feat: Added base modal runner and changed eval script

Dockerfile.modal

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+FROM python:3.11-slim
+
+# Set environment variables
+ENV PIP_NO_CACHE_DIR=true
+ENV PATH="${PATH}:/root/.poetry/bin"
+ENV PYTHONPATH=/app
+ENV RUN_MODE=modal
+ENV SKIP_MIGRATIONS=true
+
+# System dependencies
+RUN apt-get update && apt-get install -y \
+    gcc \
+    libpq-dev \
+    git \
+    curl \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+
+ENV PYTHONPATH=/app
+WORKDIR /app
+COPY pyproject.toml poetry.lock /app/
+
+
+RUN pip install poetry
+
+# Don't create virtualenv since docker is already isolated
+RUN poetry config virtualenvs.create false
+
+# Install the dependencies
+RUN poetry install --all-extras --no-root --without dev
+
+RUN pip install python-dotenv
+RUN pip install transformers
+RUN pip install swebench
+RUN pip install sentencepiece
+
+
+COPY  cognee/ /app/cognee
+COPY evals/ /app/evals
+COPY README.md /app/README.md
+COPY process_single_repo.py /app/
+

eval_with_modal.py

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+# File: eval_with_modal.py
+from shutil import ignore_patterns
+
+import modal
+import os
+import json
+from pathlib import Path
+from typing import Optional
+import sys
+import dotenv
+
+dotenv.load_dotenv()
+app = modal.App("cognee-runner")
+
+# Get the parent directory path
+PARENT_DIR = Path(__file__).resolve().parent.parent
+
+
+MODAL_DOCKERFILE_PATH = Path( "Dockerfile.modal")
+
+
+# Define ignore patterns
+IGNORE_PATTERNS = [
+    ".venv/**/*",
+    "__pycache__",
+    "*.pyc",
+    ".git",
+    ".pytest_cache",
+    "*.egg-info",
+    "RAW_GIT_REPOS/**/*"
+]
+
+# Create image from Modal-specific Dockerfile
+image = modal.Image.from_dockerfile(
+    path=MODAL_DOCKERFILE_PATH,
+    gpu="T4",
+    force_build=False,
+    ignore=IGNORE_PATTERNS
+).copy_local_file("pyproject.toml", "pyproject.toml").copy_local_file("poetry.lock", "poetry.lock").env({"ENV": os.getenv('ENV'), "LLM_API_KEY": os.getenv("LLM_API_KEY")}).poetry_install_from_file(poetry_pyproject_toml="pyproject.toml")
+
+
+@app.function(
+    image=image,
+    gpu="T4",
+    concurrency_limit=5
+)
+async def run_single_repo(instance_data: dict, disable_cognee: bool = False):
+    import os
+    import json
+    from process_single_repo import process_repo  # Import the async function directly
+
+    # Process the instance
+    result = await process_repo(instance_data, disable_cognee=disable_cognee)
+
+    # Save the result
+    instance_id = instance_data["instance_id"]
+    filename = f"pred_{'nocognee' if disable_cognee else 'cognee'}_{instance_id}.json"
+    path_in_container = os.path.join("/app", filename)
+
+    with open(path_in_container, "w") as f:
+        json.dump(result, f, indent=2)
+
+    with open(path_in_container, "r") as f:
+        content = f.read()
+
+    return (filename, content)
+# async def run_single_repo(instance_data: dict, disable_cognee: bool = False):
+#     import subprocess
+#     import json
+#     import os
+#
+#     # Install project dependencies
+#     subprocess.run(
+#         ["poetry", "install", "--no-interaction"],
+#         cwd="/app",
+#         check=True
+#     )
+#
+#     instance_json_str = json.dumps(instance_data)
+#
+#     # cmd = [
+#     #     "poetry",
+#     #     "run",
+#     #     "python",
+#     #     "process_single_repo.py",
+#     #     f"--instance_json={instance_json_str}",
+#     # ]
+#     # if disable_cognee:
+#     #     cmd.append("--disable-cognee")
+#     #
+#     # subprocess.run(cmd, cwd="/app", check=True, env={
