From 76d6f3497651dbf8572ea439ece14648376341b3 Mon Sep 17 00:00:00 2001
From: openmindev <147775420+openminddev@users.noreply.github.com>
Date: Tue, 7 Apr 2026 16:28:34 -0700
Subject: [PATCH 01/10] Add OpenAI-compatible API, client, and benchmarks

Convert server to an OpenAI-compatible API (/v1/chat/completions and /v1/models) that returns tool_calls for robot_action and show_emotion; update request/response models and usage/usage estimation. Add an examples/chat_client_openai.py client and reorganize benchmark tooling into a benchmarks/ directory with README and updated multilingual/server benchmarks to call the new OpenAI-style endpoint. Move scripts and data into scripts/ and data/ directories, remove legacy chat_client files, and rename docker/Dockerfile.functiongemma -> docker/Dockerfile. Update README with OpenAI-compatible usage and testing notes and adjust CI workflow to use the new Docker image name and Dockerfile path.
---
 .github/workflows/release.yml                 |   4 +-
 .../benchmark-g1-server-multilingual.py       |  53 ++--
 .../benchmark-g1-server.py                    |  47 +++-
 benchmark-g1.py => benchmarks/benchmark-g1.py |   0
 chat_client-multilingual.py                   |  34 ---
 chat_client.py                                |  33 ---
 train-g1.jsonl => data/train-g1.jsonl         |   0
 .../{Dockerfile.functiongemma => Dockerfile}  |   0
 examples/chat_client_openai.py                | 132 +++++++++
 readme.md                                     | 110 +++++++-
 chat-g1.py => scripts/chat-g1.py              |   0
 train-g1.py => scripts/train-g1.py            |   0
 src/functiongemma/server.py                   | 262 ++++++++++--------
 13 files changed, 440 insertions(+), 235 deletions(-)
 rename benchmark-g1-server-multilingual.py => benchmarks/benchmark-g1-server-multilingual.py (85%)
 rename benchmark-g1-server.py => benchmarks/benchmark-g1-server.py (52%)
 rename benchmark-g1.py => benchmarks/benchmark-g1.py (100%)
 delete mode 100644 chat_client-multilingual.py
 delete mode 100644 chat_client.py
 rename train-g1.jsonl => data/train-g1.jsonl (100%)
 rename docker/{Dockerfile.functiongemma => Dockerfile} (100%)
 create mode 100644 examples/chat_client_openai.py
 rename chat-g1.py => scripts/chat-g1.py (100%)
 rename train-g1.py => scripts/train-g1.py (100%)

diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index c60726e..93123ce 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -30,7 +30,7 @@ jobs:
         id: meta
         uses: docker/metadata-action@v5
         with:
-          images: openmindagi/functiongemma-service
+          images: openmindagi/functiongemma_service
           tags: |
             type=semver,pattern={{version}},prefix=v
             type=semver,pattern={{major}}.{{minor}},prefix=v
@@ -42,7 +42,7 @@ jobs:
         uses: docker/build-push-action@v5
         with:
           context: .
-          file: ./docker/Dockerfile.functiongemma
+          file: ./docker/Dockerfile
           push: true
           platforms: linux/arm64
           tags: ${{ steps.meta.outputs.tags }}
diff --git a/benchmark-g1-server-multilingual.py b/benchmarks/benchmark-g1-server-multilingual.py
similarity index 85%
rename from benchmark-g1-server-multilingual.py
rename to benchmarks/benchmark-g1-server-multilingual.py
index 23c21cc..c285b88 100644
--- a/benchmark-g1-server-multilingual.py
+++ b/benchmarks/benchmark-g1-server-multilingual.py
@@ -1,9 +1,10 @@
 """
-Benchmark the FunctionGemma server (multilingual).
+Benchmark the FunctionGemma server (multilingual) using OpenAI-compatible API.
 Usage: python3 benchmark-g1-server.py [--url http://localhost:8200]
 """
 
 import argparse
+import json
 import time
 
 import requests
@@ -95,7 +96,13 @@ def main():
     # Warmup
     print("Warming up...")
     for _ in range(3):
-        requests.post(f"{args.url}/predict", json={"text": "hello"})
+        requests.post(
+            f"{args.url}/v1/chat/completions",
+            json={
+                "model": "functiongemma-finetuned-g1",
+                "messages": [{"role": "user", "content": "hello"}],
+            },
+        )
     print("Done!\n")
 
     # Benchmark
@@ -104,14 +111,33 @@ def main():
 
     for t in TESTS:
         start = time.time()
-        r = requests.post(f"{args.url}/predict", json={"text": t["text"]})
+        r = requests.post(
+            f"{args.url}/v1/chat/completions",
+            json={
+                "model": "functiongemma-finetuned-g1",
+                "messages": [{"role": "user", "content": t["text"]}],
+            },
+        )
         total_ms = (time.time() - start) * 1000
 
         data = r.json()
-        inference_ms = data["latency_ms"]
+
+        # Extract action and emotion from tool_calls
+        tool_calls = data["choices"][0]["message"]["tool_calls"]
+        action = None
+        emotion = None
+        for tc in tool_calls:
+            func_name = tc["function"]["name"]
+            args = json.loads(tc["function"]["arguments"])
+            if func_name == "robot_action":
+                action = args["action_name"]
+            elif func_name == "show_emotion":
+                emotion = args["emotion"]
+
+        inference_ms = total_ms - 10  # Rough estimate
         lang = t["lang"]
         expected = t["action"]
-        correct = data["action"] == expected
+        correct = action == expected
         status = "✓" if correct else "✗"
 
         if lang not in lang_stats:
@@ -124,7 +150,7 @@ def main():
 
         print(
             f"  {lang} {status} {inference_ms:5.0f}ms inf | {total_ms:5.0f}ms total | "
-            f"{t['text']:<35s} expect={expected:<16s} got={data['action']:<16s} {data['emotion']}"
+            f"{t['text']:<35s} expect={expected:<16s} got={action:<16s} {emotion}"
         )
 
     # Latency
@@ -158,19 +184,8 @@ def main():
         bar = "█" * int(pct / 5) + "░" * (20 - int(pct / 5))
         print(f"  {name:<10s} {bar} {stats['correct']}/{stats['total']} ({pct:.0f}%)")
 
-    # Batch test
-    all_texts = [t["text"] for t in TESTS]
-    print(f"\n{'=' * 70}")
-    print(f"BATCH TEST ({len(all_texts)} inputs)")
-    print(f"{'=' * 70}")
-    start = time.time()
-    r = requests.post(f"{args.url}/predict_batch", json={"texts": all_texts})
-    total_ms = (time.time() - start) * 1000
-    data = r.json()
-    print(f"  Inference: {data['total_latency_ms']:.0f}ms")
-    print(f"  Total:     {total_ms:.0f}ms (with network)")
-    print(f"  Per input: {data['total_latency_ms']/len(all_texts):.0f}ms avg inference")
+    print()  # Final newline
 
 
 if __name__ == "__main__":
-    main()
\ No newline at end of file
+    main()
diff --git a/benchmark-g1-server.py b/benchmarks/benchmark-g1-server.py
similarity index 52%
rename from benchmark-g1-server.py
rename to benchmarks/benchmark-g1-server.py
index 00b01cf..6382b48 100644
--- a/benchmark-g1-server.py
+++ b/benchmarks/benchmark-g1-server.py
@@ -1,9 +1,10 @@
 """
-Benchmark the FunctionGemma server.
+Benchmark the FunctionGemma server using OpenAI-compatible API.
 Usage: python3 benchmark_client.py [--url http://localhost:8200]
 """
 
 import argparse
+import json
 import time
 
 import requests
@@ -39,7 +40,13 @@ def main():
     # Warmup
     print("Warming up...")
     for _ in range(3):
-        requests.post(f"{args.url}/predict", json={"text": "hello"})
+        requests.post(
+            f"{args.url}/v1/chat/completions",
+            json={
+                "model": "functiongemma-finetuned-g1",
+                "messages": [{"role": "user", "content": "hello"}],
+            },
+        )
     print("Done!\n")
 
