[Evaluation] Use the latest official SWE-Bench Dockerization for evaluation (#2728)

* add newline after patch to fix patch apply

* new swebench wip

* add newline after patch to fix patch apply

* only add newline if not empty

* update swebench source and update

* update gitignore for swebench eval

* update old prep_eval

* update gitignore

* add scripts for push and pull swebench images

* update eval_infer.sh

* update eval_infer for new docker workflow

* update script to create markdown report based on report.json

* update eval infer to use update output

* update readme

* only move result to folder if running whole file

* remove set-x

* update conversion script

* Update evaluation/swe_bench/README.md

* Update evaluation/swe_bench/README.md

* Update evaluation/swe_bench/README.md

* make sure last line end with newline

* switch to an fix attempt branch of swebench

* Update evaluation/swe_bench/README.md

* Update evaluation/swe_bench/README.md

---------

Co-authored-by: Engel Nyst <enyst@users.noreply.github.com>

.gitignore

@@ -212,4 +212,8 @@ cache
 config.toml
 config.toml.bak
 
-containers/agnostic_sandbox
+containers/agnostic_sandbox
+
+# swe-bench-eval
+image_build_logs
+run_instance_logs

evaluation/swe_bench/README.md

@@ -2,6 +2,8 @@
 
 This folder contains the evaluation harness that we built on top of the original [SWE-Bench benchmark](https://www.swebench.com/) ([paper](https://arxiv.org/abs/2310.06770)). We created [a fork of SWE-Bench](https://github.com/OpenDevin/OD-SWE-bench.git) mostly built on top of [the original repo](https://github.com/princeton-nlp/SWE-bench) and [containerized](#opendevin-swe-bench-docker-image) it for easy evaluation.
 
+**UPDATE (7/1/2024): We now support the official SWE-Bench dockerized evaluation as announced [here](https://github.com/princeton-nlp/SWE-bench/blob/main/docs/20240627_docker/README.md).**
+
 ## Setup Environment
 
 Please follow [this document](https://github.com/OpenDevin/OpenDevin/blob/main/Development.md) to set up a local development environment for OpenDevin.
@@ -10,7 +12,7 @@ Please follow [this document](https://github.com/OpenDevin/OpenDevin/blob/main/D
 
 In [OpenDevin-SWE-Bench fork](https://github.com/OpenDevin/OD-SWE-bench.git) (mostly from [original repo](https://github.com/princeton-nlp/SWE-bench) with some fixes), we try to pre-build the **testbed** (i.e., code of the repository we want the agent to edit) AND the **conda environment**, so that in evaluation (inference) time, we can directly leverage existing environments for efficient evaluation.
 
-**We pack everything you need for SWE-Bench evaluation into one, gigantic, docker image.** To use it:
+**We pack everything you need for SWE-Bench inference into one, gigantic, docker image.** To use it:
 
 ```bash
 docker pull ghcr.io/opendevin/eval-swe-bench:full-v1.2.1
@@ -124,16 +126,23 @@ After running the inference, you will obtain a `output.jsonl` (by default it wil
 
 With `output.jsonl` file, you can run `eval_infer.sh` to evaluate generated patches, and produce a fine-grained report.
 
+**This evaluation is performed using the official dockerized evaluation announced [here](https://github.com/princeton-nlp/SWE-bench/blob/main/docs/20240627_docker/README.md).**
+
 If you want to evaluate existing results, you should first run this to clone existing outputs
 
 ```bash
 git clone https://huggingface.co/spaces/OpenDevin/evaluation evaluation/evaluation_outputs
 ```
 
-To prepare for swe-bench evaluation, you should pull evaluation docker from [OpenDevin/SWE-bench-docker](https://github.com/OpenDevin/SWE-bench-docker) and download swe-bench data by running:
+If you have extra local space (e.g., 500GB), you can try pull the [instance-level docker images](https://github.com/princeton-nlp/SWE-bench/blob/main/docs/20240627_docker/README.md#choosing-the-right-cache_level) we've prepared to speed up the evaluation by running:
 
