feat: pass context argument to tasks that require it (#788)

<!-- .github/pull_request_template.md -->

## Description
<!-- Provide a clear description of the changes in this PR -->

## DCO Affirmation
I affirm that all code in every commit of this pull request conforms to
the terms of the Topoteretes Developer Certificate of Origin.

---------

Co-authored-by: Hande <159312713+hande-k@users.noreply.github.com>
Co-authored-by: Vasilije <8619304+Vasilije1990@users.noreply.github.com>

README.md

@@ -32,6 +32,14 @@ Build dynamic Agent memory using scalable, modular ECL (Extract, Cognify, Load)
 
 More on [use-cases](https://docs.cognee.ai/use-cases) and [evals](https://github.com/topoteretes/cognee/tree/main/evals) 
 
+  <p align="center">
+  🌐 Available Languages
+  :
+  <a href="community/README.pt.md">🇵🇹 Português</a>
+  ·
+  <a href="community/README.zh.md">🇨🇳 [中文]</a>
+  </p>
+
 <div style="text-align: center">
   <img src="https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/main/assets/cognee_benefits.png" alt="Why cognee?" width="50%" />
 </div>
@@ -116,17 +124,15 @@ Example output:
   Natural Language Processing (NLP) is a cross-disciplinary and interdisciplinary field that involves computer science and information retrieval. It focuses on the interaction between computers and human language, enabling machines to understand and process natural language.
   
