diff --git a/.changeset/fair-pets-leave.md b/.changeset/fair-pets-leave.md
new file mode 100644
index 0000000000000000000000000000000000000000..9b74c155568ba80dccb1c00486b5d055e5e6c1c7
--- /dev/null
+++ b/.changeset/fair-pets-leave.md
@@ -0,0 +1,5 @@
+---
+"llamaindex": patch
+---
+
+Strong types for prompts.
diff --git a/apps/simple/csv.ts b/apps/simple/csv.ts
index d1c413ce97ea06dcc8e824d472e69a8e2c5775ef..1e0a11237297b086fbc0c2d20b38ef6bea68c818 100644
--- a/apps/simple/csv.ts
+++ b/apps/simple/csv.ts
@@ -4,7 +4,6 @@ import {
PapaCSVReader,
ResponseSynthesizer,
serviceContextFromDefaults,
- SimplePrompt,
VectorStoreIndex,
} from "llamaindex";
@@ -23,9 +22,7 @@ async function main() {
serviceContext,
});
- const csvPrompt: SimplePrompt = (input) => {
- const { context = "", query = "" } = input;
-
+ const csvPrompt = ({ context = "", query = "" }) => {
return `The following CSV file is loaded from ${path}
\`\`\`csv
${context}
diff --git a/apps/simple/openai.ts b/apps/simple/openai.ts
index 1c40fb9ba5a556af8d135449369f0044ef51b5ea..4c7856be0ab9e5912cac3ca119416c6157c750ad 100644
--- a/apps/simple/openai.ts
+++ b/apps/simple/openai.ts
@@ -1,14 +1,7 @@
import { OpenAI } from "llamaindex";
(async () => {
- const llm = new OpenAI({
- model: "gpt-3.5-turbo",
- temperature: 0.1,
- additionalChatOptions: { frequency_penalty: 0.1 },
- additionalSessionOptions: {
- defaultHeaders: { "X-Test-Header-Please-Ignore": "true" },
- },
- });
+ const llm = new OpenAI({ model: "gpt-3.5-turbo", temperature: 0.0 });
// complete api
const response1 = await llm.complete("How are you?");
diff --git a/apps/simple/vectorIndexCustomize.ts b/apps/simple/vectorIndexCustomize.ts
index b9dbe8d8bbeb1f3619a139fc9f295d79bb934200..5ad55cff6c50defaca130c1e1cefe43857564741 100644
--- a/apps/simple/vectorIndexCustomize.ts
+++ b/apps/simple/vectorIndexCustomize.ts
@@ -12,7 +12,7 @@ async function main() {
const document = new Document({ text: essay, id_: "essay" });
const serviceContext = serviceContextFromDefaults({
- llm: new OpenAI({ model: "gpt-3.5-turbo", temperature: 0.0 }),
+ llm: new OpenAI({ model: "gpt-3.5-turbo", temperature: 0.1 }),
});
const index = await VectorStoreIndex.fromDocuments([document], {
diff --git a/examples/csv.ts b/examples/csv.ts
index d1c413ce97ea06dcc8e824d472e69a8e2c5775ef..1e0a11237297b086fbc0c2d20b38ef6bea68c818 100644
--- a/examples/csv.ts
+++ b/examples/csv.ts
@@ -4,7 +4,6 @@ import {
PapaCSVReader,
ResponseSynthesizer,
serviceContextFromDefaults,
- SimplePrompt,
VectorStoreIndex,
} from "llamaindex";
@@ -23,9 +22,7 @@ async function main() {
serviceContext,
});
- const csvPrompt: SimplePrompt = (input) => {
- const { context = "", query = "" } = input;
-
+ const csvPrompt = ({ context = "", query = "" }) => {
return `The following CSV file is loaded from ${path}
\`\`\`csv
${context}
diff --git a/examples/openai.ts b/examples/openai.ts
index f53709c6495d2a098a439e97b1a1f54321ec6ca3..4c7856be0ab9e5912cac3ca119416c6157c750ad 100644
--- a/examples/openai.ts
+++ b/examples/openai.ts
@@ -2,12 +2,14 @@ import { OpenAI } from "llamaindex";
(async () => {
const llm = new OpenAI({ model: "gpt-3.5-turbo", temperature: 0.0 });
-
+
// complete api
const response1 = await llm.complete("How are you?");
console.log(response1.message.content);
// chat api
- const response2 = await llm.chat([{ content: "Tell me a joke!", role: "user" }]);
+ const response2 = await llm.chat([
+ { content: "Tell me a joke!", role: "user" },
+ ]);
console.log(response2.message.content);
