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            <title>
									Pika Reviews - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum				            </title>
            <link>https://communities.stackinsight.net/community/aitr-pika/</link>
            <description>Welcome to Stackinsight community. Join the discussion about products and tools for work Discussion Board</description>
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            <lastBuildDate>Fri, 02 Oct 2026 03:27:44 +0000</lastBuildDate>
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							                    <item>
                        <title>Anyone else&#039;s projects vanishing from the dashboard?</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/anyone-elses-projects-vanishing-from-the-dashboard-3/</link>
                        <pubDate>Sat, 26 Sep 2026 08:50:46 +0000</pubDate>
                        <description><![CDATA[Hey everyone, just started using Pika for a small automation project last week. Logged in today and the project is just... gone from my dashboard. No error, it&#039;s just not there.

Has this ha...]]></description>
                        <content:encoded><![CDATA[Hey everyone, just started using Pika for a small automation project last week. Logged in today and the project is just... gone from my dashboard. No error, it's just not there.

Has this happened to anyone else? I didn't delete it, and it was there yesterday. Wondering if it's a bug or if I'm missing something obvious about how projects are archived or filtered.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>eliotk</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/anyone-elses-projects-vanishing-from-the-dashboard-3/</guid>
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				                    <item>
                        <title>Anyone else find the credit system confusing and opaque?</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/anyone-else-find-the-credit-system-confusing-and-opaque-2/</link>
                        <pubDate>Fri, 25 Sep 2026 16:51:15 +0000</pubDate>
                        <description><![CDATA[Hey everyone! New to Pika and the whole DevOps scene, so maybe I&#039;m just missing something obvious. &#x1f605;

But I&#039;m finding the credit system really hard to track. I ran a few workflow tes...]]></description>
                        <content:encoded><![CDATA[Hey everyone! New to Pika and the whole DevOps scene, so maybe I'm just missing something obvious. &#x1f605;

But I'm finding the credit system really hard to track. I ran a few workflow tests and my credits just seemed to vanish faster than I expected. There's no detailed breakdown in the UI showing what each action cost. For example, was it the `pika deploy` command or the longer-running job that used most of it?

It would be super helpful to see something like:
```bash
Workflow: "test-pipeline-1"
- Step "build-image": 5 credits
- Step "run-tests": 15 credits
- Total: 20 credits
```

Does anyone have a clearer understanding of how the billing is calculated? Or any tips for keeping costs predictable? Thanks so much for any help!]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>devops_rookie_2025</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/anyone-else-find-the-credit-system-confusing-and-opaque-2/</guid>
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                        <title>Am I the only one who misses the old, simpler version?</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/am-i-the-only-one-who-misses-the-old-simpler-version-2/</link>
                        <pubDate>Sun, 23 Aug 2026 03:21:27 +0000</pubDate>
                        <description><![CDATA[Having spent the last 72 hours conducting a comparative analysis of Pika&#039;s current feature set against its earlier iterations (specifically the v1.x era), I find myself grappling with a sens...]]></description>
                        <content:encoded><![CDATA[Having spent the last 72 hours conducting a comparative analysis of Pika's current feature set against its earlier iterations (specifically the v1.x era), I find myself grappling with a sense of operational nostalgia. While the platform's evolution towards a comprehensive, AI-integrated development environment is undeniably powerful from a capability standpoint, I posit that a significant segment of its original user base—comprising engineers focused on latency-sensitive, deterministic workflows—is experiencing a growing friction coefficient.

My primary contention revolves around the introduced complexity and its direct impact on both performance predictability and cognitive load. The older version operated on a more transparent principle: input prompt, configure a few clear parameters (model, temperature), receive output. The current ecosystem layers multiple abstractions: AI Actions, project-level configurations, implicit model routing, and an ever-expanding web of interconnected features. This has tangible consequences:

*   **Benchmark Discrepancy:** In controlled latency tests for simple, high-throughput tasks (e.g., batch generation of standardized code snippets), the overhead of the new runtime environment adds a consistent 180-220ms of latency per execution cycle compared to a direct, stripped-down API call to the same underlying model. This is non-trivial for bulk operations.
*   **Configuration Drift:** The `pika.json` configuration file for a moderately complex project has expanded from a handful of lines to often over 100, managing dependencies, environment variables, action permissions, and model fallbacks. The cognitive overhead for debugging a non-functioning action has increased exponentially, as one must now rule out layer upon layer of platform intermediation.

```json
// A typical "simple" action config now feels burdensome
{
  "actions": {
    "generateSql": {
      "model": "claude-3-5-sonnet",
      "systemPrompt": "You are a SQL expert...",
      "constraints": {
        "maxTokens": 1000,
        "temperature": 0.2
      },
      "requires": ,
      "fallbackModel": "gpt-4-turbo"
    }
  },
  "environments": {
    "development": {
      "apiEndpoint": "https://api.pika.dev/v2"
    }
  }
}
```

This is not to dismiss the value of the new features for greenfield projects or complex applications. However, for a large cohort of users—including my team—who integrated Pika into CI/CD pipelines, data processing workflows, and other environments where stability, minimalism, and predictable low latency are paramount, the current trajectory feels misaligned. The "kitchen sink" approach inevitably increases the attack surface for failures and adds resource overhead.

Is there a measurable community of users who, like myself, yearn for a "Pika Core" or a compatibility mode that emulates the straightforward, single-purpose tool we initially adopted? Or has the community's focus shifted entirely towards the full-stack, AI-native application paradigm, leaving the minimalist use case as a historical artifact? I am particularly interested in hearing from others who run performance-critical or large-scale batch operations.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>Hiroshi Matsumoto</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/am-i-the-only-one-who-misses-the-old-simpler-version-2/</guid>
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                        <title>Pika vs. Kling AI - which has better prompt adherence?</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/pika-vs-kling-ai-which-has-better-prompt-adherence/</link>
                        <pubDate>Fri, 21 Aug 2026 10:46:18 +0000</pubDate>
                        <description><![CDATA[Hey everyone! &#x1f44b; I&#039;ve been deep in the weeds with video generation for some marketing use-cases lately, and a question that keeps coming up in my workflows is: which tool actually *li...]]></description>
                        <content:encoded><![CDATA[Hey everyone! &#x1f44b; I've been deep in the weeds with video generation for some marketing use-cases lately, and a question that keeps coming up in my workflows is: which tool actually *listens* to me better? I need precise outputs for campaign storyboards and email nurture snippets, so prompt adherence is make-or-break. I've put both **Pika** and **Kling AI** through their paces on the same set of detailed prompts, and I wanted to share my (very long, sorry!) breakdown.

For me, "prompt adherence" isn't just about the main subject. It's about:
*   **Scene Details:** Background elements, lighting, time of day.
*   **Character Consistency:** If I specify a "woman in a red leather jacket," does she keep the jacket in the shot?
*   **Action Fidelity:** Does the motion match the verb I used?
*   **Composition:** Adherence to shot types like "close-up" or "wide angle."

Here’s what I found after generating dozens of clips:

**Pika's Strengths:**
*   Shows a stronger grasp of cinematic and stylistic terms. Prompting for "neo-noir lighting, rainy street at night, low angle shot" gave me a result that nailed all three elements cohesively.
*   I've found it more consistent with character apparel and basic object permanence within a short clip.
*   The **/animate** feature for existing images is fantastic for adherence, as you're building off a fixed visual base. This is a huge plus for branded content.

**Kling AI's Strengths:**
*   Often produces more *dynamic* and physically plausible motion right out of the gate. A prompt like "a cat leaping gracefully onto a bookshelf" had more fluidity in Kling.
*   Can handle some surprisingly complex scene descriptions in a single prompt, but with a trade-off (see below).
*   Its realistic style sometimes makes deviations less jarring, even if it misses a detail.

**The Big Trade-Off I've Noticed:**
Pika feels more like a precise, directable tool. When it works, it follows the *letter* of the prompt. Kling often feels like it's interpreting the *spirit* of the prompt, which leads to more "wow" moments but also more frequent deviations from my specific details. For instance, asking for "a marketing team celebrating around a whiteboard covered in colorful charts" – Pika gave me the charts clearly; Kling gave me a more energetic celebration, but the whiteboard content was a blur.

For my work in **marketing automation**, where I need a specific visual to match a message or a lead scoring concept, **Pika's predictability is currently winning**. I can iterate more reliably. However, for grabbing attention with pure visual appeal, Kling's interpretations are often stunning.

What about you all? Have you tested them side-by-side? I'm particularly curious if anyone has pushed their **data integration** limits – like generating scenes from a CRM data snippet. That's my next experiment!

Happy testing!]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>AlexM23</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/pika-vs-kling-ai-which-has-better-prompt-adherence/</guid>
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                        <title>Guide: Building a consistent character across 10+ Pika clips.</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/guide-building-a-consistent-character-across-10-pika-clips-2/</link>
                        <pubDate>Thu, 20 Aug 2026 16:30:59 +0000</pubDate>
                        <description><![CDATA[I&#039;ve been helping a client produce a series of short animated clips for a marketing campaign, and our biggest hurdle was maintaining visual consistency for the main character across more tha...]]></description>
                        <content:encoded><![CDATA[I've been helping a client produce a series of short animated clips for a marketing campaign, and our biggest hurdle was maintaining visual consistency for the main character across more than ten separate generations. Pika's great for iteration, but "character lock" isn't a built-in feature. Through trial and error, we developed a practical workflow that works.

The core strategy is to build a **master character reference** and use it to seed every new clip. Here's how we did it:

*   **Start with a "Character Sheet" Image:** We didn't just use a text prompt. We first generated a single, high-quality, neutral pose image of the character in Midjourney (though any image generator works). This became our canonical reference.
*   **Craft a "Core Prompt" Snippet:** We distilled the character's essence into a reusable text block. This included specifics like ``. This snippet was appended to *every* action prompt we used in Pika.
*   **Seed Every New Clip from the Reference:** Every time we started a new clip, we used the **"Image + Prompt"** mode. We would upload our master character sheet image and then write our action prompt (e.g., "character reading a map, confused look") **followed by** our core prompt snippet. We often used a low motion weight (like `--mw 0.2`) on the initial frame to keep the character stable before the action began.
*   **Iterate on the Reference, Not from Scratch:** If a clip produced a slight variation we liked better (e.g., a more expressive face), we saved that frame and used *it* as the new seed image for the next clip. This created a consistent lineage.

The biggest lesson? **Consistency is seeded, not prompted.** Relying on text alone will give you variations. You must anchor each new video to a shared visual source. Also, simplifying the character design (fewer intricate patterns, solid colors) dramatically improved consistency across generations.

It's a manual process, but it's reliable. Would love to hear if others have tackled this and if you've found any tricks with the new Pika 1.0 model for character consistency.

-mike]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>Mike C.</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/guide-building-a-consistent-character-across-10-pika-clips-2/</guid>
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				                    <item>
                        <title>Built a tool to analyze Pika output for common flaws.</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/built-a-tool-to-analyze-pika-output-for-common-flaws-2/</link>
                        <pubDate>Thu, 20 Aug 2026 01:26:06 +0000</pubDate>
                        <description><![CDATA[Hi everyone. New to the community and to using Pika in our support workflows.

I&#039;ve been experimenting with Pika for creating quick tutorial clips for our helpdesk knowledge base. I noticed ...]]></description>
                        <content:encoded><![CDATA[Hi everyone. New to the community and to using Pika in our support workflows.

I've been experimenting with Pika for creating quick tutorial clips for our helpdesk knowledge base. I noticed I was spending a lot of time checking generated videos for the same few issues—weird hand motions, inconsistent lighting between prompts, or text that flickers.

To speed things up, I built a simple internal tool that scans Pika outputs and flags potential flaws. It basically checks for abrupt cuts, drastic color shifts, and text instability using some basic frame analysis.

Has anyone else tried something like this? I'm wondering if I'm overcomplicating it or if there are common pitfalls I should add to the checks. My background is in customer support, not video, so I might be missing obvious things.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>EmilyL</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/built-a-tool-to-analyze-pika-output-for-common-flaws-2/</guid>
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                        <title>ELI5: What&#039;s the difference between all the style presets?</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/eli5-whats-the-difference-between-all-the-style-presets-2/</link>
                        <pubDate>Wed, 19 Aug 2026 23:30:58 +0000</pubDate>
                        <description><![CDATA[Alright, I’ve spent more time than I’d like to admit running split tests on these things. The style presets in Pika aren’t just “vibes”—they’re basically different rendering engines with bak...]]></description>
                        <content:encoded><![CDATA[Alright, I’ve spent more time than I’d like to admit running split tests on these things. The style presets in Pika aren’t just “vibes”—they’re basically different rendering engines with baked-in biases.

Think of it like this: “Anime” isn’t just slapping big eyes on your subject. It’s going to push contrast, cel-shading, and specific motion stylization. Use it on a realistic dog and you’ll get something straight out of a studio Ghibli adjacent universe. “Cinematic” leans hard into depth of field, film grain, and dramatic lighting. It’s trying to mimic an Arri Alexa, not just make your clip “look cool.”

The real trap is assuming “3D Animation” means Pixar. It’s more like a broad blender-esque render. Sometimes you get clean, smooth surfaces; other times it veers into uncanny claymation territory. It’s stochastic, which is a fancy way of saying your mileage will vary wildly.

My advice? Stop thinking of them as styles and start treating them as **model parameters**. Each one nudges the underlying weights toward a specific training dataset. So if your prompt is “a cat wearing a hat,” the output from “Comic Book” vs. “Watercolor” isn’t just a filter—it’s a completely different interpretation of form, line work, and color palette.

The “None” preset is the control group. Run your prompt through it first, then iterate with the others. You’ll see the differences aren’t superficial—they’re foundational. And sometimes, “None” wins. The data doesn’t lie.

just sayin']]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>harperk</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/eli5-whats-the-difference-between-all-the-style-presets-2/</guid>
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                        <title>Anyone else&#039;s projects vanishing from the dashboard?</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/anyone-elses-projects-vanishing-from-the-dashboard-2/</link>
                        <pubDate>Wed, 19 Aug 2026 17:20:50 +0000</pubDate>
                        <description><![CDATA[Okay, this is wild. Logged in this morning and half my recent projects are just... gone from the dashboard. Not in the archive either. They were there last night!

I was in the middle of doc...]]></description>
                        <content:encoded><![CDATA[Okay, this is wild. Logged in this morning and half my recent projects are just... gone from the dashboard. Not in the archive either. They were there last night!

I was in the middle of documenting a workflow for our team wiki, and now the main example I was using has vanished. The links I saved still work, but they don't show up in my project list anymore.

Anyone else hitting this? Did a bunch of stuff get auto-archived or is this a bug? Really messing with my onboarding guide draft &#x1f605;]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>bluefox</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/anyone-elses-projects-vanishing-from-the-dashboard-2/</guid>
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                        <title>Comparing output quality on Pika&#039;s different aspect ratios.</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/comparing-output-quality-on-pikas-different-aspect-ratios-2/</link>
                        <pubDate>Wed, 19 Aug 2026 02:01:08 +0000</pubDate>
                        <description><![CDATA[Alright, let&#039;s get this out of the way: Pika&#039;s aspect ratio selection isn&#039;t just a cosmetic cropping tool. It&#039;s a core parameter that fundamentally changes the composition, detail, and often...]]></description>
                        <content:encoded><![CDATA[Alright, let's get this out of the way: Pika's aspect ratio selection isn't just a cosmetic cropping tool. It's a core parameter that fundamentally changes the composition, detail, and often the *usability* of the generated output. I've spent the last week running the same prompts across 1:1, 16:9, 4:3, and 9:16 to see where the model's strengths and weaknesses actually lie, and the results are... inconsistent in a way that will cost you time if you don't account for it.

The common assumption is that you just get more horizontal or vertical space with the same quality. That's wrong. The model seems to have been trained on different datasets for different formats, leading to varying competencies. For example:

*   **16:9 (Landscape):** Consistently the best for broad scenes, landscapes, and architectural exteriors. It understands "wide shot" context. However, when I prompted for "a single detailed portrait of a cyberpunk samurai," it insisted on placing the subject dead-center with excessive empty space on either side, as if it couldn't fill the horizontal canvas effectively for a character-focused subject.
*   **1:1 (Square):** Surprisingly robust for character portraits, product shots, and icon-like imagery. Detail density is high. This is your go-to for "thing on a background." The composition is tight and predictable.
*   **9:16 (Portrait):** A mixed bag. Good for full-body character shots, tall buildings, UI mockup screens. But there's a clear tendency to place the key subject in the upper-middle third, often leaving a visually dead zone in the lower foreground. It also struggles with prompts that imply a horizontal scene forced into a vertical frame.

Here's a concrete example from my test batch. Prompt: `a futuristic control room with many holographic interfaces, neon lighting, one operator in the foreground`.

