Added Ollama osmosis structure (#92)

* ollama osmosis structure

* format

Author: NilayYadav

ollama/.beamignore

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+# Generated by Beam SDK
+.beamignore
+pyproject.toml
+.git
+.idea
+.python-version
+.vscode
+.venv
+venv
+__pycache__
+.DS_Store
+.config
+drive/MyDrive
+.coverage
+.pytest_cache
+.ipynb
+.ruff_cache
+.dockerignore
+.ipynb_checkpoints
+.env.local
+.envrc
+**/__pycache__/
+**/.pytest_cache/
+**/node_modules/
+**/.venv/
+*.pyc
+.next/
+.circleci

ollama/README.md

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+## Ollama Osmosis-Structure-0.6B
+
+1. Install [Beam](https://beam.cloud) on your computer
+2. Clone this repo
+3. Deploy the Osmosis-Structure-0.6B: `beam deploy app.py:generate`
+
+Once deployed, you can access the API through your browser, or via API. `test.py` shows an example API call to the Osmosis-Structure-0.6B model.

ollama/app.py

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+from beam import endpoint, Image
+from pydantic import BaseModel
+
+
+class Answer(BaseModel):
+    json: dict
+
+
+image = (
+    Image(python_version="python3.11")
+    .add_python_packages(
+        [
+            "git+https://github.com/huggingface/transformers",
+            "numpy<2",
+            "fastapi[standard]==0.115.4",
+            "pydantic==2.9.2",
+            "starlette==0.41.2",
+            "torch==2.4.0",
+            "ollama",
+        ]
+    )
+    .add_commands(
+        [
+            "curl -fsSL https://ollama.com/install.sh | sh",
+        ]
+    )
+)
+
+
+def load_model():
+    import subprocess
+    import time
+
+    subprocess.Popen(["ollama", "serve"])
+    time.sleep(5)
+    subprocess.run(["ollama", "pull", "Osmosis/Osmosis-Structure-0.6B"], check=True)
+
+
+@endpoint(
+    name="ollamap-osmosis-structure",
+    image=image,
+    cpu=12,
+    memory="32Gi",
+    gpu="A10G",
+    on_start=load_model,
+)
+def generate(**inputs):
+    from ollama import chat
+
+    messages = inputs.get("messages", "")
+
+    response = chat(
+        messages=messages,
+        model="Osmosis/Osmosis-Structure-0.6B",
+        format=Answer.model_json_schema(),
+    )
+
+    answer = Answer.model_validate_json(response.message.content)
+    print(answer)
+    return {"answer": answer.json}

ollama/test.py

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+import requests
+
+AUTH_TOKEN = "YOUR_BEAM_AUTH_TOKEN"  # Replace with your actual Beam auth token
+
+url = "https://78f2e172-6ae5-4cef-b43a-9823238f.app.beam.cloud"
+
+headers = {
+    "Connection": "keep-alive",
+    "Content-Type": "application/json",
+    "Authorization": f"Bearer {AUTH_TOKEN}",
+}
+
+reasoning_trace = """
+    Product ID: P-001
+    Product Name: Wireless Ergonomic Mouse
+    Price: $29.99
+    In Stock: Yes
+    Features: Adjustable DPI, Rechargeable Battery, Silent Clicks
+    Compatible OS: Windows, macOS, Linux
+"""
+
+data = {
+    "messages": [
+        {
+            "role": "system",
+            "content": "You are a helpful assistant that understands and translates text to JSON format",
+        },
+        {"role": "user", "content": reasoning_trace},
+    ]
+}
+
+response = requests.post(url, headers=headers, json=data)
+print(response.text)