mirror of
https://github.com/crewAIInc/crewAI-examples.git
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new examples
This commit is contained in:
João Moura
@@ -5,11 +5,9 @@ This is a collection of examples of different ways to use the crewAI framework t
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By [@joaomdmoura](https://x.com/joaomdmoura).
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## Examples
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- [Marketing Posts](https://github.com/joaomdmoura/crewAI-examples/tree/main/marketing_posts_example)
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- [Company Report]()
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- [Marketing Posts](https://github.com/joaomdmoura/crewAI-examples/tree/main/marketing%20strategy)
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- [Surprise Trip](https://github.com/joaomdmoura/crewAI-examples/tree/main/surprise%20trip)
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- [Match to Proposal]()
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- [Surprise Trip]()
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- [Recruitment]()
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## Old Examples, need to be updated
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@@ -7,7 +7,7 @@ authors = ["Your Name <you@example.com>"]
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[tool.poetry.dependencies]
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python = ">=3.10,<=3.13"
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crewai = { extras = ["tools"], version = "^0.35.8" }
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crewai-tools = "^0.4.7"
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crewai-tools = "^0.4.6"
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[tool.poetry.scripts]
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marketing_posts = "marketing_posts.main:run"
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marketing_strategy/trained_agents_data.pkl
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marketing_strategy/trained_agents_data.pkl
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<EFBFBD>}<7D>.
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2
match_profile_to_positions/.env.example
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match_profile_to_positions/.env.example
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@@ -0,0 +1,2 @@
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OPENAI_API_KEY=
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OPENAI_MODEL_NAME=gpt-4o
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39
match_profile_to_positions/README.md
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match_profile_to_positions/README.md
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@@ -0,0 +1,39 @@
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# AI Crew for Matching CVs to Job Proposals
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## Introduction
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This project demonstrates the use of the CrewAI framework to automate the process of matching CVs to job proposals. CrewAI orchestrates autonomous AI agents, enabling them to collaborate and execute complex tasks efficiently.
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By [@joaomdmoura](https://x.com/joaomdmoura)
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- [CrewAI Framework](#crewai-framework)
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- [Running the script](#running-the-script)
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- [Details & Explanation](#details--explanation)
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- [Contributing](#contributing)
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- [Support and Contact](#support-and-contact)
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- [License](#license)
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## CrewAI Framework
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CrewAI is designed to facilitate the collaboration of role-playing AI agents. In this example, these agents work together to extract relevant information from CVs and match them to job opportunities, ensuring the best fit between candidates and job roles.
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## Running the Script
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It uses GPT-4o by default so you should have access to that to run it.
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***Disclaimer:** This will use gpt-4o unless you change it to use a different model, and by doing so it may incur different costs.*
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- **Configure Environment**: Copy `.env.example` and set up the environment variables for [OpenAI](https://platform.openai.com/api-keys) and other tools as needed.
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- **Install Dependencies**: Run `poetry lock && poetry install`.
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- **Customize**: Modify `src/match_to_proposal/main.py` to add custom inputs for your agents and tasks.
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- **Customize Further**: Check `src/match_to_proposal/config/agents.yaml` to update your agents and `src/match_to_proposal/config/tasks.yaml` to update your tasks.
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- **Execute the Script**: Run `poetry run match_to_proposal` and input your project details.
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## Details & Explanation
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- **Running the Script**: Execute `poetry run match_to_proposal`. The script will leverage the CrewAI framework to match CVs to job proposals and generate a detailed report.
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- **Key Components**:
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- `src/match_to_proposal/main.py`: Main script file.
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- `src/match_to_proposal/crew.py`: Main crew file where agents and tasks come together, and the main logic is executed.
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- `src/match_to_proposal/config/agents.yaml`: Configuration file for defining agents.
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- `src/match_to_proposal/config/tasks.yaml`: Configuration file for defining tasks.
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- `src/match_to_proposal/tools`: Contains tool classes used by the agents.
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## License
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This project is released under the MIT License.
