Merge pull request #580 from khoj-ai/fix-upgrade-chat-to-create-images

Support Image Generation with Khoj

pyproject.toml

@@ -42,7 +42,7 @@ dependencies = [
     "fastapi >= 0.104.1",
     "python-multipart >= 0.0.5",
     "jinja2 == 3.1.2",
-    "openai >= 0.27.0, < 1.0.0",
+    "openai >= 1.0.0",
     "tiktoken >= 0.3.2",
     "tenacity >= 8.2.2",
     "pillow ~= 9.5.0",

src/interface/desktop/chat.html

@@ -179,7 +179,13 @@
             return numOnlineReferences;
         }
 
-        function renderMessageWithReference(message, by, context=null, dt=null, onlineContext=null) {
+        function renderMessageWithReference(message, by, context=null, dt=null, onlineContext=null, intentType=null) {
+            if (intentType === "text-to-image") {
+                let imageMarkdown = `![](data:image/png;base64,${message})`;
+                renderMessage(imageMarkdown, by, dt);
+                return;
+            }
+
             if (context == null && onlineContext == null) {
                 renderMessage(message, by, dt);
                 return;
@@ -244,6 +250,17 @@
             // Remove any text between <s>[INST] and </s> tags. These are spurious instructions for the AI chat model.
             newHTML = newHTML.replace(/<s>\[INST\].+(<\/s>)?/g, '');
 
+            // Customize the rendering of images
+            md.renderer.rules.image = function(tokens, idx, options, env, self) {
+                let token = tokens[idx];
+
+                // Add class="text-to-image" to images
+                token.attrPush(['class', 'text-to-image']);
+
+                // Use the default renderer to render image markdown format
+                return self.renderToken(tokens, idx, options);
+            };
+
             // Render markdown
             newHTML = md.render(newHTML);
             // Get any elements with a class that starts with "language"
@@ -328,109 +345,142 @@
             let chatInput = document.getElementById("chat-input");
             chatInput.classList.remove("option-enabled");
 
-            // Call specified Khoj API which returns a streamed response of type text/plain
+            // Call specified Khoj API
-            fetch(url, { headers })
+            let response = await fetch(url, { headers });
-            .then(response => {
+            let rawResponse = "";
-                    const reader = response.body.getReader();
+            const contentType = response.headers.get("content-type");
-                    const decoder = new TextDecoder();
-                    let rawResponse = "";
-                    let references = null;
 
-                    function readStream() {
+            if (contentType === "application/json") {
-                        reader.read().then(({ done, value }) => {
+                // Handle JSON response
-                            if (done) {
+                try {
-                                // Append any references after all the data has been streamed
+                    const responseAsJson = await response.json();
-                                if (references != null) {
+                    if (responseAsJson.image) {
-                                    newResponseText.appendChild(references);
+                        // If response has image field, response is a generated image.
-                                }
+                        rawResponse += `![${query}](data:image/png;base64,${responseAsJson.image})`;
-                                document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
+                    }
-                                document.getElementById("chat-input").removeAttribute("disabled");
+                    if (responseAsJson.detail) {
-                                return;
+                        // If response has detail field, response is an error message.
+                        rawResponse += responseAsJson.detail;
+                    }
+                } catch (error) {
+                    // If the chunk is not a JSON object, just display it as is
+                    rawResponse += chunk;
+                } finally {
+                    newResponseText.innerHTML = "";
+                    newResponseText.appendChild(formatHTMLMessage(rawResponse));
+
+                    document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
+                    document.getElementById("chat-input").removeAttribute("disabled");
+                }
+            } else {
+                // Handle streamed response of type text/event-stream or text/plain
+                const reader = response.body.getReader();
+                const decoder = new TextDecoder();
+                let references = null;
+
+                readStream();
+
+                function readStream() {
+                    reader.read().then(({ done, value }) => {
+                        if (done) {
+                            // Append any references after all the data has been streamed
+                            if (references != null) {
+                                newResponseText.appendChild(references);
+                            }
+                            document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
+                            document.getElementById("chat-input").removeAttribute("disabled");
+                            return;
+                        }
+
+                        // Decode message chunk from stream
+                        const chunk = decoder.decode(value, { stream: true });
+
+                        if (chunk.includes("### compiled references:")) {
+                            const additionalResponse = chunk.split("### compiled references:")[0];
+                            rawResponse += additionalResponse;
+                            newResponseText.innerHTML = "";
+                            newResponseText.appendChild(formatHTMLMessage(rawResponse));
+
+                            const rawReference = chunk.split("### compiled references:")[1];
+                            const rawReferenceAsJson = JSON.parse(rawReference);
+                            references = document.createElement('div');
+                            references.classList.add("references");
+
+                            let referenceExpandButton = document.createElement('button');
+                            referenceExpandButton.classList.add("reference-expand-button");
+
+                            let referenceSection = document.createElement('div');
+                            referenceSection.classList.add("reference-section");
+                            referenceSection.classList.add("collapsed");
+
+                            let numReferences = 0;
+
+                            // If rawReferenceAsJson is a list, then count the length
+                            if (Array.isArray(rawReferenceAsJson)) {
+                                numReferences = rawReferenceAsJson.length;
+
+                                rawReferenceAsJson.forEach((reference, index) => {
+                                let polishedReference = generateReference(reference, index);
+                                referenceSection.appendChild(polishedReference);
+                            });
+                            } else {
+                                numReferences += processOnlineReferences(referenceSection, rawReferenceAsJson);
                             }
 
-                            // Decode message chunk from stream
+                            references.appendChild(referenceExpandButton);
-                            const chunk = decoder.decode(value, { stream: true });
 
-                            if (chunk.includes("### compiled references:")) {
+                            referenceExpandButton.addEventListener('click', function() {
-                                const additionalResponse = chunk.split("### compiled references:")[0];
+                                if (referenceSection.classList.contains("collapsed")) {
-                                rawResponse += additionalResponse;
+                                    referenceSection.classList.remove("collapsed");
+                                    referenceSection.classList.add("expanded");
+                                } else {
+                                    referenceSection.classList.add("collapsed");
+                                    referenceSection.classList.remove("expanded");
+                                }
+                            });
+
+                            let expandButtonText = numReferences == 1 ? "1 reference" : `${numReferences} references`;
+                            referenceExpandButton.innerHTML = expandButtonText;
+                            references.appendChild(referenceSection);
+                            readStream();
+                        } else {
+                            // Display response from Khoj
+                            if (newResponseText.getElementsByClassName("spinner").length > 0) {
+                                newResponseText.removeChild(loadingSpinner);
+                            }
+
+                            // Try to parse the chunk as a JSON object. It will be a JSON object if there is an error.
+                            if (chunk.startsWith("{") && chunk.endsWith("}")) {
+                                try {
+                                    const responseAsJson = JSON.parse(chunk);
+                                    if (responseAsJson.image) {
+                                        rawResponse += `![${query}](data:image/png;base64,${responseAsJson.image})`;
+                                    }
+                                    if (responseAsJson.detail) {
+                                        rawResponse += responseAsJson.detail;
+                                    }
+                                } catch (error) {
+                                    // If the chunk is not a JSON object, just display it as is
+                                    rawResponse += chunk;
+                                } finally {
+                                    newResponseText.innerHTML = "";
+                                    newResponseText.appendChild(formatHTMLMessage(rawResponse));
+                                }
+                            } else {
+                                // If the chunk is not a JSON object, just display it as is
+                                rawResponse += chunk;
                                 newResponseText.innerHTML = "";
                                 newResponseText.appendChild(formatHTMLMessage(rawResponse));
 
-                                const rawReference = chunk.split("### compiled references:")[1];
-                                const rawReferenceAsJson = JSON.parse(rawReference);
-                                references = document.createElement('div');
-                                references.classList.add("references");
-
-                                let referenceExpandButton = document.createElement('button');
-                                referenceExpandButton.classList.add("reference-expand-button");
-
-                                let referenceSection = document.createElement('div');
-                                referenceSection.classList.add("reference-section");
-                                referenceSection.classList.add("collapsed");
-
-                                let numReferences = 0;
-
-                                // If rawReferenceAsJson is a list, then count the length
-                                if (Array.isArray(rawReferenceAsJson)) {
-                                    numReferences = rawReferenceAsJson.length;
-
-                                    rawReferenceAsJson.forEach((reference, index) => {
-                                    let polishedReference = generateReference(reference, index);
-                                    referenceSection.appendChild(polishedReference);
-                                });
-                                } else {
-                                    numReferences += processOnlineReferences(referenceSection, rawReferenceAsJson);
-                                }
-
-                                references.appendChild(referenceExpandButton);
-
-                                referenceExpandButton.addEventListener('click', function() {
-                                    if (referenceSection.classList.contains("collapsed")) {
-                                        referenceSection.classList.remove("collapsed");
-                                        referenceSection.classList.add("expanded");
-                                    } else {
-                                        referenceSection.classList.add("collapsed");
-                                        referenceSection.classList.remove("expanded");
-                                    }
-                                });
-
-                                let expandButtonText = numReferences == 1 ? "1 reference" : `${numReferences} references`;
-                                referenceExpandButton.innerHTML = expandButtonText;
-                                references.appendChild(referenceSection);
                                 readStream();
-                            } else {
-                                // Display response from Khoj
-                                if (newResponseText.getElementsByClassName("spinner").length > 0) {
-                                    newResponseText.removeChild(loadingSpinner);
-                                }
-                                // Try to parse the chunk as a JSON object. It will be a JSON object if there is an error.
-                                if (chunk.startsWith("{") && chunk.endsWith("}")) {
-                                    try {
-                                        const responseAsJson = JSON.parse(chunk);
-                                        if (responseAsJson.detail) {
-                                            newResponseText.innerHTML += responseAsJson.detail;
-                                        }
-                                    } catch (error) {
-                                        // If the chunk is not a JSON object, just display it as is
-                                        newResponseText.innerHTML += chunk;
-                                    }
-                                } else {
-                                    // If the chunk is not a JSON object, just display it as is
-                                    rawResponse += chunk;
-                                    newResponseText.innerHTML = "";
-                                    newResponseText.appendChild(formatHTMLMessage(rawResponse));
-
-                                    readStream();
-                                }
                             }
+                        }
 
-                            // Scroll to bottom of chat window as chat response is streamed
+                        // Scroll to bottom of chat window as chat response is streamed
-                            document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
+                        document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
-                        });
+                    });
-                    }
+                }
-                    readStream();
+            }
-                });
         }
 
         function incrementalChat(event) {
@@ -522,7 +572,7 @@
                 .then(response => {
                     // Render conversation history, if any
                     response.forEach(chat_log => {
-                        renderMessageWithReference(chat_log.message, chat_log.by, chat_log.context, new Date(chat_log.created), chat_log.onlineContext);
+                        renderMessageWithReference(chat_log.message, chat_log.by, chat_log.context, new Date(chat_log.created), chat_log.onlineContext, chat_log.intent?.type);
                     });
                 })
                 .catch(err => {
@@ -625,9 +675,13 @@
                     .then(response => response.ok ? response.json() : Promise.reject(response))
                     .then(data => { chatInput.value += data.text; })
                     .catch(err => {
-                        err.status == 422
+                        if (err.status === 501) {
-                        ? flashStatusInChatInput("⛔️ Configure speech-to-text model on server.")
+                          flashStatusInChatInput("⛔️ Configure speech-to-text model on server.")
-                        : flashStatusInChatInput("⛔️ Failed to transcribe audio")
+                        } else if (err.status === 422) {
+                          flashStatusInChatInput("⛔️ Audio file to large to process.")
+                        } else {
+                          flashStatusInChatInput("⛔️ Failed to transcribe audio.")
+                        }
                     });
             };
 
@@ -810,6 +864,9 @@
             margin-top: -10px;
             transform: rotate(-60deg)
         }
+        img.text-to-image {
+            max-width: 60%;
+        }
 
         #chat-footer {
             padding: 0;
@@ -1050,6 +1107,9 @@
                 margin: 4px;
                 grid-template-columns: auto;
             }
+            img.text-to-image {
+                max-width: 100%;
+            }
         }
         @media only screen and (min-width: 600px) {
             body {

src/interface/obsidian/src/chat_modal.ts

@@ -2,6 +2,12 @@ import { App, MarkdownRenderer, Modal, request, requestUrl, setIcon } from 'obsi
 import { KhojSetting } from 'src/settings';
 import fetch from "node-fetch";
 
+export interface ChatJsonResult {
+    image?: string;
+    detail?: string;
+}
+
+
 export class KhojChatModal extends Modal {
     result: string;
     setting: KhojSetting;
@@ -105,15 +111,19 @@ export class KhojChatModal extends Modal {
         return referenceButton;
     }
 
-    renderMessageWithReferences(chatEl: Element, message: string, sender: string, context?: string[], dt?: Date) {
+    renderMessageWithReferences(chatEl: Element, message: string, sender: string, context?: string[], dt?: Date, intentType?: string) {
         if (!message) {
             return;
+        } else if (intentType === "text-to-image") {
+            let imageMarkdown = `![](data:image/png;base64,${message})`;
+            this.renderMessage(chatEl, imageMarkdown, sender, dt);
+            return;
         } else if (!context) {
             this.renderMessage(chatEl, message, sender, dt);
-            return
+            return;
         } else if (!!context && context?.length === 0) {
             this.renderMessage(chatEl, message, sender, dt);
-            return
+            return;
         }
         let chatMessageEl = this.renderMessage(chatEl, message, sender, dt);
         let chatMessageBodyEl = chatMessageEl.getElementsByClassName("khoj-chat-message-text")[0]
@@ -225,7 +235,7 @@ export class KhojChatModal extends Modal {
         let response = await request({ url: chatUrl, headers: headers });
         let chatLogs = JSON.parse(response).response;
         chatLogs.forEach((chatLog: any) => {
-            this.renderMessageWithReferences(chatBodyEl, chatLog.message, chatLog.by, chatLog.context, new Date(chatLog.created));
+            this.renderMessageWithReferences(chatBodyEl, chatLog.message, chatLog.by, chatLog.context, new Date(chatLog.created), chatLog.intent?.type);
         });
     }
 
@@ -266,8 +276,25 @@ export class KhojChatModal extends Modal {
 
             this.result = "";
             responseElement.innerHTML = "";
+            if (response.headers.get("content-type") == "application/json") {
+                let responseText = ""
+                try {
+                    const responseAsJson = await response.json() as ChatJsonResult;
+                    if (responseAsJson.image) {
+                        responseText = `![${query}](data:image/png;base64,${responseAsJson.image})`;
+                    } else if (responseAsJson.detail) {
+                        responseText = responseAsJson.detail;
+                    }
+                } catch (error) {
+                    // If the chunk is not a JSON object, just display it as is
+                    responseText = response.body.read().toString()
+                } finally {
+                    this.renderIncrementalMessage(responseElement, responseText);
+                }
+            }
+
             for await (const chunk of response.body) {
-                const responseText = chunk.toString();
+                let responseText = chunk.toString();
                 if (responseText.includes("### compiled references:")) {
                     const additionalResponse = responseText.split("### compiled references:")[0];
                     this.renderIncrementalMessage(responseElement, additionalResponse);
@@ -310,6 +337,12 @@ export class KhojChatModal extends Modal {
                     referenceExpandButton.innerHTML = expandButtonText;
                     references.appendChild(referenceSection);
                 } else {
+                    if (responseText.startsWith("{") && responseText.endsWith("}")) {
+                    } else {
+                        // If the chunk is not a JSON object, just display it as is
+                        continue;
+                    }
+
                     this.renderIncrementalMessage(responseElement, responseText);
                 }
             }
@@ -389,10 +422,12 @@ export class KhojChatModal extends Modal {
             if (response.status === 200) {
                 console.log(response);
                 chatInput.value += response.json.text;
-            } else if (response.status === 422) {
+            } else if (response.status === 501) {
-                throw new Error("⛔️ Failed to transcribe audio");
-            } else {
                 throw new Error("⛔️ Configure speech-to-text model on server.");
+            } else if (response.status === 422) {
+                throw new Error("⛔️ Audio file to large to process.");
+            } else {
+                throw new Error("⛔️ Failed to transcribe audio.");
             }
         };
 

src/interface/obsidian/styles.css

@@ -217,7 +217,9 @@ button.copy-button:hover {
     background: #f5f5f5;
     cursor: pointer;
 }
-
+img {
+    max-width: 60%;
+}
 
 #khoj-chat-footer {
     padding: 0;

src/khoj/configure.py

@@ -7,6 +7,7 @@ import requests
 import os
 
 # External Packages
+import openai
 import schedule
 from starlette.middleware.sessions import SessionMiddleware
 from starlette.middleware.authentication import AuthenticationMiddleware
@@ -22,6 +23,7 @@ from starlette.authentication import (
 # Internal Packages
 from khoj.database.models import KhojUser, Subscription
 from khoj.database.adapters import (
+    ConversationAdapters,
     get_all_users,
     get_or_create_search_model,
     aget_user_subscription_state,
@@ -138,6 +140,10 @@ def configure_server(
         config = FullConfig()
     state.config = config
 
+    if ConversationAdapters.has_valid_openai_conversation_config():
+        openai_config = ConversationAdapters.get_openai_conversation_config()
+        state.openai_client = openai.OpenAI(api_key=openai_config.api_key)
+
     # Initialize Search Models from Config and initialize content
     try:
         state.embeddings_model = EmbeddingsModel(get_or_create_search_model().bi_encoder)

src/khoj/database/adapters/__init__.py

@@ -22,6 +22,7 @@ from khoj.database.models import (
     GithubConfig,
     GithubRepoConfig,
     GoogleUser,
+    TextToImageModelConfig,
     KhojApiUser,
     KhojUser,
     NotionConfig,
@@ -426,6 +427,10 @@ class ConversationAdapters:
         else:
             raise ValueError("Invalid conversation config - either configure offline chat or openai chat")
 
+    @staticmethod
+    async def aget_text_to_image_model_config():
+        return await TextToImageModelConfig.objects.filter().afirst()
+
 
 class EntryAdapters:
     word_filer = WordFilter()

src/khoj/database/migrations/0022_texttoimagemodelconfig.py

@@ -0,0 +1,25 @@
+# Generated by Django 4.2.7 on 2023-12-04 22:17
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("database", "0021_speechtotextmodeloptions_and_more"),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name="TextToImageModelConfig",
+            fields=[
+                ("id", models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
+                ("created_at", models.DateTimeField(auto_now_add=True)),
+                ("updated_at", models.DateTimeField(auto_now=True)),
+                ("model_name", models.CharField(default="dall-e-3", max_length=200)),
+                ("model_type", models.CharField(choices=[("openai", "Openai")], default="openai", max_length=200)),
+            ],
+            options={
+                "abstract": False,
+            },
+        ),
+    ]

src/khoj/database/models/__init__.py

@@ -112,6 +112,14 @@ class SearchModelConfig(BaseModel):
     cross_encoder = models.CharField(max_length=200, default="cross-encoder/ms-marco-MiniLM-L-6-v2")
 
 
+class TextToImageModelConfig(BaseModel):
+    class ModelType(models.TextChoices):
+        OPENAI = "openai"
+
+    model_name = models.CharField(max_length=200, default="dall-e-3")
+    model_type = models.CharField(max_length=200, choices=ModelType.choices, default=ModelType.OPENAI)
+
+
 class OpenAIProcessorConversationConfig(BaseModel):
     api_key = models.CharField(max_length=200)
 

src/khoj/interface/web/chat.html

@@ -183,12 +183,18 @@ To get started, just start typing below. You can also type / to see a list of co
                         referenceSection.appendChild(polishedReference);
                     }
                 }
-        }
+            }
 
             return numOnlineReferences;
-                    }
+        }
+
+        function renderMessageWithReference(message, by, context=null, dt=null, onlineContext=null, intentType=null) {
+            if (intentType === "text-to-image") {
+                let imageMarkdown = `![](data:image/png;base64,${message})`;
+                renderMessage(imageMarkdown, by, dt);
+                return;
+            }
 
-        function renderMessageWithReference(message, by, context=null, dt=null, onlineContext=null) {
             if (context == null && onlineContext == null) {
                 renderMessage(message, by, dt);
                 return;
@@ -253,6 +259,17 @@ To get started, just start typing below. You can also type / to see a list of co
             // Remove any text between <s>[INST] and </s> tags. These are spurious instructions for the AI chat model.
             newHTML = newHTML.replace(/<s>\[INST\].+(<\/s>)?/g, '');
 
+            // Customize the rendering of images
+            md.renderer.rules.image = function(tokens, idx, options, env, self) {
+                let token = tokens[idx];
+
+                // Add class="text-to-image" to images
+                token.attrPush(['class', 'text-to-image']);
+
+                // Use the default renderer to render image markdown format
+                return self.renderToken(tokens, idx, options);
+            };
+
             // Render markdown
             newHTML = md.render(newHTML);
             // Get any elements with a class that starts with "language"
@@ -292,7 +309,7 @@ To get started, just start typing below. You can also type / to see a list of co
             return element
         }
 
-        function chat() {
+        async function chat() {
             // Extract required fields for search from form
             let query = document.getElementById("chat-input").value.trim();
             let resultsCount = localStorage.getItem("khojResultsCount") || 5;
@@ -333,113 +350,123 @@ To get started, just start typing below. You can also type / to see a list of co
             let chatInput = document.getElementById("chat-input");
             chatInput.classList.remove("option-enabled");
 
-            // Call specified Khoj API which returns a streamed response of type text/plain
+            // Call specified Khoj API
-            fetch(url)
+            let response = await fetch(url);
-                .then(response => {
+            let rawResponse = "";
-                    const reader = response.body.getReader();
+            const contentType = response.headers.get("content-type");
-                    const decoder = new TextDecoder();
-                    let rawResponse = "";
-                    let references = null;
 
-                    function readStream() {
+            if (contentType === "application/json") {
-                        reader.read().then(({ done, value }) => {
+                // Handle JSON response
-                            if (done) {
+                try {
-                                // Append any references after all the data has been streamed
+                    const responseAsJson = await response.json();
-                                if (references != null) {
+                    if (responseAsJson.image) {
-                                    newResponseText.appendChild(references);
+                        // If response has image field, response is a generated image.
-                                }
+                        rawResponse += `![${query}](data:image/png;base64,${responseAsJson.image})`;
-                                document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
-                                document.getElementById("chat-input").removeAttribute("disabled");
-                                return;
-                            }
-
-                            // Decode message chunk from stream
-                            const chunk = decoder.decode(value, { stream: true });
-
-                            if (chunk.includes("### compiled references:")) {
-                                const additionalResponse = chunk.split("### compiled references:")[0];
-                                rawResponse += additionalResponse;
-                                newResponseText.innerHTML = "";
-                                newResponseText.appendChild(formatHTMLMessage(rawResponse));
-
-                                const rawReference = chunk.split("### compiled references:")[1];
-                                const rawReferenceAsJson = JSON.parse(rawReference);
-                                references = document.createElement('div');
-                                references.classList.add("references");
-
-                                let referenceExpandButton = document.createElement('button');
-                                referenceExpandButton.classList.add("reference-expand-button");
-
-                                let referenceSection = document.createElement('div');
-                                referenceSection.classList.add("reference-section");
-                                referenceSection.classList.add("collapsed");
-
-                                let numReferences = 0;
-
-                                // If rawReferenceAsJson is a list, then count the length
-                                if (Array.isArray(rawReferenceAsJson)) {
-                                    numReferences = rawReferenceAsJson.length;
-
-                                    rawReferenceAsJson.forEach((reference, index) => {
-                                    let polishedReference = generateReference(reference, index);
-                                    referenceSection.appendChild(polishedReference);
-                                });
-                                } else {
-                                    numReferences += processOnlineReferences(referenceSection, rawReferenceAsJson);
-                                }
-
-                                references.appendChild(referenceExpandButton);
-
-                                referenceExpandButton.addEventListener('click', function() {
-                                    if (referenceSection.classList.contains("collapsed")) {
-                                        referenceSection.classList.remove("collapsed");
-                                        referenceSection.classList.add("expanded");
-                                    } else {
-                                        referenceSection.classList.add("collapsed");
-                                        referenceSection.classList.remove("expanded");
-                                    }
-                                });
-
-                                let expandButtonText = numReferences == 1 ? "1 reference" : `${numReferences} references`;
-                                referenceExpandButton.innerHTML = expandButtonText;
-                                references.appendChild(referenceSection);
-                                readStream();
-                            } else {
-                                // Display response from Khoj
-                                if (newResponseText.getElementsByClassName("spinner").length > 0) {
-                                    newResponseText.removeChild(loadingSpinner);
-                                }
-
-                                // Try to parse the chunk as a JSON object. It will be a JSON object if there is an error.
-                                if (chunk.startsWith("{") && chunk.endsWith("}")) {
-                                    try {
-                                        const responseAsJson = JSON.parse(chunk);
-                                        if (responseAsJson.detail) {
-                                            rawResponse += responseAsJson.detail;
-                                        }
-                                    } catch (error) {
-                                        // If the chunk is not a JSON object, just display it as is
-                                        rawResponse += chunk;
-                                    } finally {
-                                        newResponseText.innerHTML = "";
-                                        newResponseText.appendChild(formatHTMLMessage(rawResponse));
-                                    }
-                                } else {
-                                    // If the chunk is not a JSON object, just display it as is
-                                    rawResponse += chunk;
-                                    newResponseText.innerHTML = "";
-                                    newResponseText.appendChild(formatHTMLMessage(rawResponse));
-                                    readStream();
-                                }
-                            }
-
-                            // Scroll to bottom of chat window as chat response is streamed
-                            document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
-                        });
                     }
-                    readStream();
+                    if (responseAsJson.detail) {
-                });
+                        // If response has detail field, response is an error message.
-        }
+                        rawResponse += responseAsJson.detail;
+                    }
+                } catch (error) {
+                    // If the chunk is not a JSON object, just display it as is
+                    rawResponse += chunk;
+                } finally {
+                    newResponseText.innerHTML = "";
+                    newResponseText.appendChild(formatHTMLMessage(rawResponse));
+
+                    document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
+                    document.getElementById("chat-input").removeAttribute("disabled");
+                }
+            } else {
+                // Handle streamed response of type text/event-stream or text/plain
+                const reader = response.body.getReader();
+                const decoder = new TextDecoder();
+                let references = null;
+
+                readStream();
+
+                function readStream() {
+                    reader.read().then(({ done, value }) => {
+                        if (done) {
+                            // Append any references after all the data has been streamed
+                            if (references != null) {
+                                newResponseText.appendChild(references);
+                            }
+                            document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
+                            document.getElementById("chat-input").removeAttribute("disabled");
+                            return;
+                        }
+
+                        // Decode message chunk from stream
+                        const chunk = decoder.decode(value, { stream: true });
+
+                        if (chunk.includes("### compiled references:")) {
+                            const additionalResponse = chunk.split("### compiled references:")[0];
+                            rawResponse += additionalResponse;
+                            newResponseText.innerHTML = "";
+                            newResponseText.appendChild(formatHTMLMessage(rawResponse));
+
+                            const rawReference = chunk.split("### compiled references:")[1];
+                            const rawReferenceAsJson = JSON.parse(rawReference);
+                            references = document.createElement('div');
+                            references.classList.add("references");
+
+                            let referenceExpandButton = document.createElement('button');
+                            referenceExpandButton.classList.add("reference-expand-button");
+
+                            let referenceSection = document.createElement('div');
+                            referenceSection.classList.add("reference-section");
+                            referenceSection.classList.add("collapsed");
+
+                            let numReferences = 0;
+
+                            // If rawReferenceAsJson is a list, then count the length
+                            if (Array.isArray(rawReferenceAsJson)) {
+                                numReferences = rawReferenceAsJson.length;
+
+                                rawReferenceAsJson.forEach((reference, index) => {
+                                let polishedReference = generateReference(reference, index);
+                                referenceSection.appendChild(polishedReference);
+                            });
+                            } else {
+                                numReferences += processOnlineReferences(referenceSection, rawReferenceAsJson);
+                            }
+
+                            references.appendChild(referenceExpandButton);
+
+                            referenceExpandButton.addEventListener('click', function() {
+                                if (referenceSection.classList.contains("collapsed")) {
+                                    referenceSection.classList.remove("collapsed");
+                                    referenceSection.classList.add("expanded");
+                                } else {
+                                    referenceSection.classList.add("collapsed");
+                                    referenceSection.classList.remove("expanded");
+                                }
+                            });
+
+                            let expandButtonText = numReferences == 1 ? "1 reference" : `${numReferences} references`;
+                            referenceExpandButton.innerHTML = expandButtonText;
+                            references.appendChild(referenceSection);
+                            readStream();
+                        } else {
+                            // Display response from Khoj
+                            if (newResponseText.getElementsByClassName("spinner").length > 0) {
+                                newResponseText.removeChild(loadingSpinner);
+                            }
+
+                            // If the chunk is not a JSON object, just display it as is
+                            rawResponse += chunk;
+                            newResponseText.innerHTML = "";
+                            newResponseText.appendChild(formatHTMLMessage(rawResponse));
+                            readStream();
+                        }
+                    });
+
+                    // Scroll to bottom of chat window as chat response is streamed
+                    document.getElementById("chat-body").scrollTop = document.getElementById("chat-body").scrollHeight;
+                };
+            }
+        };
 
         function incrementalChat(event) {
             if (!event.shiftKey && event.key === 'Enter') {
@@ -516,7 +543,7 @@ To get started, just start typing below. You can also type / to see a list of co
                 .then(response => {
                     // Render conversation history, if any
                     response.forEach(chat_log => {
-                        renderMessageWithReference(chat_log.message, chat_log.by, chat_log.context, new Date(chat_log.created), chat_log.onlineContext);
+                        renderMessageWithReference(chat_log.message, chat_log.by, chat_log.context, new Date(chat_log.created), chat_log.onlineContext, chat_log.intent?.type);
                     });
                 })
                 .catch(err => {
@@ -611,9 +638,13 @@ To get started, just start typing below. You can also type / to see a list of co
                     .then(response => response.ok ? response.json() : Promise.reject(response))
                     .then(data => { chatInput.value += data.text; })
                     .catch(err => {
-                        err.status == 422
+                        if (err.status === 501) {
-                        ? flashStatusInChatInput("⛔️ Configure speech-to-text model on server.")
+                          flashStatusInChatInput("⛔️ Configure speech-to-text model on server.")
-                        : flashStatusInChatInput("⛔️ Failed to transcribe audio")
+                        } else if (err.status === 422) {
+                          flashStatusInChatInput("⛔️ Audio file to large to process.")
+                        } else {
+                          flashStatusInChatInput("⛔️ Failed to transcribe audio.")
+                        }
                     });
             };
 
@@ -902,6 +933,9 @@ To get started, just start typing below. You can also type / to see a list of co
             margin-top: -10px;
             transform: rotate(-60deg)
         }
+        img.text-to-image {
+            max-width: 60%;
+        }
 
         #chat-footer {
             padding: 0;
@@ -1029,6 +1063,9 @@ To get started, just start typing below. You can also type / to see a list of co
                 margin: 4px;
                 grid-template-columns: auto;
             }
+            img.text-to-image {
+                max-width: 100%;
+            }
         }
         @media only screen and (min-width: 700px) {
             body {

src/khoj/processor/conversation/offline/chat_model.py

@@ -47,7 +47,7 @@ def extract_questions_offline(
 
     if use_history:
         for chat in conversation_log.get("chat", [])[-4:]:
-            if chat["by"] == "khoj":
+            if chat["by"] == "khoj" and chat["intent"].get("type") != "text-to-image":
                 chat_history += f"Q: {chat['intent']['query']}\n"
                 chat_history += f"A: {chat['message']}\n"
 

src/khoj/processor/conversation/offline/utils.py

@@ -12,11 +12,12 @@ def download_model(model_name: str):
         logger.info("There was an error importing GPT4All. Please run pip install gpt4all in order to install it.")
         raise e
 
-    # Download the chat model
-    chat_model_config = gpt4all.GPT4All.retrieve_model(model_name=model_name, allow_download=True)
-
     # Decide whether to load model to GPU or CPU
+    chat_model_config = None
     try:
+        # Download the chat model and its config
+        chat_model_config = gpt4all.GPT4All.retrieve_model(model_name=model_name, allow_download=True)
+
         # Try load chat model to GPU if:
         # 1. Loading chat model to GPU isn't disabled via CLI and
         # 2. Machine has GPU
@@ -26,6 +27,12 @@ def download_model(model_name: str):
         )
     except ValueError:
         device = "cpu"
+    except Exception as e:
+        if chat_model_config is None:
+            device = "cpu"  # Fallback to CPU as can't determine if GPU has enough memory
+            logger.debug(f"Unable to download model config from gpt4all website: {e}")
+        else:
+            raise e
 
     # Now load the downloaded chat model onto appropriate device
     chat_model = gpt4all.GPT4All(model_name=model_name, device=device, allow_download=False)

src/khoj/processor/conversation/openai/gpt.py

@@ -41,7 +41,7 @@ def extract_questions(
         [
             f'Q: {chat["intent"]["query"]}\n\n{chat["intent"].get("inferred-queries") or list([chat["intent"]["query"]])}\n\n{chat["message"]}\n\n'
             for chat in conversation_log.get("chat", [])[-4:]
-            if chat["by"] == "khoj"
+            if chat["by"] == "khoj" and chat["intent"].get("type") != "text-to-image"
         ]
     )
 
@@ -123,8 +123,8 @@ def send_message_to_model(
 
 def converse(
     references,
-    online_results,
     user_query,
+    online_results=[],
     conversation_log={},
     model: str = "gpt-3.5-turbo",
     api_key: Optional[str] = None,

src/khoj/processor/conversation/openai/utils.py

@@ -36,11 +36,11 @@ class StreamingChatCallbackHandler(StreamingStdOutCallbackHandler):
 
 @retry(
     retry=(
-        retry_if_exception_type(openai.error.Timeout)
+        retry_if_exception_type(openai._exceptions.APITimeoutError)
-        | retry_if_exception_type(openai.error.APIError)
+        | retry_if_exception_type(openai._exceptions.APIError)
-        | retry_if_exception_type(openai.error.APIConnectionError)
+        | retry_if_exception_type(openai._exceptions.APIConnectionError)
-        | retry_if_exception_type(openai.error.RateLimitError)
+        | retry_if_exception_type(openai._exceptions.RateLimitError)
-        | retry_if_exception_type(openai.error.ServiceUnavailableError)
+        | retry_if_exception_type(openai._exceptions.APIStatusError)
     ),
     wait=wait_random_exponential(min=1, max=10),
     stop=stop_after_attempt(3),
@@ -57,11 +57,11 @@ def completion_with_backoff(**kwargs):
 
 @retry(
     retry=(
-        retry_if_exception_type(openai.error.Timeout)
+        retry_if_exception_type(openai._exceptions.APITimeoutError)
-        | retry_if_exception_type(openai.error.APIError)
+        | retry_if_exception_type(openai._exceptions.APIError)
-        | retry_if_exception_type(openai.error.APIConnectionError)
+        | retry_if_exception_type(openai._exceptions.APIConnectionError)
-        | retry_if_exception_type(openai.error.RateLimitError)
+        | retry_if_exception_type(openai._exceptions.RateLimitError)
-        | retry_if_exception_type(openai.error.ServiceUnavailableError)
+        | retry_if_exception_type(openai._exceptions.APIStatusError)
     ),
     wait=wait_exponential(multiplier=1, min=4, max=10),
     stop=stop_after_attempt(3),

src/khoj/processor/conversation/openai/whisper.py

@@ -3,13 +3,13 @@ from io import BufferedReader
 
 # External Packages
 from asgiref.sync import sync_to_async
-import openai
+from openai import OpenAI
 
 
-async def transcribe_audio(audio_file: BufferedReader, model, api_key) -> str:
+async def transcribe_audio(audio_file: BufferedReader, model, client: OpenAI) -> str:
     """
     Transcribe audio file using Whisper model via OpenAI's API
     """
     # Send the audio data to the Whisper API
-    response = await sync_to_async(openai.Audio.translate)(model=model, file=audio_file, api_key=api_key)
+    response = await sync_to_async(client.audio.translations.create)(model=model, file=audio_file)
-    return response["text"]
+    return response.text

src/khoj/processor/conversation/utils.py

@@ -4,6 +4,7 @@ from time import perf_counter
 import json
 from datetime import datetime
 import queue
+from typing import Any, Dict, List
 import tiktoken
 
 # External packages
@@ -11,6 +12,8 @@ from langchain.schema import ChatMessage
 from transformers import AutoTokenizer
 
 # Internal Packages
+from khoj.database.adapters import ConversationAdapters
+from khoj.database.models import KhojUser
 from khoj.utils.helpers import merge_dicts
 
 
@@ -89,6 +92,32 @@ def message_to_log(
     return conversation_log
 
 
+def save_to_conversation_log(
+    q: str,
+    chat_response: str,
+    user: KhojUser,
+    meta_log: Dict,
+    user_message_time: str = None,
+    compiled_references: List[str] = [],
+    online_results: Dict[str, Any] = {},
+    inferred_queries: List[str] = [],
+    intent_type: str = "remember",
+):
+    user_message_time = user_message_time or datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    updated_conversation = message_to_log(
+        user_message=q,
+        chat_response=chat_response,
+        user_message_metadata={"created": user_message_time},
+        khoj_message_metadata={
+            "context": compiled_references,
+            "intent": {"inferred-queries": inferred_queries, "type": intent_type},
+            "onlineContext": online_results,
+        },
+        conversation_log=meta_log.get("chat", []),
+    )
+    ConversationAdapters.save_conversation(user, {"chat": updated_conversation})
+
+
 def generate_chatml_messages_with_context(
     user_message,
     system_message,

src/khoj/routers/api.py

@@ -19,7 +19,7 @@ from starlette.authentication import requires
 from khoj.configure import configure_server
 from khoj.database import adapters
 from khoj.database.adapters import ConversationAdapters, EntryAdapters
-from khoj.database.models import ChatModelOptions
+from khoj.database.models import ChatModelOptions, SpeechToTextModelOptions
 from khoj.database.models import Entry as DbEntry
 from khoj.database.models import (
     GithubConfig,
@@ -35,12 +35,14 @@ from khoj.processor.conversation.offline.whisper import transcribe_audio_offline
 from khoj.processor.conversation.openai.gpt import extract_questions
 from khoj.processor.conversation.openai.whisper import transcribe_audio
 from khoj.processor.conversation.prompts import help_message, no_entries_found
+from khoj.processor.conversation.utils import save_to_conversation_log
 from khoj.processor.tools.online_search import search_with_google
 from khoj.routers.helpers import (
     ApiUserRateLimiter,
     CommonQueryParams,
     agenerate_chat_response,
     get_conversation_command,
+    text_to_image,
     is_ready_to_chat,
     update_telemetry_state,
     validate_conversation_config,
@@ -622,17 +624,15 @@ async def transcribe(request: Request, common: CommonQueryParams, file: UploadFi
 
         # Send the audio data to the Whisper API
         speech_to_text_config = await ConversationAdapters.get_speech_to_text_config()
-        openai_chat_config = await ConversationAdapters.get_openai_chat_config()
         if not speech_to_text_config:
-            # If the user has not configured a speech to text model, return an unprocessable entity error
+            # If the user has not configured a speech to text model, return an unsupported on server error
-            status_code = 422
+            status_code = 501
-        elif openai_chat_config and speech_to_text_config.model_type == ChatModelOptions.ModelType.OPENAI:
+        elif state.openai_client and speech_to_text_config.model_type == SpeechToTextModelOptions.ModelType.OPENAI:
-            api_key = openai_chat_config.api_key
             speech2text_model = speech_to_text_config.model_name
-            user_message = await transcribe_audio(audio_file, model=speech2text_model, api_key=api_key)
+            user_message = await transcribe_audio(audio_file, speech2text_model, client=state.openai_client)
-        elif speech_to_text_config.model_type == ChatModelOptions.ModelType.OFFLINE:
+        elif speech_to_text_config.model_type == SpeechToTextModelOptions.ModelType.OFFLINE:
             speech2text_model = speech_to_text_config.model_name
-            user_message = await transcribe_audio_offline(audio_filename, model=speech2text_model)
+            user_message = await transcribe_audio_offline(audio_filename, speech2text_model)
     finally:
         # Close and Delete the temporary audio file
         audio_file.close()
@@ -665,7 +665,7 @@ async def chat(
     rate_limiter_per_minute=Depends(ApiUserRateLimiter(requests=10, subscribed_requests=60, window=60)),
     rate_limiter_per_day=Depends(ApiUserRateLimiter(requests=10, subscribed_requests=600, window=60 * 60 * 24)),
 ) -> Response:
-    user = request.user.object
+    user: KhojUser = request.user.object
 
     await is_ready_to_chat(user)
     conversation_command = get_conversation_command(query=q, any_references=True)
@@ -703,6 +703,11 @@ async def chat(
                 media_type="text/event-stream",
                 status_code=200,
             )
+    elif conversation_command == ConversationCommand.Image:
+        image, status_code = await text_to_image(q)
+        await sync_to_async(save_to_conversation_log)(q, image, user, meta_log, intent_type="text-to-image")
+        content_obj = {"image": image, "intentType": "text-to-image"}
+        return Response(content=json.dumps(content_obj), media_type="application/json", status_code=status_code)
 
     # Get the (streamed) chat response from the LLM of choice.
     llm_response, chat_metadata = await agenerate_chat_response(
@@ -786,7 +791,6 @@ async def extract_references_and_questions(
         conversation_config = await ConversationAdapters.aget_conversation_config(user)
         if conversation_config is None:
             conversation_config = await ConversationAdapters.aget_default_conversation_config()
-        openai_chat_config = await ConversationAdapters.aget_openai_conversation_config()
         if (
             offline_chat_config
             and offline_chat_config.enabled
@@ -803,7 +807,7 @@ async def extract_references_and_questions(
             inferred_queries = extract_questions_offline(
                 defiltered_query, loaded_model=loaded_model, conversation_log=meta_log, should_extract_questions=False
             )
-        elif openai_chat_config and conversation_config.model_type == ChatModelOptions.ModelType.OPENAI:
+        elif conversation_config and conversation_config.model_type == ChatModelOptions.ModelType.OPENAI:
             openai_chat_config = await ConversationAdapters.get_openai_chat_config()
             openai_chat = await ConversationAdapters.get_openai_chat()
             api_key = openai_chat_config.api_key

src/khoj/routers/helpers.py

@@ -9,23 +9,23 @@ from functools import partial
 from time import time
 from typing import Annotated, Any, Dict, Iterator, List, Optional, Tuple, Union
 
+# External Packages
 from fastapi import Depends, Header, HTTPException, Request, UploadFile
+import openai
 from starlette.authentication import has_required_scope
-from asgiref.sync import sync_to_async
-
 
+# Internal Packages
 from khoj.database.adapters import ConversationAdapters, EntryAdapters
-from khoj.database.models import KhojUser, Subscription
+from khoj.database.models import KhojUser, Subscription, TextToImageModelConfig
 from khoj.processor.conversation import prompts
 from khoj.processor.conversation.offline.chat_model import converse_offline, send_message_to_model_offline
 from khoj.processor.conversation.openai.gpt import converse, send_message_to_model
-from khoj.processor.conversation.utils import ThreadedGenerator, message_to_log
+from khoj.processor.conversation.utils import ThreadedGenerator, save_to_conversation_log
-
-# Internal Packages
 from khoj.utils import state
 from khoj.utils.config import GPT4AllProcessorModel
 from khoj.utils.helpers import ConversationCommand, log_telemetry
 
+
 logger = logging.getLogger(__name__)
 
 executor = ThreadPoolExecutor(max_workers=1)
@@ -102,6 +102,8 @@ def get_conversation_command(query: str, any_references: bool = False) -> Conver
         return ConversationCommand.General
     elif query.startswith("/online"):
         return ConversationCommand.Online
+    elif query.startswith("/image"):
+        return ConversationCommand.Image
     # If no relevant notes found for the given query
     elif not any_references:
         return ConversationCommand.General
@@ -186,30 +188,7 @@ def generate_chat_response(
     conversation_command: ConversationCommand = ConversationCommand.Default,
     user: KhojUser = None,
 ) -> Tuple[Union[ThreadedGenerator, Iterator[str]], Dict[str, str]]:
-    def _save_to_conversation_log(
-        q: str,
-        chat_response: str,
-        user_message_time: str,
-        compiled_references: List[str],
-        online_results: Dict[str, Any],
-        inferred_queries: List[str],
-        meta_log,
-    ):
-        updated_conversation = message_to_log(
-            user_message=q,
-            chat_response=chat_response,
-            user_message_metadata={"created": user_message_time},
-            khoj_message_metadata={
-                "context": compiled_references,
-                "intent": {"inferred-queries": inferred_queries},
-                "onlineContext": online_results,
-            },
-            conversation_log=meta_log.get("chat", []),
-        )
-        ConversationAdapters.save_conversation(user, {"chat": updated_conversation})
-
     # Initialize Variables
-    user_message_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
     chat_response = None
     logger.debug(f"Conversation Type: {conversation_command.name}")
 
@@ -217,13 +196,13 @@ def generate_chat_response(
 
     try:
         partial_completion = partial(
-            _save_to_conversation_log,
+            save_to_conversation_log,
             q,
-            user_message_time=user_message_time,
+            user=user,
+            meta_log=meta_log,
             compiled_references=compiled_references,
             online_results=online_results,
             inferred_queries=inferred_queries,
-            meta_log=meta_log,
         )
 
         conversation_config = ConversationAdapters.get_valid_conversation_config(user)
@@ -251,9 +230,9 @@ def generate_chat_response(
             chat_model = conversation_config.chat_model
             chat_response = converse(
                 compiled_references,
-                online_results,
                 q,
-                meta_log,
+                online_results=online_results,
+                conversation_log=meta_log,
                 model=chat_model,
                 api_key=api_key,
                 completion_func=partial_completion,
@@ -271,6 +250,29 @@ def generate_chat_response(
     return chat_response, metadata
 
 
+async def text_to_image(message: str) -> Tuple[Optional[str], int]:
+    status_code = 200
+    image = None
+
+    # Send the audio data to the Whisper API
+    text_to_image_config = await ConversationAdapters.aget_text_to_image_model_config()
+    if not text_to_image_config:
+        # If the user has not configured a text to image model, return an unsupported on server error
+        status_code = 501
+    elif state.openai_client and text_to_image_config.model_type == TextToImageModelConfig.ModelType.OPENAI:
+        text2image_model = text_to_image_config.model_name
+        try:
+            response = state.openai_client.images.generate(
+                prompt=message, model=text2image_model, response_format="b64_json"
+            )
+            image = response.data[0].b64_json
+        except openai.OpenAIError as e:
+            logger.error(f"Image Generation failed with {e.http_status}: {e.error}")
+            status_code = 500
+
+    return image, status_code
+
+
 class ApiUserRateLimiter:
     def __init__(self, requests: int, subscribed_requests: int, window: int):
         self.requests = requests

src/khoj/utils/helpers.py

@@ -273,6 +273,7 @@ class ConversationCommand(str, Enum):
     Notes = "notes"
     Help = "help"
     Online = "online"
+    Image = "image"
 
 
 command_descriptions = {
@@ -280,6 +281,7 @@ command_descriptions = {
     ConversationCommand.Notes: "Only talk about information that is available in your knowledge base.",
     ConversationCommand.Default: "The default command when no command specified. It intelligently auto-switches between general and notes mode.",
     ConversationCommand.Online: "Look up information on the internet.",
+    ConversationCommand.Image: "Generate images by describing your imagination in words.",
     ConversationCommand.Help: "Display a help message with all available commands and other metadata.",
 }
 

src/khoj/utils/initialization.py

@@ -7,6 +7,7 @@ from khoj.database.models import (
     OpenAIProcessorConversationConfig,
     ChatModelOptions,
     SpeechToTextModelOptions,
+    TextToImageModelConfig,
 )
 
 from khoj.utils.constants import default_offline_chat_model, default_online_chat_model
@@ -103,6 +104,15 @@ def initialization():
                 model_name=openai_speech2text_model, model_type=SpeechToTextModelOptions.ModelType.OPENAI
             )
 
+            default_text_to_image_model = "dall-e-3"
+            openai_text_to_image_model = input(
+                f"Enter the OpenAI text to image model you want to use (default: {default_text_to_image_model}): "
+            )
+            openai_speech2text_model = openai_text_to_image_model or default_text_to_image_model
+            TextToImageModelConfig.objects.create(
+                model_name=openai_text_to_image_model, model_type=TextToImageModelConfig.ModelType.OPENAI
+            )
+
         if use_offline_model == "y" or use_openai_model == "y":
             logger.info("🗣️  Chat model configuration complete")
 

src/khoj/utils/models.py

@@ -22,17 +22,9 @@ class BaseEncoder(ABC):
 
 
 class OpenAI(BaseEncoder):
-    def __init__(self, model_name, device=None):
+    def __init__(self, model_name, client: openai.OpenAI, device=None):
         self.model_name = model_name
-        if (
+        self.openai_client = client
-            not state.processor_config
-            or not state.processor_config.conversation
-            or not state.processor_config.conversation.openai_model
-        ):
-            raise Exception(
-                f"Set OpenAI API key under processor-config > conversation > openai-api-key in config file: {state.config_file}"
-            )
-        openai.api_key = state.processor_config.conversation.openai_model.api_key
         self.embedding_dimensions = None
 
     def encode(self, entries, device=None, **kwargs):
@@ -43,7 +35,7 @@ class OpenAI(BaseEncoder):
             processed_entry = entries[index].replace("\n", " ")
 
             try:
-                response = openai.Embedding.create(input=processed_entry, model=self.model_name)
+                response = self.openai_client.embeddings.create(input=processed_entry, model=self.model_name)
                 embedding_tensors += [torch.tensor(response.data[0].embedding, device=device)]
                 # Use current models embedding dimension, once available
                 # Else default to embedding dimensions of the text-embedding-ada-002 model

src/khoj/utils/state.py

@@ -1,15 +1,16 @@
 # Standard Packages
+from collections import defaultdict
 import os
+from pathlib import Path
 import threading
 from typing import List, Dict
-from collections import defaultdict
 
 # External Packages
-from pathlib import Path
+from openai import OpenAI
-from khoj.processor.embeddings import CrossEncoderModel, EmbeddingsModel
 from whisper import Whisper
 
 # Internal Packages
+from khoj.processor.embeddings import CrossEncoderModel, EmbeddingsModel
 from khoj.utils import config as utils_config
 from khoj.utils.config import ContentIndex, SearchModels, GPT4AllProcessorModel
 from khoj.utils.helpers import LRU, get_device
@@ -21,6 +22,7 @@ search_models = SearchModels()
 embeddings_model: EmbeddingsModel = None
 cross_encoder_model: CrossEncoderModel = None
 content_index = ContentIndex()
+openai_client: OpenAI = None
 gpt4all_processor_config: GPT4AllProcessorModel = None
 whisper_model: Whisper = None
 config_file: Path = None

tests/test_openai_chat_director.py

@@ -68,10 +68,10 @@ def test_chat_with_online_content(chat_client):
     response_message = response_message.split("### compiled references")[0]
 
     # Assert
-    expected_responses = ["http://www.paulgraham.com/greatwork.html"]
+    expected_responses = ["http://www.paulgraham.com/greatwork.html", "Please set your SERPER_DEV_API_KEY"]
     assert response.status_code == 200
     assert any([expected_response in response_message for expected_response in expected_responses]), (
-        "Expected assistants name, [K|k]hoj, in response but got: " + response_message
+        "Expected links or serper not setup in response but got: " + response_message
     )