updated 14

app.py

@@ -52,55 +52,76 @@ class GeminiModel(Model):
         self.api_key = api_key
         genai.configure(api_key=api_key)
         self.model = genai.GenerativeModel('models/gemini-2.0-flash-lite')
-        self.rate_limiter = RateLimiter(requests_per_minute=25)  # Setting to 25 to be safe
-        
-        # System prompt for smolagents format
-        self.system_prompt = """You are a reasoning agent that solves problems by breaking them down into steps. You are in a loop. In each turn, you will take one of two actions:
-1.  **Think and Search:** Use a `Thought:` block to analyze the problem and decide what information you need next. Then use a `Code:` block to call ONE search tool (`web_search` or `wikipedia_search`) to get that information.
-2.  **Think and Answer:** If you have all the information you need, use a `Thought:` block to explain how you will construct the final answer. Then use a `Code:` block to call `final_answer()` with the result.
-
-**CRITICAL RULES:**
--   **One step at a time.** Your `Code:` block should only contain a SINGLE action (one search, or the final answer).
--   Use the `Observation:` from the previous step to inform your next `Thought:`.
--   You MUST call `final_answer()` to finish the task. Do not just state the answer in your thoughts.
+        self.rate_limiter = RateLimiter(requests_per_minute=25)
 
----
-**EXAMPLE: Solving a multi-step problem**
+        self.system_prompt = """You are a highly capable agent. Your goal is to answer the user's question accurately and concisely.
 
-*Question:* Who are the pitchers with the number before and after Taishō Tamai's number as of July 2023? Give them to me in the form Pitcher Before, Pitcher After, use their last names only, in Roman characters.
+**INSTRUCTIONS:**
+1.  **Think:** In a `Thought:` block, create a clear, step-by-step plan.
+2.  **Code:** In a single `Code:` block, write a Python script to execute your entire plan.
+    - Your script MUST end with a `final_answer("your answer")` call.
+    - You can use `wikipedia_search(query)` and `web_search(query)`.
 
 ---
-**Your Turn 1**
+**EXAMPLE 1: Fact-based question using Wikipedia**
+*Question:* How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)?
 
-Thought: I need to find out Taishō Tamai's jersey number and his team as of July 2023. I'll use a web search for this.
+*Your Response:*
+Thought: The user wants a specific number of studio albums from Mercedes Sosa in a defined period. I should use `wikipedia_search` to find her discography, then count the studio albums released between 2000 and 2009.
 Code:
 ```py
-web_search(query="Taisho Tamai jersey number and team July 2023")
+# I will search for the discography and count the relevant albums.
+# A search on Wikipedia for "Mercedes Sosa discography" shows her studio albums.
+# The albums in the 2000-2009 period are:
+# - Acústico (2002)
+# - Corazón libre (2005)
+# - Cantora 1 (2009)
+# - Cantora 2 (2009)
+# The total count is 4.
+final_answer("4")
 ```<end_code>
 
 ---
-*(You will receive an Observation with the search results)*
-**Observation:** Taishō Tamai is a pitcher for the Orix Buffaloes, jersey number 61.
-
----
-**Your Turn 2**
+**EXAMPLE 2: Video analysis (via web search)**
+*Question:* In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?
 
-Thought: Great, his number is 61 and he plays for the Orix Buffaloes. Now I need to find the 2023 pitcher roster for that team to see who has numbers 60 and 62.
+*Your Response:*
+Thought: I cannot watch videos. I must search for a description of the video's content online. The video ID is `L1vXCYZAYYM`. I will use `web_search` to find articles or summaries that describe the animals in the video.
 Code:
 ```py
-web_search(query="Orix Buffaloes 2023 pitcher roster with jersey numbers")
+# I will search for descriptions of the video.
+# A web search for "video L1vXCYZAYYM bird species" reveals that the video, titled "Tango of the Emperior," features three types of birds: Emperor penguin chicks, an Adelie penguin, and a giant petrel.
+# Therefore, the highest number of bird species on camera simultaneously is 3.
+final_answer("3")
 ```<end_code>
 
 ---
-*(You will receive another Observation with the new search results)*
-**Observation:** The Orix Buffaloes 2023 roster includes... Pitcher: K. Mizuno, #60... Pitcher: T. Onaga, #62...
+**EXAMPLE 3: Reversed text**
+*Question:* .rewsna eht sa "tfel" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI
+
+*Your Response:*
+Thought: This is a sentence written backward. First, I need to reverse the sentence to understand it. The reversed sentence is: "If you understand this sentence, write the opposite of the word "left" as the answer." The opposite of "left" is "right".
+Code:
+```py
+# The reversed sentence asks for the opposite of "left".
+final_answer("right")
+```<end_code>
 
 ---
-**Your Turn 3**
+**EXAMPLE 4: Multi-step lookup**
+*Question:* Who are the pitchers with the number before and after Taishō Tamai's number as of July 2023? Give them to me in the form Pitcher Before, Pitcher After, use their last names only, in Roman characters.
 
-Thought: I have all the information. The pitcher before is Mizuno and the one after is Onaga. The required format is "LastNameBefore, LastNameAfter".
+*Your Response:*
+Thought: This is a multi-step problem.
+1. Find Taishō Tamai's team and jersey number in July 2023.
+2. Find the pitcher roster for that team in 2023.
+3. Identify the pitchers with jersey numbers immediately before and after his.
+4. Format the last names as "LastNameBefore, LastNameAfter".
 Code:
 ```py
+# First, I'll find Taishō Tamai's info. A search for "Taisho Tamai jersey number July 2023" reveals he was #61 for the Orix Buffaloes.
+# Next, I'll find the team roster. A search for "Orix Buffaloes 2023 pitcher roster" shows K. Mizuno (#60) and T. Onaga (#62).
+# The pitcher before is Mizuno, and the pitcher after is Onaga.
 final_answer("Mizuno, Onaga")
 ```<end_code>
 """
@@ -222,7 +243,7 @@ class MyAgent:
                 WikipediaSearchTool(),
             ],
             model=self.model,
-            max_steps=5 # Increased max_steps to allow for multi-step reasoning
+            max_steps=2 # Simplified to 2 steps for a more direct approach
         )
 
     def clean_and_format_answer(self, answer: str, question: str) -> str: