updated readme

README.md

@@ -2,7 +2,7 @@
 
 Automated pull request review system using [CrewAI](https://crewai.com) Flows and MCP (Model Context Protocol) tools.
 
-Performs three parallel reviews — code quality, security, and infrastructure — then synthesizes a consolidated report via a REST API.
+Performs three parallel reviews — code quality, security, and infrastructure — then synthesizes a consolidated report via a REST API. Supports both a direct API and a Gitea webhook integration that fetches diffs automatically and posts the review as a PR comment.
 
 ## Features
 
@@ -10,32 +10,10 @@ Performs three parallel reviews — code quality, security, and infrastructure
 - **Security Review** — vulnerabilities, injection risks, auth issues (powered by Trivy)
 - **Infrastructure Review** — Dockerfiles, Kubernetes manifests, IaC (powered by Hadolint + Checkov)
 - **Summarisation** — merges all three reviews into a single actionable report
-- **REST API** — FastAPI endpoints for health check and review trigger
+- **REST API** — FastAPI endpoints for health check, manual review trigger, and Gitea webhook
+- **Gitea Webhook** — process PR events directly; fetches diffs, runs reviews, posts results as a PR comment
 - **Dockerized** — multi-stage build with all tools bundled
 
-## Architecture
-
-```
-POST /api/v1/review
-        │
-        ▼
-  CodeReviewFlow (CrewAI Flow)
-        │
-   ┌────┼──────────────┐
-   ▼    ▼              ▼
- Code  Security     Infra
-Review  Review      Review
-   │     │            │
-   └─────┼────────────┘
-         ▼
-   Summariser
-         │
-         ▼
-   JSON Response
-```
-
-LLM-agnostic via CrewAI's LLM abstraction — works with OpenAI, Anthropic, or Ollama.
-
 ## Quick Start
 
 ### Prerequisites
@@ -85,6 +63,34 @@ curl -X POST http://localhost:8000/api/v1/review \
   }'
 ```
 
+## Architecture
+
+```
+POST /api/v1/review         POST /api/v1/gitea-webhook
+        │                            │
+        │                    Gitea webhook payload
+        │                            │
+        │                     fetch diffs from
+        │                      Gitea API
+        │                            │
+        ▼                            ▼
+  CodeReviewFlow (CrewAI Flow)
+        │
+   ┌────┼──────────────┐
+   ▼    ▼              ▼
+ Code  Security     Infra
+Review  Review      Review
+   │     │            │
+   └─────┼────────────┘
+         ▼
+   Summariser
+         │
+         ▼
+   JSON Response / PR Comment
+```
+
+LLM-agnostic via CrewAI's LLM abstraction — works with OpenAI, Anthropic, or Ollama.
+
 ## API
 
 ### `GET /api/v1/health`
@@ -97,7 +103,7 @@ Returns service status.
 
 ### `POST /api/v1/review`
 
-Triggers a full PR review.
+Triggers a full PR review. Provide file contents and diffs directly in the request body.
 
 **Request body:**
 
@@ -144,6 +150,42 @@ Triggers a full PR review.
 }
 ```
 
+### `POST /api/v1/gitea-webhook`
+
+Receives Gitea webhook events. Only processes `pull_request` events with actions `opened`, `synchronize`, or `reopened`. All other events and actions are ignored.
+
+The endpoint:
+
+1. Validates the `X-Gitea-Signature` header using HMAC-SHA256 (if `ACCESS_GITEA_SECRET` is configured)
+2. Fetches changed files and their contents from the Gitea API
+3. Runs the full review pipeline (code, security, infrastructure, summariser)
+4. Posts the review summary as a comment on the PR via the Gitea API
+
+## Gitea Webhook Setup
+
+### 1. Create an access token
+
+In your Gitea instance, go to **Settings → Applications → Generate New Token** and create a token with `read:repository` scope.
+
+### 2. Add the webhook
+
+In your Gitea repository, go to **Settings → Webhooks → Add Webhook → Gitea**:
+
+- **Target URL**: `http://<host>:30001/api/v1/gitea-webhook`
+- **HTTP Method**: `POST`
+- **Secret**: a random string (optional but recommended)
+- **Trigger On**: Pull Request
+
+### 3. Configure environment variables
+
+Set the following in the container (or k8s secret):
+
+| Variable | Required | Default | Description |
+|----------|----------|---------|-------------|
+| `ACCESS_GITEA_URL` | yes | `http://192.168.178.160:3000` | Gitea instance base URL |
+| `ACCESS_GITEA_TOKEN` | yes | — | Gitea personal access token with `read:repository` scope |
+| `ACCESS_GITEA_SECRET` | no | `""` | Webhook secret; if set, signatures are validated |
+
 ## Configuration
 
 All configuration via environment variables in `.env`:
@@ -154,10 +196,23 @@ All configuration via environment variables in `.env`:
 | `LLM_PROVIDER` | (required) | `openai`, `anthropic`, or `ollama` |
 | `LLM_BASE_URL` | — | API base URL |
 | `LLM_API_KEY` | — | API key (not needed for Ollama) |
+| `ACCESS_GITEA_URL` | `http://192.168.178.160:3000` | Gitea instance base URL |
+| `ACCESS_GITEA_TOKEN` | — | Gitea personal access token with `read:repository` scope |
+| `ACCESS_GITEA_SECRET` | — | Webhook secret for HMAC-SHA256 signature verification |
 | `TOTAL_FLOW_TIMEOUT` | `600` | Max seconds for full review |
 | `PER_CREW_TIMEOUT` | `300` | Max seconds per crew |
 | `LOG_LEVEL` | `INFO` | Logging level |
 
+## Deployment
+
+### Kubernetes
+
+The repo includes a CI pipeline (`.gitea/workflows/build_push.yml`) that builds a multi-arch Docker image, pushes it to the registry, and deploys to Kubernetes.
+
+The k8s deployment uses a NodePort service exposing port 30001, which maps to the container's port 8000.
+
+Environment variables are stored in a k8s secret (`pr-reviewer-env`). The CI pipeline creates this secret automatically — add `ACCESS_GITEA_URL`, `ACCESS_GITEA_TOKEN`, and `ACCESS_GITEA_SECRET` as Gitea repo variables/secrets.
+
 ## Development
 
 ```bash
@@ -179,12 +234,13 @@ uvicorn src.pr_reviewer.main:app --reload
 ├── crews/                # Crew definitions (code, security, infra, summariser)
 ├── mcp_servers/          # MCP tool wrappers (Hadolint, Checkov)
 ├── src/pr_reviewer/      # Core application code
-│   ├── main.py           # FastAPI app
+│   ├── main.py           # FastAPI app, endpoints, webhook handler
 │   ├── flow.py           # CrewAI Flow orchestration
 │   ├── state.py          # Pydantic state models
 │   ├── llm.py            # LLM factory
 │   └── context.py        # Context resolution
 ├── tests/                # Unit and integration tests
+├── kube/                 # Kubernetes manifests
 ├── docker-compose.yaml
 ├── Dockerfile
 └── pyproject.toml