     # Benchmark
@@ -47,15 +54,35 @@ def main():
     times = []
     for t in TESTS:
         start = time.time()
-        r = requests.post(f"{args.url}/predict", json={"text": t})
+        r = requests.post(
+            f"{args.url}/v1/chat/completions",
+            json={
+                "model": "functiongemma-finetuned-g1",
+                "messages": [{"role": "user", "content": t}],
+            },
+        )
         total_ms = (time.time() - start) * 1000
 
         data = r.json()
-        inference_ms = data["latency_ms"]
+
+        # Extract action and emotion from tool_calls
+        tool_calls = data["choices"][0]["message"]["tool_calls"]
+        action = None
+        emotion = None
+        for tc in tool_calls:
+            func_name = tc["function"]["name"]
+            args = json.loads(tc["function"]["arguments"])
+            if func_name == "robot_action":
+                action = args["action_name"]
+            elif func_name == "show_emotion":
+                emotion = args["emotion"]
+
+        # Estimate inference time (total - network overhead estimate)
+        inference_ms = total_ms - 10  # Rough estimate
         times.append(inference_ms)
 
         print(
-            f"  {inference_ms:5.0f}ms inference | {total_ms:5.0f}ms total | {t:<30s} -> {data['action']:<16s} {data['emotion']}"
+            f"  {inference_ms:5.0f}ms inference | {total_ms:5.0f}ms total | {t:<30s} -> {action:<16s} {emotion}"
         )
 
     print("\n--- Inference (model only) ---")
@@ -63,16 +90,6 @@ def main():
     print(f"Max:     {max(times):.0f}ms")
     print(f"Average: {sum(times)/len(times):.0f}ms")
 
-    # Batch test
-    print(f"\n--- Batch test ({len(TESTS)} inputs) ---")
-    start = time.time()
-    r = requests.post(f"{args.url}/predict_batch", json={"texts": TESTS})
-    total_ms = (time.time() - start) * 1000
-    data = r.json()
-    print(
-        f"Total:   {data['total_latency_ms']:.0f}ms inference | {total_ms:.0f}ms with network"
-    )
-
 
 if __name__ == "__main__":
     main()
diff --git a/benchmark-g1.py b/benchmarks/benchmark-g1.py
similarity index 100%
rename from benchmark-g1.py
rename to benchmarks/benchmark-g1.py
diff --git a/chat_client-multilingual.py b/chat_client-multilingual.py
deleted file mode 100644
index 327c698..0000000
--- a/chat_client-multilingual.py
+++ /dev/null
@@ -1,34 +0,0 @@
-"""
-Chat with the FunctionGemma server (multilingual).
-Usage: python3 chat_client.py [--url http://localhost:8200]
-"""
-
-import argparse
-
-import requests
-
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--url", default="http://localhost:8200")
-    args = parser.parse_args()
-
-    print(f"Connected to {args.url}")
-    print(f"Actions: {requests.get(f'{args.url}/actions').json()}")
-    print("Supports: English, 中文, 日本語, Français, Deutsch, Español")
-    print("Type 'quit' to exit.\n")
-
-    while True:
-        text = input("You: ").strip()
-        if text.lower() in ("quit", "exit", "q"):
-            break
-
-        r = requests.post(f"{args.url}/predict", json={"text": text})
-        data = r.json()
-        print(
-            f"Robot ({data['latency_ms']:.0f}ms): action={data['action']}  emotion={data['emotion']}\n"
-        )
-
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/chat_client.py b/chat_client.py
deleted file mode 100644
index 33ca58d..0000000
--- a/chat_client.py
+++ /dev/null
@@ -1,33 +0,0 @@
-"""
-Chat with the FunctionGemma server.
-Usage: python3 chat_client.py [--url http://localhost:8200]
-"""
-
-import argparse
-
-import requests
-
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--url", default="http://localhost:8200")
-    args = parser.parse_args()
-
-    print(f"Connected to {args.url}")
-    print(f"Actions: {requests.get(f'{args.url}/actions').json()}")
-    print()
-
-    while True:
-        text = input("You: ").strip()
-        if text.lower() in ("quit", "exit", "q"):
-            break
-
-        r = requests.post(f"{args.url}/predict", json={"text": text})
-        data = r.json()
-        print(
-            f"Robot ({data['latency_ms']:.0f}ms): action={data['action']}  emotion={data['emotion']}\n"
-        )
-
-
-if __name__ == "__main__":
-    main()
diff --git a/train-g1.jsonl b/data/train-g1.jsonl
similarity index 100%
rename from train-g1.jsonl
rename to data/train-g1.jsonl
diff --git a/docker/Dockerfile.functiongemma b/docker/Dockerfile
similarity index 100%
rename from docker/Dockerfile.functiongemma
rename to docker/Dockerfile
diff --git a/examples/chat_client_openai.py b/examples/chat_client_openai.py
new file mode 100644
index 0000000..f63ba01
--- /dev/null
+++ b/examples/chat_client_openai.py
@@ -0,0 +1,132 @@
+"""
+OpenAI-compatible client for FunctionGemma robot-action server.
+
+Demonstrates how to use the /v1/chat/completions endpoint with OpenAI SDK
+or standard HTTP requests.
+"""
+
+import json
+import requests
+
+# Can also use: from openai import OpenAI
+
+SERVER_URL = "http://localhost:8200"
+
+
+def test_with_requests():
+    """Test using standard HTTP requests."""
+    print("Testing with requests library...")
+    print("-" * 60)
+
+    test_commands = [
+        "Hello! Nice to meet you!",
+        "Can you wave at me?",
+        "Show me you're thinking",
+        "I'm confused about something",
+    ]
+
+    for command in test_commands:
+        response = requests.post(
+            f"{SERVER_URL}/v1/chat/completions",
+            json={
+                "model": "functiongemma-finetuned-g1",
+                "messages": [{"role": "user", "content": command}],
+            },
+        )
+
+        if response.status_code == 200:
+            data = response.json()
+            print(f"\n📝 User: {command}")
+            print(f"🤖 Model: {data['model']}")
+
+            choice = data["choices"][0]
+            if choice.get("message", {}).get("tool_calls"):
+                print("🔧 Tool Calls:")
+                for tool_call in choice["message"]["tool_calls"]:
+                    func_name = tool_call["function"]["name"]
+                    func_args = json.loads(tool_call["function"]["arguments"])
+                    print(f"   • {func_name}({func_args})")
+
+            usage = data.get("usage", {})
+            print(
+                f"📊 Tokens: {usage.get('prompt_tokens')} prompt + "
+                f"{usage.get('completion_tokens')} completion = "
+                f"{usage.get('total_tokens')} total"
+            )
+        else:
+            print(f"❌ Error: {response.status_code} - {response.text}")
+
+    print("\n" + "=" * 60)
+
+
+def test_with_openai_sdk():
+    """Test using OpenAI Python SDK (if installed)."""
+    try:
+        from openai import OpenAI
+
+        print("\nTesting with OpenAI SDK...")
+        print("-" * 60)
+
+        # Initialize client pointing to local server
+        client = OpenAI(
+            base_url=f"{SERVER_URL}/v1",
+            api_key="dummy-key",  # Not validated, but required by SDK
+        )
+
+        response = client.chat.completions.create(
+            model="functiongemma-finetuned-g1",
+            messages=[
+                {"role": "user", "content": "Wave your hand and show excitement!"}
+            ],
+        )
+
+        print(f"\n📝 User: Wave your hand and show excitement!")
+        print(f"🤖 Model: {response.model}")
+
+        choice = response.choices[0]
+        if choice.message.tool_calls:
+            print("🔧 Tool Calls:")
+            for tool_call in choice.message.tool_calls:
+                print(
+                    f"   • {tool_call.function.name}"
+                    f"({tool_call.function.arguments})"
+                )
+
+        print(f"📊 Tokens: {response.usage.prompt_tokens} prompt + "
+              f"{response.usage.completion_tokens} completion = "
+              f"{response.usage.total_tokens} total")
+
+        print("\n" + "=" * 60)
+
+    except ImportError:
+        print(
+            "\n⚠️  OpenAI SDK not installed. Install with: pip install openai\n"
+        )
+
+
+def list_models():
+    """List available models."""
+    print("\nAvailable Models:")
+    print("-" * 60)
+
+    response = requests.get(f"{SERVER_URL}/v1/models")
+    if response.status_code == 200:
+        data = response.json()
+        for model in data["data"]:
+            print(f"• {model['id']} (owned by {model['owned_by']})")
+    else:
+        print(f"❌ Error: {response.status_code}")
+
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    print("\n" + "=" * 60)
+    print("FunctionGemma Robot Action - OpenAI Compatible Client")
+    print("=" * 60)
+
+    list_models()
+    test_with_requests()
+    test_with_openai_sdk()
+
+    print("\n✅ Testing complete!")
diff --git a/readme.md b/readme.md
index aa78044..a21ebaf 100644
--- a/readme.md
+++ b/readme.md
@@ -19,6 +19,66 @@ The model takes a user's voice/text input and outputs:
 
 For general questions or conversation, the robot defaults to `stand_still` with an appropriate emotion.
 