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match_profile_to_positions/db/chroma.sqlite3
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match_profile_to_positions/db/chroma.sqlite3
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5438
match_profile_to_positions/poetry.lock
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match_profile_to_positions/poetry.lock
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18
match_profile_to_positions/pyproject.toml
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match_profile_to_positions/pyproject.toml
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@@ -0,0 +1,18 @@
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[tool.poetry]
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name = "match_to_proposal"
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version = "0.1.0"
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description = "match_to_proposal using crewAI"
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authors = ["Your Name <you@example.com>"]
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[tool.poetry.dependencies]
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python = ">=3.10,<=3.13"
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crewai = { extras = ["tools"], version = "^0.35.8" }
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crewai-tools = "^0.4.6"
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[tool.poetry.scripts]
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match_to_proposal = "match_to_proposal.main:run"
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train = "match_to_proposal.main:train"
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[build-system]
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requires = ["poetry-core"]
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build-backend = "poetry.core.masonry.api"
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@@ -0,0 +1,23 @@
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cv_reader:
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role: >
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CV Reader
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goal: >
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Extract relevant information from the CV, such as skills, experience, and education.
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backstory: >
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With years of experience in HR, you excel at quickly identifying key qualifications in resumes.
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job_opportunities_parser:
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role: >
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Job Opportunities Parser
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goal: >
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Extract job descriptions from the CSV file, including job title, required skills, and responsibilities.
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backstory: >
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A data analyst who has transitioned into HR, you have a knack for organizing and interpreting job data.
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matcher:
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role: >
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Matcher
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goal: >
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Match the CV to the job opportunities based on skills and experience.
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backstory: >
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A seasoned recruiter, you specialize in finding the perfect fit between candidates and job roles.
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@@ -0,0 +1,34 @@
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read_cv_task:
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description: >
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Extract relevant information from the given CV. Focus on skills, experience,
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education, and key achievements.
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Ensure to capture the candidate's professional summary, technical skills,
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work history, and educational background.
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CV file: {path_to_cv}
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expected_output: >
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A structured summary of the CV, including:
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- Professional Summary
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- Technical Skills
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- Work History
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- Education
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- Key Achievements
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match_cv_task:
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description: >
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Match the CV to the job opportunities based on skills, experience, and key
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achievements.
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Evaluate how well the candidate's profile fits each job description,
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focusing on the alignment of skills, work history, and key achievements
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with the job requirements.
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Jobs CSV file: {path_to_jobs_csv}
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CV file: {path_to_cv}
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expected_output: >
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A ranked list of job opportunities that best match the CV, including:
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- Job Title
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- Match Score (based on skills and experience)
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- Key Matching Points
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53
match_profile_to_positions/src/match_to_proposal/crew.py
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match_profile_to_positions/src/match_to_proposal/crew.py
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@@ -0,0 +1,53 @@
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from crewai import Agent, Crew, Process, Task
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from crewai.project import CrewBase, agent, crew, task
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from crewai_tools import CSVSearchTool, FileReadTool
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@CrewBase
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class MatchToProposalCrew():
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"""MatchToProposal crew"""
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agents_config = 'config/agents.yaml'
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tasks_config = 'config/tasks.yaml'
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@agent
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def cv_reader(self) -> Agent:
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return Agent(
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config=self.agents_config['cv_reader'],
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tools=[FileReadTool()],
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verbose=True,
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allow_delegation=False
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)
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@agent
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def matcher(self) -> Agent:
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return Agent(
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config=self.agents_config['matcher'],
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tools=[FileReadTool(), CSVSearchTool()],
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verbose=True,
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allow_delegation=False
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)
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@task
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def read_cv_task(self) -> Task:
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return Task(
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config=self.tasks_config['read_cv_task'],
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agent=self.cv_reader()
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)
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@task
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def match_cv_task(self) -> Task:
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return Task(
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config=self.tasks_config['match_cv_task'],
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agent=self.matcher()
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)
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@crew
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def crew(self) -> Crew:
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"""Creates the MatchToProposal crew"""
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return Crew(
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agents=self.agents, # Automatically created by the @agent decorator
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tasks=self.tasks, # Automatically created by the @task decorator
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process=Process.sequential,
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verbose=2,
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# process=Process.hierarchical, # In case you want to use that instead https://docs.crewai.com/how-to/Hierarchical/
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)
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44
match_profile_to_positions/src/match_to_proposal/data/cv.md
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match_profile_to_positions/src/match_to_proposal/data/cv.md
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@@ -0,0 +1,44 @@
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# John Doe
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## Professional Summary
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Experienced Software Engineer with a strong background in Python, JavaScript, and RESTful APIs. Proven ability to develop and maintain software applications, collaborate with cross-functional teams, and ensure code quality.
