victordibia
commented
8 months ago Hi,
Which llm are you using? How is it configured?
Closed hellangleZ closed 3 weeks ago
victordibia
commented
8 months ago Hi,
Which llm are you using? How is it configured?
hellangleZ
commented
8 months ago Hi,
Which llm are you using? How is it configured?
Azure GPT-35 not turbo
This issue only occurs on linux remote, windows is working good so far
victordibia
commented
8 months ago This looks correct. As long as you have set all the values correctly, it should work with Azure OAI. note that
model=gpt-35 base_url = ... api_version= ... api_key=...
Also confirm that you have set this for all agents in your workflow, and also there are no other model configs.
hellangleZ
commented
8 months ago This looks correct. As long as you have set all the values correctly, it should work with Azure OAI. note that
model=gpt-35 base_url = ... api_version= ... api_key=...
Also confirm that you have set this for all agents in your workflow, and also there are no other model configs.
Hi Victor:
Linux agent configuration same as windows
Also only one LLM
victordibia
commented
8 months ago @monuminu, any chance you can provide some insights here since you have gotten azure oai working well with autogenstudio?
monuminu
commented
8 months ago ensure your model is the deployment name
hellangleZ
commented
8 months ago ensure your model is the deployment name
same as gpt-35
It only occurs on linux
hellangleZ
commented
8 months ago I saw the problem only occurs on remote neither Linux or windows
Below is windows error
C:\Users\bozho>autogenstudio ui --host 0.0.0.0 --port 8031 INFO: Started server process [9492] INFO: Waiting for application startup. INFO: Application startup complete. INFO: Uvicorn running on http://0.0.0.0:8031 (Press CTRL+C to quit) INFO: 192.168.1.12:52467 - "GET / HTTP/1.1" 200 OK INFO: 192.168.1.12:52467 - "GET /images/svgs/welcome.svg HTTP/1.1" 200 OK INFO: 192.168.1.12:52470 - "GET /app-e668c2f8516018ac0a1c.js HTTP/1.1" 200 OK INFO: 192.168.1.12:52473 - "GET /webpack-runtime-5401e0764f0827a2e223.js HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /framework-0e118549f33203964972.js HTTP/1.1" 200 OK INFO: 192.168.1.12:52470 - "GET /page-data/app-data.json HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /page-data/index/page-data.json HTTP/1.1" 200 OK INFO: 192.168.1.12:52473 - "GET /favicon-32x32.png?v=46131b614287332146ea078703a67d38 HTTP/1.1" 200 OK INFO: 192.168.1.12:52470 - "GET /318ce576f236b79fd96f75904c13f6e55c3eee57-bf26f3994740657e0089.js HTTP/1.1" 200 OK INFO: 192.168.1.12:52473 - "GET /component---src-pages-index-tsx-2342fef3effa18a4d864.js HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /6c05b3ab656a8bfc225a64b3d73a36a92f83c05e-6a87df80060a5da491fc.js HTTP/1.1" 200 OK INFO: 192.168.1.12:52470 - "GET /api/sessions?user_id=guestuser@gmail.com HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /api/sessions?user_id=guestuser@gmail.com HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /page-data/build/page-data.json HTTP/1.1" 200 OK INFO: 192.168.1.12:52470 - "GET /api/messages?user_id=guestuser@gmail.com&session_id=27fc468b-e65f-4efd-ba4e-9956a5cde232 HTTP/1.1" 200 OK INFO: 192.168.1.12:52470 - "GET /api/messages?user_id=guestuser@gmail.com&session_id=27fc468b-e65f-4efd-ba4e-9956a5cde232 HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /component---src-pages-build-tsx-58ddda806aafef1d02d8.js HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /page-data/gallery/page-data.json HTTP/1.1" 200 OK INFO: 192.168.1.12:52472 - "GET /component---src-pages-gallery-index-tsx-7370214343f4a0096492.js HTTP/1.1" 200 OK agent_spec.config LLMConfig(config_list=[{'model': 'gpt-35', 'api_key': '6f0e8a96694244339aa52b03d00bdfbe', 'base_url': 'https://rt.openai.azure.com/', 'api_type': 'azure', 'api_version': '2023-05-15'}], temperature=0.1, cache_seed=None, timeout=600) userproxy (to visualization_assistant):
hello
userproxy (to visualization_assistant):
Plot a chart of NVDA and TESLA stock price for 2023. Save the result to a file named nvda_tesla.png
visualization_assistant (to userproxy):
Sure, I can help you with that. To plot the chart of NVDA and TESLA stock prices for 2023, we'll need to retrieve the stock price data first. Let's start by installing the necessary libraries and retrieving the data.