+## OpenAI-Compatible API
+
+The server provides OpenAI-compatible endpoints, allowing you to use the OpenAI SDK or any OpenAI-compatible client:
+
+### Endpoints
+
+| Endpoint | Method | Description |
+|----------|--------|-------------|
+| `/v1/chat/completions` | POST | Chat endpoint with tool calls in OpenAI format |
+| `/v1/models` | GET | List available models |
+| `/actions` | GET | List supported actions and emotions |
+| `/health` | GET | Health check |
+
+### Example with OpenAI SDK
+
+```python
+from openai import OpenAI
+
+# Point to your local server
+client = OpenAI(
+    base_url="http://localhost:8200/v1",
+    api_key="dummy-key"  # Not validated
+)
+
+response = client.chat.completions.create(
+    model="functiongemma-finetuned-g1",
+    messages=[
+        {"role": "user", "content": "Wave at me!"}
+    ]
+)
+
+# Response includes tool_calls
+for tool_call in response.choices[0].message.tool_calls:
+    print(f"{tool_call.function.name}: {tool_call.function.arguments}")
+# Output:
+# robot_action: {"action_name": "face_wave"}
+# show_emotion: {"emotion": "happy"}
+```
+
+### Example with HTTP Requests
+
+```bash
+curl -X POST http://localhost:8200/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "functiongemma-finetuned-g1",
+    "messages": [
+      {"role": "user", "content": "Hello! Nice to meet you!"}
+    ]
+  }'
+```
+
+### Testing
+
+Run the OpenAI-compatible test client:
+
+```bash
+python3 chat_client_openai.py
+```
+
 ## Supported Actions
 
 | Action | Description |
@@ -53,15 +113,30 @@ Benchmarked on NVIDIA Jetson AGX Thor with constrained decoding (`benchmark.py`)
 
 The constrained decoding approach reduces autoregressive generation from ~33 tokens down to 2 forward passes (one for action, one for emotion), achieving ~18x speedup over standard `model.generate()`.
 
-## Files
+## Project Structure
 
-| File | Description |
-|------|-------------|
-| `train.py` | Fine-tuning script (LoRA on FunctionGemma 270M) |
-| `remerge.py` | Re-merge LoRA adapter with vocab size fix |
-| `chat.py` | Interactive chat using standard generation |
-| `benchmark.py` | Constrained decoding benchmark |
-| `train-g1.jsonl` | Training data (545 examples) |
+```
+functiongemma-robot-action/
+├── src/
+│   └── functiongemma/
+│       ├── __init__.py
+│       └── server.py          # FastAPI server with OpenAI-compatible API
+├── scripts/
+│   ├── train-g1.py            # Fine-tuning script (LoRA on FunctionGemma 270M)
+│   └── chat-g1.py             # Interactive chat using standard generation
+├── benchmarks/
+│   ├── benchmark-g1.py        # Constrained decoding benchmark (local)
+│   ├── benchmark-g1-server.py # Benchmark against server API
+│   └── benchmark-g1-server-multilingual.py  # Multilingual benchmark
+├── examples/
+│   └── chat_client_openai.py  # OpenAI-compatible client for testing
+├── data/
+│   └── train-g1.jsonl         # Training data (545 examples)
+├── docker/
+│   └── Dockerfile.functiongemma
+├── docker-compose.yml
+└── readme.md
+```
 
 ## Training
 
@@ -91,7 +166,7 @@ cd functiongemma-robot-actions
 ### 2. Download the model
 
 Download the functionGemma-finetuned-g1 model to the repo directory:
-1. Huggingface: OpenmindAGI/functiongemma-finetuned-g1 (English Primary MOdel)
+1. Huggingface: OpenmindAGI/functiongemma-finetuned-g1 (English Primary Model)
 2. Huggingface: OpenmindAGI/functiongemma-finetuned-g1-multilingual (supports English, Japanese, Chinese, French, German, Spanish)
 
 Place it so the directory structure looks like:
@@ -118,14 +193,19 @@ pip install torch transformers accelerate
 ### 4. Run benchmark
 
 ```bash
-python3 benchmark-g1.py
-python3 benchmark-g1-server.py # if docker env already launched the server
+python3 benchmarks/benchmark-g1.py  # Local benchmark
+python3 benchmarks/benchmark-g1-server.py  # Benchmark against running server
+python3 benchmarks/benchmark-g1-server-multilingual.py  # Test multilingual support
+```
+
+### 5. Test with OpenAI-compatible client
+
+```bash
+python3 examples/chat_client_openai.py
 ```
 
-### 5. Interactive chat
+Or use the interactive local chat:
 
 ```bash
-python3 chat-g1.py
-python3 chat-client.py # if docker env already launched the server
-# Use multilingual version for multiple language supports!
+python3 scripts/chat-g1.py
 ```
diff --git a/chat-g1.py b/scripts/chat-g1.py
similarity index 100%
rename from chat-g1.py
rename to scripts/chat-g1.py
diff --git a/train-g1.py b/scripts/train-g1.py
similarity index 100%
rename from train-g1.py
rename to scripts/train-g1.py
diff --git a/src/functiongemma/server.py b/src/functiongemma/server.py
index b507e28..849daa1 100644
--- a/src/functiongemma/server.py
+++ b/src/functiongemma/server.py
@@ -5,14 +5,14 @@
 Uses constrained decoding (2 forward passes instead of 33 autoregressive
 steps) for ~59 ms average latency on Thor.
 
-Endpoints
----------
-POST /predict
-    Convert natural language to robot action + emotion function calls.
-POST /predict_batch
-    Batch prediction for multiple inputs.
+OpenAI-Compatible API
+---------------------
+POST /v1/chat/completions
+    Chat endpoint with function/tool calls in OpenAI format.
+GET  /v1/models
+    List available models.
 GET  /actions
-    List supported actions and emotions.
+    List supported robot actions and emotions.
 GET  /health
     Health check.
 """
@@ -20,10 +20,12 @@
 import json
 import logging
 import time
+import uuid
+from typing import Literal, Optional
 
 import torch
 from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 logging.basicConfig(
@@ -83,69 +85,66 @@
 valid_emotion_first_tokens: set[int] = set()
 
 
-# Request/Response Models
-class PredictRequest(BaseModel):
-    """
-    Request body for single prediction.
+# OpenAI-Compatible Request/Response Models
+class ChatMessage(BaseModel):
+    """OpenAI chat message format."""
 
-    Attributes
-    ----------
-    text : str
-        Natural language command or conversation input.
-    """
+    role: Literal["system", "user", "assistant", "tool"]
+    content: Optional[str] = None
+    tool_calls: Optional[list[dict]] = None
 
-    text: str
 
+class ChatCompletionRequest(BaseModel):
+    """OpenAI /v1/chat/completions request format."""
 
-class PredictResponse(BaseModel):
-    """
-    Response body for single prediction.
+    model: str = "functiongemma-finetuned-g1"
+    messages: list[ChatMessage]
+    temperature: Optional[float] = Field(default=1.0, ge=0, le=2)
+    max_tokens: Optional[int] = None
+    stream: bool = False
 
-    Attributes
-    ----------
-    action : str
-        Robot action to perform (e.g. ``"shake_hand"``).
-    emotion : str
-        Emotion to display on avatar screen (e.g. ``"happy"``).
-    latency_ms : float
-        Model inference latency in milliseconds (excludes network I/O).
-    """
 
-    action: str
-    emotion: str
-    latency_ms: float
+class ToolCall(BaseModel):
+    """OpenAI tool call format."""
 
+    id: str
+    type: Literal["function"] = "function"
+    function: dict  # {name: str, arguments: str (JSON)}
 
-class BatchPredictRequest(BaseModel):
-    """
-    Request body for batch prediction.
 
-    Attributes
-    ----------
-    texts : list of str
-        List of natural language inputs to process.
-    """
+class ChatCompletionMessage(BaseModel):
+    """OpenAI response message format."""
 
-    texts: list[str]
+    role: Literal["assistant"]
+    content: Optional[str] = None
+    tool_calls: Optional[list[ToolCall]] = None
 
 
-class BatchPredictResponse(BaseModel):
-    """
-    Response body for batch prediction.
+class ChatCompletionChoice(BaseModel):
+    """OpenAI choice format."""
+
+    index: int
+    message: ChatCompletionMessage
+    finish_reason: Literal["stop", "tool_calls"]
 
-    Attributes
-    ----------
-    results : list of PredictResponse
-        One result per input text.
-    count : int
-        Number of results returned.
-    total_latency_ms : float
-        Total inference latency in milliseconds.
-    """
 
-    results: list[PredictResponse]
-    count: int
-    total_latency_ms: float
+class UsageInfo(BaseModel):
+    """OpenAI usage statistics."""
+
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
+
+
+class ChatCompletionResponse(BaseModel):
+    """OpenAI /v1/chat/completions response format."""
+
+    id: str
+    object: Literal["chat.completion"] = "chat.completion"
+    created: int
+    model: str
+    choices: list[ChatCompletionChoice]
+    usage: UsageInfo
 
 
 def build_prompt(user_input: str) -> str:
@@ -278,27 +277,43 @@ def load_model():
     logger.info("Model ready!")
 
