fix: fixing multiple files on one

src/api/network/generate.js

@@ -8,6 +8,20 @@ const MAX_FILE_SIZE = 30000; // ~30KB per file
 const MAX_TOTAL_FILES = 5; // Maximum number of files to inject
 const MAX_TOTAL_SIZE = 100000; // ~100KB total for all files
 
+/**
+ * Extracts file blocks from content
+ * @param {string} content - Content containing file blocks
+ * @returns {Array<{path: string, language: string, content: string}>} Array of file blocks
+ */
+function extractFileBlocks(content) {
+  const fileTagRegex = /<file path="(.+?)"(?: language="(.+?)")?>([\s\S]*?)<\/file>/g;
+  return [...content.matchAll(fileTagRegex)].map(([, path, lang, body]) => ({
+    path,
+    language: lang || "text",
+    content: body.trim(),
+  }));
+}
+
 /**
  * Saves an error with consistent formatting
  * @param {Error} error - The error to save
@@ -155,6 +169,158 @@ async function injectFileContent(content) {
   }
 }
 
+/**
+ * Processes a single file with the model
+ * @param {Object} params - Parameters for processing
+ * @returns {Promise<Object>} The model's response for this file
+ */
+async function processSingleFile({ 
+  file, 
+  model, 
+  systemPrompt, 
+  originalPrompt, 
+  stream = false,
+  requestData 
+}) {
+  try {
+    // Construct a focused prompt for this file
+    const focusedPrompt = `Analyze this specific file:\n\n<file path="${file.path}" language="${file.language}">\n${file.content}\n</file>\n\nContext from original prompt: ${originalPrompt}`;
+
+    const ollamaUrl = "http://localhost:11434/api/chat";
+    const payload = {
+      model,
+      messages: [
+        { role: "system", content: systemPrompt || "You are a helpful AI assistant." },
+        { role: "user", content: focusedPrompt }
+      ],
+      stream
+    };
+
+    // Save the individual file prompt
+    await savePrompt({
+      model,
+      prompt: focusedPrompt,
+      messages: payload.messages,
+      request_data: {
+        ...requestData,
+        is_multi_file: true,
+        file_index: file.path,
+        original_prompt: originalPrompt
+      }
+    });
+
+    if (stream) {
+      // For streaming, we'll handle this differently in the main function
+      return { type: 'stream', payload, file };
+    }
+
+    const response = await axios.post(ollamaUrl, payload);
+    return {
+      type: 'response',
+      file: file.path,
+      content: response.data.message?.content || response.data.response || '',
+      model: response.data.model
+    };
+  } catch (error) {
+    await logError(error, {
+      operation: 'Single file processing',
+      filePath: file.path,
+      model,
+      originalPrompt
+    });
+    return {
+      type: 'error',
+      file: file.path,
+      error: error.message
+    };
+  }
+}
+
+/**
+ * Handles multi-file processing
+ * @param {Object} params - Parameters for processing
+ * @returns {Promise<Object>} Combined responses for all files
+ */
+async function handleMultiFileProcessing({ 
+  files, 
+  model, 
+  systemPrompt, 
+  originalPrompt,
+  stream,
+  requestData,
+  res 
+}) {
+  if (stream) {
+    // For streaming, we need to handle each file sequentially
+    res.setHeader('Content-Type', 'application/x-ndjson');
+    res.setHeader('Transfer-Encoding', 'chunked');
+
+    for (const file of files) {
+      // Send a marker for the start of a new file
+      res.write(JSON.stringify({ 
+        type: 'file_start',
+        file: file.path 
+      }) + '\n');
+
+      const { payload } = await processSingleFile({ 
+        file, 
+        model, 
+        systemPrompt, 
+        originalPrompt, 
+        stream: true,
+        requestData 
+      });
+
+      const ollamaResponse = await axios.post(payload.ollamaUrl, payload, {
+        responseType: 'stream'
+      });
+
+      for await (const chunk of ollamaResponse.data) {
+        try {
+          const data = JSON.parse(chunk.toString());
+          res.write(JSON.stringify({
+            ...data,
+            file: file.path
+          }) + '\n');
+        } catch (err) {
+          console.error('Error parsing chunk:', err);
+        }
+      }
+
+      // Send a marker for the end of this file
+      res.write(JSON.stringify({ 
+        type: 'file_end',
+        file: file.path 
+      }) + '\n');
+    }
+
+    res.end();
+    return null;
+  }
+
+  // For non-streaming, process files in parallel
+  const responses = await Promise.all(
+    files.map(file => processSingleFile({ 
+      file, 
+      model, 
+      systemPrompt, 
+      originalPrompt, 
+      stream: false,
+      requestData 
+    }))
+  );
+
+  return {
+    success: true,
+    files: responses.map(r => ({
+      path: r.file,
+      content: r.content,
+      error: r.error,
+      model: r.model
+    }))
+  };
+}
+
 /**
  * Express handler for /api/generate
  * Handles both chat-style and prompt-style requests to Ollama
@@ -174,9 +340,10 @@ async function handleGenerate(req, res) {
       },
     };
 
+    // Validate request body
     if (!requestData.body) {
       await savePrompt({
-        model: requestData.body?.model || "codellama:7b",
+        model: "codellama:7b", // Use default model directly since body is null
         prompt: null,
         messages: null,
         request_data: requestData,
@@ -184,46 +351,81 @@ async function handleGenerate(req, res) {
       throw new Error("Request body is required");
     }
 
-    const isChatRequest =
+    const isChatRequest = requestData.body.messages && Array.isArray(requestData.body.messages);
-      requestData.body.messages && Array.isArray(requestData.body.messages);
+    const model = requestData.body.model || "codellama:7b";
+    const stream = requestData.body.stream !== undefined ? requestData.body.stream : true;
+    const systemPrompt = requestData.body.system;
 
-    if (
+    // Get the content to process (either from messages or prompt)
-      isChatRequest &&
+    let contentToProcess;
-      (!requestData.body.messages.length ||
+    let originalPrompt;
-        !requestData.body.messages[0].content)
+
-    ) {
+    if (isChatRequest) {
-      throw new Error(
+      const lastUserMessage = requestData.body.messages
-        "Chat request must include at least one message with content",
+        .filter(m => m.role === 'user')
-      );
+        .pop();
+      
+      if (!lastUserMessage) {
+        throw new Error("No user message found in chat request");
       }
-    if (!isChatRequest && !requestData.body.prompt) {
+
+      contentToProcess = lastUserMessage.content;
+      originalPrompt = contentToProcess;
+    } else {
+      if (!requestData.body.prompt) {
         throw new Error("Prompt request must include a prompt field");
       }
+      contentToProcess = requestData.body.prompt;
+      originalPrompt = contentToProcess;
+    }
 
-    const model = requestData.body.model || "codellama:7b";
+    // Process the content to inject file contents
-    const stream =
+    contentToProcess = await injectFileContent(contentToProcess);
-      requestData.body.stream !== undefined ? requestData.body.stream : true;
 
+    // Extract file blocks
+    const fileBlocks = extractFileBlocks(contentToProcess);
+
+    // If we have multiple files, use the multi-file processing
+    if (fileBlocks.length > 1) {
+      const result = await handleMultiFileProcessing({
+        files: fileBlocks,
+        model,
+        systemPrompt,
+        originalPrompt,
+        stream,
+        requestData,
+        res
+      });
+
+      if (!stream && result) {
+        res.json(result);
+      }
+      return;
+    }
+
+    // For single file or no files, proceed with normal processing
     const cleanedRequest = {
       model,
       stream,
       ...(isChatRequest
         ? {
-            messages: await Promise.all(
+            messages: requestData.body.messages.map((msg, index) => ({
-              requestData.body.messages.map(async (msg) => ({
               role: msg.role || "user",
-                content:
+              content: index === requestData.body.messages.length - 1 && msg.role === 'user'
-                  msg.role === "user" && typeof msg.content === "string"
+                ? contentToProcess
-                    ? await injectFileContent(msg.content.trim())
                 : msg.content.trim(),
             })),
-            ),
           }
         : {
-            prompt: await injectFileContent(requestData.body.prompt.trim()),
+            prompt: contentToProcess,
           }),
     };
 
+    if (systemPrompt) {
+      cleanedRequest.system = systemPrompt;
+    }
+
+    // Save the complete request data to database
     await savePrompt({
       model,
       prompt: isChatRequest ? null : cleanedRequest.prompt,
@@ -231,6 +433,7 @@ async function handleGenerate(req, res) {
       request_data: requestData,
     });
 
+    // Handle the request with Ollama
     const ollamaUrl = isChatRequest
       ? "http://localhost:11434/api/chat"
       : "http://localhost:11434/api/generate";
@@ -257,13 +460,10 @@ async function handleGenerate(req, res) {
       });
 
       ollamaResponse.data.on("error", async (err) => {
-        await saveError({
+        await logError(err, {
-          error_message: err.message,
+          operation: 'Ollama stream error',
-          details: {
-            stack: err.stack,
           request: requestData,
-            cleaned_request: cleanedRequest,
+          cleaned_request: cleanedRequest
-          },
         });
         if (!res.headersSent) {
           res.status(500).json({
@@ -285,23 +485,14 @@ async function handleGenerate(req, res) {
       res.status(ollamaResponse.status).json(ollamaResponse.data);
     }
   } catch (error) {
-    const errorDetails = {
+    await logError(error, {
-      message: error.message,
+      operation: 'Generate handler',
-      request: requestData,
+      request: requestData
-      response: error.response?.data,
-      stack: error.stack,
-    };
-
-    await saveError({
-      error_message: error.message,
-      details: errorDetails,
     });
 
     if (!res.headersSent) {
       res.status(error.response?.status || 500).json({
-        error: error.response?.status
+        error: error.response?.status ? "Ollama API Error" : "Internal Server Error",
-          ? "Ollama API Error"
-          : "Internal Server Error",
         message: error.message,
         details: error.response?.data || undefined,
       });