usage

Author: hfhoffman1144

python-langgraph/README.md

@@ -20,4 +20,25 @@ OPENAI_API_KEY=<YOUR-OPENAI-API-KEY>
 
 ## Usage
 
-TODO: A short note on how to run the project. You can tell them to go to the tutorial for more information.
+Once your environment is set up, you can run the final graph agent on an example input with the following code:
+
+```python
+from graphs.email_agent import email_agent_graph
+from example_emails import EMAILS
+
+escalation_criteria = """"There's an immediate risk of electrical,
+water, or fire damage"""
+
+message_with_criteria = f"""
+The escalation criteria is: {escalation_criteria}
+
+Here's the email:
+{EMAILS[3]}
+"""
+message_3 = {"messages": [("human", message_with_criteria)]}
+ 
+for chunk in email_agent_graph.stream(message_3, stream_mode="values"):
+    chunk["messages"][-1].pretty_print()
+```
+
+See the tutorial for all the details on what's going on here.

python-langgraph/chains/notice_extraction.py

@@ -64,9 +64,7 @@ class NoticeEmailExtract(BaseModel):
     @property
     def date_of_notice(self) -> date | None:
         try:
-            return datetime.strptime(
-                self.date_of_notice_str, "%Y-%m-%d"
-            ).date()
+            return datetime.strptime(self.date_of_notice_str, "%Y-%m-%d").date()
         except Exception as e:
             print(e)
             return None
@@ -75,9 +73,7 @@ def date_of_notice(self) -> date | None:
     @property
     def compliance_deadline(self) -> date | None:
         try:
-            return datetime.strptime(
-                self.compliance_deadline_str, "%Y-%m-%d"
-            ).date()
+            return datetime.strptime(self.compliance_deadline_str, "%Y-%m-%d").date()
         except Exception as e:
             print(e)
             return None
@@ -103,7 +99,6 @@ def compliance_deadline(self) -> date | None:
 
 notice_parser_model = ChatOpenAI(model="gpt-4o-mini", temperature=0)
 
-NOTICE_PARSER_CHAIN = (
-    info_parse_prompt
-    | notice_parser_model.with_structured_output(NoticeEmailExtract)
+NOTICE_PARSER_CHAIN = info_parse_prompt | notice_parser_model.with_structured_output(
+    NoticeEmailExtract
 )

python-langgraph/graphs/email_agent.py

@@ -26,7 +26,9 @@ def forward_email(email_message: str, send_to_email: str) -> bool:
 
 
 @tool
-def send_wrong_email_notification_to_sender(sender_email: str, correct_department: str):
+def send_wrong_email_notification_to_sender(
+    sender_email: str, correct_department: str
+):
     """
     Send an email back to the sender informing them that
     they have the wrong address. The email should be sent
@@ -41,7 +43,9 @@ def send_wrong_email_notification_to_sender(sender_email: str, correct_departmen
 
 
 @tool
-def extract_notice_data(email: str, escalation_criteria: str) -> NoticeEmailExtract:
+def extract_notice_data(
+    email: str, escalation_criteria: str
+) -> NoticeEmailExtract:
     """
     Extract structured fields from a regulatory notice.
     This should be used when the email message comes from
@@ -105,7 +109,9 @@ def determine_email_action(email: str) -> str:
 ]
 tool_node = ToolNode(tools)
 
-EMAIL_AGENT_MODEL = ChatOpenAI(model="gpt-4o-mini", temperature=0).bind_tools(tools)
+EMAIL_AGENT_MODEL = ChatOpenAI(model="gpt-4o-mini", temperature=0).bind_tools(
+    tools
+)
 
 
 def call_agent_model_node(state: MessagesState) -> dict[str, list[AIMessage]]:

python-langgraph/utils/graph_utils.py

@@ -32,7 +32,9 @@ def create_legal_ticket(
     ]
 
     if current_follow_ups:
-        follow_ups = [f for f in follow_ups if f not in current_follow_ups.keys()]
+        follow_ups = [
+            f for f in follow_ups if f not in current_follow_ups.keys()
+        ]
 
     follow_up = random.choice(follow_ups)