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156 lines
5.9 KiB
Plaintext
156 lines
5.9 KiB
Plaintext
---
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title: التخطيط
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description: تعرّف على كيفية إضافة التخطيط إلى طاقم CrewAI وتحسين أدائه.
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icon: ruler-combined
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mode: "wide"
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---
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## نظرة عامة
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تتيح لك ميزة التخطيط في CrewAI إضافة قدرة التخطيط إلى طاقمك. عند تفعيلها، قبل كل تكرار للطاقم،
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يتم إرسال جميع معلومات الطاقم إلى AgentPlanner الذي يخطط للمهام خطوة بخطوة، ويُضاف هذا المخطط إلى وصف كل مهمة.
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### استخدام ميزة التخطيط
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البدء بميزة التخطيط سهل جدًا، الخطوة الوحيدة المطلوبة هي إضافة `planning=True` إلى طاقمك:
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<CodeGroup>
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```python Code
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from crewai import Crew, Agent, Task, Process
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# تجميع طاقمك مع قدرات التخطيط
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my_crew = Crew(
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agents=self.agents,
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tasks=self.tasks,
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process=Process.sequential,
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planning=True,
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)
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```
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</CodeGroup>
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من هذه النقطة فصاعدًا، سيكون التخطيط مفعّلًا في طاقمك، وسيتم تخطيط المهام قبل كل تكرار.
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<Warning>
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عند تفعيل التخطيط، سيستخدم CrewAI `gpt-4o-mini` كنموذج LLM افتراضي للتخطيط، مما يتطلب مفتاح API صالحًا من OpenAI. نظرًا لأن وكلاءك قد يستخدمون نماذج LLM مختلفة، فقد يسبب ذلك ارتباكًا إذا لم يكن لديك مفتاح OpenAI API مهيأ أو إذا كنت تواجه سلوكًا غير متوقع متعلقًا باستدعاءات LLM API.
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</Warning>
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#### LLM التخطيط
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يمكنك الآن تحديد نموذج LLM الذي سيُستخدم لتخطيط المهام.
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عند تشغيل مثال الحالة الأساسية، سترى شيئًا مشابهًا للمخرجات أدناه، والتي تمثل مخرجات `AgentPlanner`
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المسؤول عن إنشاء المنطق التدريجي لإضافته إلى مهام الوكلاء.
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<CodeGroup>
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```python Code
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from crewai import Crew, Agent, Task, Process
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# تجميع طاقمك مع قدرات التخطيط ونموذج LLM مخصص
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my_crew = Crew(
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agents=self.agents,
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tasks=self.tasks,
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process=Process.sequential,
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planning=True,
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planning_llm="gpt-4o"
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)
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# تشغيل الطاقم
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my_crew.kickoff()
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```
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```markdown Result
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[2024-07-15 16:49:11][INFO]: Planning the crew execution
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**Step-by-Step Plan for Task Execution**
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**Task Number 1: Conduct a thorough research about AI LLMs**
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**Agent:** AI LLMs Senior Data Researcher
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**Agent Goal:** Uncover cutting-edge developments in AI LLMs
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**Task Expected Output:** A list with 10 bullet points of the most relevant information about AI LLMs
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**Task Tools:** None specified
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**Agent Tools:** None specified
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**Step-by-Step Plan:**
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1. **Define Research Scope:**
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- Determine the specific areas of AI LLMs to focus on, such as advancements in architecture, use cases, ethical considerations, and performance metrics.
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2. **Identify Reliable Sources:**
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- List reputable sources for AI research, including academic journals, industry reports, conferences (e.g., NeurIPS, ACL), AI research labs (e.g., OpenAI, Google AI), and online databases (e.g., IEEE Xplore, arXiv).
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3. **Collect Data:**
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- Search for the latest papers, articles, and reports published in 2024 and early 2025.
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- Use keywords like "Large Language Models 2025", "AI LLM advancements", "AI ethics 2025", etc.
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4. **Analyze Findings:**
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- Read and summarize the key points from each source.
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- Highlight new techniques, models, and applications introduced in the past year.
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5. **Organize Information:**
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- Categorize the information into relevant topics (e.g., new architectures, ethical implications, real-world applications).
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- Ensure each bullet point is concise but informative.
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6. **Create the List:**
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- Compile the 10 most relevant pieces of information into a bullet point list.
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- Review the list to ensure clarity and relevance.
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**Expected Output:**
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A list with 10 bullet points of the most relevant information about AI LLMs.
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---
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**Task Number 2: Review the context you got and expand each topic into a full section for a report**
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**Agent:** AI LLMs Reporting Analyst
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**Agent Goal:** Create detailed reports based on AI LLMs data analysis and research findings
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**Task Expected Output:** A fully fledged report with the main topics, each with a full section of information. Formatted as markdown without '```'
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**Task Tools:** None specified
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**Agent Tools:** None specified
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**Step-by-Step Plan:**
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1. **Review the Bullet Points:**
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- Carefully read through the list of 10 bullet points provided by the AI LLMs Senior Data Researcher.
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2. **Outline the Report:**
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- Create an outline with each bullet point as a main section heading.
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- Plan sub-sections under each main heading to cover different aspects of the topic.
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3. **Research Further Details:**
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- For each bullet point, conduct additional research if necessary to gather more detailed information.
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- Look for case studies, examples, and statistical data to support each section.
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4. **Write Detailed Sections:**
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- Expand each bullet point into a comprehensive section.
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- Ensure each section includes an introduction, detailed explanation, examples, and a conclusion.
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- Use markdown formatting for headings, subheadings, lists, and emphasis.
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5. **Review and Edit:**
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- Proofread the report for clarity, coherence, and correctness.
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- Make sure the report flows logically from one section to the next.
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- Format the report according to markdown standards.
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6. **Finalize the Report:**
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- Ensure the report is complete with all sections expanded and detailed.
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- Double-check formatting and make any necessary adjustments.
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**Expected Output:**
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A fully fledged report with the main topics, each with a full section of information. Formatted as markdown without '```'.
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```
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</CodeGroup>
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