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Allow hooks object for client creation #60

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46 changes: 31 additions & 15 deletions cohort_1/week2_question_classification/classify_with_yaml/yaml_classifier.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
from instructor import Instructor, AsyncInstructor
from jinja2 import Template
from textwrap import dedent
from typing import Type, TypeVar
from typing import Type, TypeVar, Any

T = TypeVar("T", bound=BaseModel)

Expand Down Expand Up @@ -115,35 +115,51 @@ def set_client(self, client: Instructor):
self._client = client

def predict(
self, query: str, model: str, response_model: Type[T], client: Instructor
self,
query: str,
model: str,
response_model: Type[T],
client: Instructor,
hooks: Any | None = None,
):
system_message = self.to_system_messages()
user_query = self.get_user_query(query)
return client.create(
model=model,
response_model=response_model,
messages=[
kwargs = {
"model": model,
"response_model": response_model,
"messages": [
{"role": "system", "content": system_message},
{"role": "user", "content": user_query},
],
validation_context={
"validation_context": {
"labels": self.get_labels(),
},
)
}
if hooks is not None:
kwargs["hooks"] = hooks
return client.create(**kwargs)

async def apredict(
self, query: str, model: str, response_model: Type[T], client: AsyncInstructor
self,
query: str,
model: str,
response_model: Type[T],
client: AsyncInstructor,
hooks: Any | None = None,
):
system_message = self.to_system_messages()
user_query = self.get_user_query(query)
return await client.create(
messages=[
kwargs = {
"messages": [
{"role": "system", "content": system_message},
{"role": "user", "content": user_query},
],
model=model,
response_model=response_model,
validation_context={
"model": model,
"response_model": response_model,
"validation_context": {
"labels": self.get_labels(),
},
)
}
if hooks is not None:
kwargs["hooks"] = hooks
return await client.create(**kwargs)
80 changes: 50 additions & 30 deletions latest/case_study/core/summarization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@ class ConversationSummary(BaseModel):
async def conversation_summary_v1(
client, # instructor-patched client
messages: List[Dict[str, Any]],
hooks: Any | None = None,
) -> ConversationSummary:
"""
Generate a concise summary focused on key topics and searchable terms.
Expand Down Expand Up @@ -61,19 +62,23 @@ async def conversation_summary_v1(
Generate a concise, searchable summary of this conversation.
"""

response = await client.chat.completions.create(
response_model=ConversationSummary,
messages=[{"role": "user", "content": prompt}],
context={"messages": messages},
max_retries=3,
)
kwargs = {
"response_model": ConversationSummary,
"messages": [{"role": "user", "content": prompt}],
"context": {"messages": messages},
"max_retries": 3,
}
if hooks is not None:
kwargs["hooks"] = hooks
response = await client.chat.completions.create(**kwargs)

return response


async def conversation_summary_v2(
client, # instructor-patched client
messages: List[Dict[str, Any]],
hooks: Any | None = None,
) -> ConversationSummary:
"""
Generate a comprehensive summary that captures conversation patterns, themes, and user interaction dynamics.
Expand Down Expand Up @@ -278,25 +283,29 @@ async def conversation_summary_v2(
{% endfor %}
"""

response = await client.chat.completions.create(
response_model=ConversationSummary,
messages=[
kwargs = {
"response_model": ConversationSummary,
"messages": [
{
"role": "system",
"content": "You are an expert at analyzing and categorizing human-AI conversations, focusing on patterns, themes, interaction characteristics, and user experience dynamics across all types of conversations.",
},
{"role": "user", "content": prompt},
],
context={"messages": messages},
max_retries=3,
)
"context": {"messages": messages},
"max_retries": 3,
}
if hooks is not None:
kwargs["hooks"] = hooks
response = await client.chat.completions.create(**kwargs)

return response


async def conversation_summary_v3(
client, # instructor-patched client
messages: List[Dict[str, Any]],
hooks: Any | None = None,
) -> ConversationSummary:
"""
Generate a concise pattern-focused summary that bridges content and patterns.
Expand Down Expand Up @@ -361,25 +370,29 @@ async def conversation_summary_v3(
Generate a concise, pattern-aware summary that balances content and conversation dynamics.
"""

response = await client.chat.completions.create(
response_model=ConversationSummary,
messages=[
kwargs = {
"response_model": ConversationSummary,
"messages": [
{
"role": "system",
"content": "You are an expert at creating concise summaries that capture both what was discussed and how the conversation unfolded. Balance pattern recognition with content summary.",
},
{"role": "user", "content": prompt},
],
context={"messages": messages},
max_retries=3,
)
"context": {"messages": messages},
"max_retries": 3,
}
if hooks is not None:
kwargs["hooks"] = hooks
response = await client.chat.completions.create(**kwargs)

return response


async def conversation_summary_v4(
client, # instructor-patched client
messages: List[Dict[str, Any]],
hooks: Any | None = None,
) -> ConversationSummary:
"""
Generate a pattern-focused summary optimized for v2-style queries.
Expand Down Expand Up @@ -461,25 +474,29 @@ async def conversation_summary_v4(
Generate a pattern-focused summary that would be discoverable by researchers looking for specific conversation types and interaction patterns.
"""

response = await client.chat.completions.create(
response_model=ConversationSummary,
messages=[
kwargs = {
"response_model": ConversationSummary,
"messages": [
{
"role": "system",
"content": "You are an expert at categorizing conversations by their patterns, types, and interaction dynamics. Focus on creating summaries that match how researchers search for conversation patterns rather than specific content.",
},
{"role": "user", "content": prompt},
],
context={"messages": messages},
max_retries=3,
)
"context": {"messages": messages},
"max_retries": 3,
}
if hooks is not None:
kwargs["hooks"] = hooks
response = await client.chat.completions.create(**kwargs)

return response


async def conversation_summary_v5(
client, # instructor-patched client
messages: List[Dict[str, Any]],
hooks: Any | None = None,
) -> ConversationSummary:
"""
Generate summaries optimized for AI agent failure analysis and improvement identification.
Expand Down Expand Up @@ -539,17 +556,20 @@ async def conversation_summary_v5(
Generate a balanced summary optimized for both pattern and content queries.
"""

response = await client.chat.completions.create(
response_model=ConversationSummary,
messages=[
kwargs = {
"response_model": ConversationSummary,
"messages": [
{
"role": "system",
"content": "You are an expert at analyzing AI conversations for system improvement. Focus on identifying failure patterns, root causes, and specific opportunities for enhancement. Your summaries should enable data-driven decisions about where to invest development effort.",
},
{"role": "user", "content": prompt},
],
context={"messages": messages},
max_retries=3,
)
"context": {"messages": messages},
"max_retries": 3,
}
if hooks is not None:
kwargs["hooks"] = hooks
response = await client.chat.completions.create(**kwargs)

return response
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