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## Technical Skills
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- **Programming Languages**: Python, JavaScript
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- **Web Development**: RESTful APIs, HTML, CSS
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- **Frameworks/Libraries**: Django, Flask, React
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- **Tools**: Git, Docker, Jenkins
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- **Databases**: MySQL, PostgreSQL
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## Work History
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### Senior Software Engineer
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**Tech Innovations Inc., San Francisco, CA**
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*January 2020 - Present*
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- Developed and maintained multiple web applications using Python and JavaScript.
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||||
- Collaborated with cross-functional teams to design and implement RESTful APIs.
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- Ensured code quality through rigorous testing and code reviews.
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||||
- Automated deployment processes using Docker and Jenkins.
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||||
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||||
### Software Engineer
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||||
**Innovative Solutions LLC, San Francisco, CA**
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*June 2017 - December 2019*
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||||
- Worked on full-stack web development projects using Python and JavaScript.
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||||
- Built and maintained RESTful APIs for various applications.
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||||
- Participated in Agile development processes, including sprint planning and daily stand-ups.
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||||
- Mentored junior developers and conducted code reviews.
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||||
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||||
## Education
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||||
**Bachelor of Science in Computer Science**
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*University of California, Berkeley*
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*Graduated: May 2017*
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||||
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||||
## Key Achievements
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||||
- Successfully led a project to migrate a legacy system to a modern web-based platform, resulting in a 30% increase in performance.
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||||
- Recognized as Employee of the Month for outstanding performance and dedication.
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||||
- Implemented a CI/CD pipeline that reduced deployment times by 50%.
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||||
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||||
## Contact Information
|
||||
- **Email**: john.doe@example.com
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||||
- **Phone**: (123) 456-7890
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||||
- **LinkedIn**: linkedin.com/in/johndoe
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||||
@@ -0,0 +1,6 @@
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||||
Job Title,Required Skills,Key Responsibilities,Company Name,Company Location
|
||||
Software Engineer,"Python,JavaScript,RESTful APIs","Develop and maintain software applications, collaborate with cross-functional teams, ensure code quality",TechCorp,San Francisco
|
||||
Data Scientist,"Python,R,Machine Learning,Data Analysis","Analyze large datasets to extract insights, build predictive models, collaborate with stakeholders",DataTech,New York
|
||||
Project Manager,"Agile, Scrum,Leadership,Communication","Manage project timelines, coordinate with team members, ensure project goals are met",ProjectPlus,Chicago
|
||||
DevOps Engineer,"Docker,Kubernetes,CI/CD","Implement and manage CI/CD pipelines, automate deployment processes, monitor system performance",DevOpsCo,Seattle
|
||||
Marketing Specialist,"SEO,Content Creation,Social Media","Develop and execute marketing campaigns, create content for various platforms, analyze campaign performance",MarketGenius,Los Angeles
|
||||
|
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match_profile_to_positions/src/match_to_proposal/main.py
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match_profile_to_positions/src/match_to_proposal/main.py
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@@ -0,0 +1,13 @@
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#!/usr/bin/env python
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import sys
|
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from match_to_proposal.crew import MatchToProposalCrew
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|
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def run():
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# Replace with your inputs, it will automatically interpolate any tasks and agents information
|
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inputs = {
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'path_to_jobs_csv': './src/match_to_proposal/data/jobs.csv',
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'path_to_cv': './src/match_to_proposal/data/cv.md'
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}
|
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MatchToProposalCrew().crew().kickoff(inputs=inputs)
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match_profile_to_positions/trained_agents_data.pkl
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match_profile_to_positions/trained_agents_data.pkl
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<EFBFBD>}<7D>.