 ```bash
-evaluation/swe_bench/scripts/eval/prep_eval.sh
+evaluation/swe_bench/scripts/docker/pull_all_eval_docker.sh instance
+```
+
+If you want to save disk space a bit (e.g., with ~50GB free disk space), while speeding up the image pre-build process, you can pull the environment-level docker images:
+```bash
+evaluation/swe_bench/scripts/docker/pull_all_eval_docker.sh env
 ```
 
 Then you can run the following:
@@ -146,12 +155,11 @@ Then you can run the following:
 
 PS: You can also pass in a JSONL with [SWE-Bench format](https://github.com/princeton-nlp/SWE-bench/blob/main/tutorials/evaluation.md#-creating-predictions) to `./evaluation/swe_bench/scripts/eval_infer.sh`, where each line is a JSON of `{"model_patch": "XXX", "model_name_or_path": "YYY", "instance_id": "ZZZ"}`.
 
-The final results will be saved to `evaluation/evaluation_outputs/outputs/swe_bench/CodeActAgent/gpt-4-1106-preview_maxiter_50_N_v1.0/` with the following files/directory (following format of [SWE-bench-docker](https://github.com/aorwall/SWE-bench-docker/tree/main/evaluations/SWE-bench_Lite_golden)):
+The final results will be saved to `evaluation/evaluation_outputs/outputs/swe_bench/CodeActAgent/gpt-4-1106-preview_maxiter_50_N_v1.0/` with the following files/directory:
 
 - `README.md`: a report showing what are the instances that passed, failed, etc.
-- `logs/`: a directory of test logs
+- `report.json`: a JSON file that contains keys like `"resolved_ids"` pointing to instance IDs that are resolved by the agent.
-- `report.json`: a JSON file that contains keys like `"resolved"` pointing to instance IDs that are resolved by the agent.
+- `eval_outputs/`: a directory of test logs
-- `summary.json`: a JSON file contains more fine-grained information for each test instance.
 
 ## Visualize Results
 

evaluation/swe_bench/scripts/docker/all-swebench-lite-instance-images.txt

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+sweb.eval.x86_64.sympy__sympy-12236:latest
+sweb.eval.x86_64.sympy__sympy-12419:latest
+sweb.eval.x86_64.sympy__sympy-12454:latest
+sweb.eval.x86_64.sympy__sympy-12481:latest
+sweb.eval.x86_64.sympy__sympy-13031:latest
+sweb.eval.x86_64.sympy__sympy-13043:latest
+sweb.eval.x86_64.sympy__sympy-13146:latest
+sweb.eval.x86_64.sympy__sympy-13177:latest
+sweb.eval.x86_64.sympy__sympy-13437:latest
+sweb.eval.x86_64.sympy__sympy-13471:latest
+sweb.eval.x86_64.sympy__sympy-13480:latest
+sweb.eval.x86_64.sympy__sympy-13647:latest
+sweb.eval.x86_64.sympy__sympy-13773:latest
+sweb.eval.x86_64.sympy__sympy-13895:latest
+sweb.eval.x86_64.sympy__sympy-13915:latest
+sweb.eval.x86_64.sympy__sympy-13971:latest
+sweb.eval.x86_64.sympy__sympy-14024:latest
+sweb.eval.x86_64.sympy__sympy-14308:latest
+sweb.eval.x86_64.sympy__sympy-14317:latest
+sweb.eval.x86_64.sympy__sympy-14396:latest
+sweb.eval.x86_64.sympy__sympy-14774:latest
+sweb.eval.x86_64.sympy__sympy-14817:latest
+sweb.eval.x86_64.sympy__sympy-15011:latest
+sweb.eval.x86_64.sympy__sympy-15308:latest
+sweb.eval.x86_64.sympy__sympy-15345:latest
+sweb.eval.x86_64.sympy__sympy-15346:latest
+sweb.eval.x86_64.sympy__sympy-15609:latest
+sweb.eval.x86_64.sympy__sympy-15678:latest
+sweb.eval.x86_64.sympy__sympy-16106:latest
+sweb.eval.x86_64.sympy__sympy-16281:latest
+sweb.eval.x86_64.sympy__sympy-16503:latest
+sweb.eval.x86_64.sympy__sympy-16792:latest
+sweb.eval.x86_64.sympy__sympy-16988:latest
+sweb.eval.x86_64.sympy__sympy-17022:latest
+sweb.eval.x86_64.sympy__sympy-17139:latest
+sweb.eval.x86_64.sympy__sympy-17630:latest
+sweb.eval.x86_64.sympy__sympy-17655:latest
+sweb.eval.x86_64.sympy__sympy-18057:latest
+sweb.eval.x86_64.sympy__sympy-18087:latest
+sweb.eval.x86_64.sympy__sympy-18189:latest
+sweb.eval.x86_64.sympy__sympy-18199:latest
+sweb.eval.x86_64.sympy__sympy-18532:latest
+sweb.eval.x86_64.sympy__sympy-18621:latest
+sweb.eval.x86_64.sympy__sympy-18698:latest
+sweb.eval.x86_64.sympy__sympy-18835:latest
+sweb.eval.x86_64.sympy__sympy-19007:latest
+sweb.eval.x86_64.sympy__sympy-19254:latest
+sweb.eval.x86_64.sympy__sympy-19487:latest
+sweb.eval.x86_64.sympy__sympy-20049:latest
+sweb.eval.x86_64.sympy__sympy-20154:latest
+sweb.eval.x86_64.sympy__sympy-20212:latest
+sweb.eval.x86_64.sympy__sympy-20322:latest
+sweb.eval.x86_64.sympy__sympy-20442:latest
+sweb.eval.x86_64.sympy__sympy-20590:latest
+sweb.eval.x86_64.sympy__sympy-20639:latest
+sweb.eval.x86_64.sympy__sympy-21055:latest
+sweb.eval.x86_64.sympy__sympy-21171:latest
+sweb.eval.x86_64.sympy__sympy-21379:latest
+sweb.eval.x86_64.sympy__sympy-21612:latest
+sweb.eval.x86_64.sympy__sympy-21614:latest
+sweb.eval.x86_64.sympy__sympy-21627:latest
+sweb.eval.x86_64.sympy__sympy-21847:latest
+sweb.eval.x86_64.sympy__sympy-22005:latest
+sweb.eval.x86_64.sympy__sympy-22714:latest
+sweb.eval.x86_64.sympy__sympy-22840:latest
+sweb.eval.x86_64.sympy__sympy-23117:latest
+sweb.eval.x86_64.sympy__sympy-23191:latest
+sweb.eval.x86_64.sympy__sympy-23262:latest
+sweb.eval.x86_64.sympy__sympy-24066:latest
+sweb.eval.x86_64.sympy__sympy-24102:latest
+sweb.eval.x86_64.sympy__sympy-24152:latest
+sweb.eval.x86_64.sympy__sympy-24213:latest
+sweb.eval.x86_64.sympy__sympy-24909:latest

evaluation/swe_bench/scripts/docker/pull_all_eval_docker.sh

@@ -1,7 +1,47 @@
 #!/bin/bash
+set -e
 
-mkdir evaluation/swe_bench/eval_workspace
+LEVEL=$1
-pushd evaluation/swe_bench/eval_workspace
+# three levels:
-git clone https://github.com/OpenDevin/SWE-bench-docker.git
+# - base, keyword "sweb.base"
-cd SWE-bench-docker
+# - env, keyword "sweb.env"
-scripts/pull_docker_images.sh docker/ xingyaoww
+# - instance, keyword "sweb.eval"
+
+if [ -z "$LEVEL" ]; then
+    echo "Usage: $0 <cache_level>"
+    echo "cache_level: base, env, or instance"
+    exit 1
+fi
+
+NAMESPACE=xingyaoww
+IMAGE_FILE="$(dirname "$0")/all-swebench-lite-instance-images.txt"
+
+# Define a pattern based on the level
+case $LEVEL in
+    base)
+        PATTERN="sweb.base"
+        ;;
+    env)
+        PATTERN="sweb.base\|sweb.env"
+        ;;
+    instance)
+        PATTERN="sweb.base\|sweb.env\|sweb.eval"
+        ;;
+    *)
+        echo "Invalid cache level: $LEVEL"
+        echo "Valid levels are: base, env, instance"
+        exit 1
