mirror of
https://github.com/temporal-community/temporal-ai-agent.git
synced 2026-03-15 14:08:08 +01:00
initial working with ollama
This commit is contained in:
Steve Androulakis
32
.gitignore
vendored
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32
.gitignore
vendored
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@@ -0,0 +1,32 @@
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||||
# OS-specific files
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||||
.DS_Store
|
||||
|
||||
# Python cache & compiled files
|
||||
__pycache__/
|
||||
*.py[cod]
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||||
*.pyd
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||||
*.pyo
|
||||
*.so
|
||||
*.egg-info/
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||||
*.egg
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||||
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||||
# Virtual environment directory
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||||
venv/
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||||
.venv/
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||||
|
||||
# Build artifacts
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build/
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dist/
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||||
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||||
# Test / coverage files
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||||
.coverage
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.coverage.*
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*.cover
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coverage.xml
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||||
.pytest_cache/
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||||
|
||||
# VSCode settings
|
||||
.vscode/
|
||||
|
||||
# PyCharm / IntelliJ settings
|
||||
.idea/
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19
README.md
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19
README.md
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@@ -0,0 +1,19 @@
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# Multi-turn chat with Ollama Entity Workflow
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Multi-Turn Chat using an Entity Workflow. The workflow runs forever unless explicitly ended. The workflow continues as new after a configurable number of chat turns to keep the prompt size small and the Temporal event history small. Each continued-as-new workflow receives a summary of the conversation history so far for context.
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To run, first see `samples-python` [README.md](../../README.md), and `ollama` [README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory:
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1. Run the worker: `poetry run python run_worker.py`
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2. In another terminal run the client with a prompt.
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Example: `poetry run python send_message.py 'What animals are marsupials?'`
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3. View the worker's output for the response.
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4. Give followup prompts by signaling the workflow.
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Example: `poetry run python send_message.py 'Do they lay eggs?'`
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5. Get the conversation history summary by querying the workflow.
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Example: `poetry run python get_history.py`
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6. To end the chat session, run `poetry run python end_chat.py`
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0
__init__.py
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0
__init__.py
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19
activities.py
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activities.py
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from temporalio import activity
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from ollama import chat, ChatResponse
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class OllamaActivities:
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@activity.defn
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def prompt_ollama(self, prompt: str) -> str:
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model_name = 'mistral'
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messages = [
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{
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'role': 'user',
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'content': prompt
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}
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]
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# Call ollama's chat function
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response: ChatResponse = chat(model=model_name, messages=messages)
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# Return the model's text response
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return response.message.content
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22
end_chat.py
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end_chat.py
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import asyncio
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import sys
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from temporalio.client import Client
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from workflows import EntityOllamaWorkflow
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async def main():
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# Create client connected to server at the given address
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client = await Client.connect("localhost:7233")
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workflow_id = "entity-ollama-workflow"
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handle = client.get_workflow_handle_for(EntityOllamaWorkflow.run, workflow_id)
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# Sends a signal to the workflow
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await handle.signal(EntityOllamaWorkflow.end_chat)
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if __name__ == "__main__":
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print("Sending signal to end chat.")
