Update app.py

Prepare for workshop

app.py

@@ -1,64 +1,85 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
+from smolagents import CodeAgent, HfApiModel, load_tool, tool
+from tools.final_answer import FinalAnswerTool
+from tools.youtube_search import YoutubeSearchTool
+from tools.play_music import PlaySomeMusicMeastro
+from tools.download_music import DownloadSomeMusicMeastro
+from typing import List
+from Gradio_UI import GradioUI
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+import os
+import base64
+import yaml
+import wikipedia
 
+@tool
+def search_wikipedia_pages(search_string: str) ->  List[str]:
+    """This tool helps to search for the names of potential names of wikipedia pages that relate to a search string.
+    This doesn't guarantee that every returned string is a perfect, exact page title that wikipedia.page() will accept without any issue.
+    This tool sends a query to the Wikipedia API's search endpoint. This endpoint performs a full-text search across Wikipedia's article titles and content.
+    This will not retrieve the actual pages, but gives oversight of the different keywords on wikipedia to find more information.
+    This tool will output the first 10 strings related to the search string as a list of strings.
+    Args:
+        search_string: the search string
+    """
+    try:
+        page_titles = wikipedia.search(search_string, results=10)
+        return page_titles
+    except wikipedia.exceptions.PageError as err:
+        s_error = f"PageError: {err}"
+    except wikipedia.exceptions.DisambiguationError as err:
+        s_error = f"DisambiguationError {err}"
+    print (f"An error occured {s_error}")
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+@tool
+def get_wikipedia_page_content(page_name: str, p_summary: bool = True) ->  str:
+    """This tool helps to get the content of wikipedia pages by their name.
+    If you use this tool based on the output of search_wikipedia_pages 
+     than remember to try a next string that was the output of search_wikipedia_pages if you get a error: Page id
+    The output is a string with the actual content of the wikipedia page.
+    Args:
+        page_name: the name of the page in wikipedia
+        p_summary: do you want the full content or only the summary of the content
+    """
+    s_error = ""
+    try:
+        a_page = wikipedia.page(title=page_name)
+        if p_summary: 
+            return a_page.summary
+        else:
+            return a_page.content
+    except wikipedia.exceptions.PageError as err:
+        s_error = f"PageError: {err}"
+    except wikipedia.exceptions.DisambiguationError as err:
+        s_error = f"DisambiguationError {err}"
+    print (f"An error occured {s_error}")
+    
+final_answer = FinalAnswerTool()
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+model = HfApiModel(
+            max_tokens=2096,
+            temperature=0.5,
+            #model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
+            model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud', 
+            custom_role_conversions=None,
+        )
 
-    messages.append({"role": "user", "content": message})
+# Import tool from Hub
+image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
-    response = ""
+with open("prompts.yaml", 'r') as stream:
+    prompt_templates = yaml.safe_load(stream)
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+agent = CodeAgent(
+    model=model,
+    tools=[final_answer, search_wikipedia_pages, get_wikipedia_page_content, PlaySomeMusicMeastro(), YoutubeSearchTool(),  DownloadSomeMusicMeastro(), image_generation_tool], 
+    max_steps=12,
+    verbosity_level=1,
+    grammar=None,
+    planning_interval=None,
+    name=None,
+    description=None,
+    prompt_templates=prompt_templates,
+    add_base_tools=True
 )
 
-
-if __name__ == "__main__":
-    demo.launch()
+GradioUI(agent).launch()