Update app.py

app.py

@@ -71,8 +71,8 @@ def txt_to_html(text):
     html_content += "</body></html>"
     return html_content
 
-def craft_cv(llm, cv_text, job_description, maxtokens, temperature, top_probability):
 # def craft_cv(llm, prompt, maxtokens, temperature, top_probability):
+def craft_cv(llm, cv_text, job_description, maxtokens, temperature, top_probability):
     instruction = "Given input CV and job description. Please revise the CV according to the given job description and output the revised CV."
     output = llm.create_chat_completion(
         messages=[
@@ -152,19 +152,20 @@ def convert_to_json(llm, cv_text, maxtokens, temperature, top_probability):
 
 # def pdf_to_text(prompt, maxtokens=2048, temperature=0, top_probability=0.95):
 @spaces.GPU(duration=40)
-def pdf_to_text(cv_file, job_description, maxtokens=2048, temperature=0, top_probability=0.95):
+def pdf_to_text(cv_file, job_description, llm_type='Fine tuned Llama3', maxtokens=2048, temperature=0, top_probability=0.95):
     
     converter = DocumentConverter()
     result = converter.convert(cv_file)
     cv_text = result.document.export_to_markdown()
-    
-    llm = Llama(
-        model_path="models/" + model_id,
-        flash_attn=True,
-        n_gpu_layers=81,
-        n_batch=1024,
-        n_ctx=8192,
-    )
+
+    if(llm_type=='Fine tuned Llama3'):
+        llm = Llama(
+            model_path="models/" + model_id,
+            flash_attn=True,
+            n_gpu_layers=81,
+            n_batch=1024,
+            n_ctx=8192,
+        )
     cv_text, crafted_cv = craft_cv(llm, cv_text, job_description, maxtokens, temperature, top_probability)
     # cv_text, crafted_cv = craft_cv(llm, prompt, maxtokens, temperature, top_probability)
     crafted_cv = convert_to_json(llm, crafted_cv, maxtokens, temperature, top_probability)
@@ -179,7 +180,7 @@ output_text = gr.Textbox()
 llm_type = gr.Radio(["Fine tuned Llama3"])
 iface = gr.Interface(
     fn=pdf_to_text,
-    inputs=[cv_file, prompt_text],
+    inputs=[cv_file, prompt_text, llm_type],
     outputs=['text'],
     title='Craft CV',
     description="This application assists to customize CV based on input job description",