# filename: stock_price_chart.py
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
# Define the ticker symbols
tickers = ['NVDA', 'TSLA']
# Define the start and end dates
start_date = '2023-01-01'
end_date = '2023-12-31'
# Retrieve the stock price data
data = yf.download(tickers, start=start_date, end=end_date)['Adj Close']
# Plot the stock price chart
data.plot(figsize=(10, 6))
# Add a line of best fit and text on the slope for each line
for ticker in tickers:
slope = (data[ticker][-1] - data[ticker][0]) / len(data[ticker])
plt.annotate(f'Slope: {slope:.2f}', xy=(data.index[-1], data[ticker][-1]), xytext=(10, -30),
textcoords='offset points', arrowprops=dict(arrowstyle='->'))
# Add a title
plt.title('Stock Price Chart - NVDA and TESLA (2023)', fontweight='bold')
# Save the chart to a file
plt.savefig('nvda_tesla.png')
# Show the chart
plt.show()Please make sure you have the following libraries installed: pandas, matplotlib, and yfinance. You can install them using pip:
pip install pandas matplotlib yfinanceAfter running the code, a file named "nvda_tesla.png" will be saved in the current directory, which contains the chart of NVDA and TESLA stock prices for 2023.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
Plot a chart of NVDA and TESLA stock price for 2023. Save the result to a file named nvda_tesla.png
visualization_assistant (to userproxy):
Sure, I can help you with that. To plot the chart of NVDA and TESLA stock prices for 2023, we'll need to retrieve the stock price data first. Let's start by installing the necessary libraries and retrieving the data.
# filename: stock_price_chart.py
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
# Define the ticker symbols
tickers = ['NVDA', 'TSLA']
# Define the start and end dates
start_date = '2023-01-01'
end_date = '2023-12-31'
# Retrieve the stock price data
data = yf.download(tickers, start=start_date, end=end_date)['Adj Close']
# Plot the stock price chart
data.plot(figsize=(10, 6))
# Add a line of best fit and text on the slope for each line
for ticker in tickers:
slope = (data[ticker][-1] - data[ticker][0]) / len(data[ticker])
plt.annotate(f'Slope: {slope:.2f}', xy=(data.index[-1], data[ticker][-1]), xytext=(10, -30),
textcoords='offset points', arrowprops=dict(arrowstyle='->'))
# Add a title
plt.title('Stock Price Chart - NVDA and TESLA (2023)', fontweight='bold')
# Save the chart to a file
plt.savefig('nvda_tesla.png')
# Show the chart
plt.show()Please make sure you have the following libraries installed: pandas, matplotlib, and yfinance. You can install them using pip:
pip install pandas matplotlib yfinanceAfter running the code, a file named "nvda_tesla.png" will be saved in the current directory, which contains the chart of NVDA and TESLA stock prices for 2023.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
Plot a chart of NVDA and TESLA stock price for 2023. Save the result to a file named nvda_tesla.png
visualization_assistant (to userproxy):
Sure, I can help you with that. To plot the chart of NVDA and TESLA stock prices for 2023, we'll need to retrieve the stock price data first. Let's start by installing the necessary libraries and retrieving the data.