})();
diff --git a/examples/vectorIndexCustomize.ts b/examples/vectorIndexCustomize.ts
index b9dbe8d8bbeb1f3619a139fc9f295d79bb934200..5ad55cff6c50defaca130c1e1cefe43857564741 100644
--- a/examples/vectorIndexCustomize.ts
+++ b/examples/vectorIndexCustomize.ts
@@ -12,7 +12,7 @@ async function main() {
const document = new Document({ text: essay, id_: "essay" });
const serviceContext = serviceContextFromDefaults({
- llm: new OpenAI({ model: "gpt-3.5-turbo", temperature: 0.0 }),
+ llm: new OpenAI({ model: "gpt-3.5-turbo", temperature: 0.1 }),
});
const index = await VectorStoreIndex.fromDocuments([document], {
diff --git a/packages/core/src/ChatEngine.ts b/packages/core/src/ChatEngine.ts
index 1cc847569e1fc2b630bf189981acf87416b3ab0c..9ba53f5fe5545c04d8560b2d14e892aee969ef2b 100644
--- a/packages/core/src/ChatEngine.ts
+++ b/packages/core/src/ChatEngine.ts
@@ -1,17 +1,18 @@
-import { ChatMessage, OpenAI, ChatResponse, LLM } from "./llm/LLM";
+import { v4 as uuidv4 } from "uuid";
import { TextNode } from "./Node";
import {
- SimplePrompt,
- contextSystemPrompt,
+ CondenseQuestionPrompt,
+ ContextSystemPrompt,
defaultCondenseQuestionPrompt,
+ defaultContextSystemPrompt,
messagesToHistoryStr,
} from "./Prompt";
import { BaseQueryEngine } from "./QueryEngine";
import { Response } from "./Response";
import { BaseRetriever } from "./Retriever";
import { ServiceContext, serviceContextFromDefaults } from "./ServiceContext";
-import { v4 as uuidv4 } from "uuid";
import { Event } from "./callbacks/CallbackManager";
+import { ChatMessage, LLM, OpenAI } from "./llm/LLM";
/**
* A ChatEngine is used to handle back and forth chats between the application and the LLM.
@@ -70,13 +71,13 @@ export class CondenseQuestionChatEngine implements ChatEngine {
queryEngine: BaseQueryEngine;
chatHistory: ChatMessage[];
serviceContext: ServiceContext;
- condenseMessagePrompt: SimplePrompt;
+ condenseMessagePrompt: CondenseQuestionPrompt;
constructor(init: {
queryEngine: BaseQueryEngine;
chatHistory: ChatMessage[];
serviceContext?: ServiceContext;
- condenseMessagePrompt?: SimplePrompt;
+ condenseMessagePrompt?: CondenseQuestionPrompt;
}) {
this.queryEngine = init.queryEngine;
this.chatHistory = init?.chatHistory ?? [];
@@ -92,14 +93,14 @@ export class CondenseQuestionChatEngine implements ChatEngine {
return this.serviceContext.llm.complete(
defaultCondenseQuestionPrompt({
question: question,
- chat_history: chatHistoryStr,
- })
+ chatHistory: chatHistoryStr,
+ }),
);
}
async chat(
message: string,
- chatHistory?: ChatMessage[] | undefined
+ chatHistory?: ChatMessage[] | undefined,
): Promise<Response> {
chatHistory = chatHistory ?? this.chatHistory;
@@ -129,16 +130,20 @@ export class ContextChatEngine implements ChatEngine {
retriever: BaseRetriever;
chatModel: OpenAI;
chatHistory: ChatMessage[];
+ contextSystemPrompt: ContextSystemPrompt;
constructor(init: {
retriever: BaseRetriever;
chatModel?: OpenAI;
chatHistory?: ChatMessage[];
+ contextSystemPrompt?: ContextSystemPrompt;
}) {
this.retriever = init.retriever;
this.chatModel =
init.chatModel ?? new OpenAI({ model: "gpt-3.5-turbo-16k" });
this.chatHistory = init?.chatHistory ?? [];
+ this.contextSystemPrompt =
+ init?.contextSystemPrompt ?? defaultContextSystemPrompt;
}
async chat(message: string, chatHistory?: ChatMessage[] | undefined) {
@@ -151,11 +156,11 @@ export class ContextChatEngine implements ChatEngine {
};
const sourceNodesWithScore = await this.retriever.retrieve(
message,
