updated app.py

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----
+MIIFazCCA1OgAwIBAgIRAIIQz7DSQONZRGPgu2OCiwAwDQYJKoZIhvcNAQELBQAw
+TzELMAkGA1UEBhMCVVMxKTAnBgNVBAoTIEludGVybmV0IFNlY3VyaXR5IFJlc2Vh
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+emyPxgcYxn/eR44/KJ4EBs+lVDR3veyJm+kXQ99b21/+jh5Xos1AnX5iItreGCc=
+-----END CERTIFICATE-----

app.py

@@ -1,9 +1,10 @@
 import yaml
 import os
-from smolagents import GradioUI, CodeAgent, InferenceClientModel, tools, Tool
+from smolagents import GradioUI, CodeAgent, InferenceClientModel, PythonInterpreterTool
 import pandas as pd
 import requests
 from io import BytesIO
+from huggingface_hub import InferenceClient
 
 # Get current directory path
 CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
@@ -22,11 +23,13 @@ from tools.final_answer import FinalAnswerTool as FinalAnswer
 # from tools.excel_analyzer import ExcelAnalyzerTool
 # from tools.wikipedia_search import WikipediaSearchTool
 
-
+# Initialize tools
 answer_question = AnswerQuestion()
 web_search = WebSearch()
 visit_webpage = VisitWebpage()
 final_answer = FinalAnswer()
+python_interpreter = PythonInterpreterTool()
+
 # youtube_analyzer = YouTubeVideoAnalysisTool()
 # file_reader = FileReaderTool()
 # code_executor = CodeExecutorTool()
@@ -37,9 +40,8 @@ final_answer = FinalAnswer()
 # wikipedia_search = WikipediaSearchTool()
 
 model = InferenceClientModel(
-    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
-    max_tokens=1000,
-)
+    model_id="Qwen/Qwen2.5-Coder-32B-Instruct", 
+    provider="together")
 
 with open(os.path.join(CURRENT_DIR, "prompts.yaml"), 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
@@ -50,6 +52,7 @@ agent_submission_agent = CodeAgent(
         answer_question, 
         web_search, 
         visit_webpage, 
+        python_interpreter,
         final_answer,
         # youtube_analyzer,
         # file_reader,
@@ -74,4 +77,4 @@ agent_submission_agent = CodeAgent(
 )
 
 if __name__ == "__main__":
-    GradioUI(agent_submission_agent).launch()
+    GradioUI(agent_submission_agent).launch()

prompts.yaml

@@ -9,6 +9,8 @@
   These print outputs will then appear in the 'Observation:' field, which will be available as input for the next step.
   In the end you have to return a final answer using the `final_answer` tool.
 
+  Never call tools (web_search, visit_webpage, etc.) from within python_interpreter code blocks. Each tool must be called separately in the Thought-Code-Observation cycle.
+
   Here are a few examples using notional tools:
   ---
   Task: "Generate an image of the oldest person in this document."

question_retriever.ipynb

@@ -228,22 +228,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'If Eliud Kipchoge could maintain his record-making marathon pace indefinitely, how many thousand hours would it take him to run the distance between the Earth and the Moon its closest approach? Please use the minimum perigee value on the Wikipedia page for the Moon when carrying out your calculation. Round your result to the nearest 1000 hours and do not use any comma separators if necessary.'"
+       "'Of the authors (First M. Last) that worked on the paper \"Pie Menus or Linear Menus, Which Is Better?\" in 2015, what was the title of the first paper authored by the one that had authored prior papers?'"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df_level1.loc[0, 'Question']"
+    "df_level1.loc[5, 'Question']"
    ]
   },
   {

requirements.txt

@@ -2,3 +2,5 @@ duckduckgo_search
 markdownify
 requests
 smolagents
+langchain
+langchain-community