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Merge fa833b3574 into bcca1d6d7d
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commit
0dc43e9477
1 changed files with 96 additions and 108 deletions
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@ -42,115 +42,103 @@ export const createAgentStream = async ({
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searchScopeRepoNames,
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});
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const stream = streamText({
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model,
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providerOptions,
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system: baseSystemPrompt,
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messages: inputMessages,
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tools: {
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[toolNames.searchCode]: createCodeSearchTool(searchScopeRepoNames),
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[toolNames.readFiles]: readFilesTool,
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[toolNames.findSymbolReferences]: findSymbolReferencesTool,
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[toolNames.findSymbolDefinitions]: findSymbolDefinitionsTool,
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[toolNames.searchRepos]: searchReposTool,
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[toolNames.listAllRepos]: listAllReposTool,
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},
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prepareStep: async ({ stepNumber }) => {
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// The first step attaches any mentioned sources to the system prompt.
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if (stepNumber === 0 && inputSources.length > 0) {
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const fileSources = inputSources.filter((source) => source.type === 'file');
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const resolvedFileSources = (
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await Promise.all(fileSources.map(resolveFileSource)))
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.filter((source) => source !== undefined)
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const fileSourcesSystemPrompt = await createFileSourcesSystemPrompt({
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files: resolvedFileSources
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});
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return {
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system: `${baseSystemPrompt}\n\n${fileSourcesSystemPrompt}`
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}
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}
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if (stepNumber === env.SOURCEBOT_CHAT_MAX_STEP_COUNT - 1) {
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return {
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system: `**CRITICAL**: You have reached the maximum number of steps!! YOU MUST PROVIDE YOUR FINAL ANSWER NOW. DO NOT KEEP RESEARCHING.\n\n${answerInstructions}`,
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activeTools: [],
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}
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}
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return undefined;
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},
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temperature: env.SOURCEBOT_CHAT_MODEL_TEMPERATURE,
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stopWhen: [
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stepCountIsGTE(env.SOURCEBOT_CHAT_MAX_STEP_COUNT),
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],
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toolChoice: "auto", // Let the model decide when to use tools
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onStepFinish: ({ toolResults }) => {
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// This takes care of extracting any sources that the LLM has seen as part of
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// the tool calls it made.
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toolResults.forEach(({ toolName, output, dynamic }) => {
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// we don't care about dynamic tool results here.
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if (dynamic) {
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return;
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}
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if (isServiceError(output)) {
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// is there something we want to do here?
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return;
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}
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if (toolName === toolNames.readFiles) {
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output.forEach((file) => {
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onWriteSource({
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type: 'file',
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language: file.language,
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repo: file.repository,
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path: file.path,
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revision: file.revision,
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name: file.path.split('/').pop() ?? file.path,
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})
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})
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}
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else if (toolName === toolNames.searchCode) {
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output.files.forEach((file) => {
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onWriteSource({
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type: 'file',
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language: file.language,
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repo: file.repository,
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path: file.fileName,
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revision: file.revision,
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name: file.fileName.split('/').pop() ?? file.fileName,
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})
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})
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}
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else if (toolName === toolNames.findSymbolDefinitions || toolName === toolNames.findSymbolReferences) {
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output.forEach((file) => {
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onWriteSource({
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type: 'file',
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language: file.language,
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repo: file.repository,
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path: file.fileName,
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revision: file.revision,
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name: file.fileName.split('/').pop() ?? file.fileName,
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})
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})
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}
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})
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},
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// Only enable langfuse traces in cloud environments.
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experimental_telemetry: {
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isEnabled: clientEnv.NEXT_PUBLIC_SOURCEBOT_CLOUD_ENVIRONMENT !== undefined,
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metadata: {
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langfuseTraceId: traceId,
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let stream;
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try {
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stream = streamText({
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model,
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providerOptions,
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system: baseSystemPrompt,
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messages: inputMessages,
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tools: {
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[toolNames.searchCode]: createCodeSearchTool(searchScopeRepoNames),
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[toolNames.readFiles]: readFilesTool,
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[toolNames.findSymbolReferences]: findSymbolReferencesTool,
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[toolNames.findSymbolDefinitions]: findSymbolDefinitionsTool,
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[toolNames.searchRepos]: searchReposTool,
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[toolNames.listAllRepos]: listAllReposTool,
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},
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},
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onError: (error) => {
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logger.error(error);
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},
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});
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prepareStep: async ({ stepNumber }) => {
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if (stepNumber === 0 && inputSources.length > 0) {
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const fileSources = inputSources.filter((source) => source.type === 'file');
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const resolvedFileSources = (
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await Promise.all(fileSources.map(resolveFileSource)))
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.filter((source) => source !== undefined)
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const fileSourcesSystemPrompt = await createFileSourcesSystemPrompt({
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files: resolvedFileSources
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});
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return {
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system: `${baseSystemPrompt}\n\n${fileSourcesSystemPrompt}`
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}
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}
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if (stepNumber === env.SOURCEBOT_CHAT_MAX_STEP_COUNT - 1) {
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return {
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system: `**CRITICAL**: You have reached the maximum number of steps!! YOU MUST PROVIDE YOUR FINAL ANSWER NOW. DO NOT KEEP RESEARCHING.\n\n${answerInstructions}`,
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activeTools: [],
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}
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}
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return undefined;
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},
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temperature: env.SOURCEBOT_CHAT_MODEL_TEMPERATURE,
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stopWhen: [
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stepCountIsGTE(env.SOURCEBOT_CHAT_MAX_STEP_COUNT),
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],
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toolChoice: "auto",
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onStepFinish: ({ toolResults }) => {
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toolResults.forEach(({ toolName, output, dynamic }) => {
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if (dynamic) return;
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if (isServiceError(output)) return;
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if (toolName === toolNames.readFiles) {
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output.forEach((file) => {
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onWriteSource({
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type: 'file',
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language: file.language,
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repo: file.repository,
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path: file.path,
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revision: file.revision,
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name: file.path.split('/').pop() ?? file.path,
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})
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})
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} else if (toolName === toolNames.searchCode) {
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output.files.forEach((file) => {
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onWriteSource({
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type: 'file',
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language: file.language,
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repo: file.repository,
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path: file.fileName,
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revision: file.revision,
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name: file.fileName.split('/').pop() ?? file.fileName,
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})
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})
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} else if (toolName === toolNames.findSymbolDefinitions || toolName === toolNames.findSymbolReferences) {
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output.forEach((file) => {
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onWriteSource({
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type: 'file',
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language: file.language,
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repo: file.repository,
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path: file.fileName,
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revision: file.revision,
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name: file.fileName.split('/').pop() ?? file.fileName,
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})
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})
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}
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})
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},
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experimental_telemetry: {
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isEnabled: clientEnv.NEXT_PUBLIC_SOURCEBOT_CLOUD_ENVIRONMENT !== undefined,
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metadata: {
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langfuseTraceId: traceId,
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},
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},
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onError: (error) => {
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logger.error(error);
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},
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});
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} catch (err) {
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if (model?.providerId === 'openai-compatible') {
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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.');
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}
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throw err;
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}
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return stream;
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}
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