 
-@app.post("/predict", response_model=PredictResponse)
-def predict(req: PredictRequest):
+@app.post("/v1/chat/completions", response_model=ChatCompletionResponse)
+def chat_completions(req: ChatCompletionRequest):
     """
-    Convert natural language input to action + emotion.
+    OpenAI-compatible chat completions endpoint.
+
+    Converts OpenAI format requests to FunctionGemma predictions and returns
+    results in OpenAI format with tool_calls.
 
     Parameters
     ----------
-    req : PredictRequest
-        Request body containing the text input.
+    req : ChatCompletionRequest
+        OpenAI-formatted request with messages array.
 
     Returns
     -------
-    PredictResponse
-        Chosen action, emotion, and inference latency.
+    ChatCompletionResponse
+        OpenAI-formatted response with tool calls for action and emotion.
     """
     if model is None:
         raise HTTPException(status_code=503, detail="Model not loaded.")
-    if not req.text.strip():
-        raise HTTPException(status_code=400, detail="Text cannot be empty.")
+    if req.stream:
+        raise HTTPException(status_code=400, detail="Streaming not supported.")
+
+    # Extract user message (last user message in conversation)
+    user_message = None
+    for msg in reversed(req.messages):
+        if msg.role == "user" and msg.content:
+            user_message = msg.content
+            break
 
-    inputs = tokenizer(build_prompt(req.text), return_tensors="pt").to(model.device)
+    if not user_message:
+        raise HTTPException(status_code=400, detail="No user message found.")
+
+    # Run prediction
+    inputs = tokenizer(build_prompt(user_message), return_tensors="pt").to(
+        model.device
+    )
 
     if torch.cuda.is_available():
         torch.cuda.synchronize()
@@ -310,61 +325,58 @@ def predict(req: PredictRequest):
         torch.cuda.synchronize()
     latency = (time.perf_counter() - start) * 1000
 
+    # Build OpenAI-format response with tool calls
+    tool_calls = [
+        ToolCall(
+            id=f"call_{uuid.uuid4().hex[:24]}",
+            type="function",
+            function={
+                "name": "robot_action",
+                "arguments": json.dumps({"action_name": action}),
+            },
+        ),
+        ToolCall(
+            id=f"call_{uuid.uuid4().hex[:24]}",
+            type="function",
+            function={
+                "name": "show_emotion",
+                "arguments": json.dumps({"emotion": emotion}),
+            },
+        ),
+    ]
+
+    # Rough token estimate (more accurate would require actual tokenization)
+    prompt_tokens = len(inputs["input_ids"][0])
+    completion_tokens = 10  # Approximate for function calls
+
+    response = ChatCompletionResponse(
+        id=f"chatcmpl-{uuid.uuid4().hex[:24]}",
+        created=int(time.time()),
+        model=req.model,
+        choices=[
+            ChatCompletionChoice(
+                index=0,
+                message=ChatCompletionMessage(
+                    role="assistant", content=None, tool_calls=tool_calls
+                ),
+                finish_reason="tool_calls",
+            )
+        ],
+        usage=UsageInfo(
+            prompt_tokens=prompt_tokens,
+            completion_tokens=completion_tokens,
+            total_tokens=prompt_tokens + completion_tokens,
+        ),
+    )
+
     logger.info(
-        'predict | text="%s" | action=%s emotion=%s | %.0fms',
-        req.text[:50],
+        'chat_completions | text="%s" | action=%s emotion=%s | %.0fms',
+        user_message[:50],
         action,
         emotion,
         latency,
     )
-    return PredictResponse(action=action, emotion=emotion, latency_ms=round(latency, 1))
-
-
-@app.post("/predict_batch", response_model=BatchPredictResponse)
-def predict_batch(req: BatchPredictRequest):
-    """
-    Process multiple inputs with constrained decoding.
-
-    Parameters
-    ----------
-    req : BatchPredictRequest
-        Request body containing list of text inputs.
-
-    Returns
-    -------
-    BatchPredictResponse
-        List of results with total latency.
-    """
-    if model is None:
-        raise HTTPException(status_code=503, detail="Model not loaded.")
-
-    results = []
-    total_start = time.perf_counter()
-
-    for text in req.texts:
-        inputs = tokenizer(build_prompt(text), return_tensors="pt").to(model.device)
-
-        if torch.cuda.is_available():
-            torch.cuda.synchronize()
-        start = time.perf_counter()
-        action, emotion = generate_constrained(inputs["input_ids"])
-        if torch.cuda.is_available():
-            torch.cuda.synchronize()
-        latency = (time.perf_counter() - start) * 1000
-
-        results.append(
-            PredictResponse(
-                action=action, emotion=emotion, latency_ms=round(latency, 1)
-            )
-        )
-
-    total_latency = (time.perf_counter() - total_start) * 1000
-    logger.info(
-        "predict_batch | count=%d | total=%.0fms", len(req.texts), total_latency
-    )
-    return BatchPredictResponse(
-        results=results, count=len(results), total_latency_ms=round(total_latency, 1)
-    )
+    return response
 
 
 @app.get("/actions")
@@ -373,6 +385,22 @@ def actions():
     return {"actions": ACTIONS, "emotions": EMOTIONS}
 
 
+@app.get("/v1/models")
+def list_models():
+    """OpenAI-compatible models endpoint."""
+    return {
+        "object": "list",
+        "data": [
+            {
+                "id": "functiongemma-finetuned-g1",
+                "object": "model",
+                "created": 1704067200,
+                "owned_by": "openmind",
+            }
+        ],
+    }
+
+
 @app.get("/health")
 def health():
     """Health check endpoint."""

From ceeb689c6ac085160f7faa1c27b7b22d27180bd4 Mon Sep 17 00:00:00 2001
From: openmindev <147775420+openminddev@users.noreply.github.com>
Date: Tue, 7 Apr 2026 16:32:00 -0700
Subject: [PATCH 02/10] Update model paths and clean example imports

Adjust model and data paths and tidy example imports:

- examples/chat_client_openai.py: consolidate OpenAI SDK import at module level and remove redundant import/extra blank lines in test_with_openai_sdk.
- scripts/chat-g1.py: switch HF_MODEL to OpenmindAGI/functiongemma-finetuned-g1-multilingual (was wenjinf0811/functiongemma-robot-actions) and remove an outdated comment block.
- scripts/train-g1.py: point TRAIN_FILE to ./data/train-g1.jsonl and simplify the function definitions header.

These changes standardize model/data locations and clean up the example code for clarity.
---
 examples/chat_client_openai.py | 5 +----
 scripts/chat-g1.py             | 6 ++----
 scripts/train-g1.py            | 5 ++---
 3 files changed, 5 insertions(+), 11 deletions(-)

diff --git a/examples/chat_client_openai.py b/examples/chat_client_openai.py
index f63ba01..bc0578d 100644
--- a/examples/chat_client_openai.py
+++ b/examples/chat_client_openai.py
@@ -7,8 +7,7 @@
 
 import json
 import requests
-
-# Can also use: from openai import OpenAI
+from openai import OpenAI
 
 SERVER_URL = "http://localhost:8200"
 
@@ -62,8 +61,6 @@ def test_with_requests():
 def test_with_openai_sdk():
     """Test using OpenAI Python SDK (if installed)."""
     try:
-        from openai import OpenAI
-
         print("\nTesting with OpenAI SDK...")
         print("-" * 60)
 
diff --git a/scripts/chat-g1.py b/scripts/chat-g1.py
index 5cd7092..08d45ec 100644
--- a/scripts/chat-g1.py
+++ b/scripts/chat-g1.py
@@ -6,10 +6,8 @@
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-# ============================================================
-# Model source — works with both Hugging Face repo ID and local path
-# ============================================================
-HF_MODEL = "wenjinf0811/functiongemma-robot-actions"
+
+HF_MODEL = "OpenmindAGI/functiongemma-finetuned-g1-multilingual"
 LOCAL_MODEL = "./functionGemma-finetuned-g1"  # For Google Drive download
 
 ACTIONS = ["shake_hand", "face_wave", "hands_up", "stand_still", "show_hand"]
diff --git a/scripts/train-g1.py b/scripts/train-g1.py
index 21ab541..b3e9469 100644
--- a/scripts/train-g1.py
+++ b/scripts/train-g1.py
@@ -14,7 +14,7 @@
 
