Create app.py

app.py

@@ -0,0 +1,504 @@
+import os
+import json
+from dataclasses import dataclass, asdict, field
+from typing import Optional, List
+
+import gradio as gr
+from openai import OpenAI
+
+# ============================================================
+# CONFIG
+# ============================================================
+
+OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+
+if not OPENROUTER_API_KEY:
+    raise RuntimeError(
+        "OPENROUTER_API_KEY environment variable not found."
+    )
+
+MODEL = os.getenv(
+    "OPENROUTER_MODEL",
+    "openai/gpt-oss-120b:free"
+)
+
+client = OpenAI(
+    base_url="https://openrouter.ai/api/v1",
+    api_key=OPENROUTER_API_KEY
+)
+
+# ============================================================
+# STATE
+# ============================================================
+
+@dataclass
+class AgentState:
+    name: Optional[str] = None
+    role: Optional[str] = None
+    goal: Optional[str] = None
+    greeting: Optional[str] = None
+    tone: Optional[str] = None
+    memory: Optional[str] = None
+    audience: Optional[str] = None
+    domain: Optional[str] = None
+
+    tools: List[str] = field(default_factory=list)
+    policies: List[str] = field(default_factory=list)
+
+    def to_dict(self):
+        return asdict(self)
+
+# ============================================================
+# PROMPTS
+# ============================================================
+
+DISCOVERY_PROMPT = """
+You are an Agent Architect.
+
+Your job is to help users create AI agents entirely through conversation.
+
+Rules:
+
+- Talk naturally.
+- Gather requirements progressively.
+- Ask only ONE important follow-up question.
+- Never mention prompts.
+- Never mention JSON.
+- Never mention implementation.
+- Focus on understanding the user's vision.
+
+The user's natural language is the source of truth.
+"""
+
+ARCHITECT_PROMPT = """
+Extract structured information from the user's message.
+
+Return ONLY JSON.
+
+Schema:
+
+{
+  "name": null,
+  "role": null,
+  "goal": null,
+  "greeting": null,
+  "tone": null,
+  "memory": null,
+  "audience": null,
+  "domain": null,
+  "tools": [],
+  "policies": []
+}
+"""
+
+CAPABILITY_PROMPT = """
+You are a Capability Planner.
+
+Given an agent specification,
+suggest useful capabilities.
+
+Return ONLY JSON.
+
+{
+  "tools": []
+}
+"""
+
+COMPILER_PROMPT = """
+You generate system prompts.
+
+Convert the specification into
+a production-grade runtime prompt.
+
+Output ONLY the prompt.
+"""
+
+# ============================================================
+# ORCHESTRATOR
+# ============================================================
+
+class AgentOrchestrator:
+
+    def __init__(self):
+        self.state = AgentState()
+        self.runtime_prompt = ""
+
+    # ========================================================
+
+    def llm(
+        self,
+        messages,
+        max_tokens=500,
+        response_format=None
+    ):
+
+        kwargs = {
+            "model": MODEL,
+            "messages": messages,
+            "max_tokens": max_tokens
+        }
+
+        if response_format:
+            kwargs["response_format"] = response_format
+
+        response = client.chat.completions.create(**kwargs)
+
+        content = response.choices[0].message.content
+
+        if not content:
+            return ""
+
+        return content.strip()
+
+    # ========================================================
+
+    def update_architecture(
+        self,
+        user_message: str
+    ):
+
+        try:
+
+            result = self.llm(
+                [
+                    {
+                        "role": "system",
+                        "content": ARCHITECT_PROMPT
+                    },
+                    {
+                        "role": "user",
+                        "content": user_message
+                    }
+                ],
+                response_format={
+                    "type": "json_object"
+                }
+            )
+
+            data = json.loads(result)
+
+            for key, value in data.items():
+
+                if value in [None, "", []]:
+                    continue
+
+                if hasattr(self.state, key):
+                    setattr(
+                        self.state,
+                        key,
+                        value
+                    )
+
+        except Exception as e:
+            print("Architect error:", e)
+
+    # ========================================================
+
+    def update_capabilities(self):
+
+        try:
+
+            result = self.llm(
+                [
+                    {
+                        "role": "system",
+                        "content": CAPABILITY_PROMPT
+                    },
+                    {
+                        "role": "user",
+                        "content": json.dumps(
+                            self.state.to_dict(),
+                            indent=2
+                        )
+                    }
+                ],
+                response_format={
+                    "type": "json_object"
+                }
+            )
+
+            data = json.loads(result)
+
+            tools = data.get("tools", [])
+
+            if isinstance(tools, list):
+
+                merged = set(
+                    self.state.tools
+                )
+
+                merged.update(tools)
+
+                self.state.tools = list(
+                    merged
+                )
+
+        except Exception as e:
+            print("Capability error:", e)
+
+    # ========================================================
+
