back to open ai

app.py

@@ -17,12 +17,12 @@ from typing import List, Dict, Optional
 from pydantic import BaseModel, Field, confloat
 
 # llm = LLM(model="deepseek/deepseek-r1-distill-qwen-32b")
-from crewai.llms import LiteLLM
+# from crewai.llms import LiteLLM
 
-llm = LiteLLM(
-    model="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
-    api_base="http://localhost:8000"  # or DeepSeek API
-)
+# llm = LiteLLM(
+#     model="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+#     api_base="http://localhost:8000"  # or DeepSeek API
+# )
 class SkillScore(BaseModel):
     skill_name: str = Field(description="Name of the skill being scored")
     required: bool = Field(description="Whether this skill is required or nice-to-have")
@@ -248,7 +248,7 @@ resume_analyzer = Agent(
                                 providing actionable suggestions for improvement. Your recommendations always
                                 focus on both human readability and ATS compatibility.""",
             verbose=True,
-            llm = llm,
+            # llm = llm,
             # knowledge_sources=[pdf_source],
         )
 job_analyzer = Agent(
@@ -261,7 +261,7 @@ job_analyzer = Agent(
                 and soft skills requirements, and can evaluate experience levels accurately.""",
             verbose=True,
             tools=[ScrapeWebsiteTool()],
-            llm = llm,
+            # llm = llm,
 
             # knowledge_sources=[pdf_source],
 )
@@ -275,7 +275,7 @@ company_researcher = Agent(
                 candidates for interviews. """,
             tools=[SerperDevTool()],
             verbose=True,
-            llm = llm,
+            # llm = llm,
 
             # knowledge_sources=[pdf_source],
 
@@ -289,7 +289,7 @@ resume_writer = Agent (
                     beautifully formatted, ATS-friendly documents that maintain professionalism
                     while showcasing candidate strengths effectively.""",
                 verbose=True,
-                llm = llm,
+                # llm = llm,
 
         )
 report_generator = Agent(
@@ -302,7 +302,7 @@ report_generator = Agent(
                     into clear, actionable insights with proper markdown formatting, emojis, and
                     visual elements that make information both appealing and easily digestible.""",
                 verbose=True,
-                llm = llm,
+                # llm = llm,
 
         )
 
@@ -499,7 +499,7 @@ def run_crew(api_key: str, job_url: str, company_name: str, resume_pdf_path: str
     if not api_key:
         return "⚠️ Please provide a valid OpenAI API Key."
 
-    # os.environ["OPENAI_API_KEY"] = f"{api_key}"  # Set API key securely
+    os.environ["OPENAI_API_KEY"] = f"{api_key}"  # Set API key securely
     # Load PDF as knowledge source
     # pdf_source = resume_pdf_path
     pdf_source = PDFKnowledgeSource(