 # CONFIG
 BASE_MODEL = "google/functiongemma-270m-it"
-TRAIN_FILE = "train-g1.jsonl"  # Your training data
+TRAIN_FILE = "./data/train-g1.jsonl"
 OUTPUT_DIR = "./functiongemma-robot-actions"
 EPOCHS = 5
 BATCH_SIZE = 2
@@ -22,8 +22,7 @@
 MAX_SEQ_LENGTH = 512
 
 
-# FUNCTION DEFINITIONS (shared across all examples)
-# These define your robot's API surface
+# FUNCTION DEFINITIONS
 FUNCTION_DEFINITIONS = [
     {
         "name": "robot_action",

From 4ecbf7d40ee215c30c301d9a924b643580414639 Mon Sep 17 00:00:00 2001
From: openmindev <147775420+openminddev@users.noreply.github.com>
Date: Tue, 7 Apr 2026 16:35:05 -0700
Subject: [PATCH 03/10] Format code, refactor prints, add typos config

Add .typos.toml with a custom word entry and apply small style/formatting cleanups across the repo: reformat LANG_NAMES and language stats dict in benchmark, wrap long f-strings into multi-line prints, normalize newlines/imports and simplify some print calls in examples, remove an extra blank line in script, and collapse a tokenizer call onto a single line in the server. These changes are purely stylistic and improve readability without altering behavior.
---
 .typos.toml                                   |  4 ++++
 .../benchmark-g1-server-multilingual.py       | 23 +++++++++++++++----
 examples/chat_client_openai.py                | 15 ++++++------
 scripts/chat-g1.py                            |  1 -
 src/functiongemma/server.py                   |  4 +---
 5 files changed, 31 insertions(+), 16 deletions(-)
 create mode 100644 .typos.toml

diff --git a/.typos.toml b/.typos.toml
new file mode 100644
index 0000000..3f40733
--- /dev/null
+++ b/.typos.toml
@@ -0,0 +1,4 @@
+[default]
+
+[default.extend-words]
+deine = "deine"
diff --git a/benchmarks/benchmark-g1-server-multilingual.py b/benchmarks/benchmark-g1-server-multilingual.py
index c285b88..33f26bb 100644
--- a/benchmarks/benchmark-g1-server-multilingual.py
+++ b/benchmarks/benchmark-g1-server-multilingual.py
@@ -79,8 +79,12 @@
 ]
 
 LANG_NAMES = {
-    "en": "English", "zh": "Chinese", "ja": "Japanese",
-    "fr": "French", "de": "German", "es": "Spanish",
+    "en": "English",
+    "zh": "Chinese",
+    "ja": "Japanese",
+    "fr": "French",
+    "de": "German",
+    "es": "Spanish",
 }
 
 
@@ -141,7 +145,12 @@ def main():
         status = "✓" if correct else "✗"
 
         if lang not in lang_stats:
-            lang_stats[lang] = {"correct": 0, "total": 0, "inference": [], "network": []}
+            lang_stats[lang] = {
+                "correct": 0,
+                "total": 0,
+                "inference": [],
+                "network": [],
+            }
         lang_stats[lang]["total"] += 1
         lang_stats[lang]["inference"].append(inference_ms)
         lang_stats[lang]["network"].append(total_ms)
@@ -160,8 +169,12 @@ def main():
     print(f"\n{'=' * 70}")
     print("LATENCY")
     print(f"{'=' * 70}")
-    print(f"  Inference:  min={min(all_inf):.0f}ms  max={max(all_inf):.0f}ms  avg={sum(all_inf)/len(all_inf):.0f}ms")
-    print(f"  Total:      min={min(all_net):.0f}ms  max={max(all_net):.0f}ms  avg={sum(all_net)/len(all_net):.0f}ms")
+    print(
+        f"  Inference:  min={min(all_inf):.0f}ms  max={max(all_inf):.0f}ms  avg={sum(all_inf)/len(all_inf):.0f}ms"
+    )
+    print(
+        f"  Total:      min={min(all_net):.0f}ms  max={max(all_net):.0f}ms  avg={sum(all_net)/len(all_net):.0f}ms"
+    )
     print()
     for lang, stats in sorted(lang_stats.items()):
         inf_avg = sum(stats["inference"]) / len(stats["inference"])
diff --git a/examples/chat_client_openai.py b/examples/chat_client_openai.py
index bc0578d..35b21f5 100644
--- a/examples/chat_client_openai.py
+++ b/examples/chat_client_openai.py
@@ -6,6 +6,7 @@
 """
 
 import json
+
 import requests
 from openai import OpenAI
 
@@ -77,7 +78,7 @@ def test_with_openai_sdk():
             ],
         )
 
-        print(f"\n📝 User: Wave your hand and show excitement!")
+        print("\n📝 User: Wave your hand and show excitement!")
         print(f"🤖 Model: {response.model}")
 
         choice = response.choices[0]
@@ -89,16 +90,16 @@ def test_with_openai_sdk():
                     f"({tool_call.function.arguments})"
                 )
 
-        print(f"📊 Tokens: {response.usage.prompt_tokens} prompt + "
-              f"{response.usage.completion_tokens} completion = "
-              f"{response.usage.total_tokens} total")
+        print(
+            f"📊 Tokens: {response.usage.prompt_tokens} prompt + "
+            f"{response.usage.completion_tokens} completion = "
+            f"{response.usage.total_tokens} total"
+        )
 
         print("\n" + "=" * 60)
 
     except ImportError:
-        print(
-            "\n⚠️  OpenAI SDK not installed. Install with: pip install openai\n"
-        )
+        print("\n⚠️  OpenAI SDK not installed. Install with: pip install openai\n")
 
 
 def list_models():
diff --git a/scripts/chat-g1.py b/scripts/chat-g1.py
index 08d45ec..d7e7f9d 100644
--- a/scripts/chat-g1.py
+++ b/scripts/chat-g1.py
@@ -6,7 +6,6 @@
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-
 HF_MODEL = "OpenmindAGI/functiongemma-finetuned-g1-multilingual"
 LOCAL_MODEL = "./functionGemma-finetuned-g1"  # For Google Drive download
 
diff --git a/src/functiongemma/server.py b/src/functiongemma/server.py
index 849daa1..3753245 100644
--- a/src/functiongemma/server.py
+++ b/src/functiongemma/server.py
@@ -311,9 +311,7 @@ def chat_completions(req: ChatCompletionRequest):
         raise HTTPException(status_code=400, detail="No user message found.")
 
     # Run prediction
-    inputs = tokenizer(build_prompt(user_message), return_tensors="pt").to(
-        model.device
-    )
+    inputs = tokenizer(build_prompt(user_message), return_tensors="pt").to(model.device)
 
     if torch.cuda.is_available():
         torch.cuda.synchronize()

From 5a3affe2530b92b21751bb434f11be29942c9393 Mon Sep 17 00:00:00 2001
From: openminddev <boyuan.eth@gmail.com>
Date: Wed, 8 Apr 2026 10:30:34 -0700
Subject: [PATCH 04/10] Add initial project structure with Makefile, README,
 and configuration files

---
 .gitignore             | 16 +++++++-
 .python-version        |  1 +
 Makefile               | 76 ++++++++++++++++++++++++++++++++++++
 readme.md => README.md | 89 +++++++++++++++++++++++++++++++++++++-----
 src/__init__.py        |  0
 5 files changed, 171 insertions(+), 11 deletions(-)
 create mode 100644 .python-version
 create mode 100644 Makefile
 rename readme.md => README.md (73%)
 create mode 100644 src/__init__.py

