Spaces:
Running
Running
increased max retires to handle mistral
Browse files- app.py +3 -3
- leoBaseProfile.json +96 -0
- profile_extenders.py +19 -0
app.py
CHANGED
@@ -75,7 +75,7 @@ def extract_resume_fields(full_text, model):
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llm = llm_dict.get(model, ChatOpenAI(temperature=0, model=model))
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chain = prompt_template | llm | parser
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max_attempts =
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attempt = 1
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while attempt <= max_attempts:
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@@ -159,7 +159,7 @@ if uploaded_file is not None:
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end_time = time.time()
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elapsed_time = end_time - start_time
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st.write(f"Extraction completed in {elapsed_time:.2f} seconds")
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display_extracted_fields(extracted_fields1, "Extracted
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with col2:
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start_time = time.time()
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@@ -167,4 +167,4 @@ if uploaded_file is not None:
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end_time = time.time()
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elapsed_time = end_time - start_time
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st.write(f"Extraction completed in {elapsed_time:.2f} seconds")
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display_extracted_fields(extracted_fields2, "Extracted
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llm = llm_dict.get(model, ChatOpenAI(temperature=0, model=model))
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chain = prompt_template | llm | parser
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+
max_attempts = 3
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attempt = 1
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while attempt <= max_attempts:
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end_time = time.time()
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elapsed_time = end_time - start_time
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st.write(f"Extraction completed in {elapsed_time:.2f} seconds")
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display_extracted_fields(extracted_fields1, f"{selected_model1} Extracted Fields ")
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with col2:
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start_time = time.time()
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end_time = time.time()
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elapsed_time = end_time - start_time
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st.write(f"Extraction completed in {elapsed_time:.2f} seconds")
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display_extracted_fields(extracted_fields2, f"{selected_model2} Extracted Fields ")
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leoBaseProfile.json
ADDED
@@ -0,0 +1,96 @@
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{
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"personal_details": {
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"full_name": "Leo Walker",
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"contact_info": {
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"email": "[email protected]",
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"phone": "(571) 294-9678",
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"linkedin": "linkedin.com/in/leowalker"
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},
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"professional_summary": "Data Scientist with expertise in Python, SQL, Data Visualization, Machine Learning, NLP, LLMs, LangChain, and LlamaIndex."
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},
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"education": [
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{
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"institution": "University of Denver",
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"degree": "MS",
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"field_of_study": "Data Science",
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"graduation_date": "November 2023"
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},
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{
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"institution": "Ranger School - the Army\u2019s Premier Leadership School",
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"degree": null,
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"field_of_study": null,
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"graduation_date": "April 2012"
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},
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{
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"institution": "Virginia Military Institute",
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"degree": "BS",
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"field_of_study": "Electrical and Computer Engineering",
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"graduation_date": "May 2011"
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}
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],
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"work_experience": [
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{
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"company": "IVP",
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"title": "Data Scientist",
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"duration": "August 2022 - September 2023",
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"description": "",
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"notable_contributions": [
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"Orchestrated comprehensive performance analysis using SQL and Python to pinpoint promising investment opportunities guided by historical investment success metrics.",
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"Improved investor engagement with 60% faster email crafting using optimized LLM pipelines.",
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"Increased accuracy and transparency of peer comparisons by implementing a refined distribution algorithm in company performance assessments."
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]
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},
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{
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"company": "BP",
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"title": "Data Scientist",
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"duration": "February 2018 - August 2022",
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"description": "",
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"notable_contributions": [
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"Developed an automated GreenHouse Gas report that reduced lead time by two weeks and saved 300 man-hours annually while increasing KPI transparency across leadership levels.",
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"Established strategic partnerships with stakeholders at all levels to enhance safety awareness through an NLP tool, leading to a 15% decrease in safety events.",
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"Developed an IT-wide portfolio tracker that integrated directly into MS DevOps to provide a single point where leaders across the organization can track project progress."
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]
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},
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{
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"company": "US Army, Special Operations Command",
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"title": "Distribution Platoon Leader",
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"duration": "May 2014 - April 2017",
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"description": "Led a cross-functional team of 28 and controlled an annual budget of $111MM.",
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"notable_contributions": [
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"Managed development of 1st mobile performance appraisal app, decreasing delivery time by 80%."
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]
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},
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{
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"company": null,
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"title": "Data Analyst",
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"duration": "April 2017 - February 2018",
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"description": "Led development project leveraging localized drilling data to provide focused drilling directives, potentially saving $300K per well with projected productivity gains valued at $43.2MM in 2019.",
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"notable_contributions": [
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"Developed a KPI dashboard to increase safety incident awareness across the company, resulting in robust data collection and strategy sessions to distribute lessons learned and reduce incidents."
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]
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}
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],
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"projects": [],
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"skills": [
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"Python",
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"SQL",
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"Data Visualization",
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"Machine Learning",
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"NLP",
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"LLMs",
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"LangChain",
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"PyTorch"
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],
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"certifications": [
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"Certified ScrumMaster",
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"PMI Agile Certified Practitioner (PMP-ACP)",
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"Project Management Professional (PMP)"
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],
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"publications": [],
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"awards": [],
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"additional_sections": {
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"volunteer_experience": [],
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"languages": [],
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"interests": []
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}
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}
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profile_extenders.py
ADDED
@@ -0,0 +1,19 @@
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from typing import List, Optional, Dict
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from langchain_core.pydantic_v1 import BaseModel, Field
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class BlogPost(BaseModel):
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title: Optional[str] = None
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url: Optional[str] = None
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date: Optional[str] = None
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summary: Optional[str] = None
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class Hackathon(BaseModel):
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name: Optional[str] = None
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date: Optional[str] = None
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description: Optional[str] = None
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role: Optional[str] = None
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achievements: Optional[List[str]] = None
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class OtherInfo(BaseModel):
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category: Optional[str] = None
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description: Optional[str] = None
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