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asyncio.run(main())
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31
get_history.py
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get_history.py
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import asyncio
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from temporalio.client import Client
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from workflows import EntityOllamaWorkflow
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async def main():
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# Create client connected to server at the given address
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client = await Client.connect("localhost:7233")
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workflow_id = "entity-ollama-workflow"
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handle = client.get_workflow_handle(workflow_id)
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# Queries the workflow for the conversation history
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history = await handle.query(EntityOllamaWorkflow.get_conversation_history)
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print("Conversation History")
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print(
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*(f"{speaker.title()}: {message}\n" for speaker, message in history), sep="\n"
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)
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# Queries the workflow for the conversation summary
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summary = await handle.query(EntityOllamaWorkflow.get_summary_from_history)
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if summary is not None:
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print("Conversation Summary:")
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print(summary)
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if __name__ == "__main__":
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asyncio.run(main())
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611
poetry.lock
generated
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611
poetry.lock
generated
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@@ -0,0 +1,611 @@
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# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
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name = "annotated-types"
|
||||
version = "0.7.0"
|
||||
description = "Reusable constraint types to use with typing.Annotated"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
|
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "4.5.2"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
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||||
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|
||||
|
||||
[package.dependencies]
|
||||
exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
|
||||
|
||||
[package.extras]
|
||||
doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
|
||||
test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21.0b1)"]
|
||||
trio = ["trio (>=0.26.1)"]
|
||||
|
||||
[[package]]
|
||||
name = "black"
|
||||
version = "23.12.1"
|
||||
description = "The uncompromising code formatter."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
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||||
|
||||
[package.dependencies]
|
||||
click = ">=8.0.0"
|
||||
mypy-extensions = ">=0.4.3"
|
||||
packaging = ">=22.0"
|
||||
pathspec = ">=0.9.0"
|
||||
platformdirs = ">=2"
|
||||
tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
|
||||
typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
|
||||
|
||||
[package.extras]
|
||||
colorama = ["colorama (>=0.4.3)"]
|
||||
d = ["aiohttp (>=3.7.4)", "aiohttp (>=3.7.4,!=3.9.0)"]
|
||||
jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
|
||||
uvloop = ["uvloop (>=0.15.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2024.12.14"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
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||||
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||||
[[package]]
|
||||
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|
||||
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|
||||
description = "Composable command line interface toolkit"
|
||||
optional = false
|
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python-versions = ">=3.7"
|
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||||
[package.dependencies]
|
||||
colorama = {version = "*", markers = "platform_system == \"Windows\""}
|
||||
|
||||
[[package]]
|
||||
name = "colorama"
|
||||
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|
||||
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|
||||
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||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
optional = false
|
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|
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||||
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||||
[package.extras]
|
||||
test = ["pytest (>=6)"]
|
||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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||||
|
||||
[[package]]
|
||||
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|
||||
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|
||||
description = "A minimal low-level HTTP client."
|
||||
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|
||||
