merged changes

app.py

@@ -87,17 +87,10 @@ st.title("Resume Parser")
 
 # Set up the LLM dictionary
 llm_dict = {
-<<<<<<< HEAD
     # "gpt-4-1106-preview": ChatOpenAI(temperature=0, model="gpt-4-1106-preview"),
     # "gpt-4": ChatOpenAI(temperature=0, model="gpt-4"),
     "gpt-3.5-turbo-1106": ChatOpenAI(temperature=0, model="gpt-3.5-turbo-1106"),
     # "claude-2": ChatAnthropic(model="claude-2", max_tokens=20_000),
-=======
-    "gpt-4-1106-preview": ChatOpenAI(temperature=0, model="gpt-4-1106-preview"),
-    "gpt-4": ChatOpenAI(temperature=0, model="gpt-4"),
-    "gpt-3.5-turbo-1106": ChatOpenAI(temperature=0, model="gpt-3.5-turbo-1106"),
-    "claude-2": ChatAnthropic(model="claude-2", max_tokens=20_000),
->>>>>>> 726975d5ca7f0a98a5047fbda8870a0f03f55283
     "claude-instant-1": ChatAnthropic(model="claude-instant-1", max_tokens=20_000)
 }
 
@@ -111,18 +104,14 @@ uploaded_file = st.file_uploader("Upload a PDF file", type="pdf")
 if uploaded_file is not None:
     # Add a button to trigger the conversion
     if st.button("Convert PDF to Text"):
-<<<<<<< HEAD
         start_time = time.time()  # Start the timer
         
-=======
->>>>>>> 726975d5ca7f0a98a5047fbda8870a0f03f55283
         # Convert the uploaded file to a string
         text = pdf_to_string(uploaded_file)
         
         # Extract resume fields using the selected model
         extracted_fields = extract_resume_fields(text, selected_model)
         
-<<<<<<< HEAD
         end_time = time.time()  # Stop the timer
         elapsed_time = end_time - start_time  # Calculate the elapsed time
         
@@ -139,7 +128,3 @@ if uploaded_file is not None:
         for key, value in extracted_fields.items():
             st.write(f"{key}: {value}")
         
-=======
-        # Display the extracted fields on the Streamlit app
-        st.json(extracted_fields)
->>>>>>> 726975d5ca7f0a98a5047fbda8870a0f03f55283