+        ;;
+esac
+
+echo "Pulling docker images for [$LEVEL] level"
+
+echo "Pattern: $PATTERN"
+echo "Image file: $IMAGE_FILE"
+
+# Read each line from the file, filter by pattern, and pull the docker image
+grep "$PATTERN" "$IMAGE_FILE" | while IFS= read -r image; do
+    echo "Pulling $NAMESPACE/$image into $image"
+    docker pull $NAMESPACE/$image
+    docker tag $NAMESPACE/$image $image
+done

evaluation/swe_bench/scripts/docker/push_eval_docker.sh

@@ -0,0 +1,30 @@
+#!/bin/bash
+
+# This is ONLY used for pushing docker images created by https://github.com/princeton-nlp/SWE-bench/blob/main/docs/20240627_docker/README.md
+
+DOCKER_NAMESPACE=$1
+# check if DOCKER_NAMESPACE is set
+if [ -z "$DOCKER_NAMESPACE" ]; then
+    echo "Usage: $0 <docker_namespace>"
+    exit 1
+fi
+
+# target namespace
+image_list=$(docker image ls --format '{{.Repository}}:{{.Tag}}' | grep sweb | grep -v $DOCKER_NAMESPACE)
+
+# There are three tiers of images
+# - base
+# - env
+# - eval (instance level)
+
+for image in $image_list; do
+    echo "=============================="
+    echo "Image: $image"
+    # rename image by replace "__" with "_s_" to comply with docker naming convention
+    new_image_name=${image//__/_s_}
+    docker tag $image $DOCKER_NAMESPACE/$new_image_name
+    echo "Tagged $image to $DOCKER_NAMESPACE/$new_image_name"
+
+    docker push $DOCKER_NAMESPACE/$new_image_name
+    echo "Pushed $DOCKER_NAMESPACE/$new_image_name"
+done

evaluation/swe_bench/scripts/eval/convert_od_output_to_swe_json.py

@@ -14,12 +14,37 @@ od_format = pd.read_json(args.od_output_file, orient='records', lines=True)
 model_name = os.path.basename(os.path.dirname(args.od_output_file))
 
 
+def process_git_patch(patch):
+    if not patch.strip():
+        # skip empty patches
+        return ''
+
+    patch = patch.replace('\r\n', '\n')
+    # There might be some weird characters at the beginning of the patch
+    # due to some OpenDevin inference command outputs
+
+    # FOR EXAMPLE:
+    # git diff --no-color --cached 895f28f9cbed817c00ab68770433170d83132d90
+    # 0
+    # diff --git a/django/db/models/sql/.backup.query.py b/django/db/models/sql/.backup.query.py
+    # new file mode 100644
+    # index 0000000000..fc13db5948
+
+    # We "find" the first line that starts with "diff" and then we remove lines before it
+    lines = patch.split('\n')
+    for i, line in enumerate(lines):
+        if line.startswith('diff --git'):
+            patch = '\n'.join(lines[i:])
+            break
+
+    patch = patch.rstrip() + '\n'  # Make sure the last line ends with a newline
+    return patch
+
+
 def convert_row_to_swebench_format(row):
     return {
         'instance_id': row['instance_id'],
-        'model_patch': row['git_patch'].replace('\r\n', '\n').rstrip() + '\n'
+        'model_patch': process_git_patch(row['git_patch']),
-        if row['git_patch'].strip()
-        else '',
         'model_name_or_path': model_name,
     }
 

evaluation/swe_bench/scripts/eval/prep_eval.sh

@@ -3,6 +3,11 @@
 echo "Cloning OpenDevin SWE-Bench Fork"
 git clone https://github.com/OpenDevin/SWE-bench.git evaluation/swe_bench/eval_workspace/SWE-bench
 
+# checkout to main-old
+pushd evaluation/swe_bench/eval_workspace/SWE-bench
+git checkout main-old
+popd
+
 echo "Pulling all evaluation dockers..."
 evaluation/swe_bench/scripts/docker/pull_all_eval_docker.sh
 

evaluation/swe_bench/scripts/eval/update_output_with_eval.py

@@ -14,24 +14,44 @@ report_json = os.path.join(dirname, 'report.json')
 
 df = pd.read_json(args.input_file, lines=True)
 
-instance_id_to_status = defaultdict(dict)
+output_md_filepath = os.path.join(dirname, 'README.md')
+instance_id_to_status = defaultdict(lambda: {'resolved': False})
 if os.path.exists(report_json):
     with open(report_json, 'r') as f:
         report = json.load(f)
 
+    output_md = (
+        "# SWE-bench Report\n"
+        "This folder contains the evaluation results of the SWE-bench using the [official evaluation docker containerization](https://github.com/princeton-nlp/SWE-bench/blob/main/docs/20240627_docker/README.md#choosing-the-right-cache_level).\n\n"
+        "## Summary\n"
+        f"- total instances: {report['total_instances']}\n"
+        f"- completed instances: {report['completed_instances']}\n"
+        f"- resolved instances: {report['resolved_instances']}\n"
+        f"- unresolved instances: {report['unresolved_instances']}\n"
+        f"- error instances: {report['error_instances']}\n"
+        f"- unstopped instances: {report['unstopped_instances']}\n"
+    )
+
+    output_md += '\n## Resolved Instances\n'
     # instance_id to status
-    for status, instance_ids in report.items():
+    for instance_id in report['resolved_ids']:
-        for instance_id in instance_ids:
+        instance_id_to_status[instance_id]['resolved'] = True
-            if status == 'resolved':
+        output_md += (
-                instance_id_to_status[instance_id]['resolved'] = True
+            f'- [{instance_id}](./eval_outputs/{instance_id}/run_instance.log)\n'
-            elif status == 'applied':
+        )
-                instance_id_to_status[instance_id]['applied'] = True
+
-            elif status == 'test_timeout':
+    output_md += '\n## Unresolved Instances\n'
-                instance_id_to_status[instance_id]['test_timeout'] = True
+    for instance_id in report['unresolved_ids']:
-            elif status == 'test_errored':
+        output_md += (
-                instance_id_to_status[instance_id]['test_errored'] = True
+            f'- [{instance_id}](./eval_outputs/{instance_id}/run_instance.log)\n'
-            elif status == 'no_generation':
+        )
-                instance_id_to_status[instance_id]['empty_generation'] = True
+
+    output_md += '\n## Error Instances\n'
+    for instance_id in report['error_ids']:
+        instance_id_to_status[instance_id]['error_eval'] = True
+        output_md += (
+            f'- [{instance_id}](./eval_outputs/{instance_id}/run_instance.log)\n'
+        )
 
     # Apply the status to the dataframe
     def apply_report(row):
@@ -52,3 +72,6 @@ if os.path.exists(args.input_file + '.bak'):