- parentEvent
+ parentEvent,
);
const systemMessage: ChatMessage = {
- content: contextSystemPrompt({
+ content: this.contextSystemPrompt({
context: sourceNodesWithScore
.map((r) => (r.node as TextNode).text)
.join("\n\n"),
@@ -167,7 +172,7 @@ export class ContextChatEngine implements ChatEngine {
const response = await this.chatModel.chat(
[systemMessage, ...chatHistory],
- parentEvent
+ parentEvent,
);
chatHistory.push(response.message);
@@ -175,7 +180,7 @@ export class ContextChatEngine implements ChatEngine {
return new Response(
response.message.content,
- sourceNodesWithScore.map((r) => r.node)
+ sourceNodesWithScore.map((r) => r.node),
);
}
diff --git a/packages/core/src/Prompt.ts b/packages/core/src/Prompt.ts
index d6ccde84ec4703629773c20b58cf391c193b1f0b..86e1a4fd4c8a9d0c96c8c4547567e48f135698f8 100644
--- a/packages/core/src/Prompt.ts
+++ b/packages/core/src/Prompt.ts
@@ -22,9 +22,7 @@ DEFAULT_TEXT_QA_PROMPT_TMPL = (
)
*/
-export const defaultTextQaPrompt: SimplePrompt = (input) => {
- const { context = "", query = "" } = input;
-
+export const defaultTextQaPrompt = ({ context = "", query = "" }) => {
return `Context information is below.
---------------------
${context}
@@ -34,6 +32,8 @@ Query: ${query}
Answer:`;
};
+export type TextQaPrompt = typeof defaultTextQaPrompt;
+
/*
DEFAULT_SUMMARY_PROMPT_TMPL = (
"Write a summary of the following. Try to use only the "
@@ -48,9 +48,7 @@ DEFAULT_SUMMARY_PROMPT_TMPL = (
)
*/
-export const defaultSummaryPrompt: SimplePrompt = (input) => {
- const { context = "" } = input;
-
+export const defaultSummaryPrompt = ({ context = "" }) => {
return `Write a summary of the following. Try to use only the information provided. Try to include as many key details as possible.
@@ -61,6 +59,8 @@ SUMMARY:"""
`;
};
+export type SummaryPrompt = typeof defaultSummaryPrompt;
+
/*
DEFAULT_REFINE_PROMPT_TMPL = (
"The original query is as follows: {query_str}\n"
@@ -77,9 +77,11 @@ DEFAULT_REFINE_PROMPT_TMPL = (
)
*/
-export const defaultRefinePrompt: SimplePrompt = (input) => {
- const { query = "", existingAnswer = "", context = "" } = input;
-
+export const defaultRefinePrompt = ({
+ query = "",
+ existingAnswer = "",
+ context = "",
+}) => {
return `The original query is as follows: ${query}
We have provided an existing answer: ${existingAnswer}
We have the opportunity to refine the existing answer (only if needed) with some more context below.
@@ -90,6 +92,8 @@ Given the new context, refine the original answer to better answer the query. If
Refined Answer:`;
};
+export type RefinePrompt = typeof defaultRefinePrompt;
+
/*
DEFAULT_TREE_SUMMARIZE_TMPL = (
"Context information from multiple sources is below.\n"
@@ -103,9 +107,7 @@ DEFAULT_TREE_SUMMARIZE_TMPL = (
)
*/
-export const defaultTreeSummarizePrompt: SimplePrompt = (input) => {
- const { context = "", query = "" } = input;
-
+export const defaultTreeSummarizePrompt = ({ context = "", query = "" }) => {
return `Context information from multiple sources is below.
---------------------
${context}
@@ -115,9 +117,9 @@ Query: ${query}
Answer:`;
};
-export const defaultChoiceSelectPrompt: SimplePrompt = (input) => {
- const { context = "", query = "" } = input;
+export type TreeSummarizePrompt = typeof defaultTreeSummarizePrompt;
+export const defaultChoiceSelectPrompt = ({ context = "", query = "" }) => {
return `A list of documents is shown below. Each document has a number next to it along
with a summary of the document. A question is also provided.
