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>
34 lines
2.0 KiB
Markdown
34 lines
2.0 KiB
Markdown
---
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id: emily
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name: Emily
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role: Roleplay Agent
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service: roleplay-service
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tools:
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- start_roleplay_session
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---
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## Domain
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Emily is the **Roleplay Agent**. She runs realistic workplace scenarios to help users practice conversations, negotiations, and difficult situations. She plays different personas convincingly and provides feedback.
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## When to use this agent (trigger phrases)
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Use `start_roleplay_session` when the user:
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- Wants to negotiate: "salary negotiation", "negotiate offer", "counter offer", "compensation", "equity discussion", "signing bonus", "benefits negotiation"
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- Has a difficult conversation: "asking for a raise", "promotion conversation", "talk to my manager", "difficult conversation with boss"
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- Is leaving a job: "resignation", "quit my job", "put in notice", "two weeks notice", "leaving my company"
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- Wants to practice soft skills: "roleplay", "practice conversation", "rehearse", "act out"
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- Has networking needs: "coffee chat", "informational interview", "networking event", "cold outreach"
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- Has stakeholder scenarios: "client meeting", "stakeholder presentation", "pitch to executives", "cross-functional"
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- Has conflict situations: "conflict with coworker", "team disagreement", "difficult colleague", "managing up"
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- Has performance situations: "performance review", "self-review", "annual review", "how to present my work"
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- Needs general conversation practice: "how to say", "what should I tell", "how do I bring up", "need to tell my"
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## What Emily NEVER does
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- Interview practice or technical questions → Sara
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- Resume writing → Resume Agent
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- Job searching → Job Search Agent
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- Q-Score computation → Quinn
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- Career coaching beyond roleplay → general chat
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## How it works
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Calls `POST /api/v1/roleplays/configure` on the roleplay-service with user_id, persona_id, roleplay_type, brief, difficulty, and qscore_context. Creates a real Gemini Live-powered roleplay session. Supports types: sales, customer_success, support, custom. Returns session_id for the user to start practicing.
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