# filename: stock_price_chart.py
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
# Define the ticker symbols
tickers = ['NVDA', 'TSLA']
# Define the start and end dates
start_date = '2023-01-01'
end_date = '2023-12-31'
# Retrieve the stock price data
data = yf.download(tickers, start=start_date, end=end_date)['Adj Close']
# Plot the stock price chart
plt.figure(figsize=(10, 6))
plt.plot(data.index, data['NVDA'], label='NVDA')
plt.plot(data.index, data['TSLA'], label='TSLA')
# Add a line of best fit and text on the slope for each line
for ticker in tickers:
slope = (data[ticker][-1] - data[ticker][0]) / len(data[ticker])
plt.annotate(f'Slope: {slope:.2f}', xy=(data.index[-1], data[ticker][-1]), xytext=(10, -30),
textcoords='offset points', arrowprops=dict(arrowstyle='->'))
# Add a title
plt.title('Stock Price Chart - NVDA and TESLA (2023)', fontweight='bold')
# Add legend
plt.legend()
# Save the chart to a file
plt.savefig('nvda_tesla.png')
# Show the chart
plt.show()Please make sure you have the following libraries installed: pandas, matplotlib, and yfinance. You can install them using pip:
pip install pandas matplotlib yfinanceAfter running the code, a file named "nvda_tesla.png" will be saved in the current directory, which contains the chart of NVDA and TESLA stock prices for 2023.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
Plot a chart of NVDA and TESLA stock price for 2023. Save the result to a file named nvda_tesla.png
visualization_assistant (to userproxy):
Sure, I can help you with that. To plot the chart of NVDA and TESLA stock prices for 2023, we'll need to retrieve the stock price data first. Let's start by installing the necessary libraries and retrieving the data.
# filename: stock_price_chart.py
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
# Define the ticker symbols
tickers = ['NVDA', 'TSLA']
# Define the start and end dates
start_date = '2023-01-01'
end_date = '2023-12-31'
# Retrieve the stock price data
data = yf.download(tickers, start=start_date, end=end_date)['Adj Close']
# Plot the stock price chart
plt.figure(figsize=(10, 6))
plt.plot(data.index, data['NVDA'], label='NVDA')
plt.plot(data.index, data['TSLA'], label='TSLA')
# Add a line of best fit and text on the slope for each line
for ticker in tickers:
slope = (data[ticker][-1] - data[ticker][0]) / len(data[ticker])
plt.annotate(f'Slope: {slope:.2f}', xy=(data.index[-1], data[ticker][-1]), xytext=(10, -30),
textcoords='offset points', arrowprops=dict(arrowstyle='->'))
# Add a title
plt.title('Stock Price Chart - NVDA and TESLA (2023)', fontweight='bold')
# Add legend
plt.legend()
# Save the chart to a file
plt.savefig('nvda_tesla.png')
# Show the chart
plt.show()Please make sure you have the following libraries installed: pandas, matplotlib, and yfinance. You can install them using pip:
pip install pandas matplotlib yfinanceAfter running the code, a file named "nvda_tesla.png" will be saved in the current directory, which contains the chart of NVDA and TESLA stock prices for 2023.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
Plot a chart of NVDA and TESLA stock price for 2023. Save the result to a file named nvda_tesla.png
visualization_assistant (to userproxy):
Sure, I can help you with that. To plot the chart of NVDA and TESLA stock prices for 2023, we'll need to retrieve the stock price data first. Let's start by installing the necessary libraries and retrieving the data.
# filename: stock_price_chart.py
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
# Define the ticker symbols
tickers = ['NVDA', 'TSLA']
# Define the start and end dates
start_date = '2023-01-01'
end_date = '2023-12-31'
# Retrieve the stock price data
data = yf.download(tickers, start=start_date, end=end_date)['Adj Close']
# Plot the stock price chart
plt.figure(figsize=(10, 6))
plt.plot(data.index, data['NVDA'], label='NVDA')
plt.plot(data.index, data['TSLA'], label='TSLA')
# Add a line of best fit and text on the slope for each line
for ticker in tickers:
slope = (data[ticker][-1] - data[ticker][0]) / len(data[ticker])
plt.annotate(f'Slope: {slope:.2f}', xy=(data.index[-1], data[ticker][-1]), xytext=(10, -30),
textcoords='offset points', arrowprops=dict(arrowstyle='->'))
# Add a title
plt.title('Stock Price Chart - NVDA and TESLA (2023)', fontweight='bold')
# Add legend
plt.legend()
# Save the chart to a file
plt.savefig('nvda_tesla.png')
# Show the chart
plt.show()Please make sure you have the following libraries installed: pandas, matplotlib, and yfinance. You can install them using pip:
pip install pandas matplotlib yfinanceAfter running the code, a file named "nvda_tesla.png" will be saved in the current directory, which contains the chart of NVDA and TESLA stock prices for 2023.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
Plot a chart of NVDA and TESLA stock price for 2023. Save the result to a file named nvda_tesla.png
visualization_assistant (to userproxy):
Sure, I can help you with that. To plot the chart of NVDA and TESLA stock prices for 2023, we'll need to retrieve the stock price data first. Let's start by installing the necessary libraries and retrieving the data.
