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This project demonstrates how AI agents can collaborate autonomously to perform complex research tasks.\n\n## 🎯 What This Does\n\nThe system deploys two specialized AI agents that work together:\n1. **Financial Investigator** - Searches and gathers information about target companies\n2. **Market Analyst** - Analyzes findings and produces structured reports\n\nThe agents collaborate sequentially to research any company and deliver a professional markdown report with insights, trends, and market perspectives.\n\n## 🧠 How CrewAI Works\n\n### Agent Runtime & Orchestration\n\nCrewAI orchestrates multiple AI agents by:\n- **Loading agent configurations** from `agents.yaml` at runtime\n- **Instantiating agents** with specific roles, goals, and backstories\n- **Assigning tasks** defined in `tasks.yaml` to appropriate agents\n- **Managing execution flow** (sequential or hierarchical)\n- **Handling context sharing** between agents through task dependencies\n\nThe runtime process:\n```\n1. main.py kickoff() → 2. Load YAML configs → 3. Create Agent instances\n→ 4. Create Task instances → 5. Execute in defined order → 6. Output results\n```\n\n### agents.yaml - Agent Definitions\n\nThis file defines **WHO** your AI agents are. Each agent has:\n\n```yaml\nagent_name:\n  role: >\n    The agent's job title and focus area\n  goal: >\n    What the agent aims to accomplish\n  backstory: >\n    The agent's expertise and personality context\n  llm: model_name  # Which LLM powers this agent\n```\n\n**Key concepts:**\n- **Role**: Shapes how the agent interprets tasks\n- **Goal**: Focuses the agent's decision-making\n- **Backstory**: Provides context that influences agent behavior\n- **LLM**: Can assign different models per agent (e.g., GPT-4 for analysis, GPT-3.5 for research)\n\nVariables like `{company}` are placeholders that get interpolated from `main.py` inputs at runtime.\n\n### tasks.yaml - Task Definitions\n\nThis file defines **WHAT** the agents must do:\n\n```yaml\ntask_name:\n  description: >\n    Detailed instructions for the task\n  expected_output: >\n    What the final deliverable should contain\n  agent: agent_name          # Which agent performs this task\n  context: [other_task]      # Dependencies - uses output from other tasks\n  output_file: path/to/file  # Optional: save output to file\n```\n\n**Key concepts:**\n- **Description**: Detailed instructions and requirements\n- **Expected Output**: Quality criteria and format expectations\n- **Agent Assignment**: Links tasks to specific agents\n- **Context**: Creates task dependencies (sequential execution)\n- **Output File**: Automatically saves task results\n\n### Agent Runtime Flow\n\n1. **Initialization**: `Src().crew()` creates the crew instance\n2. **Configuration Loading**: YAML files are parsed using the `@agent` and `@task` decorators\n3. **Agent Creation**: Each `@agent` method instantiates an Agent with:\n   - Configuration from `agents.yaml`\n   - Assigned tools (e.g., `SerperDevTool()`)\n   - LLM settings\n4. **Task Creation**: Each `@task` method creates Task objects with:\n   - Configuration from `tasks.yaml`\n   - Context dependencies\n   - Output specifications\n5. **Execution**: `kickoff(inputs)` starts the crew with:\n   - Input interpolation (replaces `{company}` placeholders)\n   - Sequential or hierarchical processing\n   - Context passing between dependent tasks\n\n## 🛠️ Tools\n\nTools extend agent capabilities beyond language understanding. Agents can use tools to interact with external systems.