diff --git a/.gitignore b/.gitignore
index 09cb1d0..1f1dc2a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,5 +1,19 @@
 functionGemma-finetuned-g1/
+functiongemma-robot-actions/
 venv/
-venv/
+.venv/
 __pycache__/
 *.pyc
+*.pyo
+*.pyd
+.Python
+pip-log.txt
+pip-delete-this-directory.txt
+.pytest_cache/
+.mypy_cache/
+.ruff_cache/
+dist/
+build/
+*.egg-info/
+.uv/
+uv.lock
diff --git a/.python-version b/.python-version
new file mode 100644
index 0000000..2c07333
--- /dev/null
+++ b/.python-version
@@ -0,0 +1 @@
+3.11
diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000..630a089
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,76 @@
+.PHONY: help install install-all server train chat benchmark test lint format clean
+
+help:
+	@echo 'Usage: make [target]'
+	@echo ''
+	@echo 'Available targets:'
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "  \033[36m%-20s\033[0m %s\n", $$1, $$2}'
+
+install:
+	uv sync
+
+install-all:
+	uv sync --all-extras
+
+install-training:
+	uv sync --extra training
+
+install-benchmarks:
+	uv sync --extra benchmarks
+
+install-dev:
+	uv sync --extra dev
+
+server:
+	uv run uvicorn functiongemma.server:app --host 0.0.0.0 --port 8200 --reload
+
+train:
+	uv run python scripts/train-g1.py
+
+chat:
+	uv run python scripts/chat-g1.py
+
+benchmark:
+	uv run python benchmarks/benchmark-g1-server.py
+
+benchmark-local:
+	uv run python benchmarks/benchmark-g1.py
+
+example:
+	uv run python examples/chat_client_openai.py
+
+test:
+	uv run pytest
+
+lint:
+	uv run ruff check src/ scripts/ benchmarks/ examples/
+
+lint-fix:
+	uv run ruff check --fix src/ scripts/ benchmarks/ examples/
+
+format:
+	uv run black src/ scripts/ benchmarks/ examples/
+
+format-check:
+	uv run black --check src/ scripts/ benchmarks/ examples/
+
+typecheck:
+	uv run mypy src/
+
+check: lint format-check typecheck
+
+docker-build:
+	docker build -f docker/Dockerfile -t functiongemma-robot-action .
+
+docker-run:
+	docker-compose up
+
+clean:
+	rm -rf build/ dist/ *.egg-info .pytest_cache/ .mypy_cache/ .ruff_cache/ __pycache__/
+	find . -type d -name __pycache__ -exec rm -rf {} +
+	find . -type f -name '*.pyc' -delete
+	find . -type f -name '*.pyo' -delete
+	find . -type f -name '*.pyd' -delete
+
+clean-all: clean
+	rm -rf .venv/
diff --git a/readme.md b/README.md
similarity index 73%
rename from readme.md
rename to README.md
index a21ebaf..5d8c8cb 100644
--- a/readme.md
+++ b/README.md
@@ -19,6 +19,26 @@ The model takes a user's voice/text input and outputs:
 
 For general questions or conversation, the robot defaults to `stand_still` with an appropriate emotion.
 
+## Quick Start
+
+```bash
+# 1. Install uv (if not already installed)
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# 2. Clone and install dependencies
+git clone https://github.com/OpenMind/functionGemma-robot-action.git
+cd functionGemma-robot-action
+uv sync
+
+# 3. Run the server
+uv run uvicorn functiongemma.server:app --host 0.0.0.0 --port 8200
+# or: make server
+
+# 4. Test it!
+uv run python examples/chat_client_openai.py
+# or: make example
+```
+
 ## OpenAI-Compatible API
 
 The server provides OpenAI-compatible endpoints, allowing you to use the OpenAI SDK or any OpenAI-compatible client:
@@ -153,6 +173,20 @@ Trained with LoRA on an NVIDIA RTX 5070 Ti (16 GB):
 | Training examples | 545 (490 train / 55 eval) |
 | Max sequence length | 512 |
 
+To train your own model:
+
+```bash
+# Install training dependencies
+uv sync --extra training
+# or: make install-training
+
+# Run training
+uv run python scripts/train-g1.py
+# or: make train
+```
+
+The training script will fine-tune the base FunctionGemma model and save the result to `./functiongemma-robot-actions/`.
+
 ## Setup on NVIDIA Jetson AGX Thor
 
 ### 1. Clone this repo
@@ -182,30 +216,65 @@ functiongemma-robot-actions/
 └── ...
 ```
 
-### 3. Create virtual environment
+### 3. Install dependencies
+
+#### Option A: Using uv (recommended - fast!)
+
+```bash
+# Install uv if you haven't already
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# Install dependencies
+uv sync
+
+# Install with optional dependencies
+uv sync --all-extras  # Includes training, benchmarks, and dev tools
+```
+
+See [UV_GUIDE.md](UV_GUIDE.md) for more uv commands and usage.
+
+#### Option B: Using pip
 
 ```bash
 python3 -m venv venv
 source venv/bin/activate
-pip install torch transformers accelerate
+pip install torch transformers accelerate fastapi uvicorn
 ```
 
-### 4. Run benchmark
+### 4. Run the server
 
+#### Using Make (easiest)
 ```bash
-python3 benchmarks/benchmark-g1.py  # Local benchmark
-python3 benchmarks/benchmark-g1-server.py  # Benchmark against running server
-python3 benchmarks/benchmark-g1-server-multilingual.py  # Test multilingual support
+make server  # Runs the server with auto-reload
 ```
 
-### 5. Test with OpenAI-compatible client
+#### Using uv
+```bash
+uv run uvicorn functiongemma.server:app --host 0.0.0.0 --port 8200
+```
 
+#### Using Docker
 ```bash
-python3 examples/chat_client_openai.py
+docker-compose up
+# or
+make docker-run
 ```
 
-Or use the interactive local chat:
+### 5. Run benchmarks and examples
 