 ```
-### cognee UI 
+
+### cognee UI
 
 You can also cognify your files and query using cognee UI. 
 
-
 <img src="assets/cognee-ui-2.webp" width="100%" alt="Cognee UI 2"></a>
 
-
 Try cognee UI out locally [here](https://docs.cognee.ai/how-to-guides/cognee-ui).
 
-
 ## Understand our architecture
 
 <div style="text-align: center">

cognee/modules/pipelines/operations/run_tasks.py

@@ -20,7 +20,9 @@ from ..tasks.task import Task
 logger = get_logger("run_tasks(tasks: [Task], data)")
 
 
-async def run_tasks_with_telemetry(tasks: list[Task], data, user: User, pipeline_name: str):
+async def run_tasks_with_telemetry(
+    tasks: list[Task], data, user: User, pipeline_name: str, context: dict = None
+):
     config = get_current_settings()
 
     logger.debug("\nRunning pipeline with configuration:\n%s\n", json.dumps(config, indent=1))
@@ -36,7 +38,7 @@ async def run_tasks_with_telemetry(tasks: list[Task], data, user: User, pipeline
             | config,
         )
 
-        async for result in run_tasks_base(tasks, data, user):
+        async for result in run_tasks_base(tasks, data, user, context):
             yield result
 
         logger.info("Pipeline run completed: `%s`", pipeline_name)
@@ -72,6 +74,7 @@ async def run_tasks(
     data: Any = None,
     user: User = None,
     pipeline_name: str = "unknown_pipeline",
+    context: dict = None,
 ):
     pipeline_id = uuid5(NAMESPACE_OID, pipeline_name)
 
@@ -82,7 +85,11 @@ async def run_tasks(
 
     try:
         async for _ in run_tasks_with_telemetry(
-            tasks=tasks, data=data, user=user, pipeline_name=pipeline_id
+            tasks=tasks,
+            data=data,
+            user=user,
+            pipeline_name=pipeline_id,
+            context=context,
         ):
             pass
 

cognee/modules/pipelines/operations/run_tasks_base.py

@@ -14,6 +14,7 @@ async def handle_task(
     leftover_tasks: list[Task],
     next_task_batch_size: int,
     user: User,
+    context: dict = None,
 ):
     """Handle common task workflow with logging, telemetry, and error handling around the core execution logic."""
     task_type = running_task.task_type
@@ -27,9 +28,16 @@ async def handle_task(
         },
     )
 
+    has_context = any(
+        [key == "context" for key in inspect.signature(running_task.executable).parameters.keys()]
+    )
+
+    if has_context:
+        args.append(context)
+
     try:
         async for result_data in running_task.execute(args, next_task_batch_size):
-            async for result in run_tasks_base(leftover_tasks, result_data, user):
+            async for result in run_tasks_base(leftover_tasks, result_data, user, context):
                 yield result
 
         logger.info(f"{task_type} task completed: `{running_task.executable.__name__}`")
@@ -55,7 +63,7 @@ async def handle_task(
         raise error
 
 
-async def run_tasks_base(tasks: list[Task], data=None, user: User = None):
+async def run_tasks_base(tasks: list[Task], data=None, user: User = None, context: dict = None):
     """Base function to execute tasks in a pipeline, handling task type detection and execution."""
     if len(tasks) == 0:
         yield data
@@ -68,5 +76,7 @@ async def run_tasks_base(tasks: list[Task], data=None, user: User = None):
     next_task = leftover_tasks[0] if len(leftover_tasks) > 0 else None
     next_task_batch_size = next_task.task_config["batch_size"] if next_task else 1
 
-    async for result in handle_task(running_task, args, leftover_tasks, next_task_batch_size, user):
+    async for result in handle_task(
+        running_task, args, leftover_tasks, next_task_batch_size, user, context
+    ):
         yield result

cognee/shared/logging_utils.py

@@ -312,7 +312,7 @@ def setup_logging(log_level=None, name=None):
     root_logger.addHandler(file_handler)
     root_logger.setLevel(log_level)
 
-    if log_level > logging.WARNING:
+    if log_level > logging.DEBUG:
         import warnings
         from sqlalchemy.exc import SAWarning
 

cognee/tests/integration/run_toy_tasks/conftest.py

@@ -1,11 +0,0 @@
-import os
-
-import pytest
-
-
-@pytest.fixture(autouse=True, scope="session")
-def copy_cognee_db_to_target_location():
-    os.makedirs("cognee/.cognee_system/databases/", exist_ok=True)
-    os.system(
-        "cp cognee/tests/integration/run_toy_tasks/data/cognee_db cognee/.cognee_system/databases/cognee_db"
-    )

cognee/tests/unit/modules/pipelines/run_tasks_test.py

@@ -48,3 +48,7 @@ async def run_and_check_tasks():
 
 def test_run_tasks():
     asyncio.run(run_and_check_tasks())
+
+
+if __name__ == "__main__":
+    test_run_tasks()

cognee/tests/unit/modules/pipelines/run_tasks_with_context_test.py

@@ -0,0 +1,47 @@
+import asyncio
+
+import cognee
+from cognee.modules.pipelines.tasks.task import Task
+from cognee.modules.users.methods import get_default_user
+from cognee.modules.pipelines.operations.run_tasks import run_tasks_base
+from cognee.infrastructure.databases.relational import create_db_and_tables
+
+
+async def run_and_check_tasks():
+    await cognee.prune.prune_data()
+    await cognee.prune.prune_system(metadata=True)
+
+    def task_1(num, context):
