Markdown JSON Mode (#246)

Co-authored-by: Jason Liu <jxnl@users.noreply.github.com>
This commit is contained in:
Anmol Jawandha
2023-12-01 16:52:37 -08:00
committed by GitHub
parent a5ea6e5c41
commit ae59ed434f
5 changed files with 141 additions and 8 deletions
+14
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@@ -40,6 +40,20 @@ from openai import OpenAI
client = instructor.patch(OpenAI(), mode=Mode.JSON)
```
## Markdown JSON Mode
!!! warning "Experimental"
This is not recommended, and may not be supported in the future, this is just left to support vision models.
```python
import instructor
from instructor import Mode
from openai import OpenAI
client = instructor.patch(OpenAI(), mode=Mode.MD_JSON)
```
### Schema Integration
In JSON Mode, the schema is part of the system message:
+63
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@@ -0,0 +1,63 @@
import instructor
from openai import OpenAI
from typing import Iterable
from pydantic import BaseModel
import base64
client = instructor.patch(OpenAI(), mode=instructor.function_calls.Mode.MD_JSON)
class Circle(BaseModel):
x: int
y: int
color: str
def encode_image(image_path):
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode('utf-8')
def draw_circle(image_size, num_circles, path):
from PIL import Image, ImageDraw
import random
image = Image.new("RGB", image_size, "white")
draw = ImageDraw.Draw(image)
for _ in range(num_circles):
# Randomize the circle properties
radius = 100#random.randint(10, min(image_size)//5) # Radius between 10 and 1/5th of the smallest dimension
x = random.randint(radius, image_size[0] - radius)
y = random.randint(radius, image_size[1] - radius)
color = ['red', 'black', 'blue', 'green'][random.randint(0, 3)]
circle_position = (x - radius, y - radius, x + radius, y + radius)
print(f"Generating circle at {x, y} with color {color}")
draw.ellipse(circle_position, fill=color, outline="black")
image.save(path)
img_path = 'circle.jpg'
draw_circle((1024,1024), 1, img_path)
base64_image = encode_image(img_path)
response = client.chat.completions.create(
model="gpt-4-vision-preview",
max_tokens=1800,
response_model=Circle,
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": 'find the circle'},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{base64_image}"
},
},
],
}
],
)
print(f"Found circle with center at x: {response.x}, y: {response.y} and color: {response.color}")
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@@ -1,4 +1,5 @@
import json
import re
from docstring_parser import parse
from functools import wraps
from typing import Any, Callable
@@ -13,6 +14,7 @@ class Mode(enum.Enum):
FUNCTIONS: str = "function_call"
TOOLS: str = "tool_call"
JSON: str = "json_mode"
MD_JSON: str = "markdown_json_mode"
class openai_function:
@@ -237,6 +239,12 @@ class OpenAISchema(BaseModel):
context=validation_context,
strict=strict,
)
elif mode == Mode.MD_JSON:
return cls.model_validate_json(
message.content,
context=validation_context,
strict=strict,
)
else:
raise ValueError(f"Invalid patch mode: {mode}")
+35 -8
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@@ -89,13 +89,27 @@ def handle_response_model(
"type": "function",
"function": {"name": response_model.openai_schema["name"]},
}
elif mode == Mode.JSON:
new_kwargs["response_format"] = {"type": "json_object"}
# check that the first message is a system message
# if it is not, add a system message to the beginning
message = f"Make sure that your response to any message matches the json_schema below, do not deviate at all: \n{response_model.model_json_schema()['properties']}"
elif mode == Mode.JSON or mode == Mode.MD_JSON:
if mode == Mode.JSON:
new_kwargs["response_format"] = {"type": "json_object"}
# check that the first message is a system message
# if it is not, add a system message to the beginning
message = f"""Make sure that your response to any message matches the json_schema below,
do not deviate at all: \n{response_model.model_json_schema()['properties']}
"""
else:
message = f"""
As a genius expert, your task is to understand the content and provide
the parsed objects in json that match the following json_schema (do not deviate at all and its okay if you cant be exact):\n
{response_model.model_json_schema()['properties']}
"""
new_kwargs["messages"].append(
{
"role": "assistant",
"content": "```json",
},
)
new_kwargs["stop"] = "```"
if new_kwargs["messages"][0]["role"] != "system":
new_kwargs["messages"].insert(
0,
@@ -110,7 +124,6 @@ def handle_response_model(
new_kwargs["messages"][0]["content"] += f"\n\n{message}"
else:
raise ValueError(f"Invalid patch mode: {mode}")
return response_model, new_kwargs
@@ -182,6 +195,13 @@ async def retry_async(
"content": f"Recall the function correctly, exceptions found\n{e}",
}
)
if mode == Mode.MD_JSON:
kwargs["messages"].append(
{
"role": "assistant",
"content": "```json",
},
)
retries += 1
if retries > max_retries:
raise e
@@ -219,6 +239,13 @@ def retry_sync(
"content": f"Recall the function correctly, exceptions found\n{e}",
}
)
if mode == Mode.MD_JSON:
kwargs["messages"].append(
{
"role": "assistant",
"content": "```json",
},
)
retries += 1
if retries > max_retries:
raise e
+21
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@@ -62,6 +62,27 @@ def test_json_mode():
assert user.age == 25
def test_markdown_json_mode():
response = client.chat.completions.create(
model="gpt-3.5-turbo-1106",
response_format={"type": "json_object"},
messages=[
{
"role": "system",
"content": f"Make sure that your response to any message matchs the json_schema below, do not deviate at all: \n{UserExtract.model_json_schema()['properties']}",
},
{
"role": "user",
"content": "Extract jason is 25 years old",
},
],
)
user = UserExtract.from_response(response, mode=Mode.MD_JSON)
assert user.name.lower() == "jason"
assert user.age == 25
@pytest.mark.parametrize("mode", [Mode.FUNCTIONS, Mode.JSON, Mode.TOOLS])
def test_mode(mode):
client = instructor.patch(OpenAI(), mode=mode)