+    def compile_runtime_prompt(self):
+
+        try:
+
+            self.runtime_prompt = self.llm(
+                [
+                    {
+                        "role": "system",
+                        "content": COMPILER_PROMPT
+                    },
+                    {
+                        "role": "user",
+                        "content": json.dumps(
+                            self.state.to_dict(),
+                            indent=2
+                        )
+                    }
+                ],
+                max_tokens=700
+            )
+
+        except Exception as e:
+
+            print("Compile error:", e)
+
+    # ========================================================
+
+    def developer_chat(
+        self,
+        message: str
+    ):
+
+        self.update_architecture(message)
+
+        self.update_capabilities()
+
+        self.compile_runtime_prompt()
+
+        reply = self.llm(
+            [
+                {
+                    "role": "system",
+                    "content": DISCOVERY_PROMPT
+                },
+                {
+                    "role": "user",
+                    "content":
+                    f"""
+Agent State:
+
+{json.dumps(self.state.to_dict(), indent=2)}
+
+Developer Message:
+
+{message}
+"""
+                }
+            ],
+            max_tokens=250
+        )
+
+        return reply
+
+    # ========================================================
+
+    def client_chat(
+        self,
+        message,
+        history
+    ):
+
+        if not self.runtime_prompt:
+            self.compile_runtime_prompt()
+
+        messages = [
+            {
+                "role": "system",
+                "content": self.runtime_prompt
+            }
+        ]
+
+        for item in history:
+
+            messages.append(
+                {
+                    "role": item["role"],
+                    "content": item["content"]
+                }
+            )
+
+        messages.append(
+            {
+                "role": "user",
+                "content": message
+            }
+        )
+
+        return self.llm(
+            messages,
+            max_tokens=700
+        )
+
+# ============================================================
+# APP STATE
+# ============================================================
+
+orchestrator = AgentOrchestrator()
+
+# ============================================================
+# UI CALLBACK
+# ============================================================
+
+def chat_handler(
+    message,
+    history,
+    mode
+):
+
+    history = history or []
+
+    if mode == "Developer":
+
+        reply = orchestrator.developer_chat(
+            message
+        )
+
+    else:
+
+        reply = orchestrator.client_chat(
+            message,
+            history
+        )
+
+    history.append(
+        {
+            "role": "user",
+            "content": message
+        }
+    )
+
+    history.append(
+        {
+            "role": "assistant",
+            "content": reply
+        }
+    )
+
+    state = orchestrator.state.to_dict()
+
+    return (
+        "",
+        history,
+        state.get("name") or "",
+        state.get("role") or "",
+        state.get("goal") or "",
+        state.get("greeting") or "",
+        state.get("memory") or "",
+        state.get("tone") or "",
+        ", ".join(state.get("tools", [])),
+        orchestrator.runtime_prompt
+    )
+
+# ============================================================
+# UI
+# ============================================================
+
+with gr.Blocks(
+    title="Agent Platform",
+    fill_height=True
+) as demo:
+
+    gr.Markdown("# Agent Platform")
+
+    with gr.Row():
+
+        # LEFT PANEL
+        with gr.Column(scale=2):
+
+            mode = gr.Dropdown(
+                choices=[
+                    "Developer",
+                    "Client"
+                ],
+                value="Developer",
+                label="Mode"
+            )
+
+            chatbot = gr.Chatbot(
+                type="messages",
+                height=700
+            )
+
+            message = gr.Textbox(
+                placeholder="Describe your agent..."
+            )
+
+        # RIGHT PANEL
+        with gr.Column(scale=1):
+
+            gr.Markdown("## Agent Definition")
+
+            name = gr.Textbox(
+                label="Name"
+            )
+
+            role = gr.Textbox(
+                label="Role"
+            )
+
+            goal = gr.Textbox(
+                label="Goal"
+            )
+
+            greeting = gr.Textbox(
+                label="Greeting"
+            )
+
+            memory = gr.Textbox(
+                label="Memory"
+            )
+
+            tone = gr.Textbox(
+                label="Tone"
+            )
+
+            tools = gr.Textbox(
+                label="Tools"
+            )
+
+            runtime_prompt = gr.Textbox(
+                label="Compiled Runtime Prompt",
+                lines=18
+            )
+
+    message.submit(
+        chat_handler,
+        inputs=[
+            message,
+            chatbot,
+            mode
+        ],
+        outputs=[
+            message,
+            chatbot,
+            name,
+            role,
+            goal,
+            greeting,
+            memory,
+            tone,
+            tools,
+            runtime_prompt
+        ]
+    )
+
+# ============================================================
+# RUN
+# ============================================================
+
+if __name__ == "__main__":
+    demo.launch(
+        share=True,
+        debug=True
+    )