 # backup the original file
 os.rename(args.input_file, args.input_file + '.bak')
 df.to_json(args.input_file, orient='records', lines=True)
+
+with open(output_md_filepath, 'w') as f:
+    f.write(output_md)

evaluation/swe_bench/scripts/eval_infer.sh

@@ -19,8 +19,6 @@ echo "INSTANCE_ID: $INSTANCE_ID"
 PROCESS_FILEPATH=$(realpath $PROCESS_FILEPATH)
 FILE_DIR=$(dirname $PROCESS_FILEPATH)
 FILE_NAME=$(basename $PROCESS_FILEPATH)
-mkdir -p $FILE_DIR/logs
-mkdir -p $FILE_DIR/swe_bench_format
 
 echo "Evaluating $FILE_NAME @ $FILE_DIR"
 DOCKERHUB_NAMESPACE="xingyaoww"
@@ -75,29 +73,58 @@ echo "=============================================================="
 echo "Running SWE-bench evaluation"
 echo "=============================================================="
 
+RUN_ID=$(date +"%Y%m%d_%H%M%S")
+N_PROCESS=16
+
 if [ -z "$INSTANCE_ID" ]; then
     echo "Running SWE-bench evaluation on the whole input file..."
+    # Default to SWE-Bench-lite
+    # change `--dataset_name` and `--split` to alter dataset
 
-    poetry run python $SWEBENCH_DOCKER_FORK_DIR/run_evaluation.py \
+    poetry run python -m swebench.harness.run_evaluation \
         --predictions_path $SWEBENCH_FORMAT_JSONL \
-        --log_dir $FILE_DIR/logs \
+        --timeout 1800 \
-        --swe_bench_tasks $SWEBENCH_TASKS \
+        --cache_level instance \
-        --namespace $DOCKERHUB_NAMESPACE \
+        --max_workers $N_PROCESS \
-        --timeout 1800
+        --run_id $RUN_ID
+
+    # get the "model_name_or_path" from the first line of the SWEBENCH_FORMAT_JSONL
+    MODEL_NAME_OR_PATH=$(jq -r '.model_name_or_path' $SWEBENCH_FORMAT_JSONL | head -n 1)
+    echo "MODEL_NAME_OR_PATH: $MODEL_NAME_OR_PATH"
+
+    RESULT_OUTPUT_DIR=$(dirname $SWEBENCH_FORMAT_JSONL)
+    echo "RESULT_OUTPUT_DIR: $RESULT_OUTPUT_DIR"
+
+    # move the eval results to the target directory
+    mkdir -p $RESULT_OUTPUT_DIR
+    mv run_instance_logs/$RUN_ID/$MODEL_NAME_OR_PATH $RESULT_OUTPUT_DIR
+    mv $RESULT_OUTPUT_DIR/$MODEL_NAME_OR_PATH $RESULT_OUTPUT_DIR/eval_outputs
+    echo "RUN_ID: $RUN_ID" > $RESULT_OUTPUT_DIR/run_id.txt
+
+    # move report file
+    REPORT_PATH=$MODEL_NAME_OR_PATH.$RUN_ID.json
+    if [ -f $REPORT_PATH ]; then
+        # check if $RESULT_OUTPUT_DIR/report.json exists
+        if [ -f $RESULT_OUTPUT_DIR/report.json ]; then
+            echo "Report file $RESULT_OUTPUT_DIR/report.json already exists. Overwriting..."
+            if [ -f $RESULT_OUTPUT_DIR/report.json.bak ]; then
+                rm $RESULT_OUTPUT_DIR/report.json.bak
+            fi
+            mv $RESULT_OUTPUT_DIR/report.json $RESULT_OUTPUT_DIR/report.json.bak
+        fi
+
+        mv $REPORT_PATH $RESULT_OUTPUT_DIR/report.json
+    fi
+
+    poetry run python evaluation/swe_bench/scripts/eval/update_output_with_eval.py $PROCESS_FILEPATH
 
 else
     echo "Running SWE-bench evaluation on the instance_id: $INSTANCE_ID"
-    poetry run python $SWEBENCH_DOCKER_FORK_DIR/run_single_instance.py \
+    poetry run python -m swebench.harness.run_evaluation \
         --predictions_path $SWEBENCH_FORMAT_JSONL \
-        --swe_bench_tasks $SWEBENCH_TASKS \
+        --timeout 1800 \
-        --namespace $DOCKERHUB_NAMESPACE \
+        --instance_ids $INSTANCE_ID \
-        --instance_id $INSTANCE_ID
+        --cache_level instance \
+        --max_workers $N_PROCESS \
+        --run_id $RUN_ID
 fi
-
-poetry run python $SWEBENCH_DOCKER_FORK_DIR/generate_report.py \
-    --predictions_path $SWEBENCH_FORMAT_JSONL \
-    --log_dir $FILE_DIR/logs \
-    --output_dir $FILE_DIR \
-    --swe_bench_tasks $SWEBENCH_TASKS
-
-poetry run python evaluation/swe_bench/scripts/eval/update_output_with_eval.py $PROCESS_FILEPATH

poetry.lock

@@ -298,13 +298,13 @@ aio = ["aiohttp (>=3.0)"]
 
 [[package]]
 name = "azure-identity"
-version = "1.16.1"
+version = "1.17.1"
 description = "Microsoft Azure Identity Library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "azure-identity-1.16.1.tar.gz", hash = "sha256:6d93f04468f240d59246d8afde3091494a5040d4f141cad0f49fc0c399d0d91e"},
+    {file = "azure-identity-1.17.1.tar.gz", hash = "sha256:32ecc67cc73f4bd0595e4f64b1ca65cd05186f4fe6f98ed2ae9f1aa32646efea"},
-    {file = "azure_identity-1.16.1-py3-none-any.whl", hash = "sha256:8fb07c25642cd4ac422559a8b50d3e77f73dcc2bbfaba419d06d6c9d7cff6726"},
+    {file = "azure_identity-1.17.1-py3-none-any.whl", hash = "sha256:db8d59c183b680e763722bfe8ebc45930e6c57df510620985939f7f3191e0382"},
 ]
 
 [package.dependencies]
@@ -312,6 +312,7 @@ azure-core = ">=1.23.0"
 cryptography = ">=2.5"
 msal = ">=1.24.0"
 msal-extensions = ">=0.3.0"
+typing-extensions = ">=4.0.0"
 
 [[package]]
 name = "backoff"
@@ -536,13 +537,13 @@ libwebarena = "0.0.3"
 
 [[package]]
 name = "browsergym-workarena"
-version = "0.3.0"
+version = "0.3.1"
 description = "WorkArena benchmark for BrowserGym"
 optional = false
 python-versions = ">3.7"
 files = [
-    {file = "browsergym_workarena-0.3.0-py3-none-any.whl", hash = "sha256:4c9208c7b37fdc676d200e4ecf29c395b71a9f05d0de91ac69f4ab0f474ee85f"},
+    {file = "browsergym_workarena-0.3.1-py3-none-any.whl", hash = "sha256:5ba113d38401ac6c4a5548a77ef91655a50cb48384d434f1a4eb691219b69957"},
-    {file = "browsergym_workarena-0.3.0.tar.gz", hash = "sha256:6ff1adf708a95721adc04aef562ecf8f46a2807f0e247fe3171990acbcaff112"},
+    {file = "browsergym_workarena-0.3.1.tar.gz", hash = "sha256:f0685e371cff206c3a54758bfc81ae7ea1473f6ae21f685e48cf01761235e61e"},
 ]
 
 [package.dependencies]
@@ -980,63 +981,63 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
 
 [[package]]
 name = "coverage"
-version = "7.5.3"
+version = "7.5.4"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "coverage-7.5.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a6519d917abb15e12380406d721e37613e2a67d166f9fb7e5a8ce0375744cd45"},
+    {file = "coverage-7.5.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6cfb5a4f556bb51aba274588200a46e4dd6b505fb1a5f8c5ae408222eb416f99"},
-    {file = "coverage-7.5.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:aea7da970f1feccf48be7335f8b2ca64baf9b589d79e05b9397a06696ce1a1ec"},
