Add initial FastAPI application and Dockerfile for chatbot integration

.gitea/workflows/demo.yaml

@@ -1,19 +0,0 @@
-name: Gitea Actions Demo
-run-name: ${{ gitea.actor }} is testing out Gitea Actions 🚀
-on: [push]
-
-jobs:
-  Explore-Gitea-Actions:
-    runs-on: home
-    steps:
-      - run: echo "🎉 The job was automatically triggered by a ${{ gitea.event_name }} event."
-      - run: echo "🐧 This job is now running on a ${{ runner.os }} server hosted by Gitea!"
-      - run: echo "🔎 The name of your branch is ${{ gitea.ref }} and your repository is ${{ gitea.repository }}."
-      - name: Check out repository code
-        uses: actions/checkout@v4
-      - run: echo "💡 The ${{ gitea.repository }} repository has been cloned to the runner."
-      - run: echo "🖥️ The workflow is now ready to test your code on the runner."
-      - name: List files in the repository
-        run: |
-          ls ${{ gitea.workspace }}
-      - run: echo "🍏 This job's status is ${{ job.status }}."

agent-api/Dockerfile

@@ -0,0 +1,11 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]

agent-api/app.py

@@ -0,0 +1,37 @@
+from fastapi import FastAPI
+from openai import OpenAI
+import os
+
+app = FastAPI()
+
+# DeepSeek OpenAI-compatible endpoint
+client = OpenAI(
+    api_key=os.getenv("DEEPSEEK_API_KEY"),
+    base_url="https://api.deepseek.com"
+)
+
+@app.post("/v1/chat/completions")
+async def chat(data: dict):
+
+    messages = data["messages"]
+
+    repo_context = """
+    This assistant has access to the repository.
+    Help the user understand the codebase.
+    This repo is building an chatbot, currently still in early stages. The main files are:
+        - app.py: The main FastAPI application that defines the API endpoints and integrates with the Deep seek API.
+        - agent.py: Contains the logic for the chatbot agent, including how it processes messages and generates responses.
+    """
+
+    messages.insert(0, {
+        "role": "system",
+        "content": repo_context
+    })
+
+    response = client.chat.completions.create(
+        model="deepseek-v4-flash",
+        messages=messages,
+        temperature=0.3
+    )
+
+    return response.model_dump()

agent-api/requirements.txt

@@ -0,0 +1,3 @@
+fastapi
+openai
+uvicorn