# filename: stock_price_chart.py
import pandas as pd
import matplotlib.pyplot as plt
import yfinance as yf
# Define the ticker symbols
tickers = ['NVDA', 'TSLA']
# Define the start and end dates
start_date = '2023-01-01'
end_date = '2023-12-31'
# Retrieve the stock price data
data = yf.download(tickers, start=start_date, end=end_date)['Adj Close']
# Plot the stock price chart
plt.figure(figsize=(10, 6))
plt.plot(data.index, data['NVDA'], label='NVDA')
plt.plot(data.index, data['TSLA'], label='TSLA')
# Add a line of best fit and text on the slope for each line
for ticker in tickers:
slope = (data[ticker][-1] - data[ticker][0]) / len(data[ticker])
plt.annotate(f'Slope: {slope:.2f}', xy=(data.index[-1], data[ticker][-1]), xytext=(10, -30),
textcoords='offset points', arrowprops=dict(arrowstyle='->'))
# Add a title
plt.title('Stock Price Chart - NVDA and TESLA (2023)', fontweight='bold')
# Add legend
plt.legend()
# Save the chart to a file
plt.savefig('nvda_tesla.png')
# Show the chart
plt.show()Please make sure you have the following libraries installed: pandas, matplotlib, and yfinance. You can install them using pip:
pip install pandas matplotlib yfinanceAfter running the code, a file named "nvda_tesla.png" will be saved in the current directory, which contains the chart of NVDA and TESLA stock prices for 2023.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
Write a python script to plot a sine wave and save it to disc as a png file sine_wave.png
visualization_assistant (to userproxy):
Certainly! Here's a Python script that plots a sine wave and saves it as a PNG file named "sine_wave.png":
# filename: sine_wave_plot.py
import numpy as np
import matplotlib.pyplot as plt
# Generate x values from 0 to 2*pi with a step of 0.1
x = np.arange(0, 2*np.pi, 0.1)
# Calculate y values as the sine of x
y = np.sin(x)
# Plot the sine wave
plt.plot(x, y)
# Add labels and title
plt.xlabel('x')
plt.ylabel('sin(x)')
plt.title('Sine Wave')
# Save the plot as a PNG file
plt.savefig('sine_wave.png')
# Show the plot
plt.show()To run this script, make sure you have the numpy and matplotlib libraries installed. You can install them using pip:
pip install numpy matplotlibAfter running the script, a file named "sine_wave.png" will be saved in the current directory, which contains the plot of the sine wave.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
automate run the code
visualization_assistant (to userproxy):
To automate the execution of the Python script, you can create a shell script that runs the Python script. Here's an example of how you can do it:
# filename: run_sine_wave_plot.sh
#!/bin/bash
# Activate the virtual environment if necessary
# source /path/to/your/virtualenv/bin/activate
# Run the Python script
python sine_wave_plot.py
# Deactivate the virtual environment if necessary
# deactivateMake sure to replace /path/to/your/virtualenv with the actual path to your virtual environment if you're using one.
Save the above shell script in the same directory as the sine_wave_plot.py script. Then, open a terminal, navigate to the directory, and run the shell script using the following command:
sh run_sine_wave_plot.shThis will execute the Python script and generate the sine_wave.png file.