+    {file = "coverage-7.5.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2174e7c23e0a454ffe12267a10732c273243b4f2d50d07544a91198f05c48f47"},
-    {file = "coverage-7.5.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:923b7b1c717bd0f0f92d862d1ff51d9b2b55dbbd133e05680204465f454bb286"},
+    {file = "coverage-7.5.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2214ee920787d85db1b6a0bd9da5f8503ccc8fcd5814d90796c2f2493a2f4d2e"},
-    {file = "coverage-7.5.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:62bda40da1e68898186f274f832ef3e759ce929da9a9fd9fcf265956de269dbc"},
+    {file = "coverage-7.5.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1137f46adb28e3813dec8c01fefadcb8c614f33576f672962e323b5128d9a68d"},
-    {file = "coverage-7.5.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d8b7339180d00de83e930358223c617cc343dd08e1aa5ec7b06c3a121aec4e1d"},
+    {file = "coverage-7.5.4-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b385d49609f8e9efc885790a5a0e89f2e3ae042cdf12958b6034cc442de428d3"},
-    {file = "coverage-7.5.3-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:25a5caf742c6195e08002d3b6c2dd6947e50efc5fc2c2205f61ecb47592d2d83"},
+    {file = "coverage-7.5.4-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:b4a474f799456e0eb46d78ab07303286a84a3140e9700b9e154cfebc8f527016"},
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 ]
 
 [package.extras]
@@ -1312,13 +1313,13 @@ websockets = ">=11.0.3"
 
 [[package]]
 name = "email-validator"
-version = "2.1.2"
+version = "2.2.0"
 description = "A robust email address syntax and deliverability validation library."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "email_validator-2.1.2-py3-none-any.whl", hash = "sha256:d89f6324e13b1e39889eab7f9ca2f91dc9aebb6fa50a6d8bd4329ab50f251115"},
+    {file = "email_validator-2.2.0-py3-none-any.whl", hash = "sha256:561977c2d73ce3611850a06fa56b414621e0c8faa9d66f2611407d87465da631"},
-    {file = "email_validator-2.1.2.tar.gz", hash = "sha256:14c0f3d343c4beda37400421b39fa411bbe33a75df20825df73ad53e06a9f04c"},
+    {file = "email_validator-2.2.0.tar.gz", hash = "sha256:cb690f344c617a714f22e66ae771445a1ceb46821152df8e165c5f9a364582b7"},
 ]
 
 [package.dependencies]
@@ -1372,13 +1373,13 @@ torch = ["torch"]
 
 [[package]]
 name = "faker"
-version = "25.8.0"
+version = "26.0.0"
 description = "Faker is a Python package that generates fake data for you."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "Faker-25.8.0-py3-none-any.whl", hash = "sha256:4c40b34a9c569018d4f9d6366d71a4da8a883d5ddf2b23197be5370f29b7e1b6"},
+    {file = "Faker-26.0.0-py3-none-any.whl", hash = "sha256:886ee28219be96949cd21ecc96c4c742ee1680e77f687b095202c8def1a08f06"},
-    {file = "Faker-25.8.0.tar.gz", hash = "sha256:bdec5f2fb057d244ebef6e0ed318fea4dcbdf32c3a1a010766fc45f5d68fc68d"},
+    {file = "Faker-26.0.0.tar.gz", hash = "sha256:0f60978314973de02c00474c2ae899785a42b2cf4f41b7987e93c132a2b8a4a9"},
 ]
 
 [package.dependencies]
@@ -1441,13 +1442,13 @@ standard = ["fastapi", "uvicorn[standard] (>=0.15.0)"]
 
 [[package]]
 name = "fastcore"
-version = "1.5.46"
+version = "1.5.48"
 description = "Python supercharged for fastai development"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "fastcore-1.5.46-py3-none-any.whl", hash = "sha256:ba96bd081e84c16035c48f87930032a568751bdfb11cb2c2d8ff92b42c11a4b0"},
+    {file = "fastcore-1.5.48-py3-none-any.whl", hash = "sha256:54f80c8bb16a5f43feb3357ddff8c416215d7ff781e63669203cb9dfdaa0c5b4"},
-    {file = "fastcore-1.5.46.tar.gz", hash = "sha256:5c916feddbf3db41b78d2963cc83387b2bfdbaf87043a01040008e6db73d4463"},
+    {file = "fastcore-1.5.48.tar.gz", hash = "sha256:39c5e1c4539c04b68d1c9b3971c031b3949001b3cfc98eb0c347ae8d91c2dc2b"},
 ]
 
 [package.dependencies]
@@ -1458,18 +1459,18 @@ dev = ["matplotlib", "nbclassic", "nbdev (>=0.2.39)", "numpy", "pandas", "pillow
 
 [[package]]
 name = "filelock"
-version = "3.15.1"
+version = "3.15.4"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "filelock-3.15.1-py3-none-any.whl", hash = "sha256:71b3102950e91dfc1bb4209b64be4dc8854f40e5f534428d8684f953ac847fac"},
+    {file = "filelock-3.15.4-py3-none-any.whl", hash = "sha256:6ca1fffae96225dab4c6eaf1c4f4f28cd2568d3ec2a44e15a08520504de468e7"},
-    {file = "filelock-3.15.1.tar.gz", hash = "sha256:58a2549afdf9e02e10720eaa4d4470f56386d7a6f72edd7d0596337af8ed7ad8"},
+    {file = "filelock-3.15.4.tar.gz", hash = "sha256:2207938cbc1844345cb01a5a95524dae30f0ce089eba5b00378295a17e3e90cb"},
 ]
 
 [package.extras]
 docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-asyncio (>=0.21)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-asyncio (>=0.21)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)", "virtualenv (>=20.26.2)"]
 typing = ["typing-extensions (>=4.8)"]
 
 [[package]]
@@ -1846,13 +1847,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 
 [[package]]
 name = "google-api-core"
-version = "2.19.0"
+version = "2.19.1"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.19.0.tar.gz", hash = "sha256:cf1b7c2694047886d2af1128a03ae99e391108a08804f87cfd35970e49c9cd10"},
+    {file = "google-api-core-2.19.1.tar.gz", hash = "sha256:f4695f1e3650b316a795108a76a1c416e6afb036199d1c1f1f110916df479ffd"},
-    {file = "google_api_core-2.19.0-py3-none-any.whl", hash = "sha256:8661eec4078c35428fd3f69a2c7ee29e342896b70f01d1a1cbcb334372dd6251"},
+    {file = "google_api_core-2.19.1-py3-none-any.whl", hash = "sha256:f12a9b8309b5e21d92483bbd47ce2c445861ec7d269ef6784ecc0ea8c1fa6125"},
 ]
 
 [package.dependencies]
@@ -1861,7 +1862,7 @@ googleapis-common-protos = ">=1.56.2,<2.0.dev0"
 grpcio = {version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}
 grpcio-status = {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}
 proto-plus = ">=1.22.3,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0.dev0"
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
 requests = ">=2.18.0,<3.0.0.dev0"
 
 [package.extras]
@@ -1871,13 +1872,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.133.0"
+version = "2.134.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-python-client-2.133.0.tar.gz", hash = "sha256:293092905b66a046d3187a99ac454e12b00cc2c70444f26eb2f1f9c1a82720b4"},
