Update to v0.1.1

Author: SyntaxError4Life

README.md

@@ -22,7 +22,7 @@ messages = [
 stream = T.clients.openrouter_request(
     client=client,
     messages=messages,
-    model="qwen/qwen3-4b:free", 
+    model="mistralai/mistral-7b-instruct:free", 
 )
 
 print("assistant : ",end="")
@@ -31,6 +31,22 @@ for token, tool, tool_bool in T.handle_streaming(stream) :
         print(token, end="")
 ```
 
+To create a simple display using gradio as backend :
+```python
+import open_taranis as T
+import open_taranis.web_front as W
+
+W.gr.ChatInterface(
+    fn=W.chat_fn_gradio(
+    client=T.clients.openrouter(api_key="api_key"),
+    request=T.clients.openrouter_request,
+    model="mistralai/mistral-7b-instruct:free",
+    _system_prompt=""
+).create_fn(),
+    title="web front"
+).launch()
+```
+
 ## Documentation :
 
 - [Base of the docs](https://zanomega.com/open-taranis/) (coding some things before the real docs)
@@ -52,6 +68,7 @@ for token, tool, tool_bool in T.handle_streaming(stream) :
 - **v0.0.4** : Add **xai** and **groq** provider
 - **v0.0.6** : Add **huggingface** provider and args for **clients.veniceai_request**
 - **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)
 
 ## Advanced Examples
 

pyproject.toml

@@ -4,10 +4,10 @@ build-backend = "hatchling.build"
 
 [project]
 name = "open-taranis"
-version = "0.1.0" 
+version = "0.1.1" 
 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"]
+dependencies = ["openai","gradio"]
 readme = "README.md"
 requires-python = ">=3.8"
 license = {text = "GPL-3.0-or-later"}

src/open_taranis/__gradio__.py

@@ -2,7 +2,7 @@
 import json
 import re
 
-__version__ = "0.1.0"
+__version__ = "0.1.1"
 
 import requests
 from packaging import version

src/open_taranis/__init__.py

@@ -0,0 +1,70 @@
+import gradio as gr
+import open_taranis as T
+
+class chat_fn_gradio:
+    def __init__(self, 
+                 client:T.openai.OpenAI,
+                 request:T.openai.Stream,
+                 model:str,
+                 _system_prompt:str=""
+                ):
+        
+        self.client:T.openai.OpenAI = client
+        self.request:T.openai.Stream = request
+        self.model = model
+        self._system_prompt = [{"role":"system", "content":_system_prompt}]
+
+        self.meta = {
+            "defaut_create_stream_used":False
+        }
+        self.memory = []
+
+    def create_stream(self, messages):
+        """
+        TO IMPLEMENT
+
+        ```
+        if self.meta["defaut_create_stream_used"]==False : # Just used to detect, must be rewritten by the user
+            print("Classic create_stream method used !")
+            self.meta=True
+
+        return self.request(self.client,messages=messages,model=self.model)
+        ```
+
+        """
+        if self.meta["defaut_create_stream_used"]==False : # Just used to detect, must be rewritten by the user
+            print("Classic create_stream method used !")
+            self.meta=True
+
+        return self.request(self.client,messages=messages,model=self.model)
+
+    def create_fn(self):
+
+            # Gradio chat function
+            #   Gradio sends:  message, history
+        def fn(message, history, *args):
+            
+            # Here we use our own internal memory rather than that of the gradio :
+            self.memory.append(T.create_user_prompt(message))
+
+            stream = self.create_stream(
+                self._system_prompt+self.memory # We make the system prompt adaptable and never at the beginning of the memory
+            )
+
+            partial = ""
+            token_nb = 0
+            for token, _, _ in T.handle_streaming(stream):
+                if token :
+                    partial += token
+                    token_nb += 1
+
+                    yield f"""Tokens : {token_nb}
+Model : {self.model}
+
+---
+
+{partial}"""
+            self.memory.append(T.create_assistant_response(partial))
+            print(partial)
+            return
+        return fn