Update app.py

app.py

@@ -1,64 +1,70 @@
+import os
+import google.generativeai as genai
 import gradio as gr
-from huggingface_hub import InferenceClient
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Set up Google API key from environment variable
+API_KEY = os.getenv("GOOGLE_API_KEY")
+if not API_KEY:
+    raise ValueError("GOOGLE_API_KEY not set. Add it in Hugging Face Space Secrets.")
 
+# Configure the Google Generative AI client
+genai.configure(api_key=API_KEY)
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+def generate_career_plan(education, skills, internships, interests):
+    """Generate a dynamic career plan using Google Gemini API without career goals."""
+    # Construct the prompt without career goals
+    prompt = (
+    f"You are a highly knowledgeable career advisor. Create a detailed, actionable career plan "
+    f"tailored to the following user inputs:\n"
+    f"- Engineering Education: {education}\n"
+    f"- Skills: {skills}\n"
+    f"- Internships/Experience: {internships}\n"
+    f"- Interests: {interests}\n\n"
+    f"Structure the plan as follows:\n"
+    f"1. Short-term steps : Break this section down into:\n"
+    f"   a. Immediate actions (0–3 months): Quick wins or high-impact tasks based on their current skills.\n"
+    f"   b. Mid-term steps (5–8 months): Actions to deepen expertise, expand network, or build relevant experience.\n"
+    f"   c. Longer short-term (1–2 years): Projects, certifications, or job transitions to solidify the foundation.\n"
+    f"2. Long-term steps (3–5 years): Steps to advance their career based on interests and background.\n"
+    f"3. Job roles to target: Relevant positions based on their profile.\n"
+    f"4. Skills to learn: New skills to acquire for success.\n"
+    f"5. Resources: Recommended courses, books, or tools (be specific).\n"
+    f"Ensure the plan is concise, practical, and directly reflects the user's inputs."
 )
 
+    try:
+        # Initialize the Gemini model
+        model = genai.GenerativeModel("gemini-1.5-flash")  # Adjust model name if needed
+        response = model.generate_content(prompt)
+        
+        # Check if response is valid
+        if not response.text:
+            return "Error: No response generated. Check API key or model availability."
+        return response.text
+    except Exception as e:
+        return f"Error: {str(e)}. Check your API key or network connection."
+
+# Gradio interface without Career Goals
+with gr.Blocks(title="Career Guidance Chatbot") as demo:
+    gr.Markdown("# Career Guidance Chatbot")
+    gr.Markdown("Enter your details to get a personalized career plan powered by Google Gemini.Response :WAIT For 10 Sec..")
+    
+    with gr.Row():
+        with gr.Column():
+            education = gr.Textbox(label="Engineering Education (e.g., Computer Science, Mechanical)")
+            skills = gr.Textbox(label="Skills (e.g., Python, CAD, project management)")
+            internships = gr.Textbox(label="Internships/Experience (e.g., 3 months at XYZ Corp)")
+            interests = gr.Textbox(label="Interests (e.g., AI, robotics, sustainable energy)")
+            submit_btn = gr.Button("Generate Career Plan")
+        
+        with gr.Column():
+            output = gr.Markdown(label="Your Career Plan")
+    
+    submit_btn.click(
+        fn=generate_career_plan,
+        inputs=[education, skills, internships, interests],
+        outputs=output
+    )
 
-if __name__ == "__main__":
-    demo.launch()
+# Launch the app
+demo.launch()