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test.py
CHANGED
@@ -12,31 +12,32 @@ from langchain.chains import LLMChain, SequentialChain
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llm = ChatOpenAI(temperature=0.0, openai_api_key=os.environ["OPENAI"])
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def generate_skills() -> list:
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template_generate_skills = """
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Can you generate me a list of skills you would need to be successfully employed in a Data Scientist role?
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Return 10 skills as a JSON list.
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"""
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prompt_generate_skills = ChatPromptTemplate.from_template(
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generate_skills_chain = SequentialChain(
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chains=[role_skills],
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input_variables=[],
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output_variables=["role_skills"],
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verbose=False
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)
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result = generate_skills_chain({})
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result_array = json.loads(result["role_skills"])["skills"]
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return result_array
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def generate_resume(skills: list) -> str:
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template_generate_resume = """
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Given the following list of skills as an array delimited by three backticks, generate a resume of a data scientist with 3 years of experience.
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Make sure to include a section "skills" in the resume.
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@@ -46,22 +47,24 @@ def generate_resume(skills: list) -> str:
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```
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"""
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prompt_generate_resume = ChatPromptTemplate.from_template(
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resume = LLMChain(llm=llm, prompt=prompt_generate_resume, output_key="resume")
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generate_resume_chain = SequentialChain(
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chains=[resume],
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input_variables=["skills"],
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output_variables=["resume"],
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verbose=False
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)
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result = generate_resume_chain({"skills": skills})
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return result
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def retrieve_skills(resume: str) -> str:
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-
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template_retrieve_skills = """
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Given the following resume delimited by three backticks, retrieve the skills this data scientist possesses.
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Return them as a JSON list.
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@@ -71,14 +74,16 @@ def retrieve_skills(resume: str) -> str:
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```
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"""
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prompt_retrieve_skills = ChatPromptTemplate.from_template(
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skills = LLMChain(llm=llm, prompt=prompt_retrieve_skills, output_key="skills")
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retrieve_skills_chain = SequentialChain(
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chains=[skills],
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input_variables=["resume"],
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output_variables=["skills"],
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verbose=False
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)
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result = retrieve_skills_chain({"resume": resume})
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@@ -86,10 +91,12 @@ def retrieve_skills(resume: str) -> str:
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return result_array
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intersection_list = [value for value in predicted_values if value in true_values]
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print(intersection_list)
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return len(intersection_list)/len(true_values)
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if __name__ == "__main__":
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role_skills = generate_skills()
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@@ -107,16 +114,16 @@ if __name__ == "__main__":
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# 's3',
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# region_name='eu-west-1'
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# )
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# s3_uri = urlparse("s3://ausy-datalake-drift-nonprod/resume-matcher/raw/resume-dataset.csv", allow_fragments=False).geturl()
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# resumes_list = pd.read_csv(s3_uri, header=None, encoding='utf-8')[0].tolist()
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@@ -125,9 +132,9 @@ if __name__ == "__main__":
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# def get_skills(resumes: str) -> list:
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# template_resumes_get_skills = """
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# Given the following string, delimited by <RESUMES> and </RESUMES> which contains resumes which are not properly formatted, categorize the resumes based on domain.
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# For each domain list the skills of the resumes that are part of that domain.
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# Create a JSON object where they keys are the domains and the values are a list containing the skills.
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# Return that JSON object only.
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@@ -155,5 +162,5 @@ if __name__ == "__main__":
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# if __name__ == "__main__":
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# resumes = get_resumes()
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# print(resumes)
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llm = ChatOpenAI(temperature=0.0, openai_api_key=os.environ["OPENAI"])
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def generate_skills() -> list:
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template_generate_skills = """
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Can you generate me a list of skills you would need to be successfully employed in a Data Scientist role?
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Return 10 skills as a JSON list.
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"""
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prompt_generate_skills = ChatPromptTemplate.from_template(
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template=template_generate_skills
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)
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role_skills = LLMChain(
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llm=llm, prompt=prompt_generate_skills, output_key="role_skills"
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)
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generate_skills_chain = SequentialChain(
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chains=[role_skills],
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input_variables=[],
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output_variables=["role_skills"],
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verbose=False,
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)
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result = generate_skills_chain({})
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result_array = json.loads(result["role_skills"])["skills"]
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return result_array
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def generate_resume(skills: list) -> str:
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template_generate_resume = """
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Given the following list of skills as an array delimited by three backticks, generate a resume of a data scientist with 3 years of experience.
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Make sure to include a section "skills" in the resume.
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```
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"""
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prompt_generate_resume = ChatPromptTemplate.from_template(
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template=template_generate_resume
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)
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resume = LLMChain(llm=llm, prompt=prompt_generate_resume, output_key="resume")
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generate_resume_chain = SequentialChain(
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chains=[resume],
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input_variables=["skills"],
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output_variables=["resume"],
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verbose=False,
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)
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result = generate_resume_chain({"skills": skills})
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return result
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def retrieve_skills(resume: str) -> str:
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template_retrieve_skills = """
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Given the following resume delimited by three backticks, retrieve the skills this data scientist possesses.
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Return them as a JSON list.
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```
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"""
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prompt_retrieve_skills = ChatPromptTemplate.from_template(
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template=template_retrieve_skills
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)
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skills = LLMChain(llm=llm, prompt=prompt_retrieve_skills, output_key="skills")
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retrieve_skills_chain = SequentialChain(
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chains=[skills],
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input_variables=["resume"],
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output_variables=["skills"],
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verbose=False,
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)
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result = retrieve_skills_chain({"resume": resume})
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return result_array
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def get_score(true_values: list, predicted_values: list) -> float:
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intersection_list = [value for value in predicted_values if value in true_values]
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print(intersection_list)
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return len(intersection_list) / len(true_values)
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if __name__ == "__main__":
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role_skills = generate_skills()
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# 's3',
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# region_name='eu-west-1'
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# )
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# resumes = s3.get_object(Bucket='ausy-datalake-drift-nonprod', Key='resume-matcher/raw/resume-dataset.csv')
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# resumes_list = resumes['Body'].read().decode('utf-8').splitlines()
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# resumes_list = resumes['Body'].read().decode('utf-8').splitlines()
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# resumes_list = str(resumes_list).replace('. ', '.\n')
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# resumes_list = str(resumes_list).replace('â¢', '\n - ')
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# resumes_list = [s.replace('. ', '.\n') for s in resumes_list]
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# resumes_list = [s.replace('â¢', '\n - ') for s in resumes_list]
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# resume_string =''.join(resumes_list)
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# s3_uri = urlparse("s3://ausy-datalake-drift-nonprod/resume-matcher/raw/resume-dataset.csv", allow_fragments=False).geturl()
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# resumes_list = pd.read_csv(s3_uri, header=None, encoding='utf-8')[0].tolist()
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# def get_skills(resumes: str) -> list:
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# template_resumes_get_skills = """
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# Given the following string, delimited by <RESUMES> and </RESUMES> which contains resumes which are not properly formatted, categorize the resumes based on domain.
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# For each domain list the skills of the resumes that are part of that domain.
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# Create a JSON object where they keys are the domains and the values are a list containing the skills.
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# Return that JSON object only.
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# if __name__ == "__main__":
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# resumes = get_resumes()
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# print(resumes)
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# for x in resumes:
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# get_skills(x)
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