Update app.py

app.py

@@ -1,27 +1,22 @@
 import gradio as gr
 import json, time
-from pydantic import BaseModel
 from huggingface_hub import create_repo, upload_file, list_models, constants
 from huggingface_hub.utils import build_hf_headers, get_session, hf_raise_for_status
 from google import genai
 from google.genai.types import Tool, GenerateContentConfig, GoogleSearch
 
-# — JSON SPEC MODEL —
-
-class RepoSpec(BaseModel):
-    repo_name: str
-    files: dict[str, str]
-
 # — USER INFO & MODEL LISTING —
 
 def show_profile(profile: gr.OAuthProfile | None) -> str:
-    return f"✅ Logged in as **{profile.username}**" if profile else "*Not logged in.*"
+    if profile is None:
+        return "*Not logged in.*"
+    return f"✅ Logged in as **{profile.username}**"
 
 def list_private_models(
     profile: gr.OAuthProfile | None,
     oauth_token: gr.OAuthToken | None
 ) -> str:
-    if not (profile and oauth_token):
+    if profile is None or oauth_token is None:
         return "Please log in to see your models."
     models = [
         f"{m.id} ({'private' if m.private else 'public'})"
@@ -29,7 +24,7 @@ def list_private_models(
     ]
     return "No models found." if not models else "Models:\n\n" + "\n - ".join(models)
 
-# — LOG FETCHING —
+# — HELPERS FOR HF SPACE LOGS —
 
 def _get_space_jwt(repo_id: str):
     url = f"{constants.ENDPOINT}/api/spaces/{repo_id}/jwt"
@@ -39,79 +34,90 @@ def _get_space_jwt(repo_id: str):
 
 def fetch_logs(repo_id: str, level: str):
     jwt = _get_space_jwt(repo_id)
-    url = f"https://api.hf.space/v1/{repo_id}/logs/{level}"
+    logs_url = f"https://api.hf.space/v1/{repo_id}/logs/{level}"
     lines = []
-    with get_session().get(url, headers=build_hf_headers(token=jwt), stream=True) as resp:
+    with get_session().get(logs_url, headers=build_hf_headers(token=jwt), stream=True) as resp:
         hf_raise_for_status(resp)
         for raw in resp.iter_lines():
             if raw.startswith(b"data: "):
                 try:
                     ev = json.loads(raw[len(b"data: "):].decode())
-                    lines.append(f"[{ev.get('timestamp','')}] {ev.get('data','')}")
+                    ts  = ev.get("timestamp","")
+                    txt = ev.get("data","")
+                    lines.append(f"[{ts}] {txt}")
                 except:
                     continue
     return "\n".join(lines)
 
-# — CORE LOOP: ASK LLM FOR JSON, WRITE & DEPLOY —
+# — CORE LOOP: send prompt & (iteratively) deploy —
 
 def handle_user_message(
     history,               # list of {"role","content"} dicts
-    user_prompt: str,
     sdk_choice: str,
     gemini_api_key: str,
     grounding_enabled: bool,
     profile: gr.OAuthProfile | None,
     oauth_token: gr.OAuthToken | None
 ):
-    if not (profile and oauth_token):
+    if profile is None or oauth_token is None:
         return history + [{"role":"assistant","content":"⚠️ Please log in first."}], "", "", "<p>No Space yet.</p>"
 
     client = genai.Client(api_key=gemini_api_key)
-
-    system_msg = {
+    chat   = [{
         "role":"system",
         "content":(
-            "Return exactly one JSON object matching this schema:\n"
-            "  • repo_name (string)\n"
-            "  • files (object mapping filename→file-content)\n\n"
-            "Files must include:\n"
-            "  - A code file (default name: app.py unless you choose otherwise)\n"
-            "  - requirements.txt with dependencies\n"
-            "  - README.md with frontmatter (title, emoji, sdk, sdk_version, app_file)\n\n"
-            "Do NOT output any extra text—only the JSON object."
+            f"You are an AI assistant writing a HuggingFace Space using the "
+            f"{sdk_choice} SDK. After producing code, wait for logs; if errors appear, fix them."
         )
-    }
+    }] + history
 
-    chat = [system_msg] + history + [{"role":"user", "content":user_prompt}]
-    repo_id = None
-    build_logs = run_logs = ""
+    code_fn   = "app.py" if sdk_choice=="gradio" else "streamlit_app.py"
+    readme_fn = "README.md"
+    reqs_fn   = "requirements.txt"
+    repo_id   = f"{profile.username}/{profile.username}-auto-space"
 
+    build_logs = run_logs = ""
     for _ in range(5):
-        # detect SDK version
-        if sdk_choice == "gradio":
-            import gradio as _gr; sdk_version = _gr.__version__
-        else:
-            import streamlit as _st; sdk_version = _st.__version__
-
-        tools = [Tool(google_search=GoogleSearch())] if grounding_enabled else []
-        cfg = GenerateContentConfig(
-            tools=tools,
-            response_modalities=["TEXT"],
-            response_mime_type="application/json",
-            response_schema=RepoSpec    # <<< use the Pydantic model here
-        )
+        tools = []
+        if grounding_enabled:
+            tools.append(Tool(google_search=GoogleSearch()))
+        cfg = GenerateContentConfig(tools=tools, response_modalities=["TEXT"])
 