Respond with the numbers of the documents
@@ -149,6 +151,8 @@ Question: ${query}
Answer:`;
};
+export type ChoiceSelectPrompt = typeof defaultChoiceSelectPrompt;
+
/*
PREFIX = """\
Given a user question, and a list of tools, output a list of relevant sub-questions \
@@ -266,9 +270,7 @@ const exampleOutput: SubQuestion[] = [
},
];
-export const defaultSubQuestionPrompt: SimplePrompt = (input) => {
- const { toolsStr, queryStr } = input;
-
+export const defaultSubQuestionPrompt = ({ toolsStr = "", queryStr = "" }) => {
return `Given a user question, and a list of tools, output a list of relevant sub-questions that when composed can help answer the full user question:
# Example 1
@@ -298,6 +300,8 @@ ${queryStr}
`;
};
+export type SubQuestionPrompt = typeof defaultSubQuestionPrompt;
+
// DEFAULT_TEMPLATE = """\
// Given a conversation (between Human and Assistant) and a follow up message from Human, \
// rewrite the message to be a standalone question that captures all relevant context \
@@ -312,9 +316,10 @@ ${queryStr}
// <Standalone question>
// """
-export const defaultCondenseQuestionPrompt: SimplePrompt = (input) => {
- const { chatHistory, question } = input;
-
+export const defaultCondenseQuestionPrompt = ({
+ chatHistory = "",
+ question = "",
+}) => {
return `Given a conversation (between Human and Assistant) and a follow up message from Human, rewrite the message to be a standalone question that captures all relevant context from the conversation.
<Chat History>
@@ -327,6 +332,8 @@ ${question}
`;
};
+export type CondenseQuestionPrompt = typeof defaultCondenseQuestionPrompt;
+
export function messagesToHistoryStr(messages: ChatMessage[]) {
return messages.reduce((acc, message) => {
acc += acc ? "\n" : "";
@@ -339,11 +346,11 @@ export function messagesToHistoryStr(messages: ChatMessage[]) {
}, "");
}
-export const contextSystemPrompt: SimplePrompt = (input) => {
- const { context } = input;
-
+export const defaultContextSystemPrompt = ({ context = "" }) => {
return `Context information is below.
---------------------
${context}
---------------------`;
};
+
+export type ContextSystemPrompt = typeof defaultContextSystemPrompt;
diff --git a/packages/core/src/QuestionGenerator.ts b/packages/core/src/QuestionGenerator.ts
index 24d46e954938be822d9ca8bac2dc984d6508d2bc..ada522b5715441c9f03567fc66b73b4d51901301 100644
--- a/packages/core/src/QuestionGenerator.ts
+++ b/packages/core/src/QuestionGenerator.ts
@@ -4,7 +4,7 @@ import {
SubQuestionOutputParser,
} from "./OutputParser";
import {
- SimplePrompt,
+ SubQuestionPrompt,
buildToolsText,
defaultSubQuestionPrompt,
} from "./Prompt";
@@ -28,7 +28,7 @@ export interface BaseQuestionGenerator {
*/
export class LLMQuestionGenerator implements BaseQuestionGenerator {
llm: LLM;
- prompt: SimplePrompt;
+ prompt: SubQuestionPrompt;
outputParser: BaseOutputParser<StructuredOutput<SubQuestion[]>>;
constructor(init?: Partial<LLMQuestionGenerator>) {
@@ -45,7 +45,7 @@ export class LLMQuestionGenerator implements BaseQuestionGenerator {
this.prompt({
toolsStr,
queryStr,
- })
+ }),
)
).message.content;
diff --git a/packages/core/src/ResponseSynthesizer.ts b/packages/core/src/ResponseSynthesizer.ts
index d781d5a198b1252f5b80bd033c8a7dbce0d7d3d2..912c02516eb2f7fc1f6cb2ac6b3424352af5a41f 100644
--- a/packages/core/src/ResponseSynthesizer.ts
+++ b/packages/core/src/ResponseSynthesizer.ts
@@ -1,6 +1,9 @@
import { MetadataMode, NodeWithScore } from "./Node";
import {
+ RefinePrompt,
SimplePrompt,
+ TextQaPrompt,
+ TreeSummarizePrompt,
defaultRefinePrompt,
defaultTextQaPrompt,
defaultTreeSummarizePrompt,
@@ -73,13 +76,13 @@ export class SimpleResponseBuilder implements BaseResponseBuilder {
*/
export class Refine implements BaseResponseBuilder {
serviceContext: ServiceContext;
- textQATemplate: SimplePrompt;
- refineTemplate: SimplePrompt;
+ textQATemplate: TextQaPrompt;