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323
surprise trip/poetry.lock → surprise_trip/poetry.lock
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surprise trip/poetry.lock → surprise_trip/poetry.lock
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@@ -1,25 +1,5 @@
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# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
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[[package]]
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name = "agentops"
|
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version = "0.1.12"
|
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description = "Python SDK for developing AI agent evals and observability"
|
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optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "agentops-0.1.12-py3-none-any.whl", hash = "sha256:b4b47c990638b74810cc1c38624ada162094b46e3fdd63883642a16bc5258386"},
|
||||
{file = "agentops-0.1.12.tar.gz", hash = "sha256:c4f762482fb240fc3503907f52498f2d8d9e4f80236ee4a12bf039317a85fcd7"},
|
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]
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[package.dependencies]
|
||||
packaging = "23.2"
|
||||
psutil = "5.9.8"
|
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requests = "2.31.0"
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||||
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[package.extras]
|
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dev = ["pytest (==7.4.0)", "requests-mock (==1.11.0)"]
|
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langchain = ["langchain (>=1.19,<2.0)"]
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[[package]]
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name = "aiohttp"
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version = "3.9.5"
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@@ -314,17 +294,17 @@ lxml = ["lxml"]
|
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[[package]]
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||||
name = "boto3"
|
||||
version = "1.34.138"
|
||||
version = "1.34.139"
|
||||
description = "The AWS SDK for Python"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "boto3-1.34.138-py3-none-any.whl", hash = "sha256:81518aa95fad71279411fb5c94da4b4a554a5d53fc876faca62b7b5c8737f1cb"},
|
||||
{file = "boto3-1.34.138.tar.gz", hash = "sha256:f79c15e33eb7706f197d98d828b193cf0891966682ad3ec5e900f6f9e7362e35"},
|
||||
{file = "boto3-1.34.139-py3-none-any.whl", hash = "sha256:98b2a12bcb30e679fa9f60fc74145a39db5ec2ca7b7c763f42896e3bd9b3a38d"},
|
||||
{file = "boto3-1.34.139.tar.gz", hash = "sha256:32b99f0d76ec81fdca287ace2c9744a2eb8b92cb62bf4d26d52a4f516b63a6bf"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
botocore = ">=1.34.138,<1.35.0"
|
||||
botocore = ">=1.34.139,<1.35.0"
|
||||
jmespath = ">=0.7.1,<2.0.0"
|
||||
s3transfer = ">=0.10.0,<0.11.0"
|
||||
|
||||
@@ -333,13 +313,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
|
||||
|
||||
[[package]]
|
||||
name = "botocore"
|
||||
version = "1.34.138"
|
||||
version = "1.34.139"
|
||||
description = "Low-level, data-driven core of boto 3."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "botocore-1.34.138-py3-none-any.whl", hash = "sha256:84e96a954c39a6f09cae4ea95b2ae582b5ae01b5040c92507b60509c9be5377a"},
|
||||
{file = "botocore-1.34.138.tar.gz", hash = "sha256:f558bbea96c4a4abbaeeedc477dabb00902311ba1ca6327974a6819b9f384920"},
|
||||
{file = "botocore-1.34.139-py3-none-any.whl", hash = "sha256:dd1e085d4caa2a4c1b7d83e3bc51416111c8238a35d498e9d3b04f3b63b086ba"},
|
||||
{file = "botocore-1.34.139.tar.gz", hash = "sha256:df023d8cf8999d574214dad4645cb90f9d2ccd1494f6ee2b57b1ab7522f6be77"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -388,13 +368,13 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2024.6.2"
|
||||
version = "2024.7.4"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "certifi-2024.6.2-py3-none-any.whl", hash = "sha256:ddc6c8ce995e6987e7faf5e3f1b02b302836a0e5d98ece18392cb1a36c72ad56"},
