wip

app.py

@@ -8,39 +8,39 @@ from threading import Timer
 from functools import partial
 import time
 
+from huggingface_hub import InferenceClient
+from smolagents import ToolCollection, CodeAgent, InferenceClientModel
+
 MODEL = "Qwen/Qwen2.5-Coder-32B-Instruct"
 
-if os.environ.get("HF_TOKEN"):
-    from huggingface_hub import InferenceClient
-
-    client = InferenceClient(
-        provider="hf-inference",
-        api_key=os.environ["HF_TOKEN"],
-    )
-
-    def generate(promt, history, code, logs):
-        print(promt, history, code)
-        completion = client.chat.completions.create(
-            model=MODEL,
-            messages=[
-                {
-                    "role": "user",
-                    "content": promt
-                }
-            ],
-        )
-        return completion.choices[0].message
-else:
-    # we try to run on a ZERO GPU space
-    import spaces
-    from diffusers import DiffusionPipeline
+BUILD_SERVER_MCP_CONFIG = {"url": "https://agents-mcp-hackathon-gradio-motioncanvas-mcp-server.hf.space/gradio_api/mcp/sse", "transport": "sse"}
+DOCS_SERVER_MCP_CONFIG = {"url": "https://prathje-gradio-motioncanvas-docs-mcp-server.hf.space/gradio_api/mcp/sse", "transport": "sse"}
 
-    pipe = DiffusionPipeline.from_pretrained(MODEL)
-    pipe.to('cuda')
+all_tools = []
+with ToolCollection.from_mcp(BUILD_SERVER_MCP_CONFIG, trust_remote_code=True) as build_tool_collection:
+    with ToolCollection.from_mcp(DOCS_SERVER_MCP_CONFIG, trust_remote_code=True) as docs_tool_collection:
+        all_tools = build_tool_collection.tools + docs_tool_collection.tools
 
-    @spaces.GPU
-    def generate(promt, history, code, logs):
-        pass
+if os.environ.get("HF_TOKEN"):
+    
+    model = InferenceClientModel(model_id=MODEL)
+
+    agent = CodeAgent(tools=[*all_tools], model=model)
+
+    def generate(message, history, code, logs):
+        try:
+            res = agent.run(
+                "From the following prompt, generate code for a standalone motion canvas scene.tsx and build. You can browse the docs to help you.",
+                additional_args={'prompt': 'Please animate the formula for the area of a circle'}
+            )
+            print(res)
+        except Exception as e:
+            print(e)
+            return "An error occurred while generating the code", "", ""
+else:
+    print("No HF_TOKEN found, Zero GPU space not implemented")
+    def generate(message, history, code, logs):
+        return "LLM not available", "", ""
 
 
 

gradio_mcp_server.py

@@ -14,8 +14,7 @@ mcp = FastMCP("Gradio MCP Server")
 
 clients = {}
 
-BUILD_SERVER_SPACE_ID = "https://agents-mcp-hackathon-gradio-motioncanvas-mcp-server.hf.space/"
-DOCS_SERVER_SPACE_ID = "https://agents-mcp-hackathon-gradio-motioncanvas-docs-mcp-server.hf.space/"
+
 
 def get_client(space_id: str) -> Client:
     """Get or create a Gradio client for the specified space."""

requirements.txt

@@ -1,2 +1,4 @@
 gradio[mcp]
-gradio_motioncanvasplayer
+gradio_motioncanvasplayer
+huggingface_hub
+smolagents[mcp]