python-versions = ">=3.8"
|
||||
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|
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||||
[package.dependencies]
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||||
certifi = "*"
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||||
h11 = ">=0.13,<0.15"
|
||||
|
||||
[package.extras]
|
||||
asyncio = ["anyio (>=4.0,<5.0)"]
|
||||
http2 = ["h2 (>=3,<5)"]
|
||||
socks = ["socksio (==1.*)"]
|
||||
trio = ["trio (>=0.22.0,<1.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "httpx"
|
||||
version = "0.27.2"
|
||||
description = "The next generation HTTP client."
|
||||
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||||
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|
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||||
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|
||||
|
||||
[package.dependencies]
|
||||
anyio = "*"
|
||||
certifi = "*"
|
||||
httpcore = "==1.*"
|
||||
idna = "*"
|
||||
sniffio = "*"
|
||||
|
||||
[package.extras]
|
||||
brotli = ["brotli", "brotlicffi"]
|
||||
cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
|
||||
http2 = ["h2 (>=3,<5)"]
|
||||
socks = ["socksio (==1.*)"]
|
||||
zstd = ["zstandard (>=0.18.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "idna"
|
||||
version = "3.10"
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opentelemetry = ["opentelemetry-api (>=1.11.1,<2.0.0)", "opentelemetry-sdk (>=1.11.1,<2.0.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "2.2.1"
|
||||
description = "A lil' TOML parser"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ece47d672db52ac607a3d9599a9d48dcb2f2f735c6c2d1f34130085bb12b112a"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6972ca9c9cc9f0acaa56a8ca1ff51e7af152a9f87fb64623e31d5c83700080ee"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c954d2250168d28797dd4e3ac5cf812a406cd5a92674ee4c8f123c889786aa8e"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8dd28b3e155b80f4d54beb40a441d366adcfe740969820caf156c019fb5c7ec4"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:e59e304978767a54663af13c07b3d1af22ddee3bb2fb0618ca1593e4f593a106"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:33580bccab0338d00994d7f16f4c4ec25b776af3ffaac1ed74e0b3fc95e885a8"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-win32.whl", hash = "sha256:465af0e0875402f1d226519c9904f37254b3045fc5084697cefb9bdde1ff99ff"},
|
||||
{file = "tomli-2.2.1-cp311-cp311-win_amd64.whl", hash = "sha256:2d0f2fdd22b02c6d81637a3c95f8cd77f995846af7414c5c4b8d0545afa1bc4b"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:4a8f6e44de52d5e6c657c9fe83b562f5f4256d8ebbfe4ff922c495620a7f6cea"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8d57ca8095a641b8237d5b079147646153d22552f1c637fd3ba7f4b0b29167a8"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4e340144ad7ae1533cb897d406382b4b6fede8890a03738ff1683af800d54192"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:db2b95f9de79181805df90bedc5a5ab4c165e6ec3fe99f970d0e302f384ad222"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:02abe224de6ae62c19f090f68da4e27b10af2b93213d36cf44e6e1c5abd19fdd"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"},
|
||||
{file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a92ef1a44547e894e2a17d24e7557a5e85a9e1d0048b0b5e7541f76c5032cb13"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9316dc65bed1684c9a98ee68759ceaed29d229e985297003e494aa825ebb0281"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e85e99945e688e32d5a35c1ff38ed0b3f41f43fad8df0bdf79f72b2ba7bc5272"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:ac065718db92ca818f8d6141b5f66369833d4a80a9d74435a268c52bdfa73140"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:d920f33822747519673ee656a4b6ac33e382eca9d331c87770faa3eef562aeb2"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-win32.whl", hash = "sha256:d3f5614314d758649ab2ab3a62d4f2004c825922f9e370b29416484086b264ec"},
|
||||
{file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"},
|
||||
{file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"},
|
||||
{file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "types-protobuf"
|
||||
version = "5.29.1.20241207"
|
||||
description = "Typing stubs for protobuf"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "types_protobuf-5.29.1.20241207-py3-none-any.whl", hash = "sha256:92893c42083e9b718c678badc0af7a9a1307b92afe1599e5cba5f3d35b668b2f"},
|
||||
{file = "types_protobuf-5.29.1.20241207.tar.gz", hash = "sha256:2ebcadb8ab3ef2e3e2f067e0882906d64ba0dc65fc5b0fd7a8b692315b4a0be9"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.12.2"
|
||||
description = "Backported and Experimental Type Hints for Python 3.8+"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
|
||||
{file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
|
||||
]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.8"
|
||||
content-hash = "85301bd486e833b45f80659b9e767579e78a4a379766e8b8e1b68d4d93d0be6a"
|
||||
33
pyproject.toml
Normal file
33
pyproject.toml
Normal file
@@ -0,0 +1,33 @@
|
||||
[tool.poetry]
|
||||
name = "temporal-ollama-agent"
|
||||
version = "0.1.0"
|
||||
description = "Temporal Ollama Agent"
|
||||
license = "MIT"
|
||||
authors = ["Steve Androulakis <steve.androulakis@temporal.io>"]
|
||||
readme = "README.md"
|
||||
|
||||
# By default, Poetry will find packages automatically,
|
||||
# but explicitly including them is fine:
|
||||
packages = [
|
||||
{ include = "**/*.py", from = "." }
|
||||
]
|
||||
|
||||
[tool.poetry.urls]
|
||||
