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8770644 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 | # # example_usage.py
# import asyncio
# import traceback
# from agents import Runner, RunContextWrapper
# from agents.exceptions import InputGuardrailTripwireTriggered
# from openai.types.responses import ResponseTextDeltaEvent
# from chatbot.chatbot_agent import innscribe_assistant
# async def query_innscribe_bot(user_message: str, stream: bool = True):
# """
# Query the Innoscribe bot with optional streaming (ChatGPT-style chunk-by-chunk output).
# Args:
# user_message: The user's message/query
# stream: If True, stream responses chunk by chunk like ChatGPT. If False, wait for complete response.
# Returns:
# The final output from the agent
# """
# try:
# ctx = RunContextWrapper(context={})
# if stream:
# # ChatGPT-style streaming: clean output, text appears chunk by chunk
# result = Runner.run_streamed(
# innscribe_assistant,
# input=user_message,
# context=ctx.context
# )
# # Stream text chunk by chunk in real-time (like ChatGPT)
# async for event in result.stream_events():
# if event.type == "raw_response_event" and isinstance(event.data, ResponseTextDeltaEvent):
# delta = event.data.delta
# if delta:
# # Print each chunk immediately as it arrives (ChatGPT-style)
# print(delta, end="", flush=True)
# print("\n") # New line after streaming completes
# return result.final_output
# else:
# # Non-streaming mode: wait for complete response
# response = await Runner.run(
# innscribe_assistant,
# input=user_message,
# context=ctx.context
# )
# return response.final_output
# except InputGuardrailTripwireTriggered as e:
# print(f"\n⚠️ Guardrail blocked the query: {e}")
# if hasattr(e, 'result') and hasattr(e.result, 'output_info'):
# print(f"Guardrail reason: {e.result.output_info}")
# print("The query was determined to be unrelated to Innoscribe services.")
# return None
# except Exception as e:
# print(f"\n❌ Error: {e}")
# print(traceback.format_exc())
# raise
# async def interactive_chat():
# """
# Interactive ChatGPT-style conversation loop.
# Type 'exit', 'quit', or 'bye' to end the conversation.
# """
# print("=" * 60)
# print("🤖 Innoscribe Assistant - ChatGPT-style Chat")
# print("Type 'exit', 'quit', or 'bye' to end the conversation")
# print("=" * 60)
# print()
# while True:
# try:
# user_message = input("👤 You: ").strip()
# # Check for exit commands
# if user_message.lower() in ['exit', 'quit', 'bye', '']:
# print("\n👋 Goodbye! Have a great day!")
# break
# # Display assistant prefix and stream response
# print("🤖 Assistant: ", end="", flush=True)
# # Stream response chunk by chunk (ChatGPT-style)
# response = await query_innscribe_bot(user_message, stream=True)
# print() # Empty line between messages
# except KeyboardInterrupt:
# print("\n\n👋 Conversation interrupted. Goodbye!")
# break
# except Exception as e:
# print(f"\n❌ Error: {e}")
# print("Please try again or type 'exit' to quit.\n")
# async def main():
# try:
# # Option 1: Single message example (ChatGPT-style streaming)
# user_message = "Hello, how can I help you?"
# print(f"👤 You: {user_message}\n")
# print("🤖 Assistant: ", end="", flush=True)
# # Stream response chunk by chunk (ChatGPT-style)
# response = await query_innscribe_bot(user_message, stream=True)
# # Option 2: Uncomment below to use interactive chat mode instead
# # await interactive_chat()
# except Exception as e:
# print(f"\n❌ Error: {e}")
# print(traceback.format_exc())
# if __name__ == "__main__":
# try:
# asyncio.run(main())
# except Exception as e:
# print(f"Fatal error: {e}")
# print(traceback.format_exc())
# example_usage.py
import asyncio
import traceback
from agents import Runner, RunContextWrapper
from agents.exceptions import InputGuardrailTripwireTriggered
from openai.types.responses import ResponseTextDeltaEvent
from chatbot.chatbot_agent import launchlabs_assistant
async def query_launchlabs_bot(user_message: str, stream: bool = True):
"""
Query the Launchlabs bot with optional streaming (ChatGPT-style chunk-by-chunk output).
Args:
user_message: The user's message/query
stream: If True, stream responses chunk by chunk like ChatGPT. If False, wait for complete response.
Returns:
The final output from the agent
"""
try:
ctx = RunContextWrapper(context={})
if stream:
# ChatGPT-style streaming: clean output, text appears chunk by chunk
result = Runner.run_streamed(
launchlabs_assistant,
input=user_message,
context=ctx.context
)
# Stream text chunk by chunk in real-time (like ChatGPT)
async for event in result.stream_events():
if event.type == "raw_response_event" and isinstance(event.data, ResponseTextDeltaEvent):
delta = event.data.delta
if delta:
# Print each chunk immediately as it arrives (ChatGPT-style)
print(delta, end="", flush=True)
print("\n") # New line after streaming completes
return result.final_output
else:
# Non-streaming mode: wait for complete response
response = await Runner.run(
launchlabs_assistant,
input=user_message,
context=ctx.context
)
return response.final_output
except InputGuardrailTripwireTriggered as e:
print(f"\n⚠️ Guardrail blocked the query: {e}")
if hasattr(e, 'result') and hasattr(e.result, 'output_info'):
print(f"Guardrail reason: {e.result.output_info}")
print("The query was determined to be unrelated to Launchlabs services.")
return None
except Exception as e:
print(f"\n❌ Error: {e}")
print(traceback.format_exc())
raise
async def interactive_chat():
"""
Interactive ChatGPT-style conversation loop.
Type 'exit', 'quit', or 'bye' to end the conversation.
"""
print("=" * 60)
print("🤖 Launchlabs Assistant - ChatGPT-style Chat")
print("Type 'exit', 'quit', or 'bye' to end the conversation")
print("=" * 60)
print()
while True:
try:
user_message = input("👤 You: ").strip()
# Check for exit commands
if user_message.lower() in ['exit', 'quit', 'bye', '']:
print("\n👋 Goodbye! Have a great day!")
break
# Display assistant prefix and stream response
print("🤖 Assistant: ", end="", flush=True)
# Stream response chunk by chunk (ChatGPT-style)
response = await query_launchlabs_bot(user_message, stream=True)
print() # Empty line between messages
except KeyboardInterrupt:
print("\n\n👋 Conversation interrupted. Goodbye!")
break
except Exception as e:
print(f"\n❌ Error: {e}")
print("Please try again or type 'exit' to quit.\n")
async def main():
try:
# Option 1: Single message example (ChatGPT-style streaming)
user_message = "Hello, tell me about your services."
print(f"👤 You: {user_message}\n")
print("🤖 Assistant: ", end="", flush=True)
# Stream response chunk by chunk (ChatGPT-style)
response = await query_launchlabs_bot(user_message, stream=True)
# Option 2: Uncomment below to use interactive chat mode instead
# await interactive_chat()
except Exception as e:
print(f"\n❌ Error: {e}")
print(traceback.format_exc())
if __name__ == "__main__":
try:
asyncio.run(main())
except Exception as e:
print(f"Fatal error: {e}")
print(traceback.format_exc()) |