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* separated utils into file * add orchestrator * add swe-agent tools * updated orchestrator, moved tools * strip extra char from error msg * changed orchestrator to vision agent and vision agent to vision agent coder * changed orch tools to meta toosl * removed old files * fixed zmq cleanup warning * vision agent uses code interpreter * added more tools * added more examples, fixed chat * added eof text * added directory info * code exec needs to keep state * format fix * need to start kernel on init * logging fix, send traceback * add example chat app * fix type errors * mypy, flake8 fixes * fix type issue' * updated docs; * added tool description func * fix retries on planning and logging * multi plan * don't test multi plan on edit code * fix flake8 * added zmq logging * flake8 * mypy * updated readme * added citation * add stylizing * fixed plan testing prompt * fix names of tabs * better formatting for obs * add image viewing * add log_progress * spelling mistakes * updated readme * fixed docs
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cff-version: 1.2.0 | ||
message: "If you use this software, please cite it as below." | ||
authors: | ||
- family-names: "Laird" | ||
given-names: "Dillon" | ||
- family-names: "Jagadeesan" | ||
given-name: "Shankar" | ||
- family-name: "Cao" | ||
given-name: "Yazhou" | ||
- family-name: "Ng" | ||
given-name: "Andrew" | ||
title: "Vision Agent" | ||
version: 0.2 | ||
date-released: 2024-02-12 | ||
url: "https://github.com/landing-ai/vision-agent" |
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::: vision_agent.agent.agent.Agent | ||
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::: vision_agent.agent.vision_agent.VisionAgent | ||
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::: vision_agent.agent.vision_agent_coder.VisionAgentCoder | ||
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::: vision_agent.agent.vision_agent_coder.AzureVisionAgentCoder |
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::: vision_agent.lmm.OpenAILMM | ||
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::: vision_agent.lmm.AzureOpenAILMM | ||
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::: vision_agent.lmm.OllamaLMM | ||
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::: vision_agent.lmm.ClaudeSonnetLMM |
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# Vision Agent Chat Application | ||
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The Vision Agent chat appliction allows you to have conversations with the agent system | ||
to accomplish a wider variety of tasks. | ||
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## Get Started | ||
To get started first install the requirements by running the following command: | ||
```bash | ||
pip install -r requirements.txt | ||
``` | ||
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There are two environment variables you must set, the first is `WORKSPACE` which is | ||
where the agent will look for and write files to: | ||
```bash | ||
export WORKSPACE=/path/to/your/workspace | ||
``` | ||
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The second is `ZMQ_PORT`, this is how the agent collects logs from subprocesses it runs | ||
for writing code: | ||
```bash | ||
export ZMQ_PORT=5555 | ||
``` | ||
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Finally you can launch the app with the following command: | ||
```bash | ||
streamlit run app.py | ||
``` | ||
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You can upload an image to your workspace in the right column first tab, then ask the | ||
agent to do a task, (be sure to include which image you want it to use for testing) for | ||
example: | ||
``` | ||
Can you count the number of people in this image? Use image.jpg for testing. | ||
``` | ||
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## Layout | ||
The are two columns, left and right, each with two tabs. | ||
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`Chat` the left column first tab is where you can chat with Vision Agent. It can answer | ||
your questions and execute python code on your behalf. Note if you ask it to generate | ||
vision code it may take awhile to run. | ||
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`Code Execution Logs` the left column second tab is where you will see intermediate logs | ||
when Vision Agent is generating vision code. Because code generation can take some | ||
time, you can monitor this tab to see what the agent is doing. | ||
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`File Browser` the right column first tab is where you can see the files in your | ||
workspace. | ||
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`Code Editor` the right column second tab is where you can examine code files the agent | ||
has written. You can also modify the code and save it in case the code is incorrect. |
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