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194 changes: 91 additions & 103 deletions packages/web/src/features/chat/agent.ts
Original file line number Diff line number Diff line change
Expand Up @@ -42,115 +42,103 @@ export const createAgentStream = async ({
searchScopeRepoNames,
});

const stream = streamText({
model,
providerOptions,
system: baseSystemPrompt,
messages: inputMessages,
tools: {
[toolNames.searchCode]: createCodeSearchTool(searchScopeRepoNames),
[toolNames.readFiles]: readFilesTool,
[toolNames.findSymbolReferences]: findSymbolReferencesTool,
[toolNames.findSymbolDefinitions]: findSymbolDefinitionsTool,
[toolNames.searchRepos]: searchReposTool,
[toolNames.listAllRepos]: listAllReposTool,
},
prepareStep: async ({ stepNumber }) => {
// The first step attaches any mentioned sources to the system prompt.
if (stepNumber === 0 && inputSources.length > 0) {
const fileSources = inputSources.filter((source) => source.type === 'file');

const resolvedFileSources = (
await Promise.all(fileSources.map(resolveFileSource)))
.filter((source) => source !== undefined)

const fileSourcesSystemPrompt = await createFileSourcesSystemPrompt({
files: resolvedFileSources
});

return {
system: `${baseSystemPrompt}\n\n${fileSourcesSystemPrompt}`
}
}

if (stepNumber === env.SOURCEBOT_CHAT_MAX_STEP_COUNT - 1) {
return {
system: `**CRITICAL**: You have reached the maximum number of steps!! YOU MUST PROVIDE YOUR FINAL ANSWER NOW. DO NOT KEEP RESEARCHING.\n\n${answerInstructions}`,
activeTools: [],
let stream;
try {
stream = streamText({
model,
providerOptions,
system: baseSystemPrompt,
messages: inputMessages,
tools: {
[toolNames.searchCode]: createCodeSearchTool(searchScopeRepoNames),
[toolNames.readFiles]: readFilesTool,
[toolNames.findSymbolReferences]: findSymbolReferencesTool,
[toolNames.findSymbolDefinitions]: findSymbolDefinitionsTool,
[toolNames.searchRepos]: searchReposTool,
[toolNames.listAllRepos]: listAllReposTool,
},
prepareStep: async ({ stepNumber }) => {
if (stepNumber === 0 && inputSources.length > 0) {
const fileSources = inputSources.filter((source) => source.type === 'file');
const resolvedFileSources = (
await Promise.all(fileSources.map(resolveFileSource)))
.filter((source) => source !== undefined)
const fileSourcesSystemPrompt = await createFileSourcesSystemPrompt({
files: resolvedFileSources
});
return {
system: `${baseSystemPrompt}\n\n${fileSourcesSystemPrompt}`
}
}
}

return undefined;
},
temperature: env.SOURCEBOT_CHAT_MODEL_TEMPERATURE,
stopWhen: [
stepCountIsGTE(env.SOURCEBOT_CHAT_MAX_STEP_COUNT),
],
toolChoice: "auto", // Let the model decide when to use tools
onStepFinish: ({ toolResults }) => {
// This takes care of extracting any sources that the LLM has seen as part of
// the tool calls it made.
toolResults.forEach(({ toolName, output, dynamic }) => {
// we don't care about dynamic tool results here.
if (dynamic) {
return;
if (stepNumber === env.SOURCEBOT_CHAT_MAX_STEP_COUNT - 1) {
return {
system: `**CRITICAL**: You have reached the maximum number of steps!! YOU MUST PROVIDE YOUR FINAL ANSWER NOW. DO NOT KEEP RESEARCHING.\n\n${answerInstructions}`,
activeTools: [],
}
}

if (isServiceError(output)) {
// is there something we want to do here?
return;
}

if (toolName === toolNames.readFiles) {
output.forEach((file) => {
onWriteSource({
type: 'file',
language: file.language,
repo: file.repository,
path: file.path,
revision: file.revision,
name: file.path.split('/').pop() ?? file.path,
return undefined;
},
temperature: env.SOURCEBOT_CHAT_MODEL_TEMPERATURE,
stopWhen: [
stepCountIsGTE(env.SOURCEBOT_CHAT_MAX_STEP_COUNT),
],
toolChoice: "auto",
onStepFinish: ({ toolResults }) => {
toolResults.forEach(({ toolName, output, dynamic }) => {
if (dynamic) return;
if (isServiceError(output)) return;
if (toolName === toolNames.readFiles) {
output.forEach((file) => {
onWriteSource({
type: 'file',
language: file.language,
repo: file.repository,
path: file.path,
revision: file.revision,
name: file.path.split('/').pop() ?? file.path,
})
})
})
}
else if (toolName === toolNames.searchCode) {
output.files.forEach((file) => {
onWriteSource({
type: 'file',
language: file.language,
repo: file.repository,
path: file.fileName,
revision: file.revision,
name: file.fileName.split('/').pop() ?? file.fileName,
} else if (toolName === toolNames.searchCode) {
output.files.forEach((file) => {
onWriteSource({
type: 'file',
language: file.language,
repo: file.repository,
path: file.fileName,
revision: file.revision,
name: file.fileName.split('/').pop() ?? file.fileName,
})
})
})
}
else if (toolName === toolNames.findSymbolDefinitions || toolName === toolNames.findSymbolReferences) {
output.forEach((file) => {
onWriteSource({
type: 'file',
language: file.language,
repo: file.repository,
path: file.fileName,
revision: file.revision,
name: file.fileName.split('/').pop() ?? file.fileName,
} else if (toolName === toolNames.findSymbolDefinitions || toolName === toolNames.findSymbolReferences) {
output.forEach((file) => {
onWriteSource({
type: 'file',
language: file.language,
repo: file.repository,
path: file.fileName,
revision: file.revision,
name: file.fileName.split('/').pop() ?? file.fileName,
})
})
})
}
})
},
// Only enable langfuse traces in cloud environments.
experimental_telemetry: {
isEnabled: clientEnv.NEXT_PUBLIC_SOURCEBOT_CLOUD_ENVIRONMENT !== undefined,
metadata: {
langfuseTraceId: traceId,
}
})
},
},
onError: (error) => {
logger.error(error);
},
});

experimental_telemetry: {
isEnabled: clientEnv.NEXT_PUBLIC_SOURCEBOT_CLOUD_ENVIRONMENT !== undefined,
metadata: {
langfuseTraceId: traceId,
},
},
onError: (error) => {
logger.error(error);
},
});
} catch (err) {
if (model?.providerId === 'openai-compatible') {
throw new Error('The selected AI provider does not support codebase tool calls. Please use a provider that supports function/tool calls for codebase-related questions.');
}
throw err;
}
return stream;
}

Expand Down