+    {file = "google-api-python-client-2.134.0.tar.gz", hash = "sha256:4a8f0bea651a212997cc83c0f271fc86f80ef93d1cee9d84de7dfaeef2a858b6"},
-    {file = "google_api_python_client-2.133.0-py2.py3-none-any.whl", hash = "sha256:396fe676ea0dfed066654dcf9f8dea77a1342f9d9bb23bb88e45b7b81e773926"},
+    {file = "google_api_python_client-2.134.0-py2.py3-none-any.whl", hash = "sha256:ba05d60f6239990b7994f6328f17bb154c602d31860fb553016dc9f8ce886945"},
 ]
 
 [package.dependencies]
@@ -1950,17 +1951,17 @@ dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "py
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.63.1"
+version = "1.63.2"
 description = "Common protobufs used in Google APIs"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "googleapis-common-protos-1.63.1.tar.gz", hash = "sha256:c6442f7a0a6b2a80369457d79e6672bb7dcbaab88e0848302497e3ec80780a6a"},
+    {file = "googleapis-common-protos-1.63.2.tar.gz", hash = "sha256:27c5abdffc4911f28101e635de1533fb4cfd2c37fbaa9174587c799fac90aa87"},
-    {file = "googleapis_common_protos-1.63.1-py2.py3-none-any.whl", hash = "sha256:0e1c2cdfcbc354b76e4a211a35ea35d6926a835cba1377073c4861db904a1877"},
+    {file = "googleapis_common_protos-1.63.2-py2.py3-none-any.whl", hash = "sha256:27a2499c7e8aff199665b22741997e485eccc8645aa9176c7c988e6fae507945"},
 ]
 
 [package.dependencies]
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
+protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
 
 [package.extras]
 grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
@@ -2797,23 +2798,38 @@ tokenizers = "*"
 extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "resend (>=0.8.0,<0.9.0)"]
 proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "backoff", "cryptography (>=42.0.5,<43.0.0)", "fastapi (>=0.111.0,<0.112.0)", "fastapi-sso (>=0.10.0,<0.11.0)", "gunicorn (>=22.0.0,<23.0.0)", "orjson (>=3.9.7,<4.0.0)", "python-multipart (>=0.0.9,<0.0.10)", "pyyaml (>=6.0.1,<7.0.0)", "rq", "uvicorn (>=0.22.0,<0.23.0)"]
 
+[[package]]
+name = "llama-cloud"
+version = "0.0.6"
+description = ""
+optional = false
+python-versions = "<4,>=3.8"
+files = [
+    {file = "llama_cloud-0.0.6-py3-none-any.whl", hash = "sha256:0f07c8a865be632b543dec2bcad350a68a61f13413a7421b4b03de32c36f0194"},
+    {file = "llama_cloud-0.0.6.tar.gz", hash = "sha256:33b94cd119133dcb2899c9b69e8e1c36aec7bc7e80062c55c65f15618722e091"},
+]
+
+[package.dependencies]
+httpx = ">=0.20.0"
+pydantic = ">=1.10"
+
 [[package]]
 name = "llama-index"
-version = "0.10.45.post1"
+version = "0.10.50"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index-0.10.45.post1-py3-none-any.whl", hash = "sha256:11ff93431a81f1eae5bb73092d194cfb66a36ea90f272ea145f20e6e4324c71c"},
+    {file = "llama_index-0.10.50-py3-none-any.whl", hash = "sha256:18426f1f23378bde506646a6e016c11b7e99f947bcc9c768384ae776da2aeab7"},
-    {file = "llama_index-0.10.45.post1.tar.gz", hash = "sha256:0bd3dcdbbfa468c408ad2f9e839b60562367ec6563c13c9bddcd108309881447"},
+    {file = "llama_index-0.10.50.tar.gz", hash = "sha256:57f8cbd3d981f68ebafff97268f4afb53a1f9f4af0bb748858b14310336b2a4d"},
 ]
 
 [package.dependencies]
 llama-index-agent-openai = ">=0.1.4,<0.3.0"
 llama-index-cli = ">=0.1.2,<0.2.0"
-llama-index-core = "0.10.45"
+llama-index-core = "0.10.50"
 llama-index-embeddings-openai = ">=0.1.5,<0.2.0"
-llama-index-indices-managed-llama-cloud = ">=0.1.2,<0.2.0"
+llama-index-indices-managed-llama-cloud = ">=0.2.0"
 llama-index-legacy = ">=0.9.48,<0.10.0"
 llama-index-llms-openai = ">=0.1.13,<0.2.0"
 llama-index-multi-modal-llms-openai = ">=0.1.3,<0.2.0"
@@ -2856,13 +2872,13 @@ llama-index-llms-openai = ">=0.1.1,<0.2.0"
 
 [[package]]
 name = "llama-index-core"
-version = "0.10.45"
+version = "0.10.50"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index_core-0.10.45-py3-none-any.whl", hash = "sha256:8c800c7221322b8e1cbbbc13325039b5fe3575d4b0e0be14ac9a8f1e5d14fee3"},
+    {file = "llama_index_core-0.10.50-py3-none-any.whl", hash = "sha256:8a1fc49d65156002bb7f4c82458385ee440bd11f81d1bc39ed03ce94f53c9c74"},
-    {file = "llama_index_core-0.10.45.tar.gz", hash = "sha256:f32d0448e7193ff45c8e84abd49493be030998fc8f1a0cab069387deef3e577c"},
+    {file = "llama_index_core-0.10.50.tar.gz", hash = "sha256:9e64dd54b19aca235b360b2f81d6f93014f1439304cc9369a0e53e4cba9e33aa"},
 ]
 
 [package.dependencies]
@@ -2872,18 +2888,18 @@ deprecated = ">=1.2.9.3"
 dirtyjson = ">=1.0.8,<2.0.0"
 fsspec = ">=2023.5.0"
 httpx = "*"
-llamaindex-py-client = ">=0.1.18,<0.2.0"
+llama-cloud = ">=0.0.6,<0.0.7"
 nest-asyncio = ">=1.5.8,<2.0.0"
 networkx = ">=3.0"
 nltk = ">=3.8.1,<4.0.0"
-numpy = "*"
+numpy = "<2.0.0"
 openai = ">=1.1.0"
 pandas = "*"
 pillow = ">=9.0.0"
 PyYAML = ">=6.0.1"
 requests = ">=2.31.0"
 SQLAlchemy = {version = ">=1.4.49", extras = ["asyncio"]}
-tenacity = ">=8.2.0,<9.0.0"
+tenacity = ">=8.2.0,<8.4.0 || >8.4.0,<9.0.0"
 tiktoken = ">=0.3.3"
 tqdm = ">=4.66.1,<5.0.0"
 typing-extensions = ">=4.5.0"
@@ -2952,18 +2968,18 @@ llama-index-core = ">=0.10.1,<0.11.0"
 
 [[package]]
 name = "llama-index-indices-managed-llama-cloud"
-version = "0.1.6"
+version = "0.2.1"
 description = "llama-index indices llama-cloud integration"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index_indices_managed_llama_cloud-0.1.6-py3-none-any.whl", hash = "sha256:cba33e1a3677b2a2ae7f239119acbf6dc3818f105edc92315729842b56fbc949"},
+    {file = "llama_index_indices_managed_llama_cloud-0.2.1-py3-none-any.whl", hash = "sha256:69abd37bc7b57abcea841eea2a89cb0adee29bce3fd05c61e3082ae50f047b87"},
-    {file = "llama_index_indices_managed_llama_cloud-0.1.6.tar.gz", hash = "sha256:74b3b0e9ebf9d348d3054f9fc0c657031acceb9351c31116ad8d5a7ae4729f5c"},
+    {file = "llama_index_indices_managed_llama_cloud-0.2.1.tar.gz", hash = "sha256:b07fa606f1085e22918d2d45e00ab86f3430f36057e115322bd360b695eef565"},
 ]
 
 [package.dependencies]
-llama-index-core = ">=0.10.0,<0.11.0"
+llama-cloud = ">=0.0.6,<0.0.7"
-llamaindex-py-client = ">=0.1.19,<0.2.0"
+llama-index-core = ">=0.10.48.post1,<0.11.0"
 
 [[package]]
 name = "llama-index-legacy"
@@ -3023,13 +3039,13 @@ llama-index-llms-openai = ">=0.1.1,<0.2.0"
 
 [[package]]
 name = "llama-index-llms-openai"