|
||||
{file = "certifi-2024.6.2.tar.gz", hash = "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516"},
|
||||
{file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"},
|
||||
{file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -759,38 +739,34 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "crewai"
|
||||
version = "0.35.10"
|
||||
version = "0.35.8"
|
||||
description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
|
||||
optional = false
|
||||
python-versions = ">=3.10,<=3.13"
|
||||
files = []
|
||||
develop = false
|
||||
python-versions = "<=3.13,>=3.10"
|
||||
files = [
|
||||
{file = "crewai-0.35.8-py3-none-any.whl", hash = "sha256:3e2d64591d6afd95bf4529aac06127e258531511aa37bffed5a7cab71a9c958a"},
|
||||
{file = "crewai-0.35.8.tar.gz", hash = "sha256:981236f35e250eba26bff393a711bb55afc7173fbd500df9b620705bba69b3a6"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
agentops = {version = "^0.1.9", optional = true}
|
||||
appdirs = "^1.4.4"
|
||||
click = "^8.1.7"
|
||||
crewai-tools = {version = "^0.4.6", optional = true}
|
||||
embedchain = "^0.1.113"
|
||||
appdirs = ">=1.4.4,<2.0.0"
|
||||
click = ">=8.1.7,<9.0.0"
|
||||
crewai-tools = {version = ">=0.4.6,<0.5.0", optional = true, markers = "extra == \"tools\""}
|
||||
embedchain = ">=0.1.113,<0.2.0"
|
||||
instructor = "1.3.3"
|
||||
jsonref = "^1.1.0"
|
||||
jsonref = ">=1.1.0,<2.0.0"
|
||||
langchain = ">=0.1.4,<0.2.0"
|
||||
openai = "^1.13.3"
|
||||
opentelemetry-api = "^1.22.0"
|
||||
opentelemetry-exporter-otlp-proto-http = "^1.22.0"
|
||||
opentelemetry-sdk = "^1.22.0"
|
||||
pydantic = "^2.4.2"
|
||||
python-dotenv = "^1.0.0"
|
||||
regex = "^2023.12.25"
|
||||
openai = ">=1.13.3,<2.0.0"
|
||||
opentelemetry-api = ">=1.22.0,<2.0.0"
|
||||
opentelemetry-exporter-otlp-proto-http = ">=1.22.0,<2.0.0"
|
||||
opentelemetry-sdk = ">=1.22.0,<2.0.0"
|
||||
pydantic = ">=2.4.2,<3.0.0"
|
||||
python-dotenv = ">=1.0.0,<2.0.0"
|
||||
regex = ">=2023.12.25,<2024.0.0"
|
||||
|
||||
[package.extras]
|
||||
agentops = ["agentops (>=0.1.9,<0.2.0)"]
|
||||
tools = ["crewai-tools (>=0.4.6,<0.5.0)"]
|
||||
|
||||
[package.source]
|
||||
type = "directory"
|
||||
url = "../crewAI"
|
||||
|
||||
[[package]]
|
||||
name = "crewai-tools"
|
||||
version = "0.4.6"
|
||||
@@ -1338,13 +1314,13 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
|
||||
|
||||
[[package]]
|
||||
name = "google-cloud-aiplatform"
|
||||
version = "1.57.0"
|
||||
version = "1.58.0"
|
||||
description = "Vertex AI API client library"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "google-cloud-aiplatform-1.57.0.tar.gz", hash = "sha256:113905f100cb0a9ad744a2445a7675f92f28600233ba499614aa704d11a809b7"},
|
||||
{file = "google_cloud_aiplatform-1.57.0-py2.py3-none-any.whl", hash = "sha256:ca5391a56e0cc8f4ed39a2beb7be02f51936ff04fd5304775a72a86c345d0e47"},
|
||||
{file = "google-cloud-aiplatform-1.58.0.tar.gz", hash = "sha256:7a05aceac4a6c7eaa26e684e9f202b829cc7e57f82bffe7281684275a553fcad"},
|
||||
{file = "google_cloud_aiplatform-1.58.0-py2.py3-none-any.whl", hash = "sha256:21f1320860f4916183ec939fdf2ff3fc1d7fdde97fe5795974257ab21f9458ec"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -1365,7 +1341,7 @@ autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
|
||||
cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
|
||||
datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)"]
|
||||
endpoint = ["requests (>=2.28.1)"]
|
||||
full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "nest-asyncio (>=1.0.0,<1.6.0)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)"]
|
||||
full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "tqdm (>=4.23.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)"]
|
||||
langchain = ["langchain (>=0.1.16,<0.3)", "langchain-core (<0.2)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "tenacity (<=8.3)"]
|
||||