Let me know if you need any further assistance. TERMINATE
userproxy (to visualization_assistant):
Plot a chart of NVDA and TESLA stock price for 2023. Save the result to a file named nvda_tesla.png
visualization_assistant (to userproxy):
Sure, I can help you with that. To plot the chart of NVDA and TESLA stock prices for 2023, we'll need to retrieve the stock price data first. Let's start by installing the necessary libraries and retrieving the data
userproxy (to visualization_assistant):
I apologize for the confusion, but as a language model AI, I don't have the capability to install libraries or retrieve real-time data. However, I can provide you with the code to plot the chart if you already have the stock price data for NVDA and TESLA for 2023.
Here's an example of how you can plot the chart using matplotlib:
import matplotlib.pyplot as plt
# Define the stock price data for NVDA and TESLA for 2023
nvda_prices = [100, 110, 120, ...] # Replace with actual NVDA stock prices
tesla_prices = [200, 210, 220, ...] # Replace with actual TESLA stock prices
# Define the x-axis values (e.g., dates)
dates = ['2023-01-01', '2023-01-02', '2023-01-03', ...] # Replace with actual dates
# Plot the stock price chart
plt.plot(dates, nvda_prices, label='NVDA')
plt.plot(dates, tesla_prices, label='TESLA')
# Add labels and title
plt.xlabel('Date')
plt.ylabel('Stock Price')
plt.title('NVDA and TESLA Stock Prices in 2023')
# Add legend
plt.legend()
# Save the chart to a file
plt.savefig('nvda_tesla.png')
# Show the chart
plt.show()In the code above, replace the nvda_prices and tesla_prices lists with the actual stock price data for NVDA and TESLA for each corresponding date in the dates list. Once you have the data, you can run the code to plot the chart and save it as nvda_tesla.png.
Let me know if you need any further assistance.
EXECUTING CODE BLOCK 0 (inferred language is python)... execute_code was called without specifying a value for use_docker. Since the python docker package is not available, code will be run natively. Note: this fallback behavior is subject to change SIGALRM is not supported on Windows. No timeout will be enforced. visualization_assistant (to userproxy):
exitcode: 1 (execution failed)
Code output:
Traceback (most recent call last):
File "", line 11, in
Traceback (most recent call last): File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogenstudio\web\app.py", line 74, in add_message response_message: Message = chatmanager.chat( File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogenstudio\chatmanager.py", line 29, in chat flow.run(message=f"{message_text}", clear_history=False) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogenstudio\workflowmanager.py", line 197, in run self.sender.initiate_chat( File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 672, in initiate_chat self.send(self.generate_init_message(context), recipient, silent=silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 420, in send recipient.receive(message, self, request_reply, silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 580, in receive self.send(reply, sender, silent=silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 420, in send recipient.receive(message, self, request_reply, silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 580, in receive self.send(reply, sender, silent=silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 420, in send recipient.receive(message, self, request_reply, silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 580, in receive self.send(reply, sender, silent=silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 420, in send recipient.receive(message, self, request_reply, silent) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 578, in receive reply = self.generate_reply(messages=self.chat_messages[sender], sender=sender) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 1241, in generate_reply final, reply = reply_func(self, messages=messages, sender=sender, config=reply_func_tuple["config"]) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\agentchat\conversable_agent.py", line 761, in generate_oai_reply response = client.create( File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\oai\client.py", line 266, in create response = self._completions_create(client, params) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\autogen\oai\client.py", line 531, in _completions_create response = completions.create(params) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\openai_utils_utils.py", line 299, in wrapper return func(*args, **kwargs) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\openai\resources\chat\completions.py", line 598, in create return self._post( File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\openai_base_client.py", line 1055, in post return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)) File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\openai_base_client.py", line 834, in request return self._request( File "C:\Users\bozho\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\LocalCache\local-packages\Python310\site-packages\openai_base_client.py", line 877, in _request raise self._make_status_error_from_response(err.response) from None openai.BadRequestError: Error code: 400 - {'error': {'message': "This model's maximum context length is 4096 tokens. However, your messages resulted in 4539 tokens. Please reduce the length of the messages.", 'type': 'invalid_request_error', 'param': 'messages', 'code': 'context_length_exceeded'}}