         resp = client.models.generate_content(
             model="gemini-2.5-flash-preview-04-17",
             contents=[m["content"] for m in chat],
             config=cfg
         )
-        # validate & parse
-        spec = RepoSpec.model_validate_json(resp.text)
-        repo_name = spec.repo_name
-        files     = spec.files
-
-        repo_id = f"{profile.username}/{repo_name}"
+        code = resp.text
+        chat.append({"role":"assistant","content":code})
+
+        # write code file
+        with open(code_fn, "w") as f:
+            f.write(code)
+
+        # write README.md
+        with open(readme_fn, "w") as f:
+            f.write(f"""---
+title: Wuhp Auto Space
+emoji: 🐢
+colorFrom: red
+colorTo: pink
+sdk: {sdk_choice}
+sdk_version: 1.44.1
+app_file: {code_fn}
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+""")
+
+        # write requirements.txt
+        base_reqs = "pandas\n"
+        extra     = "streamlit\n" if sdk_choice=="streamlit" else "gradio\n"
+        with open(reqs_fn, "w") as f:
+            f.write(base_reqs + extra)
+
+        # deploy all three files
         create_repo(
             repo_id=repo_id,
             token=oauth_token.token,
@@ -119,13 +125,7 @@ def handle_user_message(
             repo_type="space",
             space_sdk=sdk_choice
         )
-
-        # write & upload files
-        for fn, content in files.items():
-            if fn.lower() == "readme.md":
-                content = content.replace("<SDK_VERSION>", sdk_version)
-            with open(fn, "w") as f:
-                f.write(content)
+        for fn in (code_fn, readme_fn, reqs_fn):
             upload_file(
                 path_or_fileobj=fn,
                 path_in_repo=fn,
@@ -136,6 +136,7 @@ def handle_user_message(
 
         build_logs = fetch_logs(repo_id, "build")
         run_logs   = fetch_logs(repo_id, "run")
+
         if "ERROR" not in build_logs.upper() and "ERROR" not in run_logs.upper():
             break
 
@@ -144,12 +145,12 @@ def handle_user_message(
             "content":(
                 f"Build logs:\n{build_logs}\n\n"
                 f"Run logs:\n{run_logs}\n\n"
-                "Please fix the JSON spec and return updated JSON only."
+                "Please fix the code."
             )
         })
         time.sleep(2)
 
-    messages = [{"role":m["role"], "content":m["content"]} for m in chat if m["role"]!="system"]
+    messages = [{"role":m["role"],"content":m["content"]} for m in chat if m["role"]!="system"]
     iframe   = f'<iframe src="https://huggingface.co/spaces/{repo_id}" width="100%" height="500px"></iframe>'
     return messages, build_logs, run_logs, iframe
 
@@ -157,33 +158,39 @@ def handle_user_message(
 
 with gr.Blocks(title="HF Space Auto‑Builder") as demo:
     gr.Markdown("## Sign in + Auto‑Build Spaces\n\n"
-                "1. Sign in   2. Prompt   3. Deploy & Debug\n\n"
-                "_LLM controls filenames, code, README, requirements, and loops until successful._\n\n---")
+                "1. Sign in\n2. Enter your prompt\n3. Watch code, README, requirements, logs, and preview\n\n---")
 
+    # LOGIN & MODEL LISTING
     login_btn = gr.LoginButton(variant="huggingface", size="lg")
     status_md = gr.Markdown("*Not logged in.*")
     models_md = gr.Markdown()
-    demo.load(show_profile,        None, status_md)
-    demo.load(list_private_models, None, models_md)
-    login_btn.click(show_profile,        None, status_md)
-    login_btn.click(list_private_models, None, models_md)
 
-    sdk_choice = gr.Radio(["gradio","streamlit"], "gradio", label="SDK")
+    # Implicitly injects profile (and token) when calling these
+    demo.load(show_profile,        inputs=None, outputs=status_md)
+    demo.load(list_private_models, inputs=None, outputs=models_md)
+    login_btn.click(show_profile,        inputs=None, outputs=status_md)
+    login_btn.click(list_private_models, inputs=None, outputs=models_md)
+
+    # CONTROLS
+    sdk_choice = gr.Radio(["gradio","streamlit"], value="gradio", label="SDK template")
     api_key    = gr.Textbox(label="Gemini API Key", type="password")
-    grounding  = gr.Checkbox(label="Enable grounding")
+    grounding  = gr.Checkbox(label="Enable grounding", value=False)
 
+    # CHAT + OUTPUTS
     chatbot   = gr.Chatbot(type="messages")
-    user_in   = gr.Textbox(label="Prompt", placeholder="e.g. Build a CSV inspector…")
+    user_in   = gr.Textbox(placeholder="Your prompt…", label="Prompt")
     send_btn  = gr.Button("Send")
-    build_box = gr.Textbox(label="Build logs", lines=5)
-    run_box   = gr.Textbox(label="Run logs",   lines=5)
+
+    build_box = gr.Textbox(label="Build logs", lines=5, interactive=False)
+    run_box   = gr.Textbox(label="Run logs",   lines=5, interactive=False)
     preview   = gr.HTML("<p>No Space yet.</p>")
 
+    # Only user inputs here—profile/token are auto‑injected
     send_btn.click(
         fn=handle_user_message,
-        inputs=[chatbot, user_in, sdk_choice, api_key, grounding],
+        inputs=[chatbot, sdk_choice, api_key, grounding],
         outputs=[chatbot, build_box, run_box, preview]
     )
 
-if __name__ == "__main__":
+if __name__=="__main__":
     demo.launch()