langchain-testing = ["absl-py", "cloudpickle (>=3.0,<4.0)", "langchain (>=0.1.16,<0.3)", "langchain-core (<0.2)", "langchain-google-vertexai (<2)", "openinference-instrumentation-langchain (>=0.1.19,<0.2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "pydantic (>=2.6.3,<3)", "pytest-xdist", "tenacity (<=8.3)"]
|
||||
lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
|
||||
@@ -1374,12 +1350,12 @@ pipelines = ["pyyaml (>=5.3.1,<7)"]
|
||||
prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<=0.109.1)", "httpx (>=0.23.0,<0.25.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
|
||||
preview = ["cloudpickle (<3.0)", "google-cloud-logging (<4.0)"]
|
||||
private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
|
||||
rapid-evaluation = ["nest-asyncio (>=1.0.0,<1.6.0)", "pandas (>=1.0.0,<2.2.0)"]
|
||||
rapid-evaluation = ["pandas (>=1.0.0,<2.2.0)", "tqdm (>=4.23.0)"]
|
||||
ray = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "setuptools (<70.0.0)"]
|
||||
ray-testing = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pytest-xdist", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "ray[train] (==2.9.3)", "scikit-learn", "setuptools (<70.0.0)", "tensorflow", "torch (>=2.0.0,<2.1.0)", "xgboost", "xgboost-ray"]
|
||||
reasoningengine = ["cloudpickle (>=3.0,<4.0)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "pydantic (>=2.6.3,<3)"]
|
||||
tensorboard = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
|
||||
testing = ["bigframes", "cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-api-core (>=2.11,<3.0.0)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "ipython", "kfp (>=2.6.0,<3.0.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "nest-asyncio (>=1.0.0,<1.6.0)", "nltk", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyfakefs", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "sentencepiece (>=0.2.0)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (==2.13.0)", "tensorflow (==2.16.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0)", "torch (>=2.2.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
|
||||
testing = ["bigframes", "cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.109.1)", "google-api-core (>=2.11,<3.0.0)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "ipython", "kfp (>=2.6.0,<3.0.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "nltk", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyfakefs", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<=2.9.3)", "ray[default] (>=2.5,<=2.9.3)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "sentencepiece (>=0.2.0)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (==2.13.0)", "tensorflow (==2.16.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0)", "torch (>=2.2.0)", "tqdm (>=4.23.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
|
||||
tokenization = ["sentencepiece (>=0.2.0)"]
|
||||
vizier = ["google-vizier (>=0.1.6)"]
|
||||
xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
|
||||
@@ -2882,13 +2858,13 @@ sympy = "*"
|
||||
|
||||
[[package]]
|
||||
name = "openai"
|
||||
version = "1.35.9"
|
||||
version = "1.35.10"
|
||||
description = "The official Python library for the openai API"
|
||||
optional = false
|
||||
python-versions = ">=3.7.1"
|
||||
files = [
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||||
{file = "openai-1.35.9-py3-none-any.whl", hash = "sha256:d73d353bcc0bd46b9516e78a0c6fb1cffaaeb92906c7c7b467c4fa088332a150"},
|
||||
{file = "openai-1.35.9.tar.gz", hash = "sha256:4f5c1b90526cf48eaedac7b32d11b5c92fa7064b82617ad8f5f3279cd9ef090d"},
|
||||
{file = "openai-1.35.10-py3-none-any.whl", hash = "sha256:962cb5c23224b5cbd16078308dabab97a08b0a5ad736a4fdb3dc2ffc44ac974f"},
|
||||
{file = "openai-1.35.10.tar.gz", hash = "sha256:85966949f4f960f3e4b239a659f9fd64d3a97ecc43c44dc0a044b5c7f11cccc6"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -3406,34 +3382,6 @@ files = [
|
||||
{file = "protobuf-4.25.3.tar.gz", hash = "sha256:25b5d0b42fd000320bd7830b349e3b696435f3b329810427a6bcce6a5492cc5c"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "psutil"
|
||||
version = "5.9.8"
|
||||
description = "Cross-platform lib for process and system monitoring in Python."