\n\n### Built-in Tools Used\n\n**SerperDevTool** - Google Search API wrapper\n- Enables the investigator agent to search the web\n- Retrieves real-time company information, news, and data\n- Configured in `crew.py`: `tools=[SerperDevTool()]`\n\n### Custom Tools\n\nCreate custom tools by extending `BaseTool`:\n\n```python\nfrom crewai.tools import BaseTool\nfrom pydantic import BaseModel, Field\n\nclass MyCustomToolInput(BaseModel):\n    argument: str = Field(..., description=\"Input description\")\n\nclass MyCustomTool(BaseTool):\n    name: str = \"Tool Name\"\n    description: str = \"What this tool does\"\n    args_schema: Type[BaseModel] = MyCustomToolInput\n\n    def _run(self, argument: str) -> str:\n        # Implementation\n        return result\n```\n\nThen assign to agents: `tools=[MyCustomTool(), SerperDevTool()]`\n\n## 📋 Project Structure\n\n```\nsrc/\n├── src/\n│   ├── config/\n│   │   ├── agents.yaml      # Agent definitions\n│   │   └── tasks.yaml       # Task definitions\n│   ├── tools/\n│   │   └── custom_tool.py   # Custom tool template\n│   ├── crew.py              # Crew orchestration logic\n│   └── main.py              # Entry point\n├── output/\n│   └── reporte.md           # Generated reports\n├── .env                     # API keys configuration\n└── pyproject.toml           # Project dependencies\n```\n\n## 🚀 Installation\n\n### Prerequisites\n- Python 3.10, 3.11, 3.12, or 3.13\n- UV package manager\n\n### Setup\n\n1. Install UV package manager:\n```bash\npip install uv\n```\n\n2. Install dependencies:\n```bash\ncrewai install\n```\n\n3. Configure environment variables in `.env`:\n```bash\nGEMINI_API_KEY=your_gemini_api_key\nSERPER_API_KEY=your_serper_api_key\nMODEL=gemini-2.5-flash\n```\n\nGet your API keys:\n- **Gemini API**: [https://ai.google.dev/](https://ai.google.dev/)\n- **Serper API**: [https://serper.dev/](https://serper.dev/)\n\n## 💻 Usage\n\n### Run the Crew\n\n```bash\ncrewai run\n```\n\nThis executes the research workflow and generates `output/reporte.md` with a comprehensive company analysis.\n\n### Customize Research Target\n\nEdit `src/src/main.py`:\n\n```python\ndef run():\n    inputs = {\n        'company': 'Your Target Company Name'\n    }\n    Src().crew().kickoff(inputs=inputs)\n```\n\n### Training Mode\n\nImprove agent performance through feedback:\n```bash\ncrewai train\n```\n\n### Testing\n\nRun crew with test inputs:\n```bash\ncrewai test\n```\n\n## 🔧 Customization\n\n### Add New Agents\n\n1. Define in `src/config/agents.yaml`:\n```yaml\nmy_new_agent:\n  role: >\n    Data Analyst\n  goal: >\n    Analyze financial data\n  backstory: >\n    Expert in financial modeling\n  llm: gemini/gemini-2.5-flash\n```\n\n2. Create agent method in `crew.py`:\n```python\n@agent\ndef my_new_agent(self) -> Agent:\n    return Agent(\n        config=self.agents_config['my_new_agent'],\n        tools=[MyTool()]\n    )\n```\n\n### Add New Tasks\n\n1. Define in `src/config/tasks.yaml`:\n```yaml\nmy_new_task:\n  description: >\n    Task instructions\n  expected_output: >\n    Output requirements\n  agent: my_new_agent\n  context: [previous_task]\n```\n\n2. Create task method in `crew.py`:\n```python\n@task\ndef my_new_task(self) -> Task:\n    return Task(\n        config=self.tasks_config['my_new_task']\n    )\n```\n\n### Change Execution Process\n\nIn `crew.py`, modify the crew configuration:\n\n```python\n@crew\ndef crew(self) -> Crew:\n    return Crew(\n        agents=self.agents,\n        tasks=self.tasks,\n        process=Process.hierarchical,  # or Process.sequential\n        verbose=True\n    )\n```\n\n**Process types:**\n- **Sequential**: Tasks execute one after another (default)\n- **Hierarchical**: Manager agent delegates tasks to worker agents\n\n## 📚 Learn More\n\n- **CrewAI Documentation**: [https://docs.crewai.com](https://docs.crewai.com)\n- **Agent Configuration**: [https://docs.crewai.com/concepts/agents](https://docs.crewai.com/concepts/agents)\n- **Task Configuration**: [https://docs.crewai.com/concepts/tasks](https://docs.crewai.com/concepts/tasks)\n- **Tools Guide**: [https://docs.crewai.com/concepts/tools](https://docs.crewai.com/concepts/tools)\n\n## 🤝 Support\n\n- [CrewAI Documentation](https://docs.crewai.com)\n- [GitHub Repository](https://github.com/joaomdmoura/crewai)\n- [Discord Community](https://discord.com/invite/X4JWnZnxPb)\n\n---\n\n**Built with CrewAI** - Enabling AI agents to collaborate autonomously\n","readmeExcerpt":"Company Researcher - CrewAI Multi-Agent System $1 $1 $1 $1 $1 An intelligent multi-agent system built with CrewAI that researches companies, analyzes market data, and generates comprehensive business reports. 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