Update app.py

app.py

@@ -17,68 +17,41 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 SYSTEM_PROMPT = """You are an agent solving the GAIA benchmark and you are required to provide exact answers.
 Rules to follow:
 1. Return only the exact requested answer: no explanation and no reasoning.
-2. For yes/no questions, return exactly "Yes" or "No".
+2. For yes/no questions, return exactly \"Yes\" or \"No\".
 3. For dates, use the exact format requested.
 4. For numbers, use the exact number, no other format.
 5. For names, use the exact name as found in sources.
 6. If the question has an associated file, process it accordingly.
 Examples of good responses:
-- "42"
-- "Yes"
-- "October 5, 2001"
-- "Buenos Aires"
-Never include phrases like "the answer is..." or "Based on my research".
+- \"42\"
+- \"Yes\"
+- \"October 5, 2001\"
+- \"Buenos Aires\"
+Never include phrases like \"the answer is...\" or \"Based on my research\".
 Only return the exact answer."""
 
 # Define agent tools
 audio_tool = AudioTranscriptionTool()
 image_tool = ImageAnalysisTool()
+wikipedia_tool = Tool.from_function(
+    name="wikipedia_search",
+    description="Search for facts using Wikipedia.",
+    input_schema={"query": {"type": "string", "description": "Search query"}},
+    output_type="string",
+    forward=lambda query: WikipediaSearcher().search(query)
+)
 
-class WikipediaTool(Tool):
-    name = "wikipedia_search"
-    description = "Search for facts using Wikipedia."
-    inputs = {
-        "query": {"type": "string", "description": "Search query"}
-    }
-    output_type = "string"
-
-    def forward(self, query: str) -> str:
-        return WikipediaSearcher().search(query)
-
-wiki_tool = WikipediaTool()
-
-tools = [audio_tool, image_tool, wiki_tool]
-
-# Define the custom agent using Mixtral on Hugging Face
-#class MyAgent(CodeAgent):
- #   def __init__(self):
- #       model = HfApiModel(
-  #          api_url="https://api-inference.huggingface.com/models/mistralai/Mixtral-8x7B-Instruct-v0.1",
-   #         api_key=os.getenv("HF_API_TOKEN")
-   #     )
-   #     super().__init__(model=model, tools=tools, system_prompt=SYSTEM_PROMPT)
-
-api_key = os.getenv("HF_API_TOKEN", "").strip()
-
+tools = [audio_tool, image_tool, wikipedia_tool]
 
+# Define the custom agent using Dolphin model (free Mixtral)
 class MyAgent(CodeAgent):
     def __init__(self):
         model = HfApiModel(
-            model="mistralai/Mixtral-8x7B-Instruct-v0.1",  # pass model ID, not full URL
-            api_key=api_key
+            model="cognitivecomputations/dolphin-2.6-mixtral-8x7b",
+            api_key=os.getenv("HF_API_TOKEN", "").strip()
         )
         super().__init__(model=model, tools=tools)
 
-    def __call__(self, question_dict):
-        question = question_dict.get("question", "")
-        full_prompt = SYSTEM_PROMPT + "\n\n" + question
-        new_input = question_dict.copy()
-        new_input["question"] = full_prompt
-        return super().__call__(new_input)
-
-
-
-
 # Evaluation + Submission function
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")