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
|
||||
files = [
|
||||
{file = "psutil-5.9.8-cp27-cp27m-macosx_10_9_x86_64.whl", hash = "sha256:26bd09967ae00920df88e0352a91cff1a78f8d69b3ecabbfe733610c0af486c8"},
|
||||
{file = "psutil-5.9.8-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:05806de88103b25903dff19bb6692bd2e714ccf9e668d050d144012055cbca73"},
|
||||
{file = "psutil-5.9.8-cp27-cp27m-manylinux2010_x86_64.whl", hash = "sha256:611052c4bc70432ec770d5d54f64206aa7203a101ec273a0cd82418c86503bb7"},
|
||||
{file = "psutil-5.9.8-cp27-cp27mu-manylinux2010_i686.whl", hash = "sha256:50187900d73c1381ba1454cf40308c2bf6f34268518b3f36a9b663ca87e65e36"},
|
||||
{file = "psutil-5.9.8-cp27-cp27mu-manylinux2010_x86_64.whl", hash = "sha256:02615ed8c5ea222323408ceba16c60e99c3f91639b07da6373fb7e6539abc56d"},
|
||||
{file = "psutil-5.9.8-cp27-none-win32.whl", hash = "sha256:36f435891adb138ed3c9e58c6af3e2e6ca9ac2f365efe1f9cfef2794e6c93b4e"},
|
||||
{file = "psutil-5.9.8-cp27-none-win_amd64.whl", hash = "sha256:bd1184ceb3f87651a67b2708d4c3338e9b10c5df903f2e3776b62303b26cb631"},
|
||||
{file = "psutil-5.9.8-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:aee678c8720623dc456fa20659af736241f575d79429a0e5e9cf88ae0605cc81"},
|
||||
{file = "psutil-5.9.8-cp36-abi3-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8cb6403ce6d8e047495a701dc7c5bd788add903f8986d523e3e20b98b733e421"},
|
||||
{file = "psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d06016f7f8625a1825ba3732081d77c94589dca78b7a3fc072194851e88461a4"},
|
||||
{file = "psutil-5.9.8-cp36-cp36m-win32.whl", hash = "sha256:7d79560ad97af658a0f6adfef8b834b53f64746d45b403f225b85c5c2c140eee"},
|
||||
{file = "psutil-5.9.8-cp36-cp36m-win_amd64.whl", hash = "sha256:27cc40c3493bb10de1be4b3f07cae4c010ce715290a5be22b98493509c6299e2"},
|
||||
{file = "psutil-5.9.8-cp37-abi3-win32.whl", hash = "sha256:bc56c2a1b0d15aa3eaa5a60c9f3f8e3e565303b465dbf57a1b730e7a2b9844e0"},
|
||||
{file = "psutil-5.9.8-cp37-abi3-win_amd64.whl", hash = "sha256:8db4c1b57507eef143a15a6884ca10f7c73876cdf5d51e713151c1236a0e68cf"},
|
||||
{file = "psutil-5.9.8-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:d16bbddf0693323b8c6123dd804100241da461e41d6e332fb0ba6058f630f8c8"},
|
||||
{file = "psutil-5.9.8.tar.gz", hash = "sha256:6be126e3225486dff286a8fb9a06246a5253f4c7c53b475ea5f5ac934e64194c"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
|
||||
|
||||
[[package]]
|
||||
name = "pulsar-client"
|
||||
version = "3.5.0"
|
||||
@@ -3578,18 +3526,18 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "pydantic"
|
||||
version = "2.8.0"
|
||||
version = "2.8.2"
|
||||
description = "Data validation using Python type hints"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
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||||
{file = "pydantic-2.8.0-py3-none-any.whl", hash = "sha256:ead4f3a1e92386a734ca1411cb25d94147cf8778ed5be6b56749047676d6364e"},
|
||||
{file = "pydantic-2.8.0.tar.gz", hash = "sha256:d970ffb9d030b710795878940bd0489842c638e7252fc4a19c3ae2f7da4d6141"},
|
||||
{file = "pydantic-2.8.2-py3-none-any.whl", hash = "sha256:73ee9fddd406dc318b885c7a2eab8a6472b68b8fb5ba8150949fc3db939f23c8"},
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||||
{file = "pydantic-2.8.2.tar.gz", hash = "sha256:6f62c13d067b0755ad1c21a34bdd06c0c12625a22b0fc09c6b149816604f7c2a"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
annotated-types = ">=0.4.0"
|
||||
pydantic-core = "2.20.0"
|
||||
pydantic-core = "2.20.1"
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{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:407653af5617f0757261ae249d3fba09504d7a71ab36ac057c938572d1bc9331"},
