Update app.py

app.py

@@ -5,7 +5,6 @@ import docx
 import requests
 import json
 
-
 # Function to extract text from PDF
 def extract_text_from_pdf(file):
     pdf_reader = PyPDF2.PdfReader(file)
@@ -31,27 +30,29 @@ def process_uploaded_file(file):
 
 # Function to call Together API for Mistral inference
 def analyze_with_mistral(resume_text, job_description):
-    # Replace with your Together API key
     TOGETHER_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
-    url = "https://router.huggingface.co/together/v1"
+    url = "https://api.together.xyz/v1/chat/completions"
     
-    # Construct the prompt
-    prompt = f"""
-    Analyze the following resume against the job description for ATS compatibility.
-    Provide a detailed breakdown of ATS parameters (keywords, formatting, skills match, experience relevance, education) 
-    and assign a score out of 100 for each, along with an overall score. Return the result in JSON format.
+    # Constructing the message format
+    messages = [
+        {"role": "system", "content": "You are an AI expert in ATS resume analysis."},
+        {"role": "user", "content": f"""
+        Analyze the following resume against the job description for ATS compatibility.
+        Provide a detailed breakdown of ATS parameters (keywords, formatting, skills match, 
+        experience relevance, education) and assign a score out of 100 for each, along with an overall score.
+        Return the result in JSON format.
 
-    Resume:
-    {resume_text}
+        Resume:
+        {resume_text}
 
-    Job Description:
-    {job_description}
-    """
+        Job Description:
+        {job_description}
+        """}
+    ]
     
-    # API request payload
     payload = {
         "model": "mistralai/Mistral-7B-Instruct-v0.3",
-        "prompt": prompt,
+        "messages": messages,
         "max_tokens": 1000,
         "temperature": 0.7,
         "top_p": 0.9,
@@ -62,13 +63,11 @@ def analyze_with_mistral(resume_text, job_description):
         "Content-Type": "application/json",
     }
     
-    # Make the API call
     response = requests.post(url, json=payload, headers=headers)
     
     if response.status_code == 200:
         result = response.json()
-        # Assuming the API returns the generated text in 'output' field
-        return result.get("output", json.dumps({"error": "No output from API"}, indent=2))
+        return result.get("choices", [{}])[0].get("message", {}).get("content", "No response from API")
     else:
         return json.dumps({"error": f"API request failed with status {response.status_code}: {response.text}"}, indent=2)
 
@@ -87,7 +86,7 @@ with gr.Blocks(fill_height=True, title="Smart ATS Resume Analyzer") as demo:
         gr.Markdown("# Smart ATS Resume Analyzer")
         gr.Markdown("Upload your resume (PDF/Word) and enter a job description to get an ATS compatibility score.")
         button = gr.LoginButton("Sign in with Hugging Face")
-
+    
     with gr.Row():
         with gr.Column(scale=1):
             resume_upload = gr.File(label="Upload Resume (PDF or Word)", file_types=[".pdf", ".docx"])
@@ -95,12 +94,11 @@ with gr.Blocks(fill_height=True, title="Smart ATS Resume Analyzer") as demo:
             submit_btn = gr.Button("Analyze Resume")
         with gr.Column(scale=2):
             output = gr.JSON(label="ATS Analysis Result")
-
-    # Connect the button to the analysis function
+    
     submit_btn.click(
         fn=analyze_resume,
         inputs=[resume_upload, job_desc],
         outputs=output
     )
 
-demo.launch()
+demo.launch()