Initial commit

test-job-app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load the SmolLM model and tokenizer
+model_name = "HuggingFaceTB/SmolLM2-135M-Instruct" # "HuggingFaceTB/SmolLM2-360m-Instruct"
+model = AutoModelForCausalLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+def smol_lm_process(job_description):
+    # System Prompt: "Extract key qualifications, skills, and requirements from this job description. Output as bullet points. Remove benefits/salary fluff."
+    prompt = f"""<|im_start|>system
+Extract key qualifications, skills, and requirements from this job description. Output as bullet points. Remove benefits/salary fluff.<|im_end|>
+<|im_start|>user
+{job_description}<|im_end|>
+<|im_start|>assistant
+"""
+    inputs = tokenizer(prompt, return_tensors="pt").to(device)
+    output = model.generate(**inputs, max_new_tokens=512)
+    response = tokenizer.decode(output[0], skip_special_tokens=False)
+    # Extract the assistant's response
+    start_idx = response.find("<|im_start|>assistant")
+    end_idx = response.find("<|im_end|>", start_idx)
+    response = response[start_idx + len("<|im_start|>assistant\n"):end_idx].strip()
+    return response
+
+def process_job_description(company_name, company_url, job_description):
+    role_requirements = smol_lm_process(job_description)
+    return {
+        "Company Name": company_name,
+        "Company URL": company_url,
+        "Job Description": job_description,
+        "Role Requirements": role_requirements
+    }
+
+# Create the Gradio app
+demo = gr.Blocks()
+
+with demo:
+    gr.Markdown("# Job Description Input")
+    company_name = gr.Textbox(label="Company Name")
+    company_url = gr.Textbox(label="Company URL")
+    job_description = gr.TextArea(label="Paste Job Description")
+
+    gr.Button("Submit").click(
+        process_job_description,
+        inputs=[company_name, company_url, job_description],
+        outputs=gr.JSON(label="Output")
+    )
+
+if __name__ == "__main__":
+    demo.launch()
+