|
||||
{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:c693e916709c2465b02ca0ad7b387c4f8423d1db7b4649c551f27a529181c5ad"},
|
||||
{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5b5ff4911aea936a47d9376fd3ab17e970cc543d1b68921886e7f64bd28308d1"},
|
||||
{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:177f55a886d74f1808763976ac4efd29b7ed15c69f4d838bbd74d9d09cf6fa86"},
|
||||
{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:964faa8a861d2664f0c7ab0c181af0bea66098b1919439815ca8803ef136fc4e"},
|
||||
{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:4dd484681c15e6b9a977c785a345d3e378d72678fd5f1f3c0509608da24f2ac0"},
|
||||
{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f6d6cff3538391e8486a431569b77921adfcdef14eb18fbf19b7c0a5294d4e6a"},
|
||||
{file = "pydantic_core-2.20.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:a6d511cc297ff0883bc3708b465ff82d7560193169a8b93260f74ecb0a5e08a7"},
|
||||
{file = "pydantic_core-2.20.1.tar.gz", hash = "sha256:26ca695eeee5f9f1aeeb211ffc12f10bcb6f71e2989988fda61dabd65db878d4"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -4187,13 +4136,13 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.31.0"
|
||||
version = "2.32.3"
|
||||
description = "Python HTTP for Humans."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
|
||||
{file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
|
||||
{file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
|
||||
{file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
@@ -5508,4 +5457,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10,<=3.13"
|
||||
content-hash = "5b3f6ed47a0a2480d25f00e2ea4dfad504ecb3349ae065d0e8976da9a30048eb"
|
||||
content-hash = "f793df862dfa2db935011ffd08e56758591548025c509919e1afdfd0af0f6b75"
|
||||
@@ -6,10 +6,10 @@ authors = ["Your Name <you@example.com>"]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.10,<=3.13"
|
||||
crewai = {extras = ["agentops", "tools"], path="/Users/joaomoura/workspace/crewAI"}
|
||||
crewai = { extras = ["tools"], version = "^0.35.8" }
|
||||
crewai-tools = "^0.4.6"
|
||||
pip = "^24.1.1"
|
||||
install = "^1.3.5"
|
||||
agentops = "^0.1.9"
|
||||
|
||||
[tool.poetry.scripts]
|
||||
surprise_travel = "surprise_travel.main:run"
|
||||
0
surprise_trip/src/surprise_travel/__init__.py
Normal file
0
surprise_trip/src/surprise_travel/__init__.py
Normal file
Binary file not shown.
@@ -1,4 +1,3 @@
|
||||
import agentops
|
||||
from crewai import Agent, Crew, Process, Task
|
||||
from crewai.project import CrewBase, agent, crew, task
|
||||
|
||||
@@ -88,7 +87,6 @@ class SurpriseTravelCrew():
|
||||
|
||||
@crew
|
||||
def crew(self) -> Crew:
|
||||
agentops.init()
|
||||
"""Creates the SurpriseTravel crew"""
|
||||
return Crew(
|
||||
agents=self.agents, # Automatically created by the @agent decorator
|
||||
0
surprise_trip/src/surprise_travel/tools/__init__.py
Normal file
0
surprise_trip/src/surprise_travel/tools/__init__.py
Normal file
12
surprise_trip/src/surprise_travel/tools/custom_tool.py
Normal file
12
surprise_trip/src/surprise_travel/tools/custom_tool.py
Normal file
@@ -0,0 +1,12 @@
|
||||
from crewai_tools import BaseTool
|
||||
|
||||
|
||||
class MyCustomTool(BaseTool):
|
||||
name: str = "Name of my tool"
|
||||
description: str = (
|
||||
"Clear description for what this tool is useful for, you agent will need this information to use it."
|
||||
)
|
||||
|
||||
def _run(self, argument: str) -> str:
|
||||
# Implementation goes here
|
||||
return "this is an example of a tool output, ignore it and move along."
|
||||
Reference in New Issue
Block a user