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note_engine.py

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+from llama_index.core.tools import FunctionTool
+import os
+
+note_file = os.path.join("data", "notes.txt")
+
+
+def save_note(note):
+    if not os.path.exists(note_file):
+        open(note_file, "w")
+
+    with open(note_file, "a") as f:
+        f.writelines([note + "\n"])
+
+    return "note saved"
+
+
+note_engine = FunctionTool.from_defaults(
+    fn=save_note,
+    name="note_saver",
+    description="this tool can save a text based note to a file for the user",
+)

prompts.py

@@ -0,0 +1,26 @@
+from llama_index.core import PromptTemplate
+
+
+instruction_str = """\
+    1. Convert the query to executable Python code using Pandas.
+    2. The final line of code should be a Python expression that can be called with the `eval()` function.
+    3. The code should represent a solution to the query.
+    4. PRINT ONLY THE EXPRESSION.
+    5. Do not quote the expression."""
+
+new_prompt = PromptTemplate(
+    """\
+    You are working with a pandas dataframe in Python.
+    The name of the dataframe is `df`.
+    This is the result of `print(df.head())`:
+    {df_str}
+
+    Follow these instructions:
+    {instruction_str}
+    Query: {query_str}
+
+    Expression: """
+)
+
+context = """Purpose: The primary role of this agent is to assist users by providing accurate 
+            information about world population statistics and details about a country. """