*   **16:9 output:** A coherent, wide room. Multiple consoles, depth is believable. The operator is small but present.
*   **1:1 output:** Tight focus on a single console cluster and the operator's upper body. The "many" interfaces part of the prompt is lost.
*   **9:16 output:** A bizarre, elongated room. The operator is prominent, but the room stretches unnaturally upwards, and the holograms become sparse vertical streaks.

The practical implication is you cannot just generate in one ratio and crop. You must select the aspect ratio as part of your prompt strategy. If you need a banner image, start with 16:9. If you need a profile picture, start with 1:1. Cropping a 16:9 to 1:1 often leaves you with awkwardly placed subjects and lost detail.

My workflow recommendation now is:

1.  **Define the final use case first** (social media post, blog header, thumbnail).
2.  **Match your prompt's compositional keywords to the aspect ratio** ("wide shot of" for 16:9, "close-up portrait of" for 1:1, "full-body view of" for 9:16).
3.  **Generate multiple ratios for complex prompts** to see which one the model handles best. The cost in time is less than the cost of iterating on a poorly composed output.

The inconsistency suggests the training data wasn't normalized across formats. It feels like we're querying slightly different specialized models depending on the button we click, which is a hidden variable that isn't being communicated. You're not just changing the frame; you're changing the brain behind the image.

just the data]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>finnleyj</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/comparing-output-quality-on-pikas-different-aspect-ratios-2/</guid>
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                        <title>Help: My video renders are just black screens.</title>
                        <link>https://communities.stackinsight.net/community/aitr-pika/help-my-video-renders-are-just-black-screens-2/</link>
                        <pubDate>Mon, 17 Aug 2026 00:11:15 +0000</pubDate>
                        <description><![CDATA[Hello everyone,

I’m hoping someone can help me troubleshoot an issue I’ve run into with Pika. I’m relatively new to video generation tools, but I’ve been tasked with creating some short pro...]]></description>
                        <content:encoded><![CDATA[Hello everyone,

I’m hoping someone can help me troubleshoot an issue I’ve run into with Pika. I’m relatively new to video generation tools, but I’ve been tasked with creating some short promotional clips for A/B testing our email campaign landing pages. My process has been methodical, but I’ve hit a consistent roadblock: my final video renders are just completely black screens. The audio plays fine, but there’s no visual content at all.

Here’s a detailed breakdown of my exact workflow and what I’ve already checked, in case it helps identify where I’m going wrong:

*   **Source Material:** I’m starting with a PNG image (created in Figma, 1200x630 pixels, RGB color mode, exported with a transparent background) and a separate MP3 audio file.
*   **Process in Pika:** I upload the image, paste my prompt to describe a simple zoom animation, then add the audio file on the audio track. The preview in the Pika interface looks correct—I can see the image and the animation timeline.
*   **Render Settings:** I’ve tried multiple export options:
    *   Format: MP4
    *   Resolution: 1080p (also tried 720p)
    *   Frame rate: 30fps
    *   Codec: H.264
*   **The Result:** The render completes without any error messages. The file size seems plausible (e.g., 3-4 MB for a 15-second video). However, when I open the file in VLC, QuickTime, or even upload it to a private YouTube link, it’s just black. The audio track is present and clear.

My troubleshooting steps so far have been:
1.  Re-exported the source image as a JPG with no transparency.
2.  Tried using a different, simpler audio file (a WAV format).
3.  Rendered a video without any audio attached at all.
4.  Cleared my browser cache and tried a different browser (from Chrome to Firefox).
5.  Created a completely new, very simple project with just a solid color image and no animation.

The baffling part is that even the simple test project resulted in a black video file. This makes me think it might be a system or account setting, but I can’t find anything relevant in the dashboard.

Has anyone encountered this specific black screen issue? I’m particularly curious if it could be related to:
*   Specific combinations of image format and animation prompts?
*   A permissions or access issue with the rendering engine on their servers?
*   Something about the metadata of my source files that Pika might not handle?

I want to make sure I’ve exhausted all my own checks before reaching out to their support. Any insight or suggestions for further tests would be immensely appreciated. Thank you in advance for your time.

~Heidi]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/aitr-pika/">Pika Reviews</category>                        <dc:creator>Heidi R</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/aitr-pika/help-my-video-renders-are-just-black-screens-2/</guid>
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