"Bug Tracker" = "https://github.com/temporalio/samples-python/issues"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
temporalio = "^1.8.0"
|
||||
|
||||
# Standard library modules (e.g. asyncio, collections) don't need to be added
|
||||
# since they're built-in for Python 3.8+.
|
||||
ollama = "^0.4.5"
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
pytest = "^7.3"
|
||||
black = "^23.7"
|
||||
isort = "^5.12"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core>=1.4.0"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
21
run_ollama.py
Normal file
21
run_ollama.py
Normal file
@@ -0,0 +1,21 @@
|
||||
from ollama import chat, ChatResponse
|
||||
|
||||
def main():
|
||||
model_name = 'mistral'
|
||||
|
||||
# The messages to pass to the model
|
||||
messages = [
|
||||
{
|
||||
'role': 'user',
|
||||
'content': 'Why is the sky blue?',
|
||||
}
|
||||
]
|
||||
|
||||
# Call ollama's chat function
|
||||
response: ChatResponse = chat(model=model_name, messages=messages)
|
||||
|
||||
# Print the full message content
|
||||
print(response.message.content)
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
35
run_worker.py
Normal file
35
run_worker.py
Normal file
@@ -0,0 +1,35 @@
|
||||
import asyncio
|
||||
import concurrent.futures
|
||||
import logging
|
||||
|
||||
from temporalio.client import Client
|
||||
from temporalio.worker import Worker
|
||||
from workflows import EntityOllamaWorkflow
|
||||
|
||||
from activities import OllamaActivities
|
||||
|
||||
|
||||
async def main():
|
||||
# Create client connected to server at the given address
|
||||
client = await Client.connect("localhost:7233")
|
||||
activities = OllamaActivities()
|
||||
|
||||
# Run the worker
|
||||
with concurrent.futures.ThreadPoolExecutor(max_workers=100) as activity_executor:
|
||||
worker = Worker(
|
||||
client,
|
||||
task_queue="ollama-task-queue",
|
||||
workflows=[EntityOllamaWorkflow],
|
||||
activities=[activities.prompt_ollama],
|
||||
activity_executor=activity_executor,
|
||||
)
|
||||
await worker.run()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("Starting worker")
|
||||
print("Then run 'python send_message.py \"<prompt>\"'")
|
||||
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
|
||||
asyncio.run(main())
|
||||
30
send_message.py
Normal file
30
send_message.py
Normal file
@@ -0,0 +1,30 @@
|
||||
import asyncio
|
||||
import sys
|
||||
|
||||
from temporalio.client import Client
|
||||
from workflows import OllamaParams, EntityOllamaWorkflow
|
||||
|
||||
|
||||
async def main(prompt):
|
||||
# Create client connected to server at the given address
|
||||
client = await Client.connect("localhost:7233")
|
||||
|
||||
workflow_id = "entity-ollama-workflow"
|
||||
|
||||
# Sends a signal to the workflow (and starts it if needed)
|
||||
await client.start_workflow(
|
||||
EntityOllamaWorkflow.run,
|
||||
OllamaParams(None, None),
|
||||
id=workflow_id,
|
||||
task_queue="ollama-task-queue",
|
||||
start_signal="user_prompt",
|
||||
start_signal_args=[prompt],
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if len(sys.argv) != 2:
|
||||
print("Usage: python send_message.py '<prompt>'")
|
||||
print("Example: python send_message.py 'What animals are marsupials?'")
|
||||
else:
|
||||
asyncio.run(main(sys.argv[1]))
|
||||
164
workflows.py
Normal file
164
workflows.py
Normal file
@@ -0,0 +1,164 @@
|
||||
from collections import deque
|
||||
from dataclasses import dataclass
|
||||
from datetime import timedelta
|
||||
from typing import Deque, List, Optional, Tuple
|
||||
|
||||
from temporalio import workflow
|
||||
|
||||
with workflow.unsafe.imports_passed_through():
|
||||
from activities import OllamaActivities
|
||||
|
||||
|
||||
@dataclass
|
||||
class OllamaParams:
|
||||
conversation_summary: Optional[str] = None
|
||||
prompt_queue: Optional[Deque[str]] = None
|
||||
|
||||
|
||||
@workflow.defn
|
||||
class EntityOllamaWorkflow:
|
||||
def __init__(self) -> None:
|
||||
# List to store prompt history
|
||||
self.conversation_history: List[Tuple[str, str]] = []
|
||||
self.prompt_queue: Deque[str] = deque()
|
||||
self.conversation_summary: Optional[str] = None
|
||||
self.continue_as_new_per_turns: int = 6
|
||||
self.chat_ended: bool = False
|
||||
|
||||
@workflow.run
|
||||
async def run(
|
||||
self,
|
||||
params: OllamaParams,
|
||||
) -> str:
|
||||
|
||||
if params and params.conversation_summary:
|
||||
self.conversation_history.append(
|
||||
("conversation_summary", params.conversation_summary)
|
||||
)
|
||||
|
||||
self.conversation_summary = params.conversation_summary
|
||||
|
||||
if params and params.prompt_queue:
|
||||
self.prompt_queue.extend(params.prompt_queue)
|
||||
|
||||
while True:
|
||||
workflow.logger.info("Waiting for prompts...")
|
||||
|
||||
# Wait for a chat message (signal) or timeout
|
||||
await workflow.wait_condition(
|
||||
lambda: bool(self.prompt_queue) or self.chat_ended
|
||||
)
|
||||
|
||||
if self.prompt_queue:
|
||||
# Fetch next user prompt and add to conversation history
|
||||
prompt = self.prompt_queue.popleft()
|
||||
self.conversation_history.append(("user", prompt))
|
||||
|
||||
workflow.logger.info("Prompt: " + prompt)
|
||||
|
||||
# Send prompt to Ollama
|
||||
response = await workflow.execute_activity_method(
|
||||
OllamaActivities.prompt_ollama,
|
||||
self.prompt_with_history(prompt),
|
||||
schedule_to_close_timeout=timedelta(seconds=20),
|
||||
)
|
||||
|
||||
workflow.logger.info(f"{response}")
|
||||
|
||||
# Append the response to the conversation history
|
||||
self.conversation_history.append(("response", response))