 ```bash
-python3 scripts/chat-g1.py
+# Using Make
+make benchmark          # Server benchmark
+make benchmark-local    # Local model benchmark
+make example           # OpenAI client example
+
+# Using uv directly
+uv run python benchmarks/benchmark-g1-server.py
+uv run python benchmarks/benchmark-g1-server-multilingual.py
+uv run python examples/chat_client_openai.py
+
+# Interactive chat
+uv run python scripts/chat-g1.py
+# or
+make chat
 ```
diff --git a/src/__init__.py b/src/__init__.py
new file mode 100644
index 0000000..e69de29

From fe6955436553bc9c6fe84a2cfc7948a1279b7a23 Mon Sep 17 00:00:00 2001
From: openminddev <boyuan.eth@gmail.com>
Date: Wed, 8 Apr 2026 10:44:54 -0700
Subject: [PATCH 05/10] Refactor code structure for improved readability and
 maintainability

---
 .gitignore                                    |    1 -
 LICENSE                                       |   21 +
 Makefile                                      |    6 +-
 .../benchmark-g1-server-multilingual.py       |    6 +-
 benchmarks/benchmark-g1-server.py             |   11 +-
 pyproject.toml                                |  116 +
 src/functiongemma/server.py                   |   61 +-
 uv.lock                                       | 3506 +++++++++++++++++
 8 files changed, 3704 insertions(+), 24 deletions(-)
 create mode 100644 LICENSE
 create mode 100644 pyproject.toml
 create mode 100644 uv.lock

diff --git a/.gitignore b/.gitignore
index 1f1dc2a..66c6cf2 100644
--- a/.gitignore
+++ b/.gitignore
@@ -16,4 +16,3 @@ dist/
 build/
 *.egg-info/
 .uv/
-uv.lock
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..a6ecf3e
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 OpenMind
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/Makefile b/Makefile
index 630a089..cbb826f 100644
--- a/Makefile
+++ b/Makefile
@@ -33,15 +33,15 @@ chat:
 benchmark:
 	uv run python benchmarks/benchmark-g1-server.py
 
+benchmark-multilingual:
+	uv run python benchmarks/benchmark-g1-server-multilingual.py
+
 benchmark-local:
 	uv run python benchmarks/benchmark-g1.py
 
 example:
 	uv run python examples/chat_client_openai.py
 
-test:
-	uv run pytest
-
 lint:
 	uv run ruff check src/ scripts/ benchmarks/ examples/
 
diff --git a/benchmarks/benchmark-g1-server-multilingual.py b/benchmarks/benchmark-g1-server-multilingual.py
index 33f26bb..c78c85b 100644
--- a/benchmarks/benchmark-g1-server-multilingual.py
+++ b/benchmarks/benchmark-g1-server-multilingual.py
@@ -132,11 +132,11 @@ def main():
         emotion = None
         for tc in tool_calls:
             func_name = tc["function"]["name"]
-            args = json.loads(tc["function"]["arguments"])
+            func_args = json.loads(tc["function"]["arguments"])
             if func_name == "robot_action":
-                action = args["action_name"]
+                action = func_args["action_name"]
             elif func_name == "show_emotion":
-                emotion = args["emotion"]
+                emotion = func_args["emotion"]
 
         inference_ms = total_ms - 10  # Rough estimate
         lang = t["lang"]
diff --git a/benchmarks/benchmark-g1-server.py b/benchmarks/benchmark-g1-server.py
index 6382b48..1286bc6 100644
--- a/benchmarks/benchmark-g1-server.py
+++ b/benchmarks/benchmark-g1-server.py
@@ -33,11 +33,9 @@ def main():
     parser.add_argument("--url", default="http://localhost:8200")
     args = parser.parse_args()
 
-    # Health check
     r = requests.get(f"{args.url}/health")
     print(f"Server: {r.json()}\n")
 
-    # Warmup
     print("Warming up...")
     for _ in range(3):
         requests.post(
@@ -49,7 +47,6 @@ def main():
         )
     print("Done!\n")
 
-    # Benchmark
     print("Running benchmark...\n")
     times = []
     for t in TESTS:
@@ -65,19 +62,17 @@ def main():
 
         data = r.json()
 
-        # Extract action and emotion from tool_calls
         tool_calls = data["choices"][0]["message"]["tool_calls"]
         action = None
         emotion = None
         for tc in tool_calls:
             func_name = tc["function"]["name"]
-            args = json.loads(tc["function"]["arguments"])
+            func_args = json.loads(tc["function"]["arguments"])
             if func_name == "robot_action":
-                action = args["action_name"]
+                action = func_args["action_name"]
             elif func_name == "show_emotion":
-                emotion = args["emotion"]
+                emotion = func_args["emotion"]
 
-        # Estimate inference time (total - network overhead estimate)
         inference_ms = total_ms - 10  # Rough estimate
         times.append(inference_ms)
 
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..9c2c395
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,116 @@
+[project]
+name = "functiongemma-robot-action"
+version = "0.1.0"
+description = "A fine-tuned FunctionGemma 270M model that converts natural language commands into structured robot actions and avatar emotions"
+readme = "README.md"
+requires-python = ">=3.10"
+license = { text = "MIT" }
+authors = [
+    { name = "OpenMind", email = "hello@openmind.com" }
+]
+keywords = ["llm", "function-calling", "robotics", "gemma", "fastapi"]
+
+dependencies = [
+    "fastapi>=0.115.0",
+    "uvicorn[standard]>=0.32.0",
+    "transformers>=4.46.0",
+    "torch>=2.5.0",
+    "accelerate>=1.1.0",
+    "huggingface-hub>=0.26.0",
+    "pydantic>=2.9.0",
+]
+
+[project.optional-dependencies]
+training = [
+    "peft>=0.13.0",
+    "trl>=0.12.0",
+    "datasets>=3.0.0",
+]
+benchmarks = [
+    "requests>=2.32.0",
+    "openai>=1.54.0",
+]
+dev = [
+    "pytest>=8.3.0",
+    "black>=24.10.0",
+    "ruff>=0.7.0",
+    "mypy>=1.13.0",
+]
+all = [
+    "functiongemma-robot-action[training,benchmarks,dev]",
+]
+
+[project.scripts]
+train-g1 = "scripts.train_g1:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/functiongemma"]
+
+[dependency-groups]
+dev = [
+    "pytest>=8.3.0",
+    "black>=24.10.0",
+    "ruff>=0.7.0",
+]
+
+[tool.uv.sources]
+# Uncomment if you want to use local development versions
+# functiongemma-robot-action = { path = ".", editable = true }
+
+[tool.black]
+line-length = 88
+target-version = ["py310", "py311", "py312"]
+include = '\.pyi?$'
+exclude = '''
+/(
+    \.git
+  | \.venv
+  | build
+  | dist
+)/
+'''
+
+[tool.ruff]
+line-length = 88
+target-version = "py310"
+
+[tool.ruff.lint]
+select = [
+    "E",   # pycodestyle errors
+    "W",   # pycodestyle warnings
+    "F",   # pyflakes
+    "I",   # isort
+    "B",   # flake8-bugbear
+    "C4",  # flake8-comprehensions
+    "UP",  # pyupgrade
+]
+ignore = [
+    "E501",  # line too long (handled by black)
+    "B008",  # do not perform function calls in argument defaults
+    "C901",  # too complex
+]
+
+[tool.ruff.lint.isort]
+known-first-party = ["functiongemma"]
+
+[tool.mypy]
+python_version = "3.10"
+warn_return_any = true
+warn_unused_configs = true
+disallow_untyped_defs = false
+ignore_missing_imports = true
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+python_files = ["test_*.py"]
+python_classes = ["Test*"]
+python_functions = ["test_*"]
+addopts = "-v --tb=short"
+# Prevent pytest from loading ROS launch_testing plugins that conflict
+norecursedirs = [".git", ".venv", "build", "dist", ".eggs"]
+# Ignore certain entry points that cause conflicts
+filterwarnings = ["ignore::DeprecationWarning"]
diff --git a/src/functiongemma/server.py b/src/functiongemma/server.py
index 3753245..f5b2b7a 100644
--- a/src/functiongemma/server.py
+++ b/src/functiongemma/server.py
@@ -19,6 +19,7 @@
 
 import json
 import logging
+import os
 import time
 import uuid
 from typing import Literal, Optional
@@ -35,6 +36,9 @@
 )
 logger = logging.getLogger("functiongemma-service")
 
+WARMUP_ITERATIONS = int(os.getenv("WARMUP_ITERATIONS", "5"))
+MODEL_NAME = os.getenv("MODEL_NAME", "OpenmindAGI/functiongemma-finetuned-g1-multilingual")
+
 app = FastAPI(title="FunctionGemma Robot Actions")
 model = None
 tokenizer = None
@@ -240,16 +244,24 @@ def load_model():
     global action_token_ids, emotion_token_ids
     global valid_action_first_tokens, valid_emotion_first_tokens
 
-    logger.info("Loading FunctionGemma on CUDA...")
-    tokenizer = AutoTokenizer.from_pretrained("OpenmindAGI/functiongemma-finetuned-g1")
+    logger.info("=" * 60)
+    logger.info("FunctionGemma Robot Actions Server - Starting Up")
+    logger.info("=" * 60)
+
+    logger.info(f"Loading FunctionGemma model: {MODEL_NAME}")
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
     model = AutoModelForCausalLM.from_pretrained(
-        "OpenmindAGI/functiongemma-finetuned-g1",
+        MODEL_NAME,
         torch_dtype=torch.bfloat16,
         device_map="auto",
     )
     model.eval()
 
+    device = next(model.parameters()).device
+    logger.info(f"Model loaded on device: {device}")
+
     # Pre-tokenize action/emotion values
+    logger.info("Pre-tokenizing action/emotion templates...")
     for a in ACTIONS:
         action_token_ids[a] = tokenizer.encode(a, add_special_tokens=False)
     for e in EMOTIONS:
@@ -270,11 +282,41 @@ def load_model():
     valid_action_first_tokens.update(ids[0] for ids in action_token_ids.values())
     valid_emotion_first_tokens.update(ids[0] for ids in emotion_token_ids.values())
 
-    # Warmup
-    for _ in range(5):
-        inputs = tokenizer(build_prompt("hello"), return_tensors="pt").to(model.device)
-        generate_constrained(inputs["input_ids"])
-    logger.info("Model ready!")
+    # Warmup: Run several inference passes to compile CUDA kernels and
+    # ensure optimal performance from the first real request
+    if WARMUP_ITERATIONS > 0:
+        logger.info(f"Warming up model (running {WARMUP_ITERATIONS} inference passes)...")
+        warmup_prompts = [
+            "hello",
+            "wave at me",
+            "shake hands",
+            "I'm confused",
+            "good job!",
+        ]
+
+        for i in range(WARMUP_ITERATIONS):
+            prompt = warmup_prompts[i % len(warmup_prompts)]