INFO: 192.168.1.12:52472 - "POST /api/messages HTTP/1.1" 200 OK
Describe the bug
I used windows local 127.0.0.1:8081. it works
but when I change to linux remote, I use bellow command to stard
When I run the same demo, it stuck in this process , after 30 min, there release an error message connection time out
Steps to reproduce
No response
Expected Behavior
No response
Screenshots and logs
userproxy (to visualization_assistant):
hello
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/httpcore/_exceptions.py", line 10, in map_exceptions yield File "/aml/conda/lib/python3.10/site-packages/httpcore/backends/sync.py", line 94, in connect_tcp sock = socket.create_connection( File "/aml/conda/lib/python3.10/socket.py", line 845, in create_connection raise err File "/aml/conda/lib/python3.10/socket.py", line 833, in create_connection sock.connect(sa) ConnectionRefusedError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 60, in map_httpcore_exceptions yield File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 218, in handle_request resp = self._pool.handle_request(req) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 256, in handle_request raise exc File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 240, in handle_request response = connection.handle_request(request) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 86, in handle_request raise exc File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 63, in handle_request stream = self._connect(request) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 111, in _connect stream = self._network_backend.connect_tcp(**kwargs) File "/aml/conda/lib/python3.10/site-packages/httpcore/backends/sync.py", line 93, in connect_tcp with map_exceptions(exc_map): File "/aml/conda/lib/python3.10/contextlib.py", line 153, in exit self.gen.throw(typ, value, traceback) File "/aml/conda/lib/python3.10/site-packages/httpcore/_exceptions.py", line 14, in map_exceptions raise to_exc(exc) from exc httpcore.ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 882, in _request response = self._client.send( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 901, in send response = self._send_handling_auth( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 929, in _send_handling_auth response = self._send_handling_redirects( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 966, in _send_handling_redirects response = self._send_single_request(request) File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 1002, in _send_single_request response = transport.handle_request(request) File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 217, in handle_request with map_httpcore_exceptions(): File "/aml/conda/lib/python3.10/contextlib.py", line 153, in exit self.gen.throw(typ, value, traceback) File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 77, in map_httpcore_exceptions raise mapped_exc(message) from exc httpx.ConnectError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/httpcore/_exceptions.py", line 10, in map_exceptions yield File "/aml/conda/lib/python3.10/site-packages/httpcore/backends/sync.py", line 94, in connect_tcp sock = socket.create_connection( File "/aml/conda/lib/python3.10/socket.py", line 845, in create_connection raise err File "/aml/conda/lib/python3.10/socket.py", line 833, in create_connection sock.connect(sa) ConnectionRefusedError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 60, in map_httpcore_exceptions yield File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 218, in handle_request resp = self._pool.handle_request(req) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 256, in handle_request raise exc File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 240, in handle_request response = connection.handle_request(request) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 86, in handle_request raise exc File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 63, in handle_request stream = self._connect(request) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 111, in _connect stream = self._network_backend.connect_tcp(**kwargs) File "/aml/conda/lib/python3.10/site-packages/httpcore/backends/sync.py", line 93, in connect_tcp with map_exceptions(exc_map): File "/aml/conda/lib/python3.10/contextlib.py", line 153, in exit self.gen.throw(typ, value, traceback) File "/aml/conda/lib/python3.10/site-packages/httpcore/_exceptions.py", line 14, in map_exceptions raise to_exc(exc) from exc httpcore.ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 882, in _request response = self._client.send( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 901, in send response = self._send_handling_auth( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 929, in _send_handling_auth response = self._send_handling_redirects( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 966, in _send_handling_redirects response = self._send_single_request(request) File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 1002, in _send_single_request response = transport.handle_request(request) File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 217, in handle_request with map_httpcore_exceptions(): File "/aml/conda/lib/python3.10/contextlib.py", line 153, in exit self.gen.throw(typ, value, traceback) File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 