|
||||
|
||||
# Continue as new every x conversational turns to avoid event
|
||||
# history size getting too large. This is also to avoid the
|
||||
# prompt (with conversational history) getting too large for
|
||||
# AWS Ollama.
|
||||
|
||||
# We summarize the chat to date and use that as input to the
|
||||
# new workflow
|
||||
if len(self.conversation_history) >= self.continue_as_new_per_turns:
|
||||
# Summarize the conversation to date using Ollama
|
||||
self.conversation_summary = await workflow.start_activity_method(
|
||||
OllamaActivities.prompt_ollama,
|
||||
self.prompt_summary_from_history(),
|
||||
schedule_to_close_timeout=timedelta(seconds=20),
|
||||
)
|
||||
|
||||
workflow.logger.info(
|
||||
"Continuing as new due to %i conversational turns."
|
||||
% self.continue_as_new_per_turns,
|
||||
)
|
||||
|
||||
workflow.continue_as_new(
|
||||
args=[
|
||||
OllamaParams(
|
||||
self.conversation_summary,
|
||||
self.prompt_queue,
|
||||
)
|
||||
]
|
||||
)
|
||||
|
||||
continue
|
||||
|
||||
# If end chat signal was sent
|
||||
if self.chat_ended:
|
||||
# The workflow might be continued as new without any
|
||||
# chat to summarize, so only call Ollama if there
|
||||
# is more than the previous summary in the history.
|
||||
if len(self.conversation_history) > 1:
|
||||
# Summarize the conversation to date using Ollama
|
||||
self.conversation_summary = await workflow.start_activity_method(
|
||||
OllamaActivities.prompt_ollama,
|
||||
self.prompt_summary_from_history(),
|
||||
schedule_to_close_timeout=timedelta(seconds=20),
|
||||
)
|
||||
|
||||
workflow.logger.info(
|
||||
"Chat ended. Conversation summary:\n"
|
||||
+ f"{self.conversation_summary}"
|
||||
)
|
||||
|
||||
return f"{self.conversation_history}"
|
||||
|
||||
@workflow.signal
|
||||
async def user_prompt(self, prompt: str) -> None:
|
||||
# Chat ended but the workflow is waiting for a chat summary to be generated
|
||||
if self.chat_ended:
|
||||
workflow.logger.warn(f"Message dropped due to chat closed: {prompt}")
|
||||
return
|
||||
|
||||
self.prompt_queue.append(prompt)
|
||||
|
||||
@workflow.signal
|
||||
async def end_chat(self) -> None:
|
||||
self.chat_ended = True
|
||||
|
||||
@workflow.query
|
||||
def get_conversation_history(self) -> List[Tuple[str, str]]:
|
||||
return self.conversation_history
|
||||
|
||||
@workflow.query
|
||||
def get_summary_from_history(self) -> Optional[str]:
|
||||
return self.conversation_summary
|
||||
|
||||
# Helper method used in prompts to Ollama
|
||||
def format_history(self) -> str:
|
||||
return " ".join(f"{text}" for _, text in self.conversation_history)
|
||||
|
||||
# Create the prompt given to Ollama for each conversational turn
|
||||
def prompt_with_history(self, prompt: str) -> str:
|
||||
history_string = self.format_history()
|
||||
return (
|
||||
f"Here is the conversation history: {history_string} Please add "
|
||||
+ "a few sentence response to the prompt in plain text sentences. "
|
||||
+ "Don't editorialize or add metadata like response. Keep the "
|
||||
+ f"text a plain explanation based on the history. Prompt: {prompt}"
|
||||
)
|
||||
|
||||
# Create the prompt to Ollama to summarize the conversation history
|
||||
def prompt_summary_from_history(self) -> str:
|
||||
history_string = self.format_history()
|
||||
return (
|
||||
"Here is the conversation history between a user and a chatbot: "
|
||||
+ f"{history_string} -- Please produce a two sentence summary of "
|
||||
+ "this conversation."
|
||||
)
|
||||
Reference in New Issue
Block a user