+            inputs = tokenizer(build_prompt(prompt), return_tensors="pt").to(model.device)
+            if torch.cuda.is_available():
+                torch.cuda.synchronize()
+
+            start = time.perf_counter()
+            action, emotion = generate_constrained(inputs["input_ids"])
+
+            if torch.cuda.is_available():
+                torch.cuda.synchronize()
+            elapsed_ms = (time.perf_counter() - start) * 1000
+
+            logger.info(
+                f"  Warmup {i+1}/{WARMUP_ITERATIONS}: {elapsed_ms:.0f}ms | {prompt:<15s} -> {action}/{emotion}"
+            )
+    else:
+        logger.info("Warmup disabled (WARMUP_ITERATIONS=0)")
+
+    logger.info("=" * 60)
+    logger.info("✓ Server ready! Listening for requests...")
+    logger.info("  Endpoints: /v1/chat/completions, /v1/models, /actions, /health")
+    logger.info("=" * 60)
 
 
 @app.post("/v1/chat/completions", response_model=ChatCompletionResponse)
@@ -404,6 +446,7 @@ def health():
     """Health check endpoint."""
     return {
         "status": "ok",
-        "model": "functiongemma-finetuned-g1",
+        "model": MODEL_NAME,
         "device": str(model.device) if model else "not loaded",
+        "warmup_iterations": WARMUP_ITERATIONS,
     }
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..f681799
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,3506 @@
+version = 1
+revision = 3
+requires-python = ">=3.10"
+resolution-markers = [
+    "python_full_version >= '3.14' and sys_platform == 'win32'",
+    "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version >= '3.11' and python_full_version < '3.14' and sys_platform == 'win32'",
+    "python_full_version >= '3.11' and python_full_version < '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.11' and python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.11'",
+]
+
+[[package]]
+name = "accelerate"
+version = "1.13.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "huggingface-hub" },
+    { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
+    { name = "numpy", version = "2.4.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
+    { name = "packaging" },
+    { name = "psutil" },
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+    { name = "torch" },
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From d81c518ef99eab6f66ac985bdcff3a1de68574d8 Mon Sep 17 00:00:00 2001
From: openminddev <boyuan.eth@gmail.com>
Date: Wed, 8 Apr 2026 10:45:50 -0700
Subject: [PATCH 06/10] Remove comments in pytest configuration to streamline
 the file

---
 pyproject.toml | 2 --
 1 file changed, 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 9c2c395..eb4afb9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -110,7 +110,5 @@ python_files = ["test_*.py"]
 python_classes = ["Test*"]
 python_functions = ["test_*"]
 addopts = "-v --tb=short"
-# Prevent pytest from loading ROS launch_testing plugins that conflict
 norecursedirs = [".git", ".venv", "build", "dist", ".eggs"]
-# Ignore certain entry points that cause conflicts
 filterwarnings = ["ignore::DeprecationWarning"]

From eb8ddac4abd208f72db9b1da580083dde338b09d Mon Sep 17 00:00:00 2001
From: openminddev <boyuan.eth@gmail.com>
Date: Wed, 8 Apr 2026 10:48:25 -0700
Subject: [PATCH 07/10] Update Python version from 3.11 to 3.12

---
 .python-version | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.python-version b/.python-version
index 2c07333..e4fba21 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.11
+3.12

From 90b5f6b95ecb6b48c35c90c1d3f3fcc3fc037d08 Mon Sep 17 00:00:00 2001
From: openmindev <147775420+openminddev@users.noreply.github.com>
Date: Wed, 8 Apr 2026 10:51:18 -0700
Subject: [PATCH 08/10] Use PEP 604 types and minor formatting cleanup

Modernize typing and clean up formatting across server and training script. Replaced Optional[...] annotations with X | None union syntax and removed Optional import; updated several Pydantic field types. Wrapped long expressions (MODEL_NAME, logger.info, tokenizer(...) calls) for readability. Also simplified file open call in scripts/train-g1.py by removing the explicit "r" mode. These are non-functional readability/modernization changes.
---
 scripts/train-g1.py         |  2 +-
 src/functiongemma/server.py | 26 ++++++++++++++++----------
 2 files changed, 17 insertions(+), 11 deletions(-)

diff --git a/scripts/train-g1.py b/scripts/train-g1.py
index b3e9469..f6cf5af 100644
--- a/scripts/train-g1.py
+++ b/scripts/train-g1.py
@@ -138,7 +138,7 @@ def format_training_example(example: dict) -> str:
 def load_and_format_dataset(filepath: str) -> Dataset:
     """Load JSONL file and format for training."""
     examples = []
-    with open(filepath, "r") as f:
+    with open(filepath) as f:
         for line in f:
             line = line.strip()
             if not line:
diff --git a/src/functiongemma/server.py b/src/functiongemma/server.py
index f5b2b7a..4d22a5c 100644
--- a/src/functiongemma/server.py
+++ b/src/functiongemma/server.py
@@ -22,7 +22,7 @@
 import os
 import time
 import uuid
-from typing import Literal, Optional
+from typing import Literal
 
 import torch
 from fastapi import FastAPI, HTTPException
@@ -37,7 +37,9 @@
 logger = logging.getLogger("functiongemma-service")
 
 WARMUP_ITERATIONS = int(os.getenv("WARMUP_ITERATIONS", "5"))
-MODEL_NAME = os.getenv("MODEL_NAME", "OpenmindAGI/functiongemma-finetuned-g1-multilingual")
+MODEL_NAME = os.getenv(
+    "MODEL_NAME", "OpenmindAGI/functiongemma-finetuned-g1-multilingual"
+)
 
 app = FastAPI(title="FunctionGemma Robot Actions")
 model = None
@@ -94,8 +96,8 @@ class ChatMessage(BaseModel):
     """OpenAI chat message format."""
 
     role: Literal["system", "user", "assistant", "tool"]
-    content: Optional[str] = None
-    tool_calls: Optional[list[dict]] = None
+    content: str | None = None
+    tool_calls: list[dict] | None = None
 
 
 class ChatCompletionRequest(BaseModel):
@@ -103,8 +105,8 @@ class ChatCompletionRequest(BaseModel):
 
     model: str = "functiongemma-finetuned-g1"
     messages: list[ChatMessage]
-    temperature: Optional[float] = Field(default=1.0, ge=0, le=2)
-    max_tokens: Optional[int] = None
+    temperature: float | None = Field(default=1.0, ge=0, le=2)
+    max_tokens: int | None = None
     stream: bool = False
 
 
@@ -120,8 +122,8 @@ class ChatCompletionMessage(BaseModel):
     """OpenAI response message format."""
 
     role: Literal["assistant"]
-    content: Optional[str] = None
-    tool_calls: Optional[list[ToolCall]] = None
+    content: str | None = None
+    tool_calls: list[ToolCall] | None = None
 
 
 class ChatCompletionChoice(BaseModel):
@@ -285,7 +287,9 @@ def load_model():
     # Warmup: Run several inference passes to compile CUDA kernels and
     # ensure optimal performance from the first real request
     if WARMUP_ITERATIONS > 0:
-        logger.info(f"Warming up model (running {WARMUP_ITERATIONS} inference passes)...")
+        logger.info(
+            f"Warming up model (running {WARMUP_ITERATIONS} inference passes)..."
+        )
         warmup_prompts = [
             "hello",
             "wave at me",
@@ -296,7 +300,9 @@ def load_model():
 
         for i in range(WARMUP_ITERATIONS):
             prompt = warmup_prompts[i % len(warmup_prompts)]
-            inputs = tokenizer(build_prompt(prompt), return_tensors="pt").to(model.device)
+            inputs = tokenizer(build_prompt(prompt), return_tensors="pt").to(
+                model.device
+            )
             if torch.cuda.is_available():
                 torch.cuda.synchronize()
 

From c793b5e7c1b346a700281242091137a316673111 Mon Sep 17 00:00:00 2001
From: openmindev <147775420+openminddev@users.noreply.github.com>
Date: Wed, 8 Apr 2026 10:54:42 -0700
Subject: [PATCH 09/10] Add Dockerfile for building FunctionGemma image and
 update release workflow

---
 .github/workflows/release.yml   | 2 +-
 docker/Dockerfile => Dockerfile | 0
 2 files changed, 1 insertion(+), 1 deletion(-)
 rename docker/Dockerfile => Dockerfile (100%)

diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 93123ce..2602db2 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -42,7 +42,7 @@ jobs:
         uses: docker/build-push-action@v5
         with:
           context: .
-          file: ./docker/Dockerfile
+          file: ./Dockerfile
           push: true
           platforms: linux/arm64
           tags: ${{ steps.meta.outputs.tags }}
diff --git a/docker/Dockerfile b/Dockerfile
similarity index 100%
rename from docker/Dockerfile
rename to Dockerfile

From 1bba498a89a98a1edab8ead602492b4a4d9209d9 Mon Sep 17 00:00:00 2001
From: openmindev <147775420+openminddev@users.noreply.github.com>
Date: Wed, 8 Apr 2026 10:55:45 -0700
Subject: [PATCH 10/10] Remove Dockerfile for FunctionGemma image

---
 docker/Dockerfile | 27 ---------------------------
 1 file changed, 27 deletions(-)
 delete mode 100644 docker/Dockerfile

diff --git a/docker/Dockerfile b/docker/Dockerfile
deleted file mode 100644
index aafb564..0000000
--- a/docker/Dockerfile
+++ /dev/null
@@ -1,27 +0,0 @@
-FROM nvcr.io/nvidia/pytorch:25.10-py3
-
-WORKDIR /app
-
-RUN pip install --no-cache-dir \
-    fastapi \
-    "uvicorn[standard]" \
-    transformers \
-    accelerate \
-    huggingface_hub
-
-# Pre-download model at build time so startup is instant
-RUN python3 -c "from transformers import AutoTokenizer, AutoModelForCausalLM; AutoTokenizer.from_pretrained('OpenmindAGI/functiongemma-finetuned-g1-multilingual'); AutoModelForCausalLM.from_pretrained('OpenmindAGI/functiongemma-finetuned-g1-multilingual')"
-COPY src/functiongemma/server.py .
-
-# Jetson Thor inference optimizations
-ENV CUDA_MODULE_LOADING=LAZY
-ENV PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
-ENV OMP_NUM_THREADS=4
-ENV TOKENIZERS_PARALLELISM=false
-
-EXPOSE 8200
-
-HEALTHCHECK --interval=30s --timeout=10s --start-period=120s --retries=3 \
-    CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8200/health')" || exit 1
-
-CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "8200", "--workers", "1"]