Added job_search_tool tool in tools

.ipynb_checkpoints/agent-checkpoint.json

@@ -2,7 +2,8 @@
     "tools": [
         "web_search",
         "visit_webpage",
-        "final_answer"
+        "final_answer",
+        "job_search_tool"
     ],
     "model": {
         "class": "HfApiModel",

.ipynb_checkpoints/app-checkpoint.py

@@ -1,4 +1,4 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool, Agent
 import datetime
 import requests
 import pytz
@@ -6,6 +6,7 @@ import yaml
 from tools.final_answer import FinalAnswerTool
 from tools.visit_webpage import VisitWebpageTool
 from tools.web_search import DuckDuckGoSearchTool
+from tools.linkedin_job_search import LinkedInJobSearchTool
 
 from Gradio_UI import GradioUI
 
@@ -39,6 +40,7 @@ def get_current_time_in_timezone(timezone: str) -> str:
 final_answer = FinalAnswerTool()
 visit_webpage = VisitWebpageTool()
 web_search = DuckDuckGoSearchTool()
+job_search_tool = LinkedInJobSearchTool()
 
 
 # If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
@@ -60,7 +62,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, visit_webpage, web_search, image_generation_tool, get_current_time_in_timezone],## add your tools here (don't remove final answer)
+    tools=[final_answer, visit_webpage, web_search, image_generation_tool, get_current_time_in_timezone, job_search_tool],## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,

agent.json

@@ -2,7 +2,8 @@
     "tools": [
         "web_search",
         "visit_webpage",
-        "final_answer"
+        "final_answer",
+        "job_search_tool"
     ],
     "model": {
         "class": "HfApiModel",

app.py

@@ -1,4 +1,4 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool, Agent
 import datetime
 import requests
 import pytz
@@ -6,6 +6,7 @@ import yaml
 from tools.final_answer import FinalAnswerTool
 from tools.visit_webpage import VisitWebpageTool
 from tools.web_search import DuckDuckGoSearchTool
+from tools.linkedin_job_search import LinkedInJobSearchTool
 
 from Gradio_UI import GradioUI
 
@@ -39,6 +40,7 @@ def get_current_time_in_timezone(timezone: str) -> str:
 final_answer = FinalAnswerTool()
 visit_webpage = VisitWebpageTool()
 web_search = DuckDuckGoSearchTool()
+job_search_tool = LinkedInJobSearchTool()
 
 
 # If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
@@ -60,7 +62,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, visit_webpage, web_search, image_generation_tool, get_current_time_in_timezone],## add your tools here (don't remove final answer)
+    tools=[final_answer, visit_webpage, web_search, image_generation_tool, get_current_time_in_timezone, job_search_tool],## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,

tools/linkedin_job_search.py

@@ -0,0 +1,50 @@
+from smolagents.tools import Tool
+import requests
+from typing import Dict, List
+
+class LinkedInJobSearchTool(Tool):
+    name = "linkedin_job_search"
+    description = "Searches for jobs on LinkedIn based on job title, location, and work mode (remote, hybrid, in-office)."
+    inputs = {
+        "position": {"type": "string", "description": "Job title or keyword (e.g., Data Scientist)"},
+        "location": {"type": "string", "description": "City or country where the job is located (e.g., New York, Remote)"},
+        "work_mode": {"type": "string", "description": "Preferred work setting: remote, hybrid, in-office"}
+    }
+    output_type = "list"  # Returning a list of job postings
+
+    def forward(self, position: str, location: str, work_mode: str) -> List[Dict]:
+        """
+        Searches LinkedIn for job postings using SerpAPI.
+        """
+        SERPAPI_KEY = "2f660e5a696e7d1d08662085b95f83a61224476ec19558de3c68218baf346e43"  # Replace with your SerpAPI key
+        base_url = "https://serpapi.com/search"
+
+        params = {
+            "engine": "google_jobs",
+            "q": f"{position} {work_mode} jobs",
+            "location": location,
+            "hl": "en",
+            "api_key": SERPAPI_KEY
+        }
+
+        response = requests.get(base_url, params=params)
+
+        if response.status_code == 200:
+            data = response.json()
+            job_results = data.get("jobs_results", [])
+
+            # Extracting relevant job info
+            formatted_jobs = [
+                {
+                    "title": job["title"],
+                    "company": job.get("company_name", "N/A"),
+                    "location": job.get("location", "N/A"),
+                    "posted_date": job.get("detected_extensions", {}).get("posted_at", "N/A"),
+                    "link": job.get("job_id", "N/A")
+                }
+                for job in job_results
+            ]
+
+            return formatted_jobs
+        else:
+            return [{"error": f"Error {response.status_code}: {response.text}"}]