+ refineTemplate: RefinePrompt;
constructor(
serviceContext: ServiceContext,
- textQATemplate?: SimplePrompt,
- refineTemplate?: SimplePrompt,
+ textQATemplate?: TextQaPrompt,
+ refineTemplate?: RefinePrompt,
) {
this.serviceContext = serviceContext;
this.textQATemplate = textQATemplate ?? defaultTextQaPrompt;
@@ -209,9 +212,14 @@ export class CompactAndRefine extends Refine {
*/
export class TreeSummarize implements BaseResponseBuilder {
serviceContext: ServiceContext;
+ summaryTemplate: TreeSummarizePrompt;
- constructor(serviceContext: ServiceContext) {
+ constructor(
+ serviceContext: ServiceContext,
+ summaryTemplate?: TreeSummarizePrompt,
+ ) {
this.serviceContext = serviceContext;
+ this.summaryTemplate = summaryTemplate ?? defaultTreeSummarizePrompt;
}
async getResponse(
@@ -219,21 +227,19 @@ export class TreeSummarize implements BaseResponseBuilder {
textChunks: string[],
parentEvent?: Event,
): Promise<string> {
- const summaryTemplate: SimplePrompt = defaultTreeSummarizePrompt;
-
if (!textChunks || textChunks.length === 0) {
throw new Error("Must have at least one text chunk");
}
const packedTextChunks = this.serviceContext.promptHelper.repack(
- summaryTemplate,
+ this.summaryTemplate,
textChunks,
);
if (packedTextChunks.length === 1) {
return (
await this.serviceContext.llm.complete(
- summaryTemplate({
+ this.summaryTemplate({
context: packedTextChunks[0],
}),
parentEvent,
@@ -243,7 +249,7 @@ export class TreeSummarize implements BaseResponseBuilder {
const summaries = await Promise.all(
packedTextChunks.map((chunk) =>
this.serviceContext.llm.complete(
- summaryTemplate({
+ this.summaryTemplate({
context: chunk,
}),
parentEvent,
@@ -298,9 +304,13 @@ export class ResponseSynthesizer {
this.metadataMode = metadataMode;
}
- async synthesize(query: string, nodes: NodeWithScore[], parentEvent?: Event) {
- let textChunks: string[] = nodes.map((node) =>
- node.node.getContent(this.metadataMode)
+ async synthesize(
+ query: string,
+ nodesWithScore: NodeWithScore[],
+ parentEvent?: Event,
+ ) {
+ let textChunks: string[] = nodesWithScore.map(({ node }) =>
+ node.getContent(this.metadataMode),
);
const response = await this.responseBuilder.getResponse(
query,
@@ -309,7 +319,7 @@ export class ResponseSynthesizer {
);
return new Response(
response,
- nodes.map((node) => node.node),
+ nodesWithScore.map(({ node }) => node),
);
}
}
diff --git a/packages/core/src/indices/summary/SummaryIndexRetriever.ts b/packages/core/src/indices/summary/SummaryIndexRetriever.ts
index 61d9f2180e26643ebe34ef6f23088d31a1365d98..c7259ed8fd6af6fa97cb8d924ca8f3437109931a 100644
--- a/packages/core/src/indices/summary/SummaryIndexRetriever.ts
+++ b/packages/core/src/indices/summary/SummaryIndexRetriever.ts
@@ -1,7 +1,7 @@
import _ from "lodash";
import { globalsHelper } from "../../GlobalsHelper";
import { NodeWithScore } from "../../Node";
-import { SimplePrompt, defaultChoiceSelectPrompt } from "../../Prompt";
+import { ChoiceSelectPrompt, defaultChoiceSelectPrompt } from "../../Prompt";
import { BaseRetriever } from "../../Retriever";
import { ServiceContext } from "../../ServiceContext";
import { Event } from "../../callbacks/CallbackManager";
@@ -55,7 +55,7 @@ export class SummaryIndexRetriever implements BaseRetriever {
*/
export class SummaryIndexLLMRetriever implements BaseRetriever {
index: SummaryIndex;
- choiceSelectPrompt: SimplePrompt;
+ choiceSelectPrompt: ChoiceSelectPrompt;
choiceBatchSize: number;
formatNodeBatchFn: NodeFormatterFunction;
parseChoiceSelectAnswerFn: ChoiceSelectParserFunction;
@@ -63,7 +63,7 @@ export class SummaryIndexLLMRetriever implements BaseRetriever {
constructor(
index: SummaryIndex,
- choiceSelectPrompt?: SimplePrompt,
+ choiceSelectPrompt?: ChoiceSelectPrompt,
choiceBatchSize: number = 10,
formatNodeBatchFn?: NodeFormatterFunction,
parseChoiceSelectAnswerFn?: ChoiceSelectParserFunction,