TnR

app.py

@@ -3,6 +3,10 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from smolagents import GradioUI, CodeAgent, HfApiModel
+
+from tools import WebSearchTool, NasaImageSearchTool, ClinicalTrialsSearchTool, WikipediaSearchTool, DuckDuckGoSearchTool
+from retriever import WebSearchRetriever
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -10,6 +14,25 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
+model = HfApiModel(repo_id="google/flan-t5-small")
+
+search_tool = DuckDuckGoSearchTool()
+
+WebSearchTool = WebSearchTool()
+NasaImageSearchTool = NasaImageSearchTool()
+ClinicalTrialsSearchTool = ClinicalTrialsSearchTool()
+WikipediaSearchTool = WikipediaSearchTool()
+
+Age = CodeAgent(
+    tools=[WebSearchTool, NasaImageSearchTool, ClinicalTrialsSearchTool, WikipediaSearchTool],
+    model=model,
+    add_base_tools=True,
+    Planning_interval=3
+)
+
+if __name__ == "__main__":
+    GradioUI(agent=Age).launch(debug=True, share=False)
+
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")

retriever.py

@@ -0,0 +1,28 @@
+from smolagents import Tool
+from langchain_community.retrievers import BM25Retriever
+from langchain.docstore.document import Document
+import datasets
+
+class WebSearchRetriever(Tool):
+    name = "web_search_retriever"
+    description = "Useful for retrieving information from the web based on a search query. "
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "The search query string.",
+        }
+    }
+    output_type = "list[Document]"
+
+    def __init__(self, docs):
+        self.is_initialized = False
+        self.retriever = BM25Retriever.from_documents(docs)
+
+    def forward(self, query: str):
+        results = self.retriever.get_relevant_documents(query)
+        if results:
+            return "\n\n".join([doc.page_content for doc in results[:3]])
+        else:
+            return "No matching Information found."
+        
+

tools.py

@@ -0,0 +1,65 @@
+from smolagents import DuckDuckGoSearchTool
+from smolagents import Tool
+import random
+from huggingface_hub import list_models
+
+search_tool = DuckDuckGoSearchTool()
+
+class WebSearchTool(Tool):
+    name = "web_search"
+    description = "Useful for searching the web for information relevant to the question. "
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "The search query string.",
+        }
+    }
+    output_type = "string"
+
+    def forward(self, query: str) -> str:
+        return search_tool.forward(query)
+    
+class NasaImageSearchTool(Tool):
+    name = "nasa_image_search"
+    description = "Useful for searching NASA's image library for relevant images. "
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "The search query string.",
+        }
+    }
+    output_type = "string"
+
+    def forward(self, query: str) -> str:
+        # This is a placeholder implementation. You would replace this with actual API calls to NASA's image search.
+        return f"Image results for '{query}' from NASA's image library."
+    
+class ClinicalTrialsSearchTool(Tool):
+    name = "clinical_trials_search"
+    description = "Useful for searching clinical trial databases for relevant studies. "
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "The search query string.",
+        }
+    }
+    output_type = "string"
+
+    def forward(self, query: str) -> str:
+        # This is a placeholder implementation. You would replace this with actual API calls to clinical trial databases.
+        return f"Clinical trial results for '{query}' from clinical trial databases."
+    
+class WikipediaSearchTool(Tool):
+    name = "wikipedia_search"
+    description = "Useful for searching Wikipedia for relevant information. "
+    inputs = {
+        "query": {
+            "type": "string",
+            "description": "The search query string.",
+        }
+    }
+    output_type = "string"
+
+    def forward(self, query: str) -> str:
+        # This is a placeholder implementation. You would replace this with actual API calls to Wikipedia's search.
+        return f"Wikipedia results for '{query}' from Wikipedia's search."