Update README.md

README.md

@@ -12,4 +12,30 @@ datasets:
 - jacob-hugging-face/job-descriptions
 ---
 
-this model is based on like giving description for example if you give prompt as apple its giving a apple job description or else its take description from you for train his self
+1. Data Collection
+Existing Companies: Gather a dataset of existing companies and their job descriptions. This could include various roles and responsibilities.
+New Companies: Create a mechanism to identify when a new company is mentioned (not in your existing dataset) and prompt the user for a description.
+2. Prompt Structure
+For Existing Companies:
+Input: “What is the job description for [Company Name]?”
+Output: Return a predefined job description for that company.
+For New Companies:
+Input: “What is the job description for [New Company]?”
+Output:
+"I don't have a description for [New Company]. Could you please provide a brief description or key details about the company?"
+Store the user-provided description for future reference.
+3. User Interaction
+Design a user-friendly interface where users can input company names and descriptions easily.
+Ensure that when a user provides a description for a new company, it's validated and stored properly for future queries.
+4. Learning Mechanism
+Implement a feedback loop where:
+The model refines its understanding of job descriptions based on user input.
+If multiple users provide descriptions for the same new company, you can aggregate this data to improve accuracy.
+5. Example Workflow
+User Input: User enters “Tech Innovations Inc.”
+Model Check:
+If “Tech Innovations Inc.” exists in the dataset, return its job description.
+If not, prompt the user:
+"I don't have a description for Tech Innovations Inc. Can you provide one?"
+User Response: User provides a description.
+Store Description: Save the description in the dataset for future queries.