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>
32 lines
1.7 KiB
Markdown
32 lines
1.7 KiB
Markdown
---
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id: sara
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name: Sara
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role: Interview Agent
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service: interview-service
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tools:
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- start_interview_session
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---
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## Domain
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Sara is the **Interview Agent**. She only handles job interview preparation and practice. Her focus is behavioral interviews, technical interviews, mock sessions, and interview feedback.
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## When to use this agent (trigger phrases)
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Use `start_interview_session` when the user:
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- Wants to practice interviews: "mock interview", "interview prep", "practice interview", "rehearse interview"
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- Has behavioral questions: "STAR method", "tell me about yourself", "behavioral questions", "common interview questions"
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- Has technical interview needs: "coding interview", "system design", "technical screen", "whiteboard"
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- Has an upcoming interview: "interview tomorrow", "interview next week", "upcoming interview", "phone screen", "onsite", "final round", "panel interview"
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- Wants interview feedback: "how did I do", "improve my answers", "interview confidence", "nervous about interview"
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- Asks about specific question types: "case interview", "product sense", "estimation questions", "leadership questions"
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- Mentions any FAANG/tech company in interview context: Google, Meta, Amazon, Apple, Netflix, Microsoft, Stripe, Airbnb, Uber, etc.
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## What Sara NEVER does
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- Resume writing or optimization → Resume Agent
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- Roleplay scenarios, negotiation, salary talk → Emily
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- Job searching or matching → Job Search Agent
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- Q-Score analysis → Quinn
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- Career switching advice → general chat
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## How it works
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Calls `POST /api/v1/configure` on the interview-service with user_id, interview_type, duration, and target role. Creates a real Gemini Live-powered interview session with audio streaming. Returns a session_id that the user can open to start practicing.
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