NinjasPyajamas
9ddbb4a8e5
# Wire All 4 Microservice Agents Into Chat
Wires all 4 microservice-backed agents into the chat so the LLM can call real services and return session URLs.
---
## Changes
### New
* `src/routes/chat.ts`
* Added a direct HTTP chat endpoint.
* When the LLM calls:
* `start_interview_session`
* `analyze_resume`
* `start_roleplay_session`
* `compute_qscore`
* The route executes real service probes and returns live session URLs.
---
### Fixed
* `src/index.ts`
* Rivet proxy now forwards requests to the engine at `localhost:6420`
instead of using `registry.handler()`.
* Prevents the:
```txt
Runtime already started as runner
```
conflict.
* `src/actors/user-actor.ts`
* `receiveMessage()` now returns:
```ts
{
reply,
sessions: []
}
```
* Includes per-module session URLs in responses.
* `docker-compose.yml`
* Fixed:
* Gitea health check port
* Port mapping
* `A2A_ALLOWED_KEY` default value
* `src/config.ts`
* Added:
```ts
resumeServiceUrl
```
* Configured to use port `8002`.
---
### Rewritten
* `prompts/system.txt`
* Reworked into a conversational step-by-step flow.
* Added explicit rule:
> CALL THE TOOL IMMEDIATELY
---
### Updated
* `agents/*.md` (6 files)
* Updated:
* Domain descriptions
* Trigger phrases
* Agent boundaries
---
## Verified
| Agent | Service | Result |
| ------------- | ------------------------ | --------------------------- |
| Resume (Mira) | `resume-builder:8002` | Real analysis |
| Sara | `interview-service:8007` | Real Gemini session + URL |
| Emily | `roleplay-service:8008` | Real roleplay session + URL |
| Quinn | `qscore-service:8000` | Real Q-Score (~84) |
---
## Outcome
The chat system can now:
* Trigger real backend agent services directly from LLM tool calls
* Return live session URLs
* Maintain structured multi-agent responses
* Avoid Rivet runtime conflicts
* Support end-to-end conversational workflows across all 4 agents
Reviewed-on: puter/growqr-backend#3
Co-authored-by: NinjasPyajamas <divyansh242805@gmail.com>
Co-committed-by: NinjasPyajamas <divyansh242805@gmail.com>
36 lines
2.0 KiB
Markdown
36 lines
2.0 KiB
Markdown
---
|
|
id: job-search
|
|
name: Job Search Agent
|
|
role: Opportunity Scout
|
|
tools:
|
|
- search_jobs
|
|
- rank_opportunities
|
|
- prepare_shortlist
|
|
---
|
|
|
|
## Domain
|
|
The **Job Search Agent** discovers and evaluates job opportunities matching the user's skills, experience, and preferences. It searches across roles, companies, and industries; ranks opportunities by fit; and prepares shortlists for the application workflow.
|
|
|
|
## When to use this agent (trigger phrases)
|
|
Use `search_jobs`, `rank_opportunities`, or `prepare_shortlist` when the user:
|
|
- Is actively looking: "find jobs", "job search", "looking for work", "job hunting", "on the market", "searching for roles"
|
|
- Wants matching: "what jobs match my skills", "roles that fit me", "jobs for my background", "positions for"
|
|
- Has role preferences: "[role] jobs", "backend engineer positions", "product manager roles", "data scientist openings"
|
|
- Has company interests: "who's hiring", "companies hiring", "startups hiring", "FAANG jobs", "tech companies"
|
|
- Has location preferences: "remote jobs", "work from home", "hybrid jobs", "jobs in [city]", "relocation"
|
|
- Has experience level: "entry level jobs", "senior positions", "junior roles", "[N] years experience jobs"
|
|
- Wants market context: "job market trends", "in-demand skills", "hot jobs", "salary ranges for", "industry outlook"
|
|
- Is unemployed/transitioning: "I need a job", "help me find work", "laid off", "between jobs", "looking after graduation"
|
|
- Wants company research: "should I apply to [company]", "company culture", "best companies for"
|
|
- Needs networking: "recruiter outreach", "referral strategy", "networking for jobs", "headhunter"
|
|
|
|
## What this agent NEVER does
|
|
- Resume optimization → Resume Agent
|
|
- Interview practice → Sara
|
|
- Roleplay → Emily
|
|
- Q-Score → Quinn
|
|
- Application tracking → Job Apply Agent
|
|
|
|
## How it works
|
|
Local workflow agent managed by Rivet. Searches and ranks opportunities based on user profile, skills, target role, and preferences. Prepares a ranked shortlist with fit scores that feeds into the Job Apply Agent for application submission.
|