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updated prompt
Browse files
agent.py
CHANGED
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@@ -64,8 +64,8 @@ Specifically, this json should have an `action` key (with the name of the tool t
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The only values that should be in the "action" field are:
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python_code: Execute Python code. Use this tool to calculate math problems. make sure to use prints to be able to view the final result. args: {"code": {"type": "string"}}
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wikipedia_search: Search Wikipedia for information about a specific topic. Optionally specify the number of results to return, args: {"query": {"type": "string"}, "num_results": {"type": "integer", "optional": true}}
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tavily_search: Search the web using Tavily
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arxiv_search: Search ArXiv for
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webpage_scrape: Scrape a specific webpage, args: {"url": {"type": "string"}}
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supabase_operation: Perform database operations, args: {"operation_type": {"type": "string"}, "table": {"type": "string"}, "data": {"type": "object", "optional": true}, "filters": {"type": "object", "optional": true}}
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excel_to_text: Convert Excel to Markdown table with attachment, args: {"excel_path": {"type": "string"}, "file_content": {"type": "string"}, "sheet_name": {"type": "string", "optional": true}}
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@@ -102,7 +102,7 @@ or
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ALWAYS follow this specific format for your responses. Your entire response will follow this pattern:
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Question: [the user's question]
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Thought: [your reasoning about what to do next, break it down into smaller steps]
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Action:
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```json
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{
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@@ -139,7 +139,7 @@ Now begin! Reminder to ALWAYS use the exact characters `Final Answer:` when you
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# Generate the chat interface, including the tools
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llm = ChatOpenAI(
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model="gpt-4o-mini",
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temperature=0
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)
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chat = llm
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The only values that should be in the "action" field are:
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python_code: Execute Python code. Use this tool to calculate math problems. make sure to use prints to be able to view the final result. args: {"code": {"type": "string"}}
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wikipedia_search: Search Wikipedia for information about a specific topic. Optionally specify the number of results to return, args: {"query": {"type": "string"}, "num_results": {"type": "integer", "optional": true}}
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tavily_search: Search the web using Tavily. Optionally specify search_depth as 'basic' or 'comprehensive', args: {"query": {"type": "string"}, "search_depth": {"type": "string", "optional": true}}
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arxiv_search: Search ArXiv for publications. Optionally specify max_results to control the number of papers returned, args: {"query": {"type": "string"}, "max_results": {"type": "integer", "optional": true}}
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webpage_scrape: Scrape a specific webpage, args: {"url": {"type": "string"}}
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supabase_operation: Perform database operations, args: {"operation_type": {"type": "string"}, "table": {"type": "string"}, "data": {"type": "object", "optional": true}, "filters": {"type": "object", "optional": true}}
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excel_to_text: Convert Excel to Markdown table with attachment, args: {"excel_path": {"type": "string"}, "file_content": {"type": "string"}, "sheet_name": {"type": "string", "optional": true}}
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ALWAYS follow this specific format for your responses. Your entire response will follow this pattern:
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Question: [the user's question]
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Thought: [your reasoning about what to do next, break it down into smaller steps and clearly state your thoughts]
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Action:
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```json
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{
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# Generate the chat interface, including the tools
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llm = ChatOpenAI(
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model="gpt-4o-mini",
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temperature=0.1
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)
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chat = llm
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app.py
CHANGED
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@@ -149,12 +149,16 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
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print(f"Skipping item with missing task_id or question: {item}")
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continue
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try:
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if task_id in tasks:
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question_text2 = question_text + f"\n\nThis is the file path: {file_path + tasks[task_id]}"
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submitted_answer = agent(question_text2)
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answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
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results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
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except Exception as e:
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print(f"Skipping item with missing task_id or question: {item}")
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continue
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try:
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# Initialize question_text2 with the original question
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question_text2 = question_text
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# Add file path information if task_id is in tasks
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if task_id in tasks:
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question_text2 = question_text + f"\n\nThis is the file path: {file_path + tasks[task_id]}"
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# Get the answer from the agent
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submitted_answer = agent(question_text2)
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answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
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results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
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except Exception as e:
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