+#     #             "ENV": os.getenv('ENV'),
+#     #             "LLM_API_KEY": os.getenv("LLM_API_KEY")
+#     #         })
+#     venv_python = os.path.join("venv", "bin", "python")  # Use "Scripts" instead of "bin" on Windows
+#
+#     cmd = [
+#         "poetry",
+#         "run",
+#         "process_single_repo.py",
+#         f"--instance_json={instance_json_str}",
+#     ]
+#     if disable_cognee:
+#         cmd.append("--disable-cognee")
+#
+#     subprocess.run(cmd, cwd="/app", check=True, env={
+#         "ENV": os.getenv('ENV'),
+#         "LLM_API_KEY": os.getenv("LLM_API_KEY")
+#     })
+#     instance_id = instance_data["instance_id"]
+#     filename = f"pred_{'nocognee' if disable_cognee else 'cognee'}_{instance_id}.json"
+#     path_in_container = os.path.join("/app", filename)
+#
+#     if os.path.exists(path_in_container):
+#         with open(path_in_container, "r") as f:
+#             content = f.read()
+#         return (filename, content)
+#     else:
+#         return (filename, "")
+
+
+@app.local_entrypoint()
+async def main(disable_cognee: bool = False, num_samples: int = 2):
+    import subprocess
+    import json
+    import os
+    def check_install_package(package_name):
+        """Check if a pip package is installed and install it if not."""
+        try:
+            __import__(package_name)
+            return True
+        except ImportError:
+            try:
+                subprocess.check_call([sys.executable, "-m", "pip", "install", package_name])
+                return True
+            except subprocess.CalledProcessError:
+                return False
+
+    for dependency in ["transformers", "sentencepiece", "swebench","python-dotenv"]:
+        check_install_package(dependency)
+
+    from swebench.harness.utils import load_swebench_dataset
+
+    print(f"Configuration:")
+    print(f"• Running in Modal mode")
+    print(f"• Disable Cognee: {disable_cognee}")
+    print(f"• Number of samples: {num_samples}")
+
+    dataset_name = (
+        "princeton-nlp/SWE-bench_Lite_bm25_13K" if disable_cognee
+        else "princeton-nlp/SWE-bench_Lite"
+    )
+
+    swe_dataset = load_swebench_dataset(dataset_name, split="test")
+    swe_dataset = swe_dataset[:num_samples]
+
+    print(f"Processing {num_samples} samples from {dataset_name}")
+    import pip
+
+    # Install required dependencies
+    pip.main(['install', "pydantic>=2.0.0", "pydantic-settings>=2.0.0"])
+
+    tasks = [
+        run_single_repo.remote(instance, disable_cognee=disable_cognee)
+        for instance in swe_dataset
+    ]
+    import asyncio
+    # Run all tasks concurrently
+    results = await asyncio.gather(*tasks)
+
+    # Process results
+    merged = []
+    for filename, content in results:
+        if content:
+            with open(filename, "w") as f:
+                f.write(content)
+            print(f"Saved {filename} locally.")
+            merged.append(json.loads(content))
+
+    # Save merged results
+    merged_filename = "merged_nocognee.json" if disable_cognee else "merged_cognee.json"
+    with open(merged_filename, "w") as f:
+        json.dump(merged, f, indent=2)
+
+    print(f"Merged {len(merged)} repos into {merged_filename}!")
+    print("Done!")
+

evals/get_started.py

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+import modal
+
+app = modal.App("example-get-started")
+
+
+@app.function()
+def square(x):
+    print("This code is running on a remote worker!")
+    return x**2
+
+
+@app.local_entrypoint()
+def main():
+    print("the square is", square.remote(42))