requests
 from packaging import version
@@ -192,7 +192,7 @@ def huggingface(api_key: str=None) -> openai.OpenAI:
         Use `clients.generic_request` for call
         """
         if os.environ.get('HF_API') :
-            os.environ.get('HF_API')
+            api_key = os.environ.get('HF_API')
         return openai.OpenAI(api_key=api_key, base_url="https://router.huggingface.co/v1")
 
     @staticmethod
@@ -440,9 +440,89 @@ def create_user_prompt(content:str) -> dict[str, str] :
     return {"role":"user", "content":content}
 
 # ==============================
-# Agents coding (v0.2.0)
+# Agents base
 # ==============================
 
-class agent:
+class agent_base:
     def __init__(self):
-        pass
+
+        self._system_prompt = [create_system_prompt(None)]
+        self.messages = []
+
+        self.meta = {
+            "create_stream":True
+        }
+    
+    def create_stream(self):
+        """
+        # TO IMPLEMENT
+
+        like this :
+        ```python
+        return clients.Your_request(
+            client=clients.Your,
+            messages=self._system_prompt+self.messages, # Need to be keep !
+            model="Yout model"
+        )
+        ```
+        but with your customisation
+
+        Yout can define your client in `__init__()`
+        """
+
+        if self.meta["create_stream"]:
+            raise "You MUST define 'agent_base.create_stream()'"
+
+        
+
+    def manage_user_prompt(self, prompt):
+        """
+        # TO IMPLEMENT if needed
+        """
+
+        return prompt
+
+    def manage_assistant_response(self, response):
+        """
+        # TO IMPLEMENT if needed
+        """
+
+        return response
+
+    def manage_messages(self):
+        """
+        Example to always store only the 2 lasts turns :
+        ```python
+        self.messages = self.messages[-4:]
+        ```
+        """
+        pass
+
+    def execute_tools(self, tool_calls):
+        pass
+
+    def __call__(self, prompt):
+
+
+        run = True
+
+        self.messages.append(create_user_prompt(
+            self.manage_user_prompt(prompt)
+        ))
+        
+        while run :
+
+            respond = ""
+            for token, tool_calls, run in handle_streaming(self.create_stream()) :
+                if token :
+                    yield token
+                    respond += token
+            
+            self.messages.append(create_assistant_response(
+                self.manage_assistant_response(respond)
+            ))
+
+            self.manage_messages()
+
+            if run:
+                self.execute_tools(tool_calls)

src/open_taranis/web_front.py

@@ -20,7 +20,7 @@ def create_stream(self, messages):
 
         return self.request(
             self.client,
-            messages=messages,
+            messages=self._system_prompt+messages,
             model=self.model
         )
 
@@ -36,13 +36,6 @@ def fn(message, history, *args):
                 messages.append(T.create_user_prompt(user))
                 messages.append(T.create_assistant_response(assistant))   
             messages.append(T.create_user_prompt(message))    
-            
-
-            stream = self.request(
-                self.client,
-                messages=self._system_prompt+messages,
-                model=self.model
-            )
 
             stream = self.create_stream(
                 messages=messages