Update agent.py

agent.py

@@ -11,6 +11,10 @@ class DuckDuckGoAgent:
         }
 
     def get_duckduckgo_answer(self, query: str) -> str:
+        """
+        Attempt to get an answer from the DuckDuckGo API.
+        If no abstract text is found, fall back to scraping.
+        """
         search_query = urllib.parse.quote(query)
         url = f"https://api.duckduckgo.com/?q={search_query}&format=json&no_html=1&skip_disambig=1"
 
@@ -18,19 +22,23 @@ class DuckDuckGoAgent:
             response = requests.get(url, timeout=10)
             if response.status_code == 200:
                 data = response.json()
+                # If AbstractText exists and is non-empty, return it
                 if 'AbstractText' in data and data['AbstractText']:
                     return data['AbstractText'][:200]
                 else:
                     print("No abstract found, falling back to scraping.")
                     return self.scrape_duckduckgo(query)
             else:
-                print(f"DuckDuckGo API failed: {response.status_code}")
+                print(f"DuckDuckGo API failed with status: {response.status_code}")
                 return self.scrape_duckduckgo(query)
         except Exception as e:
             print(f"Error contacting DuckDuckGo API: {e}")
             return self.scrape_duckduckgo(query)
 
     def scrape_duckduckgo(self, query: str) -> str:
+        """
+        Fallback to scraping DuckDuckGo search results if API fails or no abstract found.
+        """
         print("Using fallback: scraping HTML results.")
         try:
             response = requests.post(
@@ -45,18 +53,21 @@ class DuckDuckGoAgent:
                 text = s.get_text().strip()
                 if text:
                     return text[:200]
-            print("No useful snippets found, using Hugging Face LLM.")
+            print("No useful snippets found, falling back to Hugging Face LLM.")
             return self.call_huggingface_llm(query)
         except Exception as e:
-            print(f"Scraping error: {e}")
+            print(f"Error scraping DuckDuckGo: {e}")
             return self.call_huggingface_llm(query)
 
     def call_huggingface_llm(self, prompt: str) -> str:
+        """
+        Fallback to Hugging Face LLM if DuckDuckGo API and scraping both fail.
+        """
         hf_api_key = os.getenv("HF_API_TOKEN")
         model = "mistralai/Mistral-7B-Instruct-v0.1"
 
         if not hf_api_key:
-            return "Error: Hugging Face API Token no configurado."
+            return "Error: Hugging Face API Token is not configured."
 
         url = f"https://api-inference.huggingface.co/models/{model}"
         headers = {
@@ -81,13 +92,17 @@ class DuckDuckGoAgent:
             elif isinstance(output, dict) and "error" in output:
                 return f"HF LLM error: {output['error']}"
             else:
-                return "No se pudo obtener respuesta del LLM."
+                return "No response generated from Hugging Face LLM."
         except Exception as e:
-            print(f"Error en Hugging Face LLM: {e}")
-            return "Error al contactar con el modelo Hugging Face."
+            print(f"Error contacting Hugging Face LLM: {e}")
+            return "Error contacting Hugging Face model."
 
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        """
+        Main entry point for the agent to process a question.
+        It will first attempt DuckDuckGo, then fall back to scraping or Hugging Face LLM.
+        """
+        print(f"Agent received question: {question[:50]}...")
         answer = self.get_duckduckgo_answer(question)
         print(f"Agent returning answer: {answer}")
         return answer