+        return num + context
+
+    def task_2(num):
+        return num * 2
+
+    def task_3(num, context):
+        return num**context
+
+    await create_db_and_tables()
+    user = await get_default_user()
+
+    pipeline = run_tasks_base(
+        [
+            Task(task_1),
+            Task(task_2),
+            Task(task_3),
+        ],
+        data=5,
+        user=user,
+        context=7,
+    )
+
+    final_result = 4586471424
+    async for result in pipeline:
+        assert result == final_result
+
+
+def test_run_tasks():
+    asyncio.run(run_and_check_tasks())
+
+
+if __name__ == "__main__":
+    test_run_tasks()

community/README.zh.md

@@ -0,0 +1,162 @@
+<div align="center">
+  <a href="https://github.com/topoteretes/cognee">
+    <img src="https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/dev/assets/cognee-logo-transparent.png" alt="Cognee Logo" height="60">
+  </a>
+
+  <br />
+
+  cognee - AI应用和智能体的记忆层
+
+  <p align="center">
+  <a href="https://www.youtube.com/watch?v=1bezuvLwJmw&t=2s">演示</a>
+  .
+  <a href="https://cognee.ai">了解更多</a>
+  ·
+  <a href="https://discord.gg/NQPKmU5CCg">加入Discord</a>
+  </p>
+
+
+  [![GitHub forks](https://img.shields.io/github/forks/topoteretes/cognee.svg?style=social&label=Fork&maxAge=2592000)](https://GitHub.com/topoteretes/cognee/network/)
+  [![GitHub stars](https://img.shields.io/github/stars/topoteretes/cognee.svg?style=social&label=Star&maxAge=2592000)](https://GitHub.com/topoteretes/cognee/stargazers/)
+  [![GitHub commits](https://badgen.net/github/commits/topoteretes/cognee)](https://GitHub.com/topoteretes/cognee/commit/)
+  [![Github tag](https://badgen.net/github/tag/topoteretes/cognee)](https://github.com/topoteretes/cognee/tags/)
+  [![Downloads](https://static.pepy.tech/badge/cognee)](https://pepy.tech/project/cognee)
+  [![License](https://img.shields.io/github/license/topoteretes/cognee?colorA=00C586&colorB=000000)](https://github.com/topoteretes/cognee/blob/main/LICENSE)
+  [![Contributors](https://img.shields.io/github/contributors/topoteretes/cognee?colorA=00C586&colorB=000000)](https://github.com/topoteretes/cognee/graphs/contributors)
+
+  可靠的AI智能体响应。
+
+
+
+使用可扩展、模块化的ECL（提取、认知、加载）管道构建动态智能体记忆。
+
+更多[使用场景](https://docs.cognee.ai/use_cases)。
+
+<div style="text-align: center">
+  <img src="cognee_benefits_zh.JPG" alt="为什么选择cognee？" width="100%" />
+</div>
+
+</div>
+
+
+
+
+## 功能特性
+
+- 互联并检索您的历史对话、文档、图像和音频转录
+- 减少幻觉、开发人员工作量和成本
+- 仅使用Pydantic将数据加载到图形和向量数据库
+- 从30多个数据源摄取数据时进行数据操作
+
+## 开始使用
+
+通过Google Colab <a href="https://colab.research.google.com/drive/1g-Qnx6l_ecHZi0IOw23rg0qC4TYvEvWZ?usp=sharing">笔记本</a>或<a href="https://github.com/topoteretes/cognee-starter">入门项目</a>快速上手
+
+## 贡献
+您的贡献是使这成为真正开源项目的核心。我们**非常感谢**任何贡献。更多信息请参阅[`CONTRIBUTING.md`](CONTRIBUTING.md)。
+
+
+
+
+
+## 📦 安装
+
+您可以使用**pip**、**poetry**、**uv**或任何其他Python包管理器安装Cognee。
+
+### 使用pip
+
+```bash
+pip install cognee
+```
+
+## 💻 基本用法
+
+### 设置
+
+```
+import os
+os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY"
+
+```
+
+您也可以通过创建.env文件设置变量，使用我们的<a href="https://github.com/topoteretes/cognee/blob/main/.env.template">模板</a>。
+要使用不同的LLM提供商，请查看我们的<a href="https://docs.cognee.ai">文档</a>获取更多信息。
+
+
+### 简单示例
+
+此脚本将运行默认管道：
+
+```python
+import cognee
+import asyncio
+
+
+async def main():
+    # Add text to cognee
+    await cognee.add("自然语言处理（NLP）是计算机科学和信息检索的跨学科领域。")
+
+    # Generate the knowledge graph
+    await cognee.cognify()
+
+    # Query the knowledge graph
+    results = await cognee.search("告诉我关于NLP")
+
+    # Display the results
+    for result in results:
+        print(result)
+
+
+if __name__ == '__main__':
+    asyncio.run(main())
+
+```
+示例输出：
+```
+  自然语言处理（NLP）是计算机科学和信息检索的跨学科领域。它关注计算机和人类语言之间的交互，使机器能够理解和处理自然语言。
+  
+```
+图形可视化：
+<a href="https://rawcdn.githack.com/topoteretes/cognee/refs/heads/main/assets/graph_visualization.html"><img src="https://rawcdn.githack.com/topoteretes/cognee/refs/heads/main/assets/graph_visualization.png" width="100%" alt="图形可视化"></a>
+在[浏览器](https://rawcdn.githack.com/topoteretes/cognee/refs/heads/main/assets/graph_visualization.html)中打开。
+
+有关更高级的用法，请查看我们的<a href="https://docs.cognee.ai">文档</a>。
+
+
+## 了解我们的架构
+
+<div style="text-align: center">
+  <img src="cognee_diagram_zh.JPG" alt="cognee概念图" width="100%" />
+</div>
+
+
+
+## 演示
+
+1. 什么是AI记忆：
+
+[了解cognee](https://github.com/user-attachments/assets/8b2a0050-5ec4-424c-b417-8269971503f0)
+
+2. 简单GraphRAG演示
+
+[简单GraphRAG演示](https://github.com/user-attachments/assets/f57fd9ea-1dc0-4904-86eb-de78519fdc32)
+
+3. cognee与Ollama
+
+[cognee与本地模型](https://github.com/user-attachments/assets/834baf9a-c371-4ecf-92dd-e144bd0eb3f6)
+
+
+## 行为准则
+
+我们致力于为我们的社区提供愉快和尊重的开源体验。有关更多信息，请参阅<a href="https://github.com/topoteretes/cognee/blob/main/CODE_OF_CONDUCT.md"><code>CODE_OF_CONDUCT</code></a>。
+
+## 💫 贡献者
+
+<a href="https://github.com/topoteretes/cognee/graphs/contributors">
+  <img alt="contributors" src="https://contrib.rocks/image?repo=topoteretes/cognee"/>
+</a>
+
+
+## Star历史
+
+[![Star History Chart](https://api.star-history.com/svg?repos=topoteretes/cognee&type=Date)](https://star-history.com/#topoteretes/cognee&Date)