Partial prompt templates in LangChain - Step-by-Step Execution

Concept Flow - Partial prompt templates

Define base prompt with placeholders

↓

Create partial prompt with .partial()

↓

Fill some placeholders

↓

Use partial template to create full prompt

↓

Send full prompt to LLM

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Get response

Shows how to create a prompt template with placeholders, partially fill some, then complete and send to the language model.

Execution Sample

LangChain

from langchain.prompts import PromptTemplate

base_prompt = PromptTemplate(
    input_variables=["name", "task"],
    template="Hello {name}, please help me with {task}."
)

partial_prompt = base_prompt.partial(name="Alice")

full_prompt = partial_prompt.format(task="writing code")
print(full_prompt)

Defines a prompt with two variables, partially fills 'name' using .partial(), then completes with 'task' and prints the full prompt.

Execution Table

Step	Action	Input Variables	Partial Variables	Resulting Prompt
1	Define base prompt	name, task	none	"Hello {name}, please help me with {task}."
2	Call base_prompt.partial(name="Alice")	task	name=Alice	"Hello Alice, please help me with {task}."
3	Format partial prompt with task	task=writing code	name=Alice	"Hello Alice, please help me with writing code."
4	Print full prompt	none	none	Hello Alice, please help me with writing code.
5	End	none	none	Execution complete

💡 All placeholders filled, prompt fully formatted and printed.

Variable Tracker

Variable	Start	After Step 2	After Step 3	Final
base_prompt.template	"Hello {name}, please help me with {task}."	"Hello {name}, please help me with {task}."	"Hello {name}, please help me with {task}."	"Hello {name}, please help me with {task}."
partial_variables	{}	{"name": "Alice"}	{"name": "Alice"}	{"name": "Alice"}
full_prompt	N/A	N/A	"Hello Alice, please help me with writing code."	"Hello Alice, please help me with writing code."

Key Moments - 2 Insights

Why does the partial prompt still have {task} after creating PartialPromptTemplate?

Because only 'name' was filled as a partial variable at Step 2, 'task' remains as a placeholder until formatting at Step 3.

What happens if we try to format the partial prompt without providing 'task'?

An error occurs because 'task' is still required and not yet filled, as shown by the need to provide 'task' at Step 3.

Visual Quiz - 3 Questions

Look at the execution table at Step 2. What does the prompt look like?

A "Hello {name}, please help me with writing code."

B "Hello Alice, please help me with writing code."

C "Hello Alice, please help me with {task}."

D "Hello {name}, please help me with {task}."

💡 Hint

Check the 'Resulting Prompt' column at Step 2 in the execution table.

At which step is the full prompt finally printed?

A Step 2

B Step 4

C Step 3

D Step 5

💡 Hint

Look for the step where the prompt is printed in the 'Action' column.

If we changed partial_variables to include 'task' instead of 'name', what would happen at Step 3?

A The prompt would still have {name} placeholder.

B The prompt would be fully formatted with no placeholders.

C An error would occur because 'name' is missing.

D The prompt would be unchanged from base.

💡 Hint

Refer to variable_tracker and how partial variables fill placeholders.

Concept Snapshot

Partial Prompt Templates in Langchain:
- Define a PromptTemplate with placeholders.
- Create partial PromptTemplate using .partial() by filling some placeholders.
- Format partial prompt with remaining variables.
- Result is a fully formatted prompt ready for LLM.
- Helps reuse prompt parts and fill variables stepwise.

Full Transcript

This visual execution shows how to use Partial Prompt Templates in Langchain. First, a base prompt is defined with placeholders for 'name' and 'task'. Then, a partial prompt is created by calling base_prompt.partial(name="Alice"). The partial prompt still has the 'task' placeholder. Next, the partial prompt is formatted by providing the 'task' value 'writing code'. This produces the full prompt: 'Hello Alice, please help me with writing code.' Finally, the prompt is printed. The execution table tracks each step, showing how placeholders are filled progressively. The variable tracker shows how the template and variables change. Key moments clarify why placeholders remain until fully formatted. The quiz tests understanding of prompt states at each step. This method helps build prompts flexibly by filling variables in parts.