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from groq import Groq
import gradio as gr
import pandas as pd
from PyPDF2 import PdfReader
from docx import Document
# -------------------------------
# Get your API key from environment
# -------------------------------
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
if not GROQ_API_KEY:
raise ValueError("Please set your GROQ_API_KEY environment variable!")
# Initialize Groq client
client = Groq(api_key=GROQ_API_KEY)
# -------------------------------
# Helper function: extract text from uploaded files
# -------------------------------
def extract_file_text(uploaded_file):
if not uploaded_file:
return ""
filename = uploaded_file.name.lower()
try:
if filename.endswith(".txt"):
with open(uploaded_file.name, "r", encoding="utf-8") as f:
return f.read()
elif filename.endswith(".pdf"):
reader = PdfReader(uploaded_file.name)
return "\n".join([page.extract_text() for page in reader.pages if page.extract_text()])
elif filename.endswith(".docx"):
doc = Document(uploaded_file.name)
return "\n".join([p.text for p in doc.paragraphs])
elif filename.endswith(".csv"):
df = pd.read_csv(uploaded_file.name)
return df.to_string()
elif filename.endswith(".xlsx"):
df = pd.read_excel(uploaded_file.name)
return df.to_string()
else:
return "[Unsupported file type]"
except Exception as e:
return f"[Error reading file: {str(e)}]"
# -------------------------------
# Chatbot logic
# -------------------------------
def healthcare_assistant(message, history, uploaded_file):
# Extract file text
file_text = extract_file_text(uploaded_file)
# System prompt
messages = [
{
"role": "system",
"content": "You are a helpful Professional Role Pathway Bot — turns a Job Description or uploaded file content into a personalized, step-by-step upskilling plan."
}
]
# Add previous chat history
for user_msg, bot_msg in history:
messages.append({"role": "user", "content": user_msg})
if bot_msg:
messages.append({"role": "assistant", "content": bot_msg})
# Combine user message + file content
combined_message = message
if file_text:
combined_message += "\n\nFile content:\n" + file_text
messages.append({"role": "user", "content": combined_message})
# Call Groq API
response = client.chat.completions.create(
model="llama-3.1-8b-instant",
messages=messages
)
return response.choices[0].message.content
# -------------------------------
# Gradio UI
# -------------------------------
with gr.Blocks() as demo:
history = gr.State([]) # store chat history
gr.Markdown("## Professional Role Pathway Bot 🤖\nPaste JD, answer prompts, or upload a file to get personalized learning roadmap.")
chatbox = gr.Chatbot()
with gr.Row():
txt = gr.Textbox(label="Type your message", placeholder="Enter text here...")
file_input = gr.File(label="Upload file (optional)", file_types=[".txt", ".pdf", ".docx", ".csv", ".xlsx"])
submit_btn = gr.Button("Send")
# Respond function
def respond(message, history, uploaded_file):
response = healthcare_assistant(message, history, uploaded_file)
history.append((message, response))
return history, ""
submit_btn.click(respond, inputs=[txt, history, file_input], outputs=[chatbox, txt])
# -------------------------------
# Launch
# -------------------------------
if __name__ == "__main__":
demo.launch()
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