77, in map_httpcore_exceptions raise mapped_exc(message) from exc httpx.ConnectError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/httpcore/_exceptions.py", line 10, in map_exceptions yield File "/aml/conda/lib/python3.10/site-packages/httpcore/backends/sync.py", line 94, in connect_tcp sock = socket.create_connection( File "/aml/conda/lib/python3.10/socket.py", line 845, in create_connection raise err File "/aml/conda/lib/python3.10/socket.py", line 833, in create_connection sock.connect(sa) ConnectionRefusedError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 60, in map_httpcore_exceptions yield File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 218, in handle_request resp = self._pool.handle_request(req) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 256, in handle_request raise exc File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection_pool.py", line 240, in handle_request response = connection.handle_request(request) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 86, in handle_request raise exc File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 63, in handle_request stream = self._connect(request) File "/aml/conda/lib/python3.10/site-packages/httpcore/_sync/connection.py", line 111, in _connect stream = self._network_backend.connect_tcp(**kwargs) File "/aml/conda/lib/python3.10/site-packages/httpcore/backends/sync.py", line 93, in connect_tcp with map_exceptions(exc_map): File "/aml/conda/lib/python3.10/contextlib.py", line 153, in exit self.gen.throw(typ, value, traceback) File "/aml/conda/lib/python3.10/site-packages/httpcore/_exceptions.py", line 14, in map_exceptions raise to_exc(exc) from exc httpcore.ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 882, in _request response = self._client.send( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 901, in send response = self._send_handling_auth( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 929, in _send_handling_auth response = self._send_handling_redirects( File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 966, in _send_handling_redirects response = self._send_single_request(request) File "/aml/conda/lib/python3.10/site-packages/httpx/_client.py", line 1002, in _send_single_request response = transport.handle_request(request) File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 217, in handle_request with map_httpcore_exceptions(): File "/aml/conda/lib/python3.10/contextlib.py", line 153, in exit self.gen.throw(typ, value, traceback) File "/aml/conda/lib/python3.10/site-packages/httpx/_transports/default.py", line 77, in map_httpcore_exceptions raise mapped_exc(message) from exc httpx.ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/aml/conda/lib/python3.10/site-packages/autogenstudio/web/app.py", line 68, in add_message response_message: Message = chatmanager.chat( File "/aml/conda/lib/python3.10/site-packages/autogenstudio/chatmanager.py", line 29, in chat flow.run(message=f"{message_text}", clear_history=False) File "/aml/conda/lib/python3.10/site-packages/autogenstudio/workflowmanager.py", line 191, in run self.sender.initiate_chat( File "/aml/conda/lib/python3.10/site-packages/autogen/agentchat/conversable_agent.py", line 672, in initiate_chat self.send(self.generate_init_message(context), recipient, silent=silent) File "/aml/conda/lib/python3.10/site-packages/autogen/agentchat/conversable_agent.py", line 420, in send recipient.receive(message, self, request_reply, silent) File "/aml/conda/lib/python3.10/site-packages/autogen/agentchat/conversable_agent.py", line 578, in receive reply = self.generate_reply(messages=self.chat_messages[sender], sender=sender) File "/aml/conda/lib/python3.10/site-packages/autogen/agentchat/conversable_agent.py", line 1241, in generate_reply final, reply = reply_func(self, messages=messages, sender=sender, config=reply_func_tuple["config"]) File "/aml/conda/lib/python3.10/site-packages/autogen/agentchat/conversable_agent.py", line 761, in generate_oai_reply response = client.create( File "/aml/conda/lib/python3.10/site-packages/autogen/oai/client.py", line 266, in create response = self._completions_create(client, params) File "/aml/conda/lib/python3.10/site-packages/autogen/oai/client.py", line 531, in _completions_create response = completions.create(params) File "/aml/conda/lib/python3.10/site-packages/openai/_utils/_utils.py", line 301, in wrapper return func(*args, **kwargs) File "/aml/conda/lib/python3.10/site-packages/openai/resources/chat/completions.py", line 598, in create return self._post( File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 1096, in post return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)) File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 856, in request return self._request( File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 929, in _request return self._retry_request( File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 966, in _retry_request return self._request( File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 929, in _request return self._retry_request( File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 966, in _retry_request return self._request( File "/aml/conda/lib/python3.10/site-packages/openai/_base_client.py", line 938, in _request raise APIConnectionError(request=request) from err openai.APIConnectionError: Connection error.
Additional Information
No response