Upload resume_parsing.py

src/resume_parsing.py

@@ -0,0 +1,72 @@
+import os
+import tempfile
+from embedding_utils import generate_embedding
+from chroma_utils import add_to_resume_chroma
+from llama_cloud_services import LlamaExtract
+from pydantic import BaseModel, Field
+
+os.environ["LLAMA_CLOUD_API_KEY"] = "llx-hIRlN84LTtmQNuAPg5AjS49LNj3vAEHVST0obWl5ZedgpVuW"
+
+class ResumeSchema(BaseModel):
+    experience: str = Field(description="Professional work experience")
+    education: str = Field(description="Educational background")
+    skills: list[str] = Field(description="Technical and soft skills")
+
+llama_extract = LlamaExtract()
+#agent = llama_extract.create_agent(name="resume_parser", data_schema=ResumeSchema)
+agent = llama_extract.get_agent(name="resume_parser")
+
+
+def parse_resume_with_llm(resume_content, name, location, file_type):
+    
+    try:
+        if file_type not in ["pdf", "docx"]:
+            raise ValueError("Unsupported file type. Only PDF and DOCX files are allowed.")
+
+        with tempfile.NamedTemporaryFile(delete=False, suffix=f".{file_type}") as temp_file:
+            temp_file.write(resume_content)
+            temp_file_path = temp_file.name 
+
+        try:
+            extracted_run = agent.extract(temp_file_path)
+            extracted_data = extracted_run.data  # Access the 'data' attribute
+        except Exception as e:
+            raise RuntimeError(f"LlamaExtract failed: {str(e)}")
+
+        finally:
+            os.remove(temp_file_path)
+
+        if not extracted_data:
+            raise ValueError("No data extracted from the resume.")
+
+
+        experience = extracted_data.get("experience", "")
+        education = extracted_data.get("education", "")
+        skills = extracted_data.get("skills", [])
+
+        combined_text_for_embedding = (
+            f"Experience: {experience} "
+            f"Education: {education} "
+            f"Skills: {skills}"
+        )
+
+        embedding = generate_embedding(combined_text_for_embedding)
+
+        metadata = {
+            "name": name,
+            "location": location,
+            "experience": experience,
+            "education": education,
+            "skills": skills,
+        }
+
+        unique_id = add_to_resume_chroma(embedding, metadata)
+        
+        return {"message": "Resume parsed successfully", "unique_id": unique_id}, embedding
+    except Exception as e:
+        return {"error": f"Failed to parse resume: {str(e)}"}, None
+    
+
+
+
+