add an rss reader tool and enable local runs with ollama

.gitignore

@@ -1,3 +1,4 @@
 /.gradio
 /.venv
+/.env
 __pycache__

Gradio_UI.py

@@ -290,7 +290,7 @@ class GradioUI:
                 [stored_messages, text_input],
             ).then(self.interact_with_agent, [stored_messages, chatbot], [chatbot])
 
-        demo.launch(debug=True, share=True, **kwargs)
+        demo.launch(debug=True, share=os.getenv("GRADIO_SHARE") == "true", **kwargs)
 
 
 __all__ = ["stream_to_gradio", "GradioUI"]

README.md

@@ -31,4 +31,30 @@ source .venv/bin/activate
 pip install -r requirements.txt
 ```
 
+## Configuration
+
+### Run locally agains a HuggingFace model
+
+If you want to run this locally agains a model hosted by HuggingFace, you'll have to set up a [user access token](https://huggingface.co/docs/hub/security-tokens).
+
+```bash
+# Copy the `huggingface.env` as `.env`
+cp huggingface.env .env
+
+# Edit the file and set your `HF_TOKEN`
+```
+
 For additional configuration, check out HuggingFace's [spaces configuration reference](https://huggingface.co/docs/hub/spaces-config-reference).
+
+### Run locally against a self-hosted Ollama model
+
+```bash
+# Copy the `ollama.env` as `.env`
+cp ollama.env .env
+
+# Edit the file and set your `OLLAMA_ENDPOINT` and `OLLAMA_MODEL`
+```
+
+### General settings
+
+Set the value of `GRADIO_SHARE` to `true` if you want to share your Gradio application.

app.py

@@ -1,22 +1,16 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+import os
 import datetime
 import requests
 import pytz
 import yaml
-from tools.final_answer import FinalAnswerTool
+from dotenv import load_dotenv
+from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, LiteLLMModel, tool
 
+from tools.read_rss_feed import ReadRssFeedTool
+from tools.final_answer import FinalAnswerTool
 from Gradio_UI import GradioUI
 
-# Below is an example of a tool that does nothing. Amaze us with your creativity !
-@tool
-def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
-    #Keep this format for the description / args / args description but feel free to modify the tool
-    """A tool that does nothing yet 
-    Args:
-        arg1: the first argument
-        arg2: the second argument
-    """
-    return "What magic will you build ?"
+load_dotenv()
 
 @tool
 def get_current_time_in_timezone(timezone: str) -> str:
@@ -33,29 +27,36 @@ def get_current_time_in_timezone(timezone: str) -> str:
     except Exception as e:
         return f"Error fetching time for timezone '{timezone}': {str(e)}"
 
-
-final_answer = FinalAnswerTool()
-
 # If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
 # model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
 
-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
-custom_role_conversions=None,
-)
+def choose_model():
+    if os.getenv("HF_TOKEN"):
+        print("Using HuggingFace")
+        return HfApiModel(
+            max_tokens=2096,
+            temperature=0.5,
+            model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+            custom_role_conversions=None,
+        )
+    else:
+        print("Using Ollama")
+        return LiteLLMModel(
+            model_id=os.getenv("OLLAMA_MODEL"),
+            api_base=os.getenv("OLLAMA_ENDPOINT"),
+            api_key=os.getenv("OLLAMA_KEY"),
+        )
 
+with open("prompts.yaml", "r") as stream:
+    prompt_templates = yaml.safe_load(stream)
 
-# Import tool from Hub
-image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
+model = choose_model()
+read_rss_feed = ReadRssFeedTool()
+final_answer = FinalAnswerTool()
 
-with open("prompts.yaml", 'r') as stream:
-    prompt_templates = yaml.safe_load(stream)
-    
 agent = CodeAgent(
     model=model,
-    tools=[final_answer], ## add your tools here (don't remove final answer)
+    tools=[read_rss_feed, final_answer],
     max_steps=6,
     verbosity_level=1,
     grammar=None,
@@ -65,5 +66,4 @@ agent = CodeAgent(
     prompt_templates=prompt_templates
 )
 
-
 GradioUI(agent).launch()

huggingface.env

@@ -0,0 +1,3 @@
+HF_TOKEN=hf_This_Is_A_Fake_Token
+
+GRADIO_SHARE=false

ollama.env

@@ -0,0 +1,5 @@
+OLLAMA_ENDPOINT="http://localhost:11434"
+OLLAMA_MODEL="ollama_chat/llama3-groq-tool-use"
+OLLAMA_KEY=""
+
+GRADIO_SHARE=false

requirements.txt

@@ -1,5 +1,8 @@
 markdownify
 smolagents
+smolagents[gradio]
+smolagents[litellm]
 requests
 duckduckgo_search
 pandas
+rss_parser

tools/read_rss_feed.py

@@ -0,0 +1,23 @@
+from smolagents.tools import Tool
+
+class ReadRssFeedTool(Tool):
+    name = "read_rss_feed"
+    description = "Read the articles from an RSS feed."
+    inputs = {'url': {'type': 'string', 'description': 'The url of the RSS feed (example: https://www.eldiario.es/rss).'}}
+    output_type = "string"
+
+    def forward(self, url: str) -> str:
+        """Read articles from an RSS feed."""
+        import re
+        from requests import get
+        from rss_parser import RSSParser
+        from markdownify import markdownify
+        response = get(url)
+        rss = RSSParser.parse(response.text)
+        articles = "# Articles\n\n"
+        for item in rss.channel.items:
+            articles += "## " + item.title.content + "\n"
+            articles += item.pub_date.content + "\n\n"
+            content = markdownify(item.description.content).strip()
+            articles += content + "\n\n"
+        return articles