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Update app.py
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app.py
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@@ -12,6 +12,9 @@ import logging
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import re
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import json
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from datetime import datetime
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from typing import Annotated, Sequence, TypedDict, List, Optional, Any, Type
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from pydantic import BaseModel, Field
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@@ -62,7 +65,6 @@ metrics_logger = setup_metrics_logger()
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def log_metric(message):
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"""Log a human-readable metric message with automatic timestamp"""
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current_time = datetime.now()
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timestamped_message = f"{message} | Logged: {current_time:%Y-%m-%d %H:%M:%S}"
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metrics_logger.info(timestamped_message)
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logger.info(timestamped_message) # Also log to console using info.logger
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@@ -264,7 +266,6 @@ class Qwen25SmallLLM(Runnable):
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super().__init__()
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logger.info(f"Loading model: {model_path} (use_4bit={use_4bit})")
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start_Loading_Model_time = time.perf_counter()
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current_time = datetime.now()
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try:
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# Load tokenizer
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@@ -370,7 +371,6 @@ class Educational_Agent:
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def __init__(self):
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start_init_and_langgraph_time = time.perf_counter()
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current_time = datetime.now()
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self.llm = Qwen25SmallLLM(model_path="Qwen/Qwen2.5-1.5B-Instruct", use_4bit=True)
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self.tool_decision_engine = Tool_Decision_Engine(self.llm)
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@@ -407,7 +407,6 @@ class Educational_Agent:
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def call_model(state: EducationalAgentState) -> dict:
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"""Call the model with tool decision logic"""
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start_call_model_time = time.perf_counter()
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current_time = datetime.now()
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messages = state["messages"]
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@@ -504,7 +503,6 @@ Otherwise, provide a regular educational response.
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def handle_tools(state: EducationalAgentState) -> dict:
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"""Handle tool execution"""
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start_handle_tools_time = time.perf_counter()
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current_time = datetime.now()
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try:
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messages = state["messages"]
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@@ -575,9 +573,7 @@ Otherwise, provide a regular educational response.
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def chat(self, message: str, thread_id: str = "default") -> str:
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"""Main chat interface"""
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start_chat_time = time.perf_counter()
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current_time = datetime.now()
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try:
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config = {"configurable": {"thread_id": thread_id}}
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import re
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import json
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from datetime import datetime
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current_time = datetime.now()
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from typing import Annotated, Sequence, TypedDict, List, Optional, Any, Type
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from pydantic import BaseModel, Field
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def log_metric(message):
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"""Log a human-readable metric message with automatic timestamp"""
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timestamped_message = f"{message} | Logged: {current_time:%Y-%m-%d %H:%M:%S}"
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metrics_logger.info(timestamped_message)
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logger.info(timestamped_message) # Also log to console using info.logger
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super().__init__()
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logger.info(f"Loading model: {model_path} (use_4bit={use_4bit})")
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start_Loading_Model_time = time.perf_counter()
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try:
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# Load tokenizer
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def __init__(self):
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start_init_and_langgraph_time = time.perf_counter()
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self.llm = Qwen25SmallLLM(model_path="Qwen/Qwen2.5-1.5B-Instruct", use_4bit=True)
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self.tool_decision_engine = Tool_Decision_Engine(self.llm)
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def call_model(state: EducationalAgentState) -> dict:
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"""Call the model with tool decision logic"""
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start_call_model_time = time.perf_counter()
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messages = state["messages"]
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def handle_tools(state: EducationalAgentState) -> dict:
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"""Handle tool execution"""
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start_handle_tools_time = time.perf_counter()
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try:
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messages = state["messages"]
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def chat(self, message: str, thread_id: str = "default") -> str:
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"""Main chat interface"""
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start_chat_time = time.perf_counter()
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try:
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config = {"configurable": {"thread_id": thread_id}}
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