-version = "0.1.22"
+version = "0.1.23"
 description = "llama-index llms openai integration"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "llama_index_llms_openai-0.1.22-py3-none-any.whl", hash = "sha256:84a8c910671460ad724ed818192f209f7481e71bcc6528553ba7e66db2e14bcd"},
+    {file = "llama_index_llms_openai-0.1.23-py3-none-any.whl", hash = "sha256:38753baac823a0459b8f6511258d84020219cb6b223a9866ec526e83ddbc94e1"},
-    {file = "llama_index_llms_openai-0.1.22.tar.gz", hash = "sha256:729bf2ea7043517465e1d585089512b77d8b3ce92233a67c138d5d621061ed56"},
+    {file = "llama_index_llms_openai-0.1.23.tar.gz", hash = "sha256:b40289c47fda9df86c8177999d6af0a47fce14fe4324572ea2fe25bbdbd05021"},
 ]
 
 [package.dependencies]
@@ -3146,21 +3162,6 @@ files = [
 [package.dependencies]
 llama-index-core = ">=0.10.29"
 
-[[package]]
-name = "llamaindex-py-client"
-version = "0.1.19"
-description = ""
-optional = false
-python-versions = "<4,>=3.8"
-files = [
-    {file = "llamaindex_py_client-0.1.19-py3-none-any.whl", hash = "sha256:fd9416fd78b97209bf323bc3c7fab314499778563e7274f10853ad560563d10e"},
-    {file = "llamaindex_py_client-0.1.19.tar.gz", hash = "sha256:73f74792bb8c092bae6dc626627a09ac13a099fa8d10f8fcc83e17a2b332cca7"},
-]
-
-[package.dependencies]
-httpx = ">=0.20.0"
-pydantic = ">=1.10"
-
 [[package]]
 name = "lxml"
 version = "5.2.2"
@@ -3242,13 +3243,9 @@ files = [
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@@ -3662,13 +3659,13 @@ tests = ["pytest (>=4.6)"]
 
 [[package]]
 name = "msal"
-version = "1.28.1"
+version = "1.29.0"
 description = "The Microsoft Authentication Library (MSAL) for Python library enables your app to access the Microsoft Cloud by supporting authentication of users with Microsoft Azure Active Directory accounts (AAD) and Microsoft Accounts (MSA) using industry standard OAuth2 and OpenID Connect."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "msal-1.29.0-py3-none-any.whl", hash = "sha256:6b301e63f967481f0cc1a3a3bac0cf322b276855bc1b0955468d9deb3f33d511"},
-    {file = "msal-1.28.1.tar.gz", hash = "sha256:d72bbfe2d5c2f2555f4bc6205be4450ddfd12976610dd9a16a9ab0f05c68b64d"},
+    {file = "msal-1.29.0.tar.gz", hash = "sha256:8f6725f099752553f9b2fe84125e2a5ebe47b49f92eacca33ebedd3a9ebaae25"},
 ]
 
 [package.dependencies]
@@ -3681,22 +3678,18 @@ broker = ["pymsalruntime (>=0.13.2,<0.17)"]
 
 [[package]]
 name = "msal-extensions"
-version = "1.1.0"
+version = "1.2.0"
 description = "Microsoft Authentication Library extensions (MSAL EX) provides a persistence API that can save your data on disk, encrypted on Windows, macOS and Linux. Concurrent data access will be coordinated by a file lock mechanism."
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "msal_extensions-1.2.0.tar.gz", hash = "sha256:6f41b320bfd2933d631a215c91ca0dd3e67d84bd1a2f50ce917d5874ec646bef"},
 ]
 
 [package.dependencies]
-msal = ">=0.4.1,<2.0.0"
+msal = ">=1.29,<2"
-packaging = "*"
+portalocker = ">=1.4,<3"
-portalocker = [
-    {version = ">=1.0,<3", markers = "platform_system != \"Windows\""},
-    {version = ">=1.6,<3", markers = "platform_system == \"Windows\""},
-]
 
 [[package]]
 name = "multidict"
@@ -4657,13 +4650,13 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "pip"
-version = "24.0"
+version = "24.1.1"
 description = "The PyPA recommended tool for installing Python packages."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "pip-24.1.1.tar.gz", hash = "sha256:5aa64f65e1952733ee0a9a9b1f52496ebdb3f3077cc46f80a16d983b58d1180a"},
 ]
 
 [[package]]
@@ -4719,13 +4712,13 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "portalocker"
-version = "2.8.2"
+version = "2.10.0"
 description = "Wraps the portalocker recipe for easy usage"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "portalocker-2.10.0-py3-none-any.whl", hash = "sha256:48944147b2cd42520549bc1bb8fe44e220296e56f7c3d551bc6ecce69d9b0de1"},
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+    {file = "portalocker-2.10.0.tar.gz", hash = "sha256:49de8bc0a2f68ca98bf9e219c81a3e6b27097c7bf505a87c5a112ce1aaeb9b81"},
 ]
 
 [package.dependencies]
@@ -4779,20 +4772,20 @@ virtualenv = ">=20.10.0"
 
 [[package]]
 name = "proto-plus"
-version = "1.23.0"
+version = "1.24.0"
 description = "Beautiful, Pythonic protocol buffers."
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
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+    {file = "proto-plus-1.24.0.tar.gz", hash = "sha256:30b72a5ecafe4406b0d339db35b56c4059064e69227b8c3bda7462397f966445"},
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 ]
 
 [package.dependencies]
-protobuf = ">=3.19.0,<5.0.0dev"
+protobuf = ">=3.19.0,<6.0.0dev"
 
 [package.extras]
-testing = ["google-api-core[grpc] (>=1.31.5)"]
+testing = ["google-api-core (>=1.31.5)"]
 
 [[package]]
 name = "protobuf"
@@ -5850,13 +5843,13 @@ files = [
 
 [[package]]
 name = "s3transfer"
-version = "0.10.1"
+version = "0.10.2"
 description = "An Amazon S3 Transfer Manager"
 optional = false
-python-versions = ">= 3.8"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -6034,45 +6027,45 @@ tests = ["black (>=24.3.0)", "matplotlib (>=3.3.4)", "mypy (>=1.9)", "numpydoc (
 
 [[package]]
 name = "scipy"
-version = "1.13.1"
+version = "1.14.0"
 description = "Fundamental algorithms for scientific computing in Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 files = [
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 ]
 
 [package.dependencies]
-numpy = ">=1.22.4,<2.3"
+numpy = ">=1.23.5,<2.3"
 
 [package.extras]
-dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pydevtool", "rich-click", "ruff", "types-psutil", "typing_extensions"]
+dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy (==1.10.0)", "pycodestyle", "pydevtool", "rich-click", "ruff (>=0.0.292)", "types-psutil", "typing_extensions"]
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+doc = ["jupyterlite-pyodide-kernel", "jupyterlite-sphinx (>=0.13.1)", "jupytext", "matplotlib (>=3.5)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (>=0.15.2)", "sphinx (>=5.0.0)", "sphinx-design (>=0.4.0)"]
-test = ["array-api-strict", "asv", "gmpy2", "hypothesis (>=6.30)", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+test = ["Cython", "array-api-strict", "asv", "gmpy2", "hypothesis (>=6.30)", "meson", "mpmath", "ninja", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
 [[package]]
 name = "seaborn"
@@ -6122,18 +6115,18 @@ train = ["accelerate (>=0.20.3)", "datasets"]
 
 [[package]]
 name = "setuptools"
-version = "70.0.0"
+version = "70.1.1"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
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+    {file = "SQLAlchemy-2.0.31.tar.gz", hash = "sha256:b607489dd4a54de56984a0c7656247504bd5523d9d0ba799aef59d4add009484"},
 ]
 
 [package.dependencies]
-greenlet = {version = "!=0.4.17", optional = true, markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\" or extra == \"asyncio\""}
+greenlet = {version = "!=0.4.17", optional = true, markers = "python_version < \"3.13\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\") or extra == \"asyncio\""}
 typing-extensions = ">=4.6.0"
 
 [package.extras]
@@ -6342,7 +6335,7 @@ files = [
 
 [[package]]
 name = "swebench"
-version = "1.1.5"
+version = "2.0.2"
 description = "The official SWE-bench package - a benchmark for evaluating LMs on software engineering"
 optional = false
 python-versions = ">=3.8"
@@ -6353,8 +6346,10 @@ develop = false
 beautifulsoup4 = "*"
 chardet = "*"
 datasets = "*"
+docker = "*"
 ghapi = "*"
 GitPython = "*"
+pre-commit = "*"
 python-dotenv = "*"
 requests = "*"
 rich = "*"
@@ -6363,8 +6358,8 @@ tqdm = "*"
 [package.source]
 type = "git"
 url = "https://github.com/OpenDevin/SWE-bench.git"
-reference = "HEAD"
+reference = "xw/attempt-fix-django-parsing"
-resolved_reference = "7b0c4b1c249ed4b4600a5bba8afb916d543e034a"
+resolved_reference = "c61bc104ae5113dd58c228004e7b52293ed73bbd"
 
 [[package]]
 name = "sympy"
@@ -6727,19 +6722,19 @@ telegram = ["requests"]
 
 [[package]]
 name = "transformers"
-version = "4.41.2"
+version = "4.42.1"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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+    {file = "transformers-4.42.1-py3-none-any.whl", hash = "sha256:d7392acf1e35a108e8abd2e3ea8f6ffc1d34dcb6c0275d6297ec337ae5de99b6"},
-    {file = "transformers-4.41.2.tar.gz", hash = "sha256:80a4db216533d573e9cc7388646c31ed9480918feb7c55eb211249cb23567f87"},
+    {file = "transformers-4.42.1.tar.gz", hash = "sha256:89adfb6b6634f684a85bae1d53cc243a43e30479392b3c873be743af61556f4f"},
 ]
 
 [package.dependencies]
 filelock = "*"
-huggingface-hub = ">=0.23.0,<1.0"
+huggingface-hub = ">=0.23.2,<1.0"
-numpy = ">=1.17"
+numpy = ">=1.17,<2.0"
 packaging = ">=20.0"
 pyyaml = ">=5.1"
 regex = "!=2019.12.17"
@@ -6751,14 +6746,15 @@ tqdm = ">=4.27"
 [package.extras]
 accelerate = ["accelerate (>=0.21.0)"]
 agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
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+all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision"]
 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+benchmark = ["optimum-benchmark (>=0.2.0)"]
 codecarbon = ["codecarbon (==1.2.0)"]
 deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
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 flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
 flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
 ftfy = ["ftfy"]
@@ -6769,25 +6765,26 @@ natten = ["natten (>=0.14.6,<0.15.0)"]
 onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
 onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
 optuna = ["optuna"]
-quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.1.5)", "urllib3 (<2.0.0)"]
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 ray = ["ray[tune] (>=2.7.0)"]
 retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
+ruff = ["ruff (==0.4.4)"]
 sagemaker = ["sagemaker (>=2.31.0)"]
 sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
 serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
 sigopt = ["sigopt"]
 sklearn = ["scikit-learn"]
 speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
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 tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
-tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
+tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
-timm = ["timm"]
+timm = ["timm (<=0.9.16)"]
 tokenizers = ["tokenizers (>=0.19,<0.20)"]
 torch = ["accelerate (>=0.21.0)", "torch"]
 torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
 torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
-torchhub = ["filelock", "huggingface-hub (>=0.23.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
+torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17,<2.0)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
 video = ["av (==9.2.0)", "decord (==0.6.0)"]
 vision = ["Pillow (>=10.0.1,<=15.0)"]
 
@@ -7076,13 +7073,13 @@ test = ["Cython (>=0.29.36,<0.30.0)", "aiohttp (==3.9.0b0)", "aiohttp (>=3.8.1)"
 
 [[package]]
 name = "virtualenv"
-version = "20.26.2"
+version = "20.26.3"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.26.2-py3-none-any.whl", hash = "sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b"},
+    {file = "virtualenv-20.26.3-py3-none-any.whl", hash = "sha256:8cc4a31139e796e9a7de2cd5cf2489de1217193116a8fd42328f1bd65f434589"},
-    {file = "virtualenv-20.26.2.tar.gz", hash = "sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c"},
+    {file = "virtualenv-20.26.3.tar.gz", hash = "sha256:4c43a2a236279d9ea36a0d76f98d84bd6ca94ac4e0f4a3b9d46d05e10fea542a"},
 ]
 
 [package.dependencies]
@@ -7749,4 +7746,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "bfb5c89e3fe1763ed5b539f77e714e9c269366ece66507ed8811dff7df614c93"
+content-hash = "bcee6d5cbe7f6ef236173bf5e94c8859a097c3d2ecde0e757be5f2c45b45a8cd"

pyproject.toml

@@ -68,12 +68,13 @@ reportlab = "*"
 [tool.coverage.run]
 concurrency = ["gevent"]
 
+
 [tool.poetry.group.evaluation.dependencies]
 streamlit = "*"
 whatthepatch = "*"
 retry = "*"
 evaluate = "*"
-swebench = { git = "https://github.com/OpenDevin/SWE-bench.git" }
+swebench = { git = "https://github.com/OpenDevin/SWE-bench.git", rev = "xw/attempt-fix-django-parsing" }
 
 [build-system]
 build-backend = "poetry.core.masonry.api"