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update intro and quickstart

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  - en
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  pipeline_tag: text-generation
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  ---
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- # CodeQwen1.5-7B-OD
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  ## Introduction
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- OpenDevin/CodeQwen1.5-7B-OD is a version based on CodeQwen1.5-7B, fine-tuned with a small amount of `Agent` format data.
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- It is an open model designed for rapid development, debugging, and iteration.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Citation
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- If you find our work helpful, feel free to give us a cite.
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  ```
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  @article{qwen,
 
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  - en
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  pipeline_tag: text-generation
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  ---
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+ # CodeQwen1.5-7B-OpenDevin
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  ## Introduction
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+ CodeQwen1.5-7B-OpenDevin is a code-specific model targeting on OpenDevin Agent tasks.
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+ The model is finetuned from CodeQwen1.5-7B, the code-specific large language model based on Qwen1.5 pretrained on large-scale code data.
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+ CodeQwen1.5-7B is strongly capable of understanding and generating codes, and it supports the context length of 65,536 tokens (for more information about CodeQwen1.5, please refer to the [blog post](https://qwenlm.github.io/blog/codeqwen1.5/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5)).
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+ The finetuned model, CodeQwen1.5-7B-OpenDevin, shares similar features, while it is designed for rapid development, debugging, and iteration.
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+
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+ ## Performance
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+ We evaluate CodeQwen1.5-7B-OpenDevin on SWE-Bench-Lite by implementing the model on OpenDevin CodeAct 1.3 and follow the OpenDevin evaluation pipeline.
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+ CodeQwen1.5-7B-OpenDevin successfully solves 4 problems by commmiting pull requests targeting on the issues.
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+
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+ ## Requirements
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+ The code of Qwen1.5 has been in the latest Hugging face transformers and we advise you to install `transformers>=4.37.0`, or you might encounter the following error:
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+ ```
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+ KeyError: 'qwen2'.
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+ ```
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+
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+ ## Quickstart
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+
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+ To use local models to run OpenDevin, we advise you to deploy CodeQwen1.5-7B-OpenDevin on a GPU device and access it through OpenAI API
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+
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+ ```bash
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+ python -m vllm.entrypoints.openai.api_server --model OpenDevin/CodeQwen1.5-7B-OpenDevin --dtype auto --api-key token-abc123
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+ ```
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+
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+ For more details, please refer to the official documentation of [vLLM for OpenAI Compatible server](https://docs.vllm.ai/en/stable/serving/openai_compatible_server.html).
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+
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+ After the deployment, following the guidance of [OpenDevin](https://github.com/OpenDevin/OpenDevin) and run the following command to set up environment variables:
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+
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+ ```bash
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+ # The directory you want OpenDevin to work with. MUST be an absolute path!
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+ export WORKSPACE_BASE=$(pwd)/workspace;
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+ export LLM_API_KEY=token-abc123;
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+ export LLM_MODEL=OpenDevin/CodeQwen1.5-7B-OpenDevin;
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+ export LLM_BASE_URL=http://localhost:8000/v1;
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+ ```
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+
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+ and run the docker command:
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+
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+ ```bash
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+ docker run \
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+ -it \
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+ --pull=always \
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+ -e SANDBOX_USER_ID=$(id -u) \
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+ -e LLM_BASE_URL=$LLM_BASE_URL \
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+ -e LLM_API_KEY=$LLM_API_KEY \
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+ -e LLM_MODEL=$LLM_MODEL \
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+ -e WORKSPACE_MOUNT_PATH=$WORKSPACE_BASE \
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+ -v $WORKSPACE_BASE:/opt/workspace_base \
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+ -v /var/run/docker.sock:/var/run/docker.sock \
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+ -p 3000:3000 \
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+ --add-host host.docker.internal:host-gateway \
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+ ghcr.io/opendevin/opendevin:0.5
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+ ```
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+
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+ Now you should be able to connect `http://localhost:3000/`. Set up the configuration at the frontend by clicking the button at the bottom right, and input the right model name and api key.
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+ Then, you can enjoy playing with OpenDevin based on CodeQwen1.5-7B-OpenDevin